The Pennsylvania State University
The Graduate School
College of Agricultural Sciences
THE INFLUENCE OF PERSONALITY AND EXPERIENCE ON THE PERCEPTION,
LIKING, AND INTAKE OF SPICY FOODS
A Dissertation in
Food Science
by
Nadia K. Byrnes
© 2014 Nadia K. Byrnes
Submitted in Partial Fulfillment
of the Requirements
for the Degree of
Doctor of Philosophy
December 2014
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The dissertation of Nadia Byrnes was reviewed and approved* by the following:
John Hayes Assistant Professor of Food Science Dissertation Adviser Committee Chair
Joshua Lambert Associate Professor of Food Science
Kathleen Keller Assistant Professor of Health and Nutritional Sciences and Food Science
Stephen Wilson Assistant Professor of Psychology Robert Roberts Professor of Food Science Department Head of Food Science
*Signatures are on file in the Graduate School
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Abstract
Chemesthetic sensations, such as the burning/stinging sensation elicited by capsaicin, the pungent
compound in chili peppers, can be very polarizing. While these sensations can act a deterrent to
consuming spicy foods for some individuals, for others, these compounds are immensely enjoyable and a
key driver in their liking of certain foods. This dissertation explored the variables that influence
perception of these compounds as well as the variables that influence liking and ultimately intake of spicy
foods. First, we developed a free sorting technique with appropriate methodological considerations so that
we could use this method to explore perception of chemesthetic compounds. Utilizing this method, we
showed that training, whether through a formal culinary program (Culinary Institute of America, Hyde
Park, NY) or through informal experiential learning, significantly influences the perception of
chemesthetic compounds. While the sorting of these stimuli follows a biological basis for the most part,
experiential learning and formal training altered the way that participants use language to describe these
stimuli. Experts and naïve assessors with high scores on the Food Involvement Scale (FIS) showed more
lexical richness surrounding these sensations, using significantly more descriptors to describe the
sensations that they perceived. However, individuals in these cohorts tended to use these words more
idiosyncratically than the naïve assessors that had low FIS scores. Only formal training however
significantly influenced the way that study participants conducted to the sorting task. The expert assessors
generated perceptual map configurations that were significantly different from both the cohort of naïve
assessors with high Food Involvement scores and the cohort of naïve assessors with low Food
Involvement scores, reflecting a possible shift in the perception of these sensations or a shift in the way
the assessors with formal training attended to the sorting task.
The second portion of this dissertation focuses on the variables that influence liking and intake of
spicy foods. Chapter four shows strong empirical evidence for the relationships between personality and
liking of spicy foods that were previously hypothesized by Rozin and colleagues. While there was no
measurable effect of desensitization in this study, individuals with high scores on Arnett’s Inventory of
Sensation Seeking and the Sensitivity to Reward subscale of the Sensitivity to Punishment and Sensitivity
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to Reward Questionnaire showed higher liking of spicy foods than individuals with low scores on either
of these personality measures. Extending on these findings, chapter five explores the nature of these
relationships in a superset of individuals using moderation models. We observed limited moderation by
personality on both the relationship between perceived burning/stinging intensity of a sampled capsaicin
stimulus and the liking of spicy foods and the relationship between liking and intake of spicy foods.
However, we did observe differences between men and women that suggest that there may be divergent
mechanisms driving the intake of spicy foods in men and women. In women, the personality trait
Sensation Seeking showed stronger effects on liking and intake of spicy foods, possibly reflecting a
stronger biological reward and motivation for women. In men, Sensitivity to Reward showed stronger
effects on liking and intake of spicy foods, suggesting that the social rewards may be more salient to drive
the consumption of spicy foods in men. In chapter six we utilized a range of different personality
measures to explore the possible divergent mechanism between Sensation Seeking and Sensitivity to
Reward. A number of related personality constructs, including sensation seeking, impulsivity, and reward
sensitivity, associate with behaviors that have been hypothetically linked with the enjoyment of eating
spicy foods such as gambling, risky sexual behavior, and risky driving practices. While these personality
traits are related, they are each multidimensional traits that associate with these behaviors to different
extents. We employed a range of personality measures, both self-report and behavioral measures, to
explore the relationships between personality and liking of spicy foods in a larger context. We observed
that Sensation Seeking and Sensitivity to Reward show significant associations with the intake of spicy
foods but only Sensation Seeking shows significant associations with measures of liking of sampled and
remembered spicy foods. We suggest that these two personality constructs, while related, tap different
dimensions of spicy food intake. Based on these data, we propose that Sensation Seeking may act through
liking of spicy foods in influence intake of spicy foods, possibly reflecting a biological or intrinsic
motivation for consuming spicy foods while Sensitivity to Reward acts through different mechanisms,
possibly reflecting more of an extrinsic motivation for the intake of spicy foods.
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Table of Contents
LIST OF FIGURES ................................................................................................................... VII
LIST OF TABLES ........................................................................................................................ X
ACKNOWLEDGEMENTS ........................................................................................................ XI OBJECTIVES ........................................................................................................................... XIII
ABBREVIATIONS/DEFINITIONS ...................................................................................... XIV
CHAPTER 1 -‐ LITERATURE REVIEW ................................................................................... 1 INTRODUCTION ........................................................................................................................................................... 1 BIOLOGICAL DIFFERENCES ....................................................................................................................................... 6 EFFECTS OF EXPOSURE ON CHEMESTHETIC RESPONSE (SOCIAL) .................................................................. 11 COGNITIVE FACTORS UNDERLYING CHEMESTHETIC RESPONSE: (INDIVIDUAL/PSYCHOLOGICAL) ........... 17 SENSORY PROFILING TECHNIQUES ...................................................................................................................... 36 REFERENCES ............................................................................................................................................................ 42
CHAPTER 2 -‐ PERCEPTUAL MAPPING OF CHEMESTHETIC STIMULI IN NAÏVE ASSESSORS. ............................................................................................................................. 55 ABSTRACT ................................................................................................................................................................. 55 INTRODUCTION ........................................................................................................................................................ 56 MATERIALS AND METHODS .................................................................................................................................. 60 RESULTS .................................................................................................................................................................... 67 DISCUSSION .............................................................................................................................................................. 74 CONCLUSIONS .......................................................................................................................................................... 84 ACKNOWLEDGMENTS ............................................................................................................................................. 86 FUNDING ................................................................................................................................................................... 86 SUPPLEMENTAL FIGURES ...................................................................................................................................... 87 REFERENCES ............................................................................................................................................................ 89
CHAPTER 3 -‐ PERCEPTION OF CHEMESTHETIC STIMULI IN GROUPS WHO DIFFER BY CULINARY EXPERIENCE. ............................................................................... 95 ABSTRACT ................................................................................................................................................................. 95 INTRODUCTION ........................................................................................................................................................ 97 MATERIALS AND METHODS ............................................................................................................................... 101 RESULTS ................................................................................................................................................................. 107 DISCUSSION ........................................................................................................................................................... 114 CONCLUSION ......................................................................................................................................................... 122 FUNDING ................................................................................................................................................................ 123 ACKNOWLEDGMENTS .......................................................................................................................................... 123 REFERENCES ......................................................................................................................................................... 124
CHAPTER 4 -‐ PERSONALITY FACTORS PREDICT SPICY FOOD LIKING AND INTAKE ................................................................................................................................... 151 ABSTRACT .............................................................................................................................................................. 151 INTRODUCTION ..................................................................................................................................................... 153
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MATERIALS AND METHODS ............................................................................................................................... 157 RESULTS ................................................................................................................................................................. 163 DISCUSSION ........................................................................................................................................................... 171 CONCLUSION ......................................................................................................................................................... 178 FUNDING ................................................................................................................................................................ 179 ACKNOWLEDGEMENTS ........................................................................................................................................ 179 REFERENCES ......................................................................................................................................................... 180
CHAPTER 5 -‐ PERSONALITY INFLUENCES LIKING AND INTAKE OF SPICY FOODS DIFFERENTLY IN MEN AND WOMEN. ........................................................................... 184 ABSTRACT .............................................................................................................................................................. 184 INTRODUCTION ..................................................................................................................................................... 186 METHODS .............................................................................................................................................................. 190 RESULTS ................................................................................................................................................................. 195 DISCUSSION ........................................................................................................................................................... 203 CONCLUSIONS ....................................................................................................................................................... 208 FUNDING ................................................................................................................................................................ 209 ACKNOWLEDGEMENTS ........................................................................................................................................ 209 REFERENCES ......................................................................................................................................................... 210
CHAPTER 6 -‐ SENSATION SEEKING, SENSITIVITY TO REWARD, AND RISK TAKING PERSONALITY TRAITS REFLECT DIFFERENT MOTIVATIONS FOR CONSUMPTION OF SPICY FOODS. .................................................................................. 213 ABSTRACT .............................................................................................................................................................. 213 INTRODUCTION ..................................................................................................................................................... 215 MATERIALS AND METHODS ............................................................................................................................... 220 RESULTS ................................................................................................................................................................. 230 DISCUSSION ........................................................................................................................................................... 236 CONCLUSIONS ....................................................................................................................................................... 248 REFERENCES ......................................................................................................................................................... 250 FUNDING ................................................................................................................................................................ 275 ACKNOWLEDGEMENTS ........................................................................................................................................ 275 SUPPLEMENTAL FIGURES ................................................................................................................................... 276
CHAPTER 7 -‐ CONCLUSIONS AND FUTURE WORK .................................................... 277
APPERNDIX A -‐ GENERALIZED DEGREE OF LIKING SURVEY SCALE AND ITEMS USED IN CHAPTERS 4 AND 5 ........................................................................................... 281
APPENDIX B -‐ GENERALIZED DEGREE OF LIKING SURVEY ITEMS USED IN CHAPTER 6 ............................................................................................................................ 283
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List of Figures
Figure 2-1. Perceptual map of 11 chemesthetic compounds sorted in a free sorting task by participants not wearing nose clips (N=30), with descriptors projected onto the map via regression. Stimuli include allyl isothiocyanate (AITC), capsaicin (CAP), carvacrol (CARV), cinnamaldehyde (CINN), citric acid (CA), eucalyptol (EUCA), eugenol (EUG), huajiao (HJ), menthol (MEN), quinine (Q), and zingerone (ZING). ................................ 68
Figure 2-2. Same as Figure 2-1 (map of 11 chemesthetic stimuli from sorting by 30 participants not wearing nose clips), but with clusters generated via agglomerative hierarchical cluster analysis (agglomerative coefficient = 0.83). Stimuli use the same abbreviations as Figure 2-1. .............................................................................................. 70
Figure 2-3. Dendrogram from agglomerative hierarchical clustering of the sorting done by 30 participants not wearing nose clips. Agglomerative coefficient is 0.83. ................ 71
Figure 2-4. Perceptual map with clusters generated by the participants that completed the free sorting task on 11 chemesthetic compounds with nose clips (N=31). A three-dimensional solution was most appropriate (stress = 0.002) for this group. Notation is in the style of the Natta projection: Dimension 3 in the bottom left of the figure with the dotted line represents values farther away from the viewer (negative values on dimension 3) and the bolded line indicating that the plane is closer to the viewer (positive values on dimension 3). The positions of points with respect to dimension 3 are indicated by the size and color of the point. Larger, lighter blue points, (e.g. CINN), are closest to the viewer, while smaller, redder points, (e.g. MEN), are farthest from the viewer. For a fully expanded 2D scatterplot matrix projection of the 3D space, see Supplemental Materials............................................................................................................................................ 72
Figure 2-5. Dendrogram from agglomerative hierarchical clustering of sorting done by 31 participants with nose clips. Agglomerative coefficient is 0.79. ................................. 73
Supplemental Figure 2-1. Scatterplot matrix of the perceptual map generated by the nose-pinched cohort. ......................................................................................................... 87
Supplemental Figure 2-2. Setup used for the sorting task for both cohorts. .................. 88
Figure 3-1. Perceptual map of 11 chemesthetic compounds sorted in a free sorting task by 26 assessors with low Food Involvement Scale scores. Regression was performed to regress descriptors generated by participants onto the perceptual map. Stimuli include allyl isothiocyanate (AITC), capsaicin (CAP), carvacrol (CARV), cinnamaldehyde (CINN), citric acid (CA), eucalyptol (EUCA), eugenol (EUG), huajiao (HJ), menthol (MEN), quinine (Q), and zingerone (ZING). .................................................................. 108
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Figure 3-2. Two-dimensional perceptual map similar to Figure 3-1, except participants were from the high FIS score group (n = 25). ................................................................ 110
Figure 3-3. Two-dimensional perceptual map similar to Figures 3-1 and 3-2, but for the expert cohort (n = 32). .................................................................................................... 111
Figure 4-1. Relationship between self-reported liking of a spicy meal and yearly chili intake. Individuals were asked to rate how much they like or dislike a spicy meal on a generalized hedonic scale. Participants reported their intake of chili-containing foods on a 7-point scale, ranging from “never” to “two or more times a day”. This intake frequency was converted to an annualized frequency and quarter root transformed. The r-value reported on the figure is the correlation between liking scores for a spicy meal and yearly chili intake (quarter root transformed). ........................................................................... 165
Figure 4-2. Strong positive relationship between scores on the Arnett Inventory of Sensation Seeking and self-reported liking of a spicy meal. Sensation Seeking was measured using Arnett’s Inventory of Sensation Seeking (1994). ................................. 167
Figure 4-3. Strong positive relationship between annualized chili intake and scores on the Arnett Inventory of Sensation Seeking and self-reported liking of a spicy meal. .... 168
Figure 4-4. Relationships between Sensitivity to Punishment, Sensitivity and Reward, and liking of a spicy meal. Sensitivity to Reward showed a significant positive correlation with the liking of a spicy meal. In contrast, Sensitivity to Punishment showed a nonsignificant trend towards a negative relationship with spicy meal liking. ................ 169
Figure 4-5. A moderate positive relationship was observed between yearly chili intake and Sensitivity to Reward. .............................................................................................. 170
Figure 5-1. Visual representation of moderation models to be tested in this protocol. Model 1 depicts the potential moderation of the relationship between perceived intensity of burning/stinging of a 25uM capsaicin sample and liking of spicy foods by personality traits. Model 2 depicts potential moderation by personality of the relationship between liking and intake of spicy foods. ..................................................................................... 190
Table 5-2. Moderator effects of personality on the relationship between liking and intake of spicy foods. Main effects of spicy foods (spicy meal, spicy Asian foods, or spicy and or BBQ spare ribs), and personality (AISS, SP, or SR), are reported for each model as well as interaction effects of spicy food and personality. AISS is Sensation Seeking, SP is Sensitivity to Punishment, and SR is Sensitivity to Reward. Standardized regression coefficients are reported. Significant main effects of personality or liking of spicy foods and significant interaction effects are highlighted .......................................................... 200
* p<0.05, ** p<0.01, *** p<0.001 .................................................................................. 200
Figure 6-1. Liking of the burning/stinging sensation in 3µM and 12µM capsaicin-spiked jelly versus perceived intensity of the burning/stinging sensation in 3 µM and 12 µM capsaicin-spiked jelly. On the left are capsaicin dislikers while on the left are capsaicin
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likers. Points on the plot indicate the location of the 3 µM capsaicin-spiked jelly sample on the plot. Along the x-axis, the labels, and corresponding values from the gLMS are plotted. ............................................................................................................................ 236
Figure 6-2. Diagram of significant correlations between personality variables used in this study. Dashed lines indicate negative relationships. Line thickness and darkness indicate strength of the correlation. * indicates association of personality measure with yearly intake of spicy foods and ** indicates association of personality measure with liking of spicy foods and yearly intake of spicy foods. ................................................................. 242
Figure 6-3. Proposed path model for the effects of various personality traits on liking and intake of spicy foods. All values shown are correlations. On the far left, the correlations between the personality measures are shown. The triple line arrows indicate that these relationships have been previously shown. * p < 0.05, ** p < 0.01, *** p < 0.0001. .... 245
Supplemental Figure 6-1. Liking versus Perceived Intensity for stimuli. The orange points lie along a hypothetical inverted-U-shaped function representing the relationship between liking and intensity across a range of concentrations. This plot highlights the possibility that sampling with two points does not provide adequate resolution to determine an individual’s hedonic response profile to capsaicin. .................................. 276
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List of Tables
Table 3-1. Summary of how three cohorts used descriptors differently. ....................... 113
Table 3-2. Mean number of attributes generated and mean number of groups formed by each cohort. Superscript letters indicate statistically significantly different values (p < 0.05). ............................................................................................................................... 113
Table 4-1. Correlation matrix of personality measures used in the present study. Private Body Consciousness (PBC) showed no correlation with any of the other measures used. Arnett’s Inventory of Sensation Seeking (AISS) showed significant correlations with both subscales of the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ). The SP and SR subscales of the SPSRQ were not correlated with each other. Bolded values are significant at p < 0.0001. ................................................................... 166
Table 5-1. Moderator effects of personality on the relationship between perceived intensity of burning/stinging and liking of spicy foods. Standardized regression coefficients are reported. * p<0.05, ** p<0.01, *** p<0.001 ......................................... 198
Table 6-1. Correlation matrix of personality measures. R-values are reported, with asterisks indicating p-values ........................................................................................... 235
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Acknowledgements
To John Hayes: It has been a learning experience from the beginning to the end, both personally and professionally, and looking back, I am surprised by how far I have come in three years. Thank you for all of the amazing opportunities and for allowing me the opportunity to work with some of the brightest minds in sensory and food science. To my committee: Thank you for providing such a supportive environment in which to do my PhD. Thank you for challenging me, making me come at things from a different angle, and treating me as an academic equal. The past three years have been an amazing and unique experience. To my lab mates: Alissa, Emma, Rachel A, Rachel P, Erin, Catherine, Sam, Alyssa, Toral, Demi, and Michelle. Thank you all for always being so supportive. From day one you have made the lab somewhere that I love coming to and somewhere where I know I can always find a friend. All of the late night g-chat conversations, venting sessions in 225, numerous hugs, tears, dance parties, sing-a-longs, and eating parties have made the past three years incredible. Thank you for helping to keep me excited about all of the wonderful things that there are to explore in the world of sensory science. You are great coworkers, role models, support systems, and motivators. You will never know how much I love, appreciate, and respect you all. The lab is what made me come to Penn State and you better bet that I will be back at Penn State to pay you all lots of visits. To the Hayes Lab undergrads: Geneva, Brianne, Meghan, Laura, and Amanda. Thank you for the numerous hours prepping samples, labeling cups, painting tongues, dealing with spit cups, running sessions, and coming in an odd hours of the morning, night, and weekends to get it all done. You are all phenomenal women and I look forward to seeing where the road takes you. To Duane, Mia, Maia, and Max: Three quarters of you will never read this but hopefully you still know how much I love you. Duane, thank you for bringing 2/3 of the M&M’s into my life and for being a loving but stubborn pain in my butt. The beginning wasn’t easy but I’m so glad that you were patiently waiting. Thank you for forcing me to slow down and enjoy life through all the work. All of the hugs, kisses, snuggles, movie nights, long walks in the game lands, and weekend sleep-ins have kept me sane. I am going to miss coming home and seeing all of your smiling faces at the end of a long day. To my family: None of this would be possible without your love and support. I have learned more from you all than I ever could from any class or book and I owe all of my success to everything that you have taught me. In your own unique way each of you has served as a
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source of inspiration and encouragement that helped me get through the past 27 years. There are no words that adequately express how much you all mean to me. Thank you for always pushing me, making me think, telling me when I was wrong, letting me vent, letting me cry, picking me up, and loving me unconditionally through all of it. I owe everything that I am and have accomplished to you. Thank you for making me the person that I am today.
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Objectives
Study 1 Aim 1: Determine if sorting can be conducted reliably with chemesthetic stimuli in naïve assessors. Aim 2: Explore perceptual similarities of nine chemesthetic stimuli and two taste stimuli using sorting in naïve assessors. Study 2 Aim1: Examine the effect of formal culinary training on the perception of chemesthetic stimuli. Aim2: Explore differences in language use pertaining to chemesthetic stimuli between individuals with formal culinary training, high food involvement naïve assessors, and low food involvement naïve assessors. Study 3 Aim 1: Explore the relationship between personality and the perceived intensity of the burning/stinging of spicy foods using the personality traits Sensation Seeking, Sensitivity to Punishment, Sensitivity to Reward, and Private Body Consciousness. Aim 2: Determine the relationship between personality and the liking of spicy foods using the personality traits Sensation Seeking, Sensitivity to Punishment, Sensitivity to Reward, and Private Body Consciousness. Aim 3: Explore the relationship between Sensation Seeking and intake of chili-containing foods. Study 4 Aim 1: Use moderation models to explore the nature of the relationship between perceived burning/stinging of spicy foods, liking of spicy foods, and personality traits. Aim 2: Use moderation models to explore the nature of the relationship between liking of spicy foods, intake of spicy foods, and personality traits. Study 5 Aim 1: Employ a number of self-report and behavioral measures of risk-related personality traits to explore the relationship between personality and liking of sampled spicy foods. Aim 2: Employ a number of self-report and behavioral measures of risk-related personality traits to explore the relationship between personality and intake of spicy foods. Aim 3:Assess how several self-report and behavioral measures of risk-related personality traits relate to one another in a non-clinical population. Aim 4: Examine whether different responder types exist regarding capsaicin liking utilizing measures of sampled food liking.
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Abbreviations/Definitions
5-HT – serotonin transporter AAP – Average adjusted pumps on the mBART Adj. R-Sq. – Adjusted R-squared ADSA – the American Dairy Science Association AISS – Arnett’s Inventory of Sensation Seeking AISS-IS – Intensity Seeking subscale of the Arnett’s Inventory of Sensation Seeking AISS-NS – Novelty Seeking subscale of Arnett’s Inventory of Sensation Seeking AITC – Allyl isothiocyanate BART – Balloon Analogue Risk Task BAS – Gray’s Behavioral Activation/Approach System BGT – Bechara Gambling Task BIS – Gray’s Behavioral Inhibition System BS – Boredom Susceptibility subscale of Zuckerman’s Sensation Seeking Scale form V BSSS – Brief Sensation Seeking Scale CA – Citric acid CAP – Capsaicin CARV – Carvacrol CATA – Check-all-that-apply Chemesthesis – The sensation that arise when chemical stimuli in foods activate free nerve endings. CINN – Cinnamaldehyde COMT – catechol-O-methyltransferase DIS – Disinhibition subscale of Zuckerman’s Sensation Seeking Scale form V DRD4 – dopamine 4 receptor gene DSM-5 - Diagnostic and Statistic Manual of Mental Disorders V EPI – Eysenck Personality Inventory EPQ-R – Eysenck’s Personality Questionnaire ES – Experience Seeking subscale of Zuckerman’s Sensation Seeking Scale form V EUCA – Eucalyptol EUG- Eugenol FCC – Food Chemical Codex FFS – Gray’s Flight/Flight System FG – Food Grade FIS – Food Involvement scale FNS – Food Neophobia Scale FP – Flash Profiling FP – fungiform papillae – one of the types of papillae on the tongue that houses taste buds gDOL – generalized Degree of Liking questionnaire GIANT-CS – Genetically Informed Analysis of Natural Tastants and Chemesthetic Stimuli gLMS – general Labeled Magnitude Scale HA – Harm Avoidance dimension on Cloninger’s taxonomy of personality HJ – huajiao IMP – inosine 5 monophosphate ImpSS – Zuckerman’s Impulsive-Sensation Seeking scale, part of the Zuckerman-Kuhlman Personality Questionnaire IQR – Interquartile range IVE – Eysenck’s Impulsivity Inventory
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mBART – Momentary Balloon Analogue Risk Task MDS – Multidimensional Scaling MEN – Menthol MSG – monosodium glutamate NEO-PI-R – Revised NEO Personality Inventory (N – Neuroticism, E – Extraversion, O – Openness to experience) NRV – Normalized RV coefficient NS – Cloninger’s personality organization, Novelty Seeking P&E – Preparation and Eating subscale of the Food Involvement Scale PBC – Private Body Consciousness PID-5 – Personality Inventory from the Diagnostic and Statistic Manual of Mental Disorders V PID5-I – Impulsivity subscale from the PID-5 PID5-RT – Risk Taking subscale from the PID-5 PROP – 6-n-propylthiouracil PSP – Polarized Sensory Positioning Q – Quinine RD – Reward Dependence dimension of Cloninger’s taxonomy of personality RO – Reverse osmosis RST – Reinforcement Sensitivity Theory S&D – Setup and Disposal subscale of the Food Involvement Scale SE – Standard Error Somatosensation – Commonly called “touch” sensations”. Actually a collection of a number of different types of sensations including mechanoreception, thermoreception, and nociception. SP – Sensitivity to Punishment subscale of the Sensitivity to Punishment and Sensitivity to Reward Questionnaire SPSRQ – Sensitivity to Punishment and Sensitivity to Reward Questionnaire SR – Sensitivity to Reward subscale of the Sensitivity to Punishment and Sensitivity to Reward Questionnaire SSS-V – Zuckerman’s Sensation Seeking Scale form V STAI-T – State-Trait-Anxiety Inventory TAS – Thrill and Adventure Seeking subscale of Zuckerman’s Sensation Seeking Scale form V TAS2R38 – gene that encodes the taste receptor 2 member 38 (TAS2R38 protein) TRPA – Transient Receptor Potential Ankyrin family of receptors TRPC – Transient Receptor Potential Canonical family of receptors TRPM – Transient Receptor Potential Melastatin family of receptors TRPV – Transient Receptor Potential Vanilloid family of receptors TRPV1 – Transient Receptor Potential Vanilloid receptor subtype 1 (Also know as VR1 or the capsaicin receptor) Type I responder – inverted-U-shaped Type II responder – linearly increasing Type III responder – linearly decreasing Type IV responder – no systematic change in response USP – U.S. Pharmacopeia grade VARSEEK – Variety Seeking scale VR1 – Vanilloid Receptor 1 (also known as TRPV1 or the capsaicin receptor) ZING – Zingerone ZKPQ – Zuckerman-Kuhlman Personality Questionnaire
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Chapter 1
Literature Review
Introduction
The desire for spices is not a new fascination, in fact, it has been suggested that
humans’ desire for spices fueled the Age of Discovery and altered the course of history,
(Le Couteur & Burreson, 2004). After being introduced to Europe by Christopher
Columbus, capsaicin, the pungent compound in chili peppers, did not catch hold in
Europe as quickly as piperine, the compound responsible for peppercorn pungency,
however, the chili pepper spread quickly around the world and in under 50 years was
incorporated into local cuisines across the globe. In the centuries since then, the desire for
this pungent compound has not diminished. A recent Mintel report from June 2014
showed that nearly 75% of Americans say that they are interested in trying spicy peppers,
chiles, and spices in restaurant dishes (Fajardo, 2014). This study also showed that across
the U.S., restaurant patrons are demanding cuisines and foods that contain chemesthetic
compounds. Anyone who has ever ingested capsaicin knows that this compound elicits a
burning sensation that can be quite unpleasant, which begs the question, why would
anyone want to be in pain?
Before exploring the motivation for voluntarily inflicting pain on oneself in the
form of capsaicin, this chapter will give a review of the pertinent literature. The review
will begin with a brief overview of chemesthesis and how capsaicin produces a pain
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response. Then, individual differences in hedonic response to this sensation will be
covered as well as motivations for food choice. Next, the review of possible motivations
for consumption of capsaicin will be split into three sections. It is unlikely that these
systems operate completely separately, but as of yet, the amount to which the systems
overlap is not determined, so for the purpose of this review the systems have been split
into three sections. The first covers biological reasons why an individual may be more or
less sensitive to capsaicin. The next section covers social reasons why an individual may
consume capsaicin. The final section covers psychological, or personality, reasons why
an individual may actually enjoy the sensation elicited by capsaicin
Somatosensation, chemesthesis, TRPV1, and capsaicin
Somatosensation, or what many call the sense of touch, is actually a collection of
different types of sensation that include mechanoreception (the detection of mechanical
stimuli or distortion), thermosensation (the detection of cooling and warming), and
nociception (the detection of noxious thermal, mechanical, and chemical stimuli that can
cause pain; (Gardner, Martin et al., 2000). Chemesthesis, a term coined by Barry Green
(Green), refers to the sensations that elicited when chemical stimuli activate nociceptors.
Chemesthetic sensations do not fit into the classical definitions of taste or smell but play
a critical role in the flavor of a number of foods, such as peppermint, chili peppers,
cinnamon, and ginger.
Stimuli in our foods, such as capsaicin in chili peppers, are initially detected by
primary afferent sensory nerve fibers that innervate the oral cavity, as well as the lips,
which transmit signal to the brain via ascending neural circuits (Basbaum & Jessell,
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2000). Taste sensations are carried by the three cranial nerves, the facial nerve (cranial
nerve VII), the glossopharyngeal nerve (cranial nerve IX), and the vagus nerve (cranial
nerve X) that innervate taste cells on the tongue and in the throat and mouth, while
chemesthetic sensations are carried by the trigeminal nerve (cranial nerve V), which
innervates the whole palate (Lawless & Heymann, 2010; Nilius & Appendino, 2011).
Noxious stimuli, such as capsaicin, are sensed when they react with a family of receptors
expressed on the trigeminal nerve, called the transient receptor potential (TRP) channels.
TRP channels were first discovered in the fly eye and more than 50 types of TRP
receptors can be found in yeast, fish, worms, insects, and mammals (Nilius & Voets,
2005; Vriens, Owsianik et al., 2004). Over 30 distinct members of the TRP family can be
found in mammals alone (Ramsey, Delling et al., 2006). TRP subunits are made up of six
transmembrane domains and a cation-permeable pore between subunits 5 and 6 and are
known to assemble into homo- or heteromeric tetramers to form a cation selective
channel (Nilius & Voets, 2005). There are six subfamilies of TRP channels, essentially
grouped based on their amino acid sequence similarity. Of receptors expressed in
mammals, the TRPM (melastatin) subfamily has eight members (TRPM1-TRPM8); the
TRPC (canonical) subfamily has seven members (TRPC1-TRPC1), the TRPA (ankyrin)
subfamily has one member (TRPA1), and the TRPV (vanilloid) subfamily has six
members (TRPV1-TRPV6).
TRPV1, or the capsaicin receptor (vanilloid receptor 1; VR1), was the first
member of the mammalian TRPV channels to be identified (Caterina, Schumacher et al.,
1997). TRPV1 is activated by noxious heat (≥ 43C), protons, pH ≤ 5.9, and an array of
compounds found in food, including piperine, eugenol, zingerone, and capsaicin
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(Tominaga, Caterina et al., 1998; Vriens, Nilius et al., 2008). When capsaicin and related
vanilloid compounds activate TRPV1, they elicit sensations of acute burning pain
accompanied by local vasodilation and inflammation, which are followed by
hypersensitivity to heat and touch (Jancso, Kiraly et al., 1977; Jancso, Jancsó‐Gábor et al.,
1967). The onset of these sensations is delayed slightly, as compared to the onset of the
taste of salt, because the binding site on TRPV1 for vanilloids is on the intracellular
portion of the receptor, and capsaicinoids must cross the cell membrane before reacting
with the binding site (Jung, Hwang et al., 1999).
The burning sensation that capsaicin produces arises from the fact that capsaicin
sensitizes the receptor to heat, lowering the thermal activation threshold of TRPV1 from
around 42C to below body temperature. While the effect of the interaction is to sensitize
the receptor to heat, capsaicin is not classified as a sensitizer, or compounds that affect
the function of the receptor indirectly (Vriens, Appendino et al., 2009), as capsaicin binds
directly to the TRPV1 receptor and acts as a positive allosteric modulator (Julius &
McCleskey, 2006). Recent work from the Julius lab has provided information regarding
the structure and activation of TRPV1, however the exact mechanism of vanilloid
binding still remains unclear (Cao, Liao et al., 2013).
Individual variation in hedonic response
A wide range of hedonic responses to capsaicin is reported, from individuals
disliking any irritation to those individuals that simply cannot get enough pungency
(Prescott & Stevenson, 1995a; Rozin & Schiller, 1980; Tepper, Keller et al., 2004). Some
individuals report even enjoying piquancy when it is isolated from food or beverages.
5
Generally, an individual’s first encounter with capsaicin is aversive, due to the oral
irritation this compound elicits, raising the question why anyone would repeatedly
consume a compound that is irritating. However, there are numerous examples of
substances that are initially aversive, yet individuals can learn to like these substances,
such as alcohol, coffee, and tobacco (Rozin & Schiller, 1980). For these foods there are
often post-ingestive or social effects that influence liking and consumption (Rozin &
Schiller, 1980), such as the energizing effects of caffeine, which may overcome the
aversive bitterness of coffee. Post-ingestive effects of capsaicin consumption, such as
increased postprandial energy expenditure and elevated body temperature, have been
reported (Ludy & Mattes, 2011b; Rozin & Schiller, 1980), and it has been posited that
these effects may be a factor in the consumption of capsaicin-containing foods (Rozin &
Schiller, 1980), however little evidence exists to support this hypothesis. Food
preferences have been linked to a number of factors including sex, age, weight, genetics,
personality, and primary type of cuisine eaten while growing up (Logue & Smith, 1986b).
Food Choice
Food choice is a complex task that individuals encounter multiple times each day
(Connors, Bisogni et al., 2001; Eertmans, Victoir et al., 2005; Rozin & Vollmecke, 1986),
with some reports citing that an average of over 200 food choice decisions are made per
day (Wansink & Sobal, 2007). There are a multitude of food-related and food-external
factors to consider when making food choices (e.g. (Bell, Meiselman et al., 1995;
Eertmans, Baeyens et al., 2001b; Rozin, Guillot et al., 2013) but without economic and
availability constraints, liking is the primary driver of consumption (Cowart, 1981; Duffy,
6
Hayes et al., 2009; Randall & Sanjur, 1981; Rozin & Zellner, 1985; Schutz, 1957).
Biological differences
Reasons proposed to explain differences in consumption of foods that elicit oral
irritation include physiological differences such as genetic variation (Hayes, Allen et al.,
2013), oral anatomy (Miller & Reedy, 1990), and taste phenotype (Duffy, 2007; Duffy &
Bartoshuk, 2000). There are well-established differences in the sensitivity of individuals
to the pungency of capsaicin and the overall liking of the irritation sensation produced by
capsaicin in foods (Lawless, Rozin et al., 1985; Prescott & Stevenson, 1995b; Stevenson
& Prescott, 1994; Stevenson & Yeomans, 1993b; Yoshioka, Doucet et al., 2001). This
section will give a brief overview of the biological variations that may result in individual
differences in perceived intensity of capsaicin and capsaicin-containing foods.
Genetics - variability in sensation and diet
Genetic variation has previously been shown to explain differences in oral
sensation and dietary choices (for a review see (Hayes, Feeney et al., 2013)). For example,
variation in the TAS2R38 gene has been associated with differences in bitterness
perception and intake of vegetables. Most commonly, there are two haplotypes, or
collections of alleles, of the TAS2R38 gene that occur, the PAV and the AVI haplotype.
These haplotypes are named based on which of two amino acids that are present at three
specific locations in the amino acid sequence. At position 49, a proline (P) or alanine (A)
is present, at position 262, an alanine (A) or valine (V) is present, and at position 296, a
7
valine (V) or isoleucine (I) is present. For further information, see Kim et al (2003).
Individuals carrying at least one copy of the PAV haplotype, or PAV carriers, tend to
report the intensity of bitter compounds higher than AVI/AVI carriers (also known as
AVI homozygotes), and report lower consumption of vegetables (Duffy, Hayes et al.,
2010; Sacerdote, Guarrera et al., 2007). Duffy and colleagues showed that TAS2R38 also
associates with alcohol intake, with PAV homozygotes consuming less alcohol than PAV
heterozygotes (one copy of PAV haplotype and one copy of AVI haplotype), who
consumed less alcohol than AVI homozygotes.
In addition to genetic variation accounting for differences in taste sensations,
variation in levels of salivary protein content have been associated with perception and
liking of astringent foods (Dinnella, Recchia et al., 2011; Dinnella, Recchia et al., 2010;
Horne, Hayes et al., 2002). Individuals that experience higher levels of salivary protein
depletion after stimulation with phenolic stimuli, or high responding (HR) individuals,
show higher perceived levels and lower liking of astringent stimuli than their low
responding (LR) counterparts. A recent study suggests that differences in salivary protein
levels, and thus, astringency perception may be genetically determined (Törnwall,
Silventoinen, Keskitalo-Vuokko et al., 2012).
As with the perception of the chemesthetic sensation, astringency, it has been
suggested that the variability in the response to capsaicin is due to polymorphisms in the
TRPV1 capsaicin receptor (Park, Lee et al., 2007; Snitker, Fujishima et al., 2009).
Recently, Törnwall and colleagues presented evidence of a common genetic mechanism
responsible for the liking of various types of oral pungency (Törnwall, Silventoinen,
Keskitalo-Vuokko et al., 2012). Between 18 and 58% of the variation in hedonic
8
responses to oral pungency were explained by genetics, however no genetic mechanism
has been identified. These values fall within the range of heritability previously reported
for sweet and sour preferences (Keskitalo, Knaapila et al., 2007).
While genotypic variation may account for some of the differences observed in
perception and liking of various oral sensations, it is critical to note that phenotypic
variation also plays a role in these perceptual differences. Variability in responses to 6-n-
propylthiouracil (PROP) are explained for the most part by polymorphisms of the
TAS2R38 gene (Kim, Jorgenson et al., 2003), with carriers of the PAV allele tending to
show a higher perceived intensity of suprathreshold PROP solutions than carriers of the
AVI allele. Originally, the term “supertaster” was used to describe these individuals that
perceived high intensity from PROP. However, work from Hayes and colleagues (Hayes,
Bartoshuk et al., 2008) have shown TAS2R38 genotype does not account for all observed
variability in PROP perception and that other receptors may play a role in determining
PROP bitterness (Hayes, Bartoshuk et al., 2008). Thus, it is possible to have a supertaster
who is heterozygous for TAS2R38 (PAV/AVI) or a medium taster who is homozygous
for the high function haplotype (PAV/PAV); that is, supertasting is based on the
phenotype, not the genotype.
This has lead to the contemporary understanding that supertasting is an overall
increased response to stimuli. It has also been suggested that in addition to heightened
taste responsivity, supertasters have greater sensory acuity and are able to discriminate
smaller differences in foods (Bartoshuk, Duffy, Chapo et al., 2004; Hayes & Pickering,
2012; Tepper & Nurse, 1998). Recently, in an effort to disentangle the concept of
supertasting as it relates to PROP response and overall taste response, there has been a
9
push by some scholars to rename this concept of overall elevated response as
“hypergeusia” (thus those individuals that are broadly supertasters would be called
“hypergeusics”; (Hayes & Keast, 2011).
With relevance to understanding the phenotypic variation in chemesthetic
sensations, researchers have shown that supertasters, based on their response to PROP,
have a broad heightened response to a wide range of chemosensory stimuli (Bajec &
Pickering, 2008; Bartoshuk, Duffy et al., 1994; Hayes, Bartoshuk et al., 2008; Hayes &
Duffy, 2007; Pickering & Robert, 2006; Pickering, Simunkova et al., 2004; Tepper &
Nurse, 1998). It is possible that supertasters also perceive more aversive sensations from
chemesthetic stimuli, as supertasters reportedly perceive increased burn from capsaicin
(Karrer & Bartoshuk, 1991b; Karrer, Bartoshuk et al., 1992). Additionally, it has been
reported that some individuals who tend to perceive higher taste intensity from
prototypical tastants report a bitter side taste from the prototypical irritants capsaicin,
piperine, and zingerone on the posterior tongue (Green & Hayes, 2004), which may also
increase the aversiveness of these chemesthetic stimuli.
Anatomy - oral phenotypes and sensation
One of the proposed reasons for differences in sensory intensity and/or acuity is
variation in oral anatomy. Fungiform papillae (FP) are one of the three types of papillae
on the tongue that house taste buds.. Taste buds are housed in FP, which are most dense
near the tip of the tongue, thus counting FP on the tip of someone’s tongue can be used as
a proxy measure of overall taste bud density, and thus, a measure of overall taste function
(Miller & Reedy, 1990). Early studies show that individuals with higher FP density
10
perceive more intensity from bitter, sweet, and salty tastes (Miller & Reedy, 1990). A
relationship has also been shown between FP density and PROP supertasting, suggesting
that PROP supertasters have more FP (Bartoshuk, Duffy et al., 1994; Essick, Chopra et
al., 2003; Miller & Reedy, 1990).
It has also been suggested that PROP supertasters perceive more burn from
capsaicin than PROP non-tasters (Karrer & Bartoshuk, 1991b; Karrer, Bartoshuk et al.,
1992). The hypothesis linking burn perception and FP density arose from the
understanding that nociceptive fibers are collocated in taste papillae. A higher density of
FP in supertasters (Bartoshuk, Duffy et al., 1994; Miller & Reedy, 1990) would lead to a
greater density of nociceptive fibers with which to perceive the burn of capsaicin.
However, evidence to support the association is inconsistent. Work from Tepper and
Nurse (Tepper & Nurse, 1998) and unpublished work from Karrer and colleagues (Karrer,
Bartoshuk et al., 1992) showed that PROP tasters had a higher density of FP and were
more sensitive to capsaicin. In contrast, Prescott and Swain-Campbell tested the
relationship between PROP supertasting and perceived capsaicin intensity and found no
association, whether PROP supertasters were in a group separate or combined with
medium tasters (Prescott & Swain-Campbell, 2000). Similarly, Törnwall and colleagues
showed no association between PROP taster status and responses to oral pungency
(Törnwall, Silventoinen, Kaprio et al., 2012). The inconsistency in findings indicate that
while PROP is a reliable predictor of taste sensitivity, this compound may not be a
reliable predictor of individual differences in response to chemesthetic stimuli.
11
Effects of exposure on chemesthetic response (Social)
While biological variation may play a role in determining baseline sensitivity to
the oral sensations elicited by chemesthetic agents, these genetic and phenotypic
differences do not account for the fact that individuals can actually come to enjoy the
sensation that capsaicin produces, irrespective of initial experience. Individual
differences in the liking of the sensation elicited by capsaicin have been proposed to arise
primarily from prior experiences and familiarity with capsaicin and capsaicin-containing
foods (Ludy & Mattes, 2012; Stevenson & Yeomans, 1995). This portion of the chapter
is devoted to exploring how exposure and familiarity with capsaicin-containing foods
might result in increased liking of capsaicin.
Desensitization
Frequent users of spicy foods often rate the burn of capsaicin as less intense and
more pleasant than infrequent users of spicy foods, and it has been suggested that the
reported liking of spicy foods is merely the effect of reduced sensitivity to the burning
sensation via desensitization (Lawless, Rozin et al., 1985; Prescott & Stevenson, 1995a;
Stevenson & Yeomans, 1995). In other words, individuals increase their consumption of
capsaicin-containing foods not because they enjoy the burning sensation, but because
they no longer perceive it as a result of their prior consumption. Both acute and chronic
desensitization to capsaicin are well-established phenomena following exposure (Cowart,
1987a; Green & Shaffer, 1993; Karrer & Bartoshuk, 1991b; Lawless, Rozin et al., 1985;
Logue & Smith, 1986b; Rozin, Mark et al., 1981; Stevenson & Prescott, 1994), however
12
the mechanism of desensitization has not yet been determined. Rozin and Schiller
examined desensitization and liking in two populations with varying levels of capsaicin
consumption – American adults and adults and children from a rural Mexican village
(Rozin & Schiller, 1980). They hypothesized that the higher consumption of capsaicin
containing foods among the Mexicans would lead to 1) higher detection thresholds for
capsaicin among the Mexicans, 2) positive correlations between detection thresholds and
degree of exposure, and 3) higher detection thresholds among individuals who report
liking capsaicin than among those who are neutral to it or dislike it. In contrast to their
expectations, only a small, non-significant difference in threshold for capsaicin was
apparent between the Mexican and American groups. Additionally, there was no
difference in thresholds between American chili likers and dislikers. When examining
detection thresholds, preference levels, and tolerance thresholds they observed an
astonishing consistency between Mexicans and Americans. Chili preference and
tolerance levels correlated with detection thresholds in the range of 0.20 to 0.39 while
preference and tolerance levels correlations were between 0.8 and 0.9. These results
suggest that decreased sensitivity at threshold (i.e. increased detection threshold) does not
predict increased liking of capsaicin-containing foods. Rozin and Schiller also explored
whether threshold increased with exposure, and hence with age, but no significant effects
were seen (Rozin & Schiller, 1980). Collectively, the work examining the effect of
desensitization on liking suggests that while there may be a small desensitization effect
from eating chili pepper in moderate amounts (Rozin, Mark et al., 1981), the effect is
slight and is unlikely to play an important role in determining the liking of capsaicin.
13
Affective shift - “learning to like”
Rather than increased liking resulting from decreased perceived intensity, it has
been proposed that spicy food likers actually do enjoy the burning sensation that comes
from eating capsaicin (Rozin & Schiller, 1980; Stevenson & Yeomans, 1993b). Indeed, in
the surveys conducted by Rozin and Schiller, Mexican subjects did not seem to like the
flavor of chili peppers when the pungency was removed (Rozin & Schiller, 1980).
Stevenson and Yeomans (Stevenson & Yeomans, 1993b) observed a similar effect, in
that pleasantness ratings were higher for likers than non-likers, even when the samples
being compared were rated as having the same perceived burning intensity. Proposed
mechanisms for this affective shift include the physiological consequences of ingestion,
such as increased salivary flow, which may help in digestion of the starch-heavy diets
that are common in areas where capsaicin is regularly consumed, such as in traditional
Mexican cuisine (Rozin & Schiller, 1980). Other mechanisms include the association of
capsaicin with satiating, or otherwise pleasant foods, which would lead to conditioned
liking for the burning sensation (Rozin & Schiller, 1980; Rozin & Vollmecke, 1986).
Culture and familiarity
Yet another proposed mechanism for the observed shift in liking of capsaicin, and
by far the most extensively studied, is the hypothesis of “mere exposure”. In the late
1960’s Zajonc suggested “mere exposure of the individual to a stimulus enhances his
attitude toward it” (Zajonc, 1968); p. 1). The effects of mere exposure have been
observed in rodents with various food stimuli, with repeated exposure to saccharin
14
(Carroll, Dinc et al., 1975; Domjan, 1972; Domjan, 1976; Domjan & Gillan, 1976;
Mitchell, Scott et al., 1977; Nachman, 1959), casein (Domjan & Bowman, 1974), milk
(Williams, 1968), garlic flavor (Capretta & Rawls, 1974), the bitterant sucrose octa-
acetate (Warren & Pfaffmann, 1959), and coffee and vinegar (Siegel, 1974) increasing
rodents’ liking of the initially unfavorable stimuli.
The “exposure hypothesis” has shown significant effects in adult humans using a
variety of stimuli such as musical passages (Mull, 1957), human faces (Zajonc, 1968),
paintings (Maslow, 1937), and foods. Under controlled conditions, repeated taste
exposures and modeling behaviors have been shown to increase preference and
acceptance of various foods in infants (Sullivan & Birch, 1994), children (Horne, Tapper
et al., 2004; Lakkakula, Geaghan et al., 2010; Sullivan & Birch, 1990; Wardle, Cooke et
al., 2003; Wardle, Herrera et al., 2003), and adults (Pliner, 1982). In examining factors
that are important to determining children’s liking of foods, Birch observed that
familiarity was one of two key dimensions (Birch, 1979a; Birch, 1979b). Birch and
Marlin later showed, in a six-week exposure period to various types of cheeses, that
preference for the cheeses in children was a clear function of exposure (Birch & Marlin,
1982). The effect of exposure on acceptance and preference of foods is not limited to
children. Similar exposure effects have also been observed in adults (e.g. (Crandall, 1985;
Pliner, 1982), with liking increasing between initial and final exposure of the stimuli.
(Also, (Stein, Nagai et al., 2003).
While there is an extensive body of literature that supports the affective shifts
from “mere exposure”, data on the number of exposures necessary to increase liking or
preference are inconsistent. In young children one exposure may be sufficient, while in
15
school-aged children and adults, up to 15 exposures may be necessary. Additionally, the
type of food presented is important in determining how many exposures will be necessary
to induce a liking or preference alteration (Costa, Balthazar et al., 2014; Horne, Tapper et
al., 2004; Liem & De Graaf, 2004; Sullivan & Birch, 1994; Wardle, Cooke et al., 2003;
Wardle, Herrera et al., 2003). For example, Costa et al. (Costa, Balthazar et al., 2014)
recently determined that even while strong positive correlations (r = 0.99) were observed
between exposure and acceptance of goat’s milk yogurts, rapid, repeated exposure over
six days were not sufficient to generate a significant change in acceptance of the product.
It is important to note that the literature presented here highlights the effects of
exposure by consuming foods, though evidence also suggests that it might not be
necessary to actually consume the novel food to see effects of mere exposure on liking
(Birch, 1980). Work by Birch (1980) showed stable preference enhancements in
preschoolers for vegetables chosen by peers. It is possible that even though a child is not
consuming chili themselves at a young age, their exposure to adults and peers consuming
chili might influence their liking of chili (Rozin & Vollmecke, 1986). Rozin reported that
the shift from disliking to liking in many chili-eating cultures occurs between the ages of
five and nine years old (Rozin, 1990b; Rozin & Schiller, 1980), while these children
begin receiving capsaicin-containing foods around three to five years of age (Rozin &
Schiller, 1980). Considering this, and the convincing evidence for mere exposure
affecting increased acceptance and liking for foods, it would not be unexpected that the
same effects exist between exposure to and liking of capsaicin. Indeed, Stevenson and
Yeomans showed that under controlled conditions, repeated exposure to capsaicin
enhanced ratings of burn pleasantness and that this shift was not due to sensory
16
adaptation (Stevenson & Yeomans, 1995).
The increase in acceptance and liking of a stimulus that happens as a result of
exposure is thought to be due to the dissipation of neophobia regarding the new stimulus
(Hill, 1978; Rozin, 1990a). In a review of animal literature, Hill suggests that neophobia
protects animals by limiting their interaction with unfamiliar substances until there is
evidence that the substance is not dangerous (Hill, 1978). While this reduction in
neophobia may result in liking for some individuals, Rozin and Schiller hypothesized that
the enjoyment that some individuals derive from consuming capsaicin has to do with the
fact that the body perceives capsaicin as dangerous (Rozin & Schiller, 1980). The
researchers suggested that some people enjoy the thrill that comes from the disparity
between bodily responses that the stimulus is harming the body (i.e. burning sensation in
the mouth, watering eyes, and running nose when consuming capsaicin) and the cognitive
realization that the stimulus is neither dangerous nor life threatening. They speculated
that there is enjoyment that comes from experiencing a constrained risk like this –
perhaps the same type of enjoyment that comes from riding rollercoasters or gambling.
Rozin and Schiller termed these type of activity “benignly masochistic” (Rozin &
Schiller, 1980). In research with Americans and Mexicans who reported enjoying spicy
foods, a number of individuals showed preferred levels of spice that were equal to their
maximum tolerable level of spice (Rozin & Schiller, 1980). Spicy food dislikers overall
showed a larger distance between preferred level of spice and maximum tolerated level of
spice than the reported spicy food likers.
17
Cognitive factors underlying chemesthetic response: (individual/psychological)
This section of the chapter will provide an overview of a variety of personality
instruments and traits that have been used in the exploration of food choice motives
including the Sensation Seeking Scale (Zuckerman, Kolin et al., 1964), Arnett’s
Inventory of Sensation Seeking (Arnett, 1994), the Novelty Seeking subscale (Cloninger,
1987), Extraversion (from Eysenck’s EPQ: (Eysenck, 1978), the Sensitivity to
Punishment and Sensitivity to Reward Questionnaire (Torrubia, Avila et al., 2001),
Private Body Consciousness (Miller, Murphy et al., 1981), Food Neophobia (Pliner,
1982), and the Food Involvement Scale (Bell & Marshall, 2003). A brief overview of the
personality traits measured by these scales will be given, followed by a review of work
linking the liking and consumption of spicy foods, specifically capsaicin-containing
foods, to traits measured by these scales.
Sensation seeking
Sensation seeking was first defined as the “need for varied, novel, and complex
sensations and experiences” (Zuckerman, Kolin et al., 1964). The first version of
Zuckerman’s Sensation Seeking Scale to measure this trait was published in 1964, and
since then, the scale has evolved to the current version: Zuckerman’s Sensation Seeking
Scale-V (SSS-V; (Zuckerman & Neeb, 1979). In this time between the first and most
recent version of the scale, four factors emerged, thrill and adventure seeking (TAS),
experience seeking (ES), disinhibition (DIS), and boredom susceptibility (BS), as
reviewed by(Zuckerman, 1996). The TAS subscale consists of items that show the desire
18
to engage in physical activities, such as mountain climbing or skydiving, which provide
unusual experiences and sensations. The items on the ES subscale show the desire to seek
new sensations and experiences through the mind, such as music, art, and travel. These
sensations are often sought through a generally nonconforming lifestyle and was
informally called the “hippie factor” in the 1970s. The DIS subscale consists of items that
indicate the desire to seek sensations through other people, or through a “hedonic lifestyle”
(Zuckerman, 2007). Activities characteristic of this lifestyle include drinking to disinhibit,
attending wild parties, and seeking out sexual variety. The BS scale represents an
aversion to monotony and a desire to avoid or break away from monotonous conditions.
Biological Basis for Sensation Seeking
As with a number of other personality theorists, Zuckerman suggested that there
might be a biological basis for the differences observed in sensation seeking (Zuckerman,
2007). Twin studies have shown that the heritability of sensation seeking, as measured
with the SSS-V, is around 0.58 (Fulker, Eysenck et al., 1980; Hur & Bouchard Jr, 1997).
These estimates are high compared to heritability measures of other personality measures,
which fall between 0.30 and 0.50 (Bouchard, 1994; Loehlin, 1992). In 1995, Zuckerman
proposed a biological model that illustrates interactions between the three behavioral
mechanisms that are assumed to underlie sensation seeking: arousal, inhibition, and
approach systems (Zuckerman, 1995). Dopamine functioning has been associated with
approach behaviors, serotonin has been associated with inhibition behaviors, and
norepinephrine has been associated with arousal behaviors (Berridge & Stalnaker, 2002).
Thus, sensation seeking is supposedly associated with strong dopamine reactivity, and
19
weak serotonin and norepinephrine reactivity. Importantly, reactivity refers to the
sensitivity of receptor cells. It was also suggested by Zuckerman that enzymes like
monoamine oxidase (MAO) and dopamine beta-hydroxylase (DBH) may also affect
reactivity (Zuckerman, 2007).
New forms of sensation seeking scales
While Zuckerman’s Sensation Seeking Scale is well validated and has been used in
numerous studies, there are a number of criticisms of the wording and format of the
scales (Arnett, 1994; Haynes, Miles et al., 2000). The original Sensation Seeking scales
contained language that is unfamiliar to younger generations. These terms include
“hippies,” “swingers,” and “jet-setters.” The forced choice response format has also been
criticized because some individuals may not feel like either answer option is
representative (Arnett, 1994). Additionally, there are a number of items on Zuckerman’s
scale that include strenuous physical activities, which may create an age bias, and thus
age-related differences in responses should be interpreted with caution. To address these
issues, a number of different scales have been created, some that are based on the original
construct of sensation seeking as defined by Zuckerman, others that redefine the trait of
sensation seeking, and still others that assess a related dimension to sensation seeking.
The following sections will overview some of these scales.
Brief Sensation Seeking scale (BSSS)
One of the criticisms of Zuckerman’s SSS-V is that the scale is too lengthy to use in
large surveys for longitudinal behavioral studies (Hoyle, Stephenson et al., 2002).
20
Additionally, as addressed previously, the forced-choice format can be difficult for some
individuals, particularly adolescents. The Brief Sensation Seeking Scale (BSSS) was
developed to create a short sensation seeking scale that maintained the structure of
Zuckerman’s SSS-V and could be used in survey research with adolescents and young
adults. Hoyle and colleagues adapted items from the original SSS-V and chose items
from a version of the SSS-V that had been altered for adolescents (Huba, Newcomb et al.,
1981). The items were chosen to exclude any items that referred to drug or alcohol use
and to exclude language that would be unfamiliar to this age group. The final version of
the scale consists of two items from each of Zuckerman’s four subscales. The response
style for the BSSS is in the format of a 5-point Likert scale ranging from “strongly agree”
to “strongly disagree.” Unlike the SSS-V, there is no scoring of the subscales. The BSSS
is available as both an eight-item scale (BSSS-8; Hoyle et al 2002) and a four-item scale
(BSSS-4: (Stephenson, Hoyle et al., 2003). Reliabilities for the two scales, measured by
Cronbach’s alpha, have been reported between 0.70 and 0.76 for the BSSS-8 ((Hoyle,
Stephenson et al., 2002; Stephenson, Hoyle et al., 2003; Stephenson, Velez et al., 2007)
and 0.66 for the BSSS-4 (Stephenson, Hoyle et al., 2003).
Arnett’s Inventory of Sensation Seeking (AISS)
Arnett’s instrument to measure sensation seeking did away with the outdated
questions in Zuckerman’s SSS but the AISS is more than a mere update to an existing
scale (Arnett 1994). The original definition of sensation seeking included novelty and
complexity as important characteristics of stimuli that would be sought out by high
sensation seekers, but it did not include intensity. Arnett emphasized the importance of
21
the intensity of the stimuli in his conceptualization of sensation seeking and divided his
scale into two subscales, the novelty seeking (NS) and intensity seeking (IS) subscales
(Arnett, 1994). In addition to this reconceptualization, Arnett gave more emphasis to the
effect that environment might have on personality and removed questions that were age
and gender biased. Much of the work with sensation seeking assessed the relationship of
this personality trait and risky behaviors such as alcohol and drug use, illegal activities
and sexual behavior, so to avoid criteria contamination Arnett removed illegal and norm-
breaking items.
The AISS is a 20-question instrument with response options in the form of a four-
point Likert scale. For each question, the answer choices are “describes me very well,”
“describes me somewhat,” “does not describe me very well,” and “does not describe me
at all.” The Novelty Seeking and Intensity Seeking subscales are each comprised of ten
items, including reverse-coded items on each. Internal reliabilities for the scale have been
reported between 0.60 and 0.70 for the AISS total score (Arnett, 1994; Carretero Dios &
Salinas Martínez de Lecea, 2008; Ferrando & Chico, 2001a; Roth, 2003; Roth &
Herzberg, 2004), between 0.50 and 0.52 for the Novelty Seeking and between 0.53 and
0.64 for the Intensity Seeking subscales (Arnett, 1994; Roth, 2003).
Although the AISS and SSS-V have different theoretical foundations, they are
designed to measure the same personality construct. However, reported correlations
between the scales are low for two scales that are supposedly measuring the same
construct. Correlations between the SSS-V and AISS have been reported as low as 0.41
and as high as 0.72 (Andrew & Cronin, 1997; Arnett, 1994; Carretero Dios & Salinas
Martínez de Lecea, 2008; Ferrando & Chico, 2001a; Zurborg, Yurgionas et al., 2007).
22
Comparing subscales of the AISS and SSS-V, Novelty Seeking is correlated with TAS
and ES but not DIS, while Intensity Seeking is correlated with TAS and DIS. Neither
Novelty Seeking nor Intensity Seeking subscales are correlated with the BS subscale of
SSS-V. Two studies specifically addressed the degree of equivalence of the scales and
found that in younger individuals (undergraduate students, mean age = 22.61 years) the
scales measure the same construct (Ferrando & Chico, 2001a). However, in older
individuals, differences between the scales are apparent (Carretero Dios & Salinas
Martínez de Lecea, 2008). These findings are consistent with the changes made by Arnett
to remove items that relate to age.
Impulsive-Sensation Seeking (ImpSS)
The Impulsive-Sensation Seeking scale (ImpSS) is part of the Zuckerman-Kuhlman
Personality Questionnaire (ZKPQ; (Zuckerman, 2002). This questionnaire was developed
to try to define the basic factors of personality or temperament. Originally, there were
nine theoretical factors, sociability, general emotionality (neuroticism), anxiety, hostility,
socialization, sensation seeking, impulsivity, activity, and social desirability, with at least
three items for each of the nine factors (Zuckerman, 2007). Factor analysis showed that
five factors were present. These factors were Sociability (Sy), Neuroticism-Anxiety (N-
Anx), Aggression-Hostility (Agg-Host), Activity (Act), and Impulsive Sensation Seeking
(ImpSS). The final format of the ZKPQ consists of 99 items that are answered in
true/false format. Factor analysis showed that the ImpSS factor is composed of two
factors, impulsivity and sensation seeking. The type of impulsivity in the ImpSS
describes a lack of planning and tendency to act quickly without thinking while the
23
sensation seeking items describe a need for change and novelty as well as a general desire
for thrills and excitement. Unlike the SSS-V, none of the items in the ImpSS reference
specific activities like risky sexual behavior, drug or alcohol use, or risky sports.
Comparing the ImpSS to the SSS-V and its subscales, strong to moderate
correlations were observed (Zuckerman, 2002). ImpSS and total score on the SSS-V
showed the strongest correlation (r = 0.66, P < 0.01). ImpSS significantly correlated with
each of the subscales of the SSS-V as well (ImpSS-TAS r = 0.49, ImpSS-ES r = 0.46,
ImpSS-Dis r = 0.48, ImpSS-BS r = 0.37, all P’s < 0.01). To examine the relationship to
other personality traits associated with impulsivity, the correlation between ImpSS and
Extraversion from both Eysenck’s Personality Questionnaire (EPQ-R; (Eysenck, Eysenck
et al., 1985) and the NEO-PI-R (Costa Jr & McCrae, 1992) was assessed. Both
Extraversion scales showed a moderate significant correlation with ImpSS (both r’s =
0.28, P <0.01). Reliabilities for the ImpSS scale have been reported as 0.86 (Stephenson,
Hoyle et al., 2003) and 0.77 for a male-only sample and 0.81 for a female-only sample
(Zurborg, Yurgionas et al., 2007).
Novelty Seeking (NS)
Like Zuckerman, Cloninger believed that sensation seeking, or novelty seeking was
a major personality factor, rather than a facet of a different factor, as it is in the Big Five
(Cloninger, 1987; Cloninger, Svrakic et al., 1993). In Cloninger’s personality
organization, Novelty Seeking is defined as the tendency to explore and experience
intense exhilaration in response to novel stimuli. While impulsivity is a core dimension in
a number of personality taxonomies (which will be addressed in the SPSRQ section), the
24
Novelty Seeking dimension is prominent in Cloninger’s model, as one of three major
factors. The other dimensions in Cloninger’s taxonomy are Harm Avoidance (HA),
which measures inhibition behavior, and Reward Dependence (RD), which measures
sensitivity to social cues. An additional dimension of Persistence, which measures an
individual’s tendency to persist at a task despite frustration, was also later suggested
(Cloninger, 1994). Individual variation in personality is the result of a combination of
each of these dimensions, which is suggested to reflect variation in neurological systems.
Zuckerman and Cloninger disagree over the level of similarity between the
constructs of NS and SS, with Zuckerman (Zuckerman, 1988) suggesting that NS is
practically identical to the trait SS, while Cloninger argued (Cloninger, 1985) that SS was
a more factorially complex construct that was a combination of NS, HA, and possibly RD.
There are clear similarities in the definitions of trait sensation seeking (SS), ImpSS, and
NS, especially between NS and ImpSS, as the items on both the NS and ImpSS scales
describe impulsivity of the non-planning type. Some studies assessing the relatedness of
NS to ImpSS and SSS-V show strong correlations between the measures (ImpSS-NS r =
0.68, NS-SSS-V r = 0.55; (Zuckerman & Cloninger, 1996), while others show weaker
correlations between NS and SSS-V (r = 0.340, p < 0.001; (McCourt, Gurrera et al.,
1993). Correlations between the total scale scores supports Zuckerman’s argument that
NS and SS are closely related. However, the strong association of HA and SS, and the
evidence that NS and HA are related to different parts of SS support Cloninger’s claim.
Similarly to Zuckerman, Cloninger attributed his three personality dimensions to
neurological systems, though the proposed system was less complex than Zuckerman’s.
NS is attributed to the dopaminergic system, HA is attributed to the serotoninergic system,
25
and RD is attributed to the noradrenaline, or norepinephrine, system (Cloninger,
Przybeck et al., 1994). Here, we will focus on studies linking the dopaminergic system to
NS. The dopamine 4 receptor (DRD4) gene shows copy number variation across the
population. In 1996, a study in Israeli participants showed that the longer form (7 repeats)
of DRD4 was associated with higher NS scores, while shorter forms (4 repeats) were
associated with lower scores on NS (Ebstein, Novick et al., 1996). In 21 studies exploring
the relationship between dopamine and NS, 11 groups were able to replicate this finding
(Prolo & Licinio, 2002). A meta-analysis of these studies shows conflicting results,
suggesting that instead of comparing the 7-repeat allele with shorter variations, only
comparing all short and long sequences showed a small but significant effect (Schinka,
Letsch et al., 2002). Other research, linking the DRD4 gene with forms of behavior
indicative of approach behaviors or high sensation seekers provides additional support for
the role of dopamine in NS (Ebstein & Auerbach, 2002).
While reports of the association of the DRD4 gene with NS conflict, other evidence
suggests that instead of a single gene, variation in NS can be attributed to the interaction
of genes within and between neurobiological systems. Given the polygenetic nature of
other personality traits, it is not surprising that additive effects of multiple dopamine
receptors have been reported (Comings, Saucier et al., 2002; Noble, 1998) and additional
variance in NS may be explained by the interaction of dopamine and serotonin systems.
In humans, the short form of the serotonin transporter (5-HT) is associated with anxiety
(Munafo, Clark et al., 2003), but when the long form of the serotonin transporter
combines with the long allele of DRD4, enhanced orientation response is observed in
infants (Ebstein, Benjamin et al., 2000). Yet another study showed that the long DRD4
26
allele alone was not associated with high NS, but when accounting for variation in 5-HT
and catechol-O-methyltransferase (COMT; an enzyme that degrades catecholamines like
dopamine and norepinephrine), the association is significant (Strobel, Lesch et al., 2003).
Sensitivity to Punishment and Sensitivity to Reward (SPSRQ)
The Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) is
an operationalization of Jeffrey Gray’s personality theory, which is not associated with a
specified scale. In order to understand the SPSRQ, one must first understand Gray’s
theory, thus an overview is presented here.
Jeffrey Gray was a bottom-up theorist whose model of personality consists of three
independent personality dimensions with three underlying neuropsychological systems
(Gray, 1981; Gray, 1982). The three behavioral systems that Gray identified are the
Behavioral Activation System (BAS; also called the Behavioral Approach System), the
Behavioral Inhibition System (BIS), and the Fight/Flight System (FFS). The BAS is
activated by stimuli associated with reward and the termination of punishment. This
system is responsible for approach behavior and individual differences in BAS function
are related to trait impulsivity. The BIS is activated by signals of punishment, frustrative
non-reward, and novel stimuli. The BIS system is related to trait anxiety. The FFS is
activated by the presence of unconditioned aversive stimuli that generate a fight or escape
behavior. This last system is less well defined than the BAS and BIS and will not be
covered in this chapter.
As previously mentioned, the BAS is associated with trait impulsivity. In common
usage, impulsivity means behaviors that have to do with a lack of planning or without
27
carefully thinking about the consequences of the behavior; however, there is no single
agreed upon definition in the psychological literature. Although anxiety, the trait
associated with BIS is a single construct, the consensus is that that impulsivity is a
multidimensional construct made up of a number of related dimensions (Evenden, 1999;
Eysenck, 1978; Gerbing, Ahadi et al., 1987; Parker & Bagby, 1997; Pickering & Gray,
1999). Even Gray and colleagues described four different types of impulsivity, and only
one of them was related to the BAS (Gray, Owen et al., 1983).
Impulsivity is considered core dimension in a number of personality systems, such
as those developed by Eysenck, Cloninger, Zuckerman, and Gray. In Eysenck’s model,
impulsivity is a combination of items from the Extraversion and Psychoticism
dimensions of the Big Three that are put together in the I7 scale (Eysenck, Pearson et al.,
1985). This scale measures two distinct types of impulsivity: a) impulsive behaviors
where consequences have been weighed, or thrill-seeking behaviors, and b) impulsive
behaviors that are impetuous, unplanned, and done without thought of the consequences.
Gray’s impulsivity dimension is also considered to be conceptually similar to Cloninger’s
NS and HA dimensions and Zuckerman considers it to be closely linked with sensation
seeking (See ImpSS; (Zuckerman, 2002).
As with a number of other personality theorists, Gray believed in a biological basis
of personality and expressly described the neurological substrates for the BAS and BIS
(Gray, 1995; Gray & McNaughton, 1996). The BAS is thought to be mediated by the
dopaminergic system while norepinephrine and serotonin are thought to be associated
with the BIS. Initially, the BIS and BAS were defined conceptually as independent
processes; however newer work shows the brain structures that Gray identified for the
28
BAS and BIS show interactions (Torrubia, Avila et al., 2001).
Gray did not develop scales to measure his personality dimensions of anxiety and
impulsivity and while there are a number of personality scales that can be used to
measure these traits, not all are designed specifically to assess the traits as they were
described by Gray. A number of different methods have been used in the literature to
assess anxiety and impulsivity traits. The first technique is to use a combination of
Neuroticism and Extraversion scales from the EPQ (Eysenck & Eysenck 1975) and to
classify impulsivity and anxiety as a combination of these dimensions (Torrubia, Avila et
al., 2001). Another method is to use measures that were not designed to tap Gray’s
dimensions but that are related to trait anxiety and impulsivity, such as the Anxiety-Trait
scale from the State-Trait-Anxiety Inventory (STAI-T; (Spielberger, Gorsuch et al.,
1970), or the impulsivity scales of the EPI (Eysenck & Eysenck, 1964) and the IVE
(Eysenck, Pearson et al., 1985). It is important to note that just because a scale uses the
terms impulsivity or impulsiveness, the scale may not be measuring Gray’s personality
dimension as he conceptualized it. Similar to this technique is the method of using scales
that were formed from personality models that share similar theoretical foundations.
Again, these scales should be used with caution, as they are measuring similar, but not
identical constructs to Gray’s model. An example of this would be Harm Avoidance from
Cloninger’s model and anxiety and Cloninger’s Novelty Seeking and Reward
Dependence and Gray’s impulsivity (TPQ; (Cloninger, Przybeck et al., 1991). Finally,
although Gray did not specify instruments to measure his personality dimensions, it is
possible to design scales to measure differences in functioning in the BAS and BIS as
depicted by Gray. Two attempts to do this have been published, the BIS/BAS scales by
29
Carver and White (Carver & White, 1994) and the Sensitivity to Punishment and
Sensitivity to Reward Questionnaire (Torrubia, Avila et al., 2001). A study exploring the
relatedness of scales commonly used to assess anxiety and impulsivity (Caseras, Avila et
al., 2003a) showed that factor analysis on a variety of scales (including the BAS/BIS and
SPSRQ) indicated that SP and HA were the best scales for measuring BIS function and
SR and I7 were the best scales to measure BAS functioning. Considering these findings,
the SPSRQ is regarded as the best measure of Gray’s BIS and BAS.
The SPSRQ is made up of two scales, the Sensitivity to Punishment scale (SP),
which measures behavioral inhibition under specific conditions of punishment or threat,
and the Sensitivity to Reward scale (SR), which measures approach behaviors to
conditioned and unconditioned stimuli that indicate rewards, such as money, sexual
partners, praise, and social status (Caseras, Avila et al., 2003a; Cooper & Gomez, 2008;
Torrubia, Avila et al., 2001). These two scales represent distinct systems such that an
individual’s personality is a combination of sensitivity to punishment and reward
(someone does not necessarily have to be low SP if they are high SR). The Susceptibility
to Punishment scale (Torrubia & Tobena, 1984) was the first attempt at a scale to
measure BIS functioning. The Susceptibility to Reward scale, designed to measure BAS
functioning was developed later (Muntaner & Torrubia, 1985). Psychometric analysis of
the data from these scales was used to produce the Sensitivity to Punishment and
Sensitivity to Reward scales in the SPSRQ (Torrubia, Avila et al., 2001). The English
language version of the scale was developed by O’Connor and colleagues (O'Connor,
Colder et al., 2004). The final version of the SPSRQ is made up of two scales, each with
24 questions. Reliabilities for both SP and SR were in the range of 0.76 to 0.84, and test-
30
retest reliabilities over a 3-month and 3-year period were 0.89 and 0.57, respectively
(O'Connor, Colder et al., 2004; Torrubia, Avila et al., 2001).
In the initial study describing the SPSRQ Torrubia and colleagues conducted
extensive analysis to explore the relation of the SP and SR scales to the array of scales
that measure either impulsivity, anxiety, or dimensions closely related to these traits,
including Eysenck’s EPQ-R; (Eysenck, 1978), Zuckerman’s SSS-V, and Cloninger’s
TPQ (Torrubia, Avila et al., 2001). When comparing the SPSRQ scales to Eysenck’s
dimensions of Extraversion (E), Psychoticism (P), and Neuroticism (N) (EPQ; (Eysenck,
1978), significant correlations between the scales were observed and thus partial
correlations were calculated. In both males and females, the correlations between SP and
E were negative (males: r = -0.48 P < 0.001, females: r = -0.41, P < 0.001), while
correlations between SP and N were positive (males: r = 0.69 P < 0.001, females: r = 0.55,
P < 0.001), (Torrubia, Avila et al., 2001). Comparing SP to Zuckerman’s SSS-V,
significant negative correlations between SP and SSS-V total score and some subscale
scores were seen in males and females (males: SP-TAS r = -0.21*, SP-ES r = -0.18*, SP-
Dis r = -0.12, SP-BS r = -0.08, SP-SSS-V r = -0.18, females: SP-TAS r = -0.19**, SP-ES
r = -0.23**, SP-Dis r = -0.11*, SP-BS r = -0.04, SP-SSS-V r = -0.21**, *p < 0.05, **p <
0.01; (Torrubia, Avila et al., 2001). Comparing the SP scale to Cloninger’s dimensions,
SP and HA showed a strong significant relationship (r = 0.67, P <0.01; (Torrubia, Avila
et al., 2001). Assessing SP and an explicit measure of anxiety, SP and STAI-T were
related, but were considered not be measuring identical constructs (Torrubia, Avila et al.,
2001).
Comparing the SR scale to the EPQ-R, SSS-V, and TPQ inventories as well as
31
explicit measures of impulsivity showed the following results (Torrubia, Avila et al.,
2001). Correlations between SR and E and N from Eysenck’s EPQ-R, when controlling
for E, N, and P appropriately, showed significant positive correlations between SR and
both E and N in males and females (SR-E males: r = 0.50 P < 0.001, females: r = 0.43, P
< 0.001, SR-N males: r = 0.52 P < 0.001, females: r = 0.38, P < 0.001; Torrubia et al.
2001). Significant positive relationships were also observed between SR and scales from
Cloninger’s model (SR-NS r = 0.27 P < 0.01, SR-RD r = 0.12* P < 0.05; Torrubia et al.
2001). Additionally, significant, positive correlations were seen between SR and almost
all subscales of Zuckerman’s SSS-V in males and females (males: SR-TAS r = 0.19*,
SR-ES r = 0.14, SR-Dis r = 0.45**, SR-BS r = 0.37**, SR-SSS-V r = 0.45**, females:
SR-TAS r = 0.14*, SR-ES r = 0.13*, SR-Dis r = 0.41**, SR-BS r = 0.27, SR-SSS-V r =
0.36**, *p < 0.05, **p < 0.01; (Torrubia, Avila et al., 2001). When compared to other
measures of impulsivity, significant positive correlations were observed, as expected
(SR-I5 r = 0.41 P < 0.01, SR-I7 r = 0.39 P <0.01; (Torrubia, Avila et al., 2001). However,
given the low relationship between SR and P and the absence of relationship between SR
and SP, it is suggested that SR and other measures of impulsivity are not interchangeable.
SPSRQ and spicy food liking
The application of the SPSRQ in food choice literature is limited. Primarily, this
measure has been used in the study of eating behaviors rather than food choice (Bégin,
St-Louis et al., 2012; Davis & Fox, 2008; Davis, Patte et al., 2007; Franken & Muris,
2005; Hou, Mogg et al., 2011; Tetley, Brunstrom et al., 2010). Given the association of
dopamine and endorphins with food-related reward (Davis & Woodside, 2002; Kelley,
32
Bakshi et al., 2002) and the association of endorphin release with capsaicin application
(e.g. (Bach & Yaksh, 1995), it is possible that the SR subscale of the SPSRQ may
associate with liking of capsaicin-containing and spicy foods. It is also possible, given
that pain, such as that elicited by capsaicin, is an unconditioned aversive stimuli that the
SP subscale will associate with the liking of spicy foods.
Private Body Consciousness (PBC)
The Private Body Consciousness (PBC) scale is a measure of self-awareness and
self-consciousness that asked about state changes that are only observable to the
individual (Miller, Murphy et al., 1981). These state changes include changes in heart
rate, hunger pains, and body temperature. Individuals are asked to rate how well five
statements characterize them using a 5-point Likert scale (0 – extremely uncharacteristic
to 4 – extremely characteristic). Individuals with high PBC have reportedly been able to
detect and identify differences in sensory properties of foods compared to low PBC
individuals as a result of their increased sensitivity to sensory stimuli (Jaeger, Andani et
al., 1998; Miller, Murphy et al., 1981; Stevens, 1990; Ueland, 2001b). PBC has also been
linked with sensitivity to sensations caused by spicy foods such that high PBC
individuals rate the perceived burning from capsaicin as more intense than low PBC
individuals (Ferguson & Ahles, 1998; Martin, Ahles et al., 1991; Stevens, 1990).
Food Neophobia and Food Involvement Scale
Two other scales that have been associated with food preference and consumption
are the Food Neophobia Scale (FNS; (Pliner & Hobden, 1992) and the Food Involvement
33
Scale (FIS; (Bell & Marshall, 2003). Pliner and Hobden developed the Food Neophobia
Scale (FNS; (Pliner & Hobden, 1992) as a measure of an individual’s reluctance or
willingness to eat new foods. There is a hypothetical evolutionary significance for the
development of food neophobia, as discussed earlier and it has been proposed that Food
Neophobia be considered a personality trait (Pliner & Hobden, 1992). While a number of
manipulations, such as the overall degree of novelty in the eating situation, has been
shown to influence the degree of food neophobia in humans and other animals, a fairly
stable propensity to approach or avoid new foods has been suggested (Pliner & Hobden,
1992). This stability, along with the hypothetical evolutionary significance of the trait,
motivated researchers to explore any hereditary component of food neophobia (Knaapila,
Tuorila et al., 2007). Findings from this study suggest that roughly two thirds of the
variance in food neophobia can be attributed to genetic effects (69% in Finnish families
and 67% in British families; (Knaapila, Tuorila et al., 2007).
The Food Neophobia scale consists of ten statements to which the respondent
replies, using a seven-point scale, how strongly they agree or disagree with (1= “strongly
disagree” to 7= “strongly agree”). The range of possible scores is 10 to 70, with higher
scores representing more neophobia, thus lower levels of approach behavior towards new
foods. Alpha coefficients for the FNS are sufficiently high (r = 0.88; (Pliner & Hobden,
1992) as are test-retest reliabilities at two to four weeks, and 12 weeks (2 to 4 weeks: r =
0.91, p < 0.01, 12 weeks: r = 0.82, p <0.01; (Pliner & Hobden, 1992).
One would expect the trait of food neophobia to be related to Zuckerman’s trait
Sensation Seeking, since those who are high Sensation Seekers should be more likely to
choose novel foods to increase their arousal level versus low Sensation Seekers. However,
34
results in the literature do not fully support this notion. Significant correlations have been
reported between scores on the ES subscale of Zuckerman’s SSS-V(Zuckerman & Neeb,
1979) and the number of unfamiliar foods an individual is willing to taste (Otis, 1984)
and to measures of neophobia (r = -0.46, p< 0.05; (Pliner & Hobden, 1992). However, in
a different study examining the relationship between the FNS and the SSS-V, no main
effect of sensation seeking was seen on the number of novel foods chosen, though a
significant interaction effect with level of arousal state was observed (Pliner & Melo,
1997). In the low arousal state, individuals with high trait SS tried significantly more
novel foods than their low SS counterparts. In overall adventurousness, individuals who
seek out experiences that are new and/or exciting tend to be less neophobic than less
adventurous individuals (Terasaki & Imada, 1988). Without considering food choice
motives, scores on the FNS significantly predict intake of spices in a group of Dutch
undergraduate students (Eertmans, Victoir et al., 2005).
The FIS, developed by Bell and Marshall (Bell & Marshall, 2003), measures the
importance of food in a person’s life by asking about the extent to which an individual
enjoys talking and thinking about food and engages in food-related activities at all of the
food “lifecycle” stages (acquisition, preparation, cooking, eating, and disposal) defined
previously by Goody (1982). Factor analysis showed two subscales that exist in the FIS,
the set and disposal (S&D) construct and the preparation and eating (P&E) construct
(Marshall & Bell, 2004). Individuals with high FIS scores were shown to make finer
discriminations between food items in sensory evaluations and hedonic ratings (Bell &
Marshall, 2003). There have been no attempts to associate FIS scores to liking of
capsaicin-containing foods, but given the relationships of this scale with the Food
35
Neophobia Scale and the VARSEEK scale (Bell & Marshall, 2003; Marshall & Bell,
2004), it is possible that individuals with high FIS scores are more adventurous with
foods, and thus more willing to try capsaicin-containing foods even if they do not enjoy
their first encounter.
Personality and Food Choice
While the personality scales addressed in the chapter are related, only some have
been linked with food choice and food liking. Many of the personality traits addressed
above have been linked with eating behaviors including overeating (e.g. (Davis, Strachan
et al., 2004) and anorexia and bulimia (e.g. (Dawe & Loxton, 2004; Loxton & Dawe,
2001), as there tends to be high comorbidity with abuse of substances and dysfunctional
eating in certain populations (e.g. (Loxton & Dawe, 2001). However, some work has
been done linking the preference for sweet tastes with increased impulsivity (Saliba,
2009).
There have been several attempts to associate sensation-seeking traits with the
liking for pungent sensations in foods and beverages. Early work linking personality
traits with foods focused on the relationship between food preferences and the oral-
passive versus oral-sadistic Freudian personality dimension (Wolowitz, 1964). Later,
Kish and Donnenwerth tested the relationship between sensation seeking and food
preferences using the Food Preference Inventory (Kish & Donnenwerth, 1972). The
findings of this study suggested that sensation seekers tend to prefer crunchy, sour, and
spicy foods to sweet, soft, and bland foods. Later work by Brown and colleagues (Brown,
Ruder et al., 1974) showed correlations between the preference for spicy foods and scores
36
on the Change Seeker Index, which indicated, similarly to the work by Kish &
Donnenwerth, that sensation seekers preferred more bold foods (Kish & Donnenwerth,
1972). Rozin and Schiller’s 1980 study (Rozin & Schiller, 1980) suggesting the
relationship between preference for chili peppers and sensation seeking is one of the most
well-known studies linking personality and spicy food liking and is often referenced as
the work that firmly establishes the relationship between these variables. In this two-part
study, they conducted studies in American college students and observed and conducted
interviews with individuals in a rural Mexican village. While Rozin and Schiller (Rozin
& Schiller, 1980) suggested relationships between sensation seeking and liking of spicy
foods, the only empirical data presented to support this hypothesis is a weak (r = 0.11,
n.s.) correlation was observed between chili preference and preference scores for three
masochistic activities. Later work by Logue and Smith (Logue & Smith, 1986a)and
Terasaki and Imada (Terasaki & Imada, 1988) showed significant correlations between
food preference ratings for spices and spicy foods and subscales of the SSS-V. While
there is a strong theoretical foundation for the existence of the relationship between
sensation seeking and the liking of spicy foods, empirical evidence is limited. The
following chapters of this dissertation seek to address this gap in the literature.
Sensory Profiling Techniques
In addition to exploring the role of personality on the liking and intake of spicy
foods, another aim of this dissertation is to focus on the perception of spicy foods and
37
how various factors, such as experience with food can alter that perception. There are a
number descriptive techniques that can be employed to provide information about the
stimuli of interest. However each method has its benefits and limitations as compared to
other techniques, and an important experimental design consideration is understanding
how the strengths and weaknesses of each technique works, or does not work, with the
stimuli being evaluated. Some of the most common descriptive techniques used by the
food industry include Quantitative Descriptive Analysis (QDA™; (Stone, Sidel et al.,
1974), Spectrum™ methods (Munoz & Civille, 1992), the Flavour Profile (Cairncross &
Sjostrom, 1997), Texture Profile (Brandt, Skinner et al., 1963), and Quantitative Flavor
Profiling (Valentin, Chollet et al., 2012). Each of these techniques uses a small group of
highly trained assessors to evaluate a range of stimuli and products. Generally, the output
from these techniques is not wholly applicable to consumers and there are significant
investments of time and money to establish a trained panel, but once a panel is
established, the results from these techniques are quick, and reliable, as the panelists are
constantly evaluated in case they need retraining.
Given the significant time investment to the aforementioned descriptive profiling
techniques, there is significant interest in the field to explore alternative methods of
profiling samples. Generally, there are three groups that the newer, so called rapid
methods fall into. They include methods that compare samples to a reference or set of
references, verbal-based methods, and similarity-based methods (Valentin, Chollet et al.,
2012).
38
Reference-based methods
The reference-based methods include techniques such as polarized sensory
positioning (PSP; (Teillet, Schlich et al., 2010) in which a large number of sensory
attributes are replaced by a small number of prototypical samples that act as references
which to compare all other samples to. The benefit of this type of technique is that, if
there are limited numbers of samples available at one time, for example in a quality
assurance setting, or if not all the samples can be presented at one time, the data can be
aggregated across evaluation sessions. Additionally, it is easy for participants to perform.
The downfalls of these techniques include the fact that all sensory information about the
stimuli being evaluated is collected by evaluating the sensory characteristics of the
representative samples that were chosen. Additionally, it is critical to have thorough a
priori knowledge of the product space in order to pick reference samples that are
representative to the whole space. Another limitation of this technique is the restriction
set by constraints on the availability of reference samples. In order to aggregate data over
a number of sessions, the references must be stable over time, which may limit the
samples that can be used as references, and possibly limit the area of product space that
can be represented by these reference samples.
Verbal-based methods
This family of methods includes methods such as flash profiling (FP: (Valentin,
Chollet et al., 2012) and check-all-that-apply (CATA; (Coombs, 1964). FP is conducted
in two sessions separated by an intersession. In the first session, all the samples are
presented at once and the participant evaluates all the samples and generates descriptive
39
attributes. In the intersession, the researcher pools the attributes that are provided to the
panelists during the second session. This attribute list is used to rank order the products
from least to most on each attribute. CATA was originally developed and used in the
field of marketing but recently was used in chemosensory and food research (Bennett &
Hayes, 2012; Lancaster & Foley, 2007). When evaluating samples using CATA,
participants evaluate each sample one at a time and select from a list of attributes, which
descriptors are appropriate to describe that sample. Unlike FP, the descriptors used in
CATA can include hedonic or emotional words as well as words referring to product
usages (Dooley, Lee et al., 2010). Compared with classical methods of descriptive
analysis, these techniques are powerful enough to discriminate between samples but they
take significantly less time. The main drawbacks to these techniques have to do with the
type of data that they produce. FP requires participants to rank stimuli, which can be very
difficult to do with large numbers of products, and may require a lot of retasting. CATA
produces counts, or frequencies, which inherently have less power than quantitative data.
Another limitation with CATA is that too many or two few descriptors can influence the
results of the test can become difficult with too many descriptors (Bennett & Hayes,
2012; Hughson & Boakes, 2002).
Similarity-based methods
The last group of techniques, the similarity-based methods addresses a key
limitation of the verbal-based methods, in that verbal methods rely heavily on the ability
to analyze the perception of stimuli and convert this perception into words. In similarity
based methods, the reliance on words can be entirely eliminated, by omitting a
40
descriptive portion of the task, or it can be minimized, by reserving the descriptive task
until after the similarity judgments have been made. Two of the most common techniques
in this group are sorting and Napping®. Free sorting is a version of sorting that is
conducted without words (Hulin & Katz, 1935). In this technique, participants evaluate a
number of samples at one time and sort them into mutually exclusive groups based on
perceived similarities or differences. Once the groupings have been made, participants
can be asked to provide descriptive terms to classify each group (Faye, Brémaud et al.,
2004; Lawless, Sheng et al., 1995; Lim & Lawless, 2005; Saint-Eve, Paçi Kora et al.,
2004; Tang & Heymann, 2002). There are a number of variations on the sorting task,
including hierarchical sorting (Rao & Katz, 1971), and directed sorting (Chollet, Lelièvre
et al., 2011). The benefits of sorting include that the maps are reproducible (Cartier, Rytz
et al., 2006; Chollet, Lelièvre et al., 2011; Lelièvre, Chollet et al., 2008) and the
technique is appropriate to use with untrained assessors (Chollet, Lelièvre et al., 2011).
Limitations of sorting include that the descriptors generated by participants can be
difficult to interpret and it this task may not be as easy as originally thought for
participants to complete (Patris, Gufoni et al., 2007).
Napping®, also known as projective mapping, is a similar technique to sorting, but
instead of forming mutually exclusive groups based on similarity, participants place the
samples on a white sheet of A3 (297mm by 420 mm) paper in a manner such that the
proximity of samples to one another indicates their level of similarity (Nestrud &
Lawless, 2011; Risvik, McEwan et al., 1994; Risvik, McEwan et al., 1997). As with
sorting, after participants have evaluated the samples, they can be asked to provide
descriptors written on the paper near the samples that they describe. The perceptual maps
41
produced by Napping® are reproducible (Kennedy & Heymann, 2009; Nestrud &
Lawless, 2011; Risvik, McEwan et al., 1994; Risvik, McEwan et al., 1997) and have been
shown to be equivalent to those generated from descriptive analysis (Nestrud & Lawless,
2011; Perrin, Symoneaux et al., 2008; Risvik, McEwan et al., 1994; Risvik, McEwan et
al., 1997). One of the major limitations of Napping® is that it limits participants to only
using two dimensions to discriminate between products. Some researchers suggest that
this may not be as large a problem as others suggest, as there are ways for the analysis to
recover higher dimensions (Nestrud & Lawless, 2011). Some of the same limitation
exists with Napping® as with sorting, that it may be difficult to interpret the descriptors
provided by participants and that there may be memory issues when the sample space
gets too big. Another consideration with using Napping® is whether all of the participants
are equally spatially capable.
42
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Chapter 2
Perceptual mapping of chemesthetic stimuli in naïve assessors.
Abstract
Chemesthetic compounds, responsible for sensations such as burning, cooling,
and astringency, are difficult stimuli to work with, especially when the evaluation task
requires retasting. Here, we developed a protocol by which chemesthetic compounds can
be assessed using sorting. We compared the performance of two cohorts of untrained
assessors, one with nose clips and the other without, on this task. Similarity data were
analyzed using multidimensional scaling (MDS) to produce perceptual maps for the two
cohorts. Overall, the groupings from the nose open cohort tended to follow a biological
basis, consistent with previous findings that suggest compounds that activate a common
receptor will elicit similar perceptual properties. The nose-open and nose-pinched cohorts
generated significantly different maps. The nose-pinched cohort had a higher variance in
the MDS solution than the nose-open group. While the nose-open cohort generated seven
clusters, the nose-pinched cohort generated only two clusters, seemingly based on
whether assessors could readily identify chemesthetic sensations or not. There was less
consensus regarding the attributes used to describe the samples in the nose-pinched
cohort than in the nose-open cohort as well, as this cohort collectively generated more
attributes but fewer were significant in regression.
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Introduction
Multidimensional Scaling (MDS), originally developed by Torgerson (Torgerson,
1952), is a family of multivariate statistical techniques that are commonly used to
visually represent the similarity of items within a data set. These methods can be used to
construct perceptual maps that pictorially represent the magnitude of perceptual distances
between stimuli and provide information on how panelists group these samples. These
techniques (reviewed by (Popper & Heymann, 1996)) have been used for odorants
(Chollet & Valentin, 2000; Lawless, 1989), tastants (Schiffman & Erickson, 1971), and
foods (Lawless, Sheng et al., 1995), but have not previously been applied to chemesthetic
stimuli. Compared to other descriptive techniques, such as flash profiling and “check-all-
that-apply” (CATA) which rely heavily on semantic labels to describe sensation, MDS
allows the researcher to explore attributes that are difficult to verbalize and offers the
advantage that there is no need to use words to judge similarities (Nestrud & Lawless,
2010; Schiffman, Reynolds et al., 1981; Valentin, Chollet et al., 2012). Participants are
free to choose the criteria that they use to make judgments, regardless of whether they
have specific words to express these similarities or differences.
Data input for MDS can be any sort of similarity (or dissimilarity) measure such
as correlations across rated attributes, interpoint distances, as in Napping, direct ratings of
pairwise comparisons, or frequency counts (e.g. the number of times that stimuli are
placed in a group together), as in sorting (Lawless & Horne, 2000; Lawless, 1989;
Nestrud & Lawless, 2010; Rosenberg & Park Kim, 1975). One of the advantages of using
similarity-based judgments versus direct scaling of multiple attributes to collect data is
57
the lack of linguistic contamination. Because MDS can be conducted without expressly
relying on words, it is particularly useful when working with sensations, such as those
produced by chemesthetic compounds, which may be unfamiliar, semantically unwieldy
(i.e., “Is it ‘hot-hot’ or ‘spicy-hot’?”), or otherwise difficult to describe (Bennett & Hayes,
2012; Cliff & Heymann, 1992; Cliff & Green, 1996).
When collecting similarity estimates via pairwise comparisons, participants must
judge the level of similarity between all pairs of stimuli. Collecting data in this way
quickly becomes fatiguing for participants, as the number of pairs assessed increases
rapidly with the number of stimuli ([N*(N-1)]/2 ratings for N stimuli, i.e. 11 stimuli
require 55 paired comparisons). Accordingly, pairwise comparisons are not well suited
for stimuli in which fatigue, adaptation, or sensitization or desensitization are a concern,
as with some tastants, odorants, or chemesthetic stimuli. One alternative technique,
sorting, takes much less time and allows for more stimuli to be tested in a single session.
In a sorting task, participants place samples into groups based on perceived similarities
and dissimilarities (Rosenberg, Nelson et al., 1968; Rosenberg & Park Kim, 1975).
Sorting was first introduced into the chemosensory literature from psychology by
Lawless specifically to deal with highly fatiguing stimuli (Lawless, 1989; Lawless &
Glatter, 1990).
One advantage of using free sorting is that the maps are reproducible (Cartier,
Rytz et al., 2006; Chollet, Lelièvre et al., 2011; Falahee & MacRae, 1997; Lelièvre,
Chollet et al., 2008) and untrained assessors can generate maps comparable to those
generated using traditional descriptive analysis techniques (Faye, Brémaud et al., 2004;
Saint-Eve, Paçi Kora et al., 2004) without the substantial time requirement of descriptive
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profiling techniques (e.g. Spectrum Descriptive Analysis, QDA). Additionally, it is
possible to ask assessors to provide descriptions of individual stimuli or groups once
sorting is complete. Asking assessors to provide their own descriptors instead of asking
for ratings on attribute scales predetermined by the experimenter provides insight into the
perception of and preference for stimuli in the sample set using attributes that are salient
to the study participants (Blancher, Clavier et al., 2012; Cartier, Rytz et al., 2006; Chollet
& Valentin, 2000; Faye, Brémaud et al., 2004; Faye, Brémaud et al., 2006; Holliins,
Faldowski et al., 1993; Lawless, 1989; Lawless, Sheng et al., 1995; Lelièvre, Chollet et
al., 2008; Lim & Lawless, 2005; Saint-Eve, Paçi Kora et al., 2004; Tang & Heymann,
2002). Cluster analysis can be used to add additional information to aid in data
interpretation by helping to differentiate groups of products as determined by consumers
(Lawless, 2013; Nestrud & Lawless, 2010).
Given the self- and cross-sensitization and desensitization commonly observed
with chemesthetic agents (Cliff & Green, 1994; Dessirier, O'Mahony et al., 2001; Green,
1989; Green, 1991; Green & Rentmeister-Bryant, 1998; Jancso, Kiraly et al., 1977; Klein,
Carstens et al., 2013; Prescott & Stevenson, 1996a; Prescott & Swain-Campbell, 2000;
Simons, Carstens et al., 2003), designing an evaluation protocol for these stimuli can be
cumbersome. Sorting is well-suited for the present study as it does not require
participants to use words to classify sensations while they sample and group the stimuli,
thus avoiding the linguistic confusion that surrounds chemesthetic sensations (Bennett &
Hayes, 2012; Cliff & Heymann, 1992; Cliff & Green, 1996). Given the risk of fatigue,
potential lapse of participant attention, sensitization, and desensitization that can take
59
place using a lengthy pairwise comparison procedure, free sorting appears to be a better-
suited method of data collection when working with chemesthetic compounds.
While qualitative differences in pungency had been alluded to previously
(Govindarajan, 1979; Lawless, 1989; Todd, Bensinger et al., 1977), the first formal study
was conducted by Cliff and Heymann (1992), who used traditional descriptive analysis
techniques to characterize the oral irritancy elicited by various chemesthetic compounds.
Stimuli were compared using four attributes (burning, tingling, numbing, and overall
irritation) in addition to temporal and spatial characteristics. Importantly, while this
seminal work provides the first quantitative characterization of perceptual differences
across irritants, use of traditional descriptive analysis potentially limits generalizability to
untrained assessors, or to other chemesthetic stimuli that are not described by the
attributes generated from the training set (e.g. buzzing from sanshool). Another key study
in exploring oral chemesthesis was conducted by Bertino and Lawless (Bertino &
Lawless, 1993), in which MDS was used to understand mouthfeel attributes of oral
healthcare products. In this study, participants sorted 21 cards with terms referring to
‘mouthfeel’ sensations and tastes into groups, generating four groups clustering around
sensations elicited by tastes, astringents, local anesthetics, and painful sensations. While
the authors hypothesized sorting with actual sampled stimuli would produce similar
responses, such a study was not conducted. We build on these prior reports by providing
sampled stimuli to participants in a sorting task.
Here, we developed a novel delivery system and testing protocol to allow us to
explore the underlying dimensions of oral chemesthesis. We presented participants with
nine stimuli that elicit a wide range of chemesthetic sensations that might all be
60
colloquially called “spicy”; two taste stimuli were also including in the sorting task. Free
sorting was conducted with naïve assessors who were split into two groups, a group that
completed the task without nose clips and a group that wore nose clips. As a number of
these chemesthetic agents have strong aromas (e.g. eucalyptol and cinnamaldehyde) we
included a nose-occluded condition with nose clips to minimize the possibility that
olfaction was used as a panelists’ primary criteria for sorting. Inclusion of a nose-
occluded condition allows data to be compared to prior work (Cliff & Heymann 1992)
while data collected in the nose open condition presumably has more ecological validity,
as this would be more representative of the experience when these compounds are
consumed in food. Utilizing free sorting, MDS, cluster analysis, and regression, we
investigated the perceptual similarities of various chemesthetic stimuli in a set of
untrained assessors.
Materials and Methods
Overview
This study was performed in two distinct groups of individuals (n’s =30 and 31).
All conditions, stimuli, and instructions were the same in the two groups, with the
exception that the second group was required to wear a nose clip for the entirety of the
testing session. All data were collected with the approval of the local Institutional Review
Board and the informed consent of participants.
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Participants
Participants were recruited from the Pennsylvania State University campus and
the surrounding area. To be eligible, individuals needed to be non-smoking, fluent
English speakers between 18 and 55 years old, with no known food allergies or defect of
taste or smell. Additional exclusion criteria included being pregnant or nursing, taking
prescription medication for any chronic pain condition, having known difficulties
swallowing, or a history of thyroid irregularities. As sorting procedures have been shown
to stabilize with around 25-30 subjects (Faye, Brémaud et al., 2006; Lawless & Horne,
2000), we tested ~ 30 participants in each cohort. To avoid any effect of learning,
different individuals participated in the nose open and nose pinched portions of the test.
Stimuli
Samples were prepared in ethanol (95%, USP, Koptec, King of Prussia, PA), with
the exception of citric acid and quinine, which were prepared in reverse osmosis (RO)
water. All samples were Food Grade (FG), Food Chemical Codex (FCC), Kosher, or U.S.
Pharmacopeia (USP) grade. Eugenol (12.2mM), menthol (38.4mM), allyl isothiocyanate
(0.36M), zingerone (vanillylacetone; 59.7mM), quinine (4.1mM), cinnamaldehyde
(0.12M), and carvacrol (0.27M) were obtained from SAFC (St. Louis, MO), citric acid
(112mM) from J. T. Baker (Phillipsburg, NJ), capsaicin (100uM) from Sigma, eucalyptol
(0.65M) from International Flavors and Fragrances (Union Beach, NJ), and huajiao (red
extract; 5% w/w) was a gift from Dr. Christopher Simons (Givaudan, Cincinnati, OH).
The stimuli concentrations used in this experiment were identified from previous
literature and pilot tested by our research team. The final concentrations of the stimuli
62
were determined to elicit similar levels of sensation intensity when delivered using our
tasting protocol.
Procedure
Samples were made as stock concentrations and kept up to three weeks. Cotton swabs
were saturated in stock solution and dried, cotton end up, with the wooden shaft pressed
into blocks of florist’s foam. Swabs impregnated with solutions in ethanol were dried for
three hours, an amount of time deemed appropriate for all of the ethanol to evaporate
from the swabs, and solutions in water were allowed to dry for 10 hours. All
concentrations above are nominal. As in Green and Hayes (2003), we did not control for
differing rates of volatility across stimuli; nonethless, the relative concentrations should
be roughly stable across participants as swabs were produced strictly following the same
protocol each time. Swabs were tagged with three-digit blinding codes and stored in
plastic zip-top bags for up to one week.
Samples were presented, cotton end down, in glass culture test tubes. Each tube had
two swabs in the tube and each sample had its own tube (11 test tubes total; see
supplemental materials for photograph). The sample presentation order was randomized
and counterbalanced so that any remaining cross- or self-sensitization would not result in
any systematic bias. Participants were instructed to pump 10 mL RO water (held at 35C)
into a medicine cup and then hold the swab in the water for three seconds, or until the
swab was fully hydrated. They were instructed to roll the swab across their tongue three
times, making sure to cross the midline, and then to rub the swab against the roof of their
mouth three times. They then breathed in through their mouth three times, allowing air to
63
pass over their tongue, and touched the tip of their tongue to the roof of their mouth three
times. Participants were instructed not to rinse with water (RO water at 35C) until after
they had placed the sample into the group they deemed appropriate. During the three-
minute interstimulus interval, participants rinsed ad libitum (at least twice) until no
lingering sensation was perceived. This interval was determined in pilot testing to be
sufficient to allow sensations to fully dissipate. Retasting was allowed, however panelists
were instructed that any retasting must be done in the same manner as the initial tasting,
using a fresh swab, new medicine cup, and new water for each stimulus. They were also
instructed that they must rinse with water and allow at least three minutes to pass
between tasting samples, moving on to the next sample only when they did not feel that
there was any lingering sensation. All samples and rinse water were expectorated.
As placeholders, participants used poker chips labeled with three-digit codes
corresponding to the codes labeling the swabs to make their groupings. They were
instructed to arrange the samples into groups based on the perceived similarities and
dissimilarities such that two samples that were similar were in the same group and two
samples that were dissimilar were in two different groups. Participants were told to form
as many groups as they felt were appropriate with the only restrictions being that they
must form between two and ten groups (number of stimuli – 1), so that there was not one
large group nor was each sample in an individual group of one. Participants were
instructed to focus only on the sensation elicited by the stimulus and not any physical
similarities or differences in the swabs or blinding code tags. Beyond this, the specific
criteria on which these groupings were formed were left up to the participants.
Participants were told at the beginning of the session that they need not worry about
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naming the groups that they formed. After they tasted all of the samples and decided on a
final configuration, participants entered their groupings into a web-based card-sorting
program (Websort, UXPunk, Chicago, IL) and were then asked to provide a description
of each group. In the description task, participants were able to use whatever attributes
they felt necessary to differentiate between groups.
In addition to the stimuli, participants were provided a notepad and pen to keep
notes if they desired. They also received a sheet with the sampling directions outlined and
a list of possible descriptors. Participants were reminded that this list was merely a
starting point and was not a comprehensive list. They were instructed to not use the
words if they did not feel that the words were appropriate to describe the sensation that
they felt. The list of words included anesthetizing, astringent, biting, bitter, burning,
buzzing, cooling, drying, hot, irritating, itching, metallic, numbing, pricking, puckering,
salty, sharp, sour, spicy, stinging, sweet, swelling, tickling, tingling, umami/savory, and
warming. No definitions were provided. These words were chosen as a compilation of
words used in previous research working with chemesthetic agents (Albin & Simons,
2010; Bennett & Hayes, 2012; Cliff & Heymann, 1992) with the prototypical tastes
added in. The list was presented in alphabetical order.
After the participants completed the sorting task, which took roughly an hour,
they completed an online personality questionnaire consisting of Arnett’s Inventory of
Sensation Seeking (AISS; (Arnett, 1994) and the Food Involvement Scale (FIS; (Bell &
Marshall, 2003); results reported elsewhere).
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Data Analysis
Multidimensional scaling (MDS) was performed on dissimilarity matrices using
The R Statistics Package (R Foundation for Statistical Computing). In R, we used the
smacof library for MDS, the agnes function in the cluster library for cluster analysis, and
the FactoMineR (Husson, Lê et al., 2007) library to calculate normalized RV coefficients
(see below).
For individual participants, data from the free sorting task was put into a binary
(0/1) matrix indicating whether two stimuli were grouped together or not. These values
were summed across all subjects and converted into a triangular similarity matrix
showing counts of times that samples were paired together across all participants. By
subtracting the triangular similarity matrix from the number of assessors in that group,
this similarity matrix was converted to a dissimilarity matrix and submitted to MDS. The
MDS procedure created iterations of a perceptual map given the submitted data and at
each step a regression was applied to the perceptual map solution using Kruskal’s
algorithm (Kruskal, 1964). This regression generated a stress value, measuring the quality
of fit of the model.
To determine the number of dimensions to be used in the multivariate
configurations, we used a Scree plot with Kruskal’s stress values shown as a function of
the number of dimensions in the respective MDS solution. As the number of dimensions
increases, the Kruskal’s stress values decrease. The appropriate number of dimensions for
the MDS solution was chosen as the point when the increase in dimensionality did not
provide a meaningful decrease in stress or did not aid in the interpretation of the
configuration. Generally, a stress level below 0.1 is considered an acceptable model fit
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(Krzanowski & Marriott, 1994). Using these criteria, two dimensions were determined to
be most appropriate for the nose open group (stress = 0.017) and three dimensions were
determined to be most appropriate for the nose pinched group (stress = 0.002)
The RV coefficient (Robert & Escoufier, 1976), a multivariate generalization of
Pearson’s R2, is commonly used as a measure of similarity between the multivariate
configurations. This coefficient ranges from 0 to 1, with 1 being more highly correlated
than 0. Here, we used the normalized RV coefficient (NRV) because the number of
stimuli in a group and dimensions in the perceptual map can influence the RV coefficient
(Nestrud & Lawless, 2008b). The NRV is interpreted similarly to a z-score, with a large
score (>2) indicating significant similarity between the maps. The coeffRV function in
FactoMineR also computes a p value for the comparison of maps.
In total, 24 separate attributes were generated for the nose open group, and 35
distinct attributes were generated for the nose pinched group. Multiple regression was
used to correlate attributes with the stimuli coordinates to visualize which attributes were
associated with individual stimuli. A linear model was used to regress the stimulus
coordinates onto the attribute. From these models, regression coefficients were used as
coordinates to show the placement of the attribute vectors in the perceptual mapping
configurations (Schiffman, Reynolds et al., 1981). The top six attributes for each sample
were submitted to regression analysis. Attributes with p-values less than 0.1 were
considered meaningful.
Agglomerative hierarchical cluster analysis was conducted on the two matrices.
This type of cluster analysis begins with each observation in its own cluster and merges
the clusters one-by-one based on proximity until only one large cluster containing all
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observations remains. Agglomerative hierarchical clustering was used as opposed to the
k-means nonhierarchical clustering method, as the advantages to using the k-means
method manifest in samples with large amounts of data, which we do not have here. In
keeping with previously reported studies (e.g. (Faye, Brémaud et al., 2004), we used
agglomerative hierarchical clustering methods with Ward’s minimum variance method as
the linkage criteria in this study. To determine the appropriate number of clusters, a plot
of amalgamation distance versus joining order was used. On this joining distance plot,
large jumps in the amalgamation distance indicate items being joined in that step have
increased dissimilarity as compared to previously joined items (See (Lawless, 2013) for
further explanation).
Results
Nose open group
Figure 5-1 shows the MDS configuration for the participants who conducted the
task without nose clips (nose open). Based on the Scree plot, a two-dimensional solution
was appropriate for these data, as adding a third dimension did not significantly reduce
the stress or add interpretability (2D stress=0.017).
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Figure 2-1. Perceptual map of 11 chemesthetic compounds sorted in a free sorting task by participants not wearing nose clips (N=30), with descriptors projected onto the map via regression. Stimuli include allyl isothiocyanate (AITC), capsaicin (CAP), carvacrol (CARV), cinnamaldehyde (CINN), citric acid (CA), eucalyptol (EUCA), eugenol (EUG), huajiao (HJ), menthol (MEN), quinine (Q), and zingerone (ZING).
The nose open group of participants generated 24 unique attributes. Significant
attributes were anesthetizing/numbing, astringent/drying, burning, cooling, minty,
pricking/stinging, puckering, sharp, sour, spicy, and warm. As shown in Figure 2-1, there
are two roughly orthogonal axes on this plot. The first axis opposes burning and cooling,
69
with the attributes burning, spicy, and pricking/stinging at one end, and the attributes
cooling and anesthetizing/numbing at the other end. The second is an opposing puckering
and warming axis, with the attributes puckering, sour, and astringent/drying at one end
and warm at the other end. Minty seems to fall between the warm and the
anesthetizing/numbing axes in this configuration.
Cluster analysis of sorting data produced six clusters (Figures 2-2 and 2-3). In
Figure 2-2, allyl isothiocyanate and the zingerone-capsaicin cluster are along the burning
axis and the eucalyptol-menthol group is at the cooling end of this axis. The eugenol-
cinnamaldehyde, citric acid-huajiao, and quinine-carvacrol groups fell between these
poles. With regard to the second axis, the eugenol-cinnamaldehyde group fell near the
warming pole with the citric acid-huajiao group near the puckering pole. The
agglomerative coefficient for this configuration is 0.83, indicating a strong clustering
structure, as shown in Figure 2-3.
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Figure 2-2. Same as Figure 2-1 (map of 11 chemesthetic stimuli from sorting by 30 participants not wearing nose clips), but with clusters generated via agglomerative hierarchical cluster analysis (agglomerative coefficient = 0.83). Stimuli use the same abbreviations as Figure 2-1.
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Figure 2-3. Dendrogram from agglomerative hierarchical clustering of the sorting done by 30 participants not wearing nose clips. Agglomerative coefficient is 0.83.
Nose pinched group
Based on the Scree plot generated from MDS on the data generated by the nose
pinched group (N=31), a three-dimensional solution was appropriate for these data.
Kruskal’s stress for a two-dimensional solution is 0.018, an acceptable value, however,
adding a third dimension added to the interpretability of the data and reduced the stress
further (stress = 0.002).
The nose pinched group generated 35 unique attributes for this task. The
significant attributes (p<0.1) were burning, cooling, hot, minty, nothing, pricking/stinging,
refreshing, sharp, and spicy. In the three-dimensional solution (not shown), there are
three main attribute dimensions (See Supplemental Figures for a full scatterplot matrix
with attribute vectors). The first attribute, burning, points slightly positive on dimensions
2 and 3 and runs parallel to dimension 1. This general dimension is made up of the
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attributes burning, hot, pricking/stinging, and spicy. The second dimension is represented
as cooling and is made up of cooling and refreshing. This attribute dimension points
toward positive values on dimensions 1, 2, and 3. The final dimension, ‘nothing’, points
towards positive values on dimension 1 and negative values with respect to dimensions 2
and 3.
Figure 2-4. Perceptual map with clusters generated by the participants that completed the free sorting task on 11 chemesthetic compounds with nose clips (N=31). A three-dimensional solution was most appropriate (stress = 0.002) for this group. Notation is in the style of the Natta projection: Dimension 3 in the bottom left of the figure with the dotted line represents values farther away from the viewer (negative values on dimension 3) and the bolded line indicating that the plane is closer to the viewer (positive values on dimension 3). The positions of points with respect to dimension 3 are indicated by the size and color of the point. Larger, lighter blue points, (e.g. CINN), are closest to the viewer, while smaller, redder points, (e.g. MEN), are farthest from the viewer. For a fully expanded 2D scatterplot matrix projection of the 3D space, see Supplemental Materials.
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Cluster analysis on the group data for the nose pinched condition resulted in two
distinct groups. The first of the two groups consisted of carvacrol, zingerone, capsaicin,
citric acid, cinnamaldehyde, menthol, and allyl isothiocyanate. The second group was
made up of quinine, huajiao, eugenol, and eucalyptol. The agglomerative coefficient for
this cluster analysis was 0.79, indicating that the clustering structure was less well
defined than the clusters in the nose open group.
Figure 2-5. Dendrogram from agglomerative hierarchical clustering of sorting done by 31 participants with nose clips. Agglomerative coefficient is 0.79.
Normalized RV coefficient
The Normalized RV coefficient (NRV) was used as a measure of similarity
between the perceptual maps (MDS plots). The NRV between the two-dimensional “nose
open” map and the three-dimensional “nose pinched” maps was 0.933. In this test, a
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significant p value of less than 0.05 indicates ‘significant similarity’, so the observed p
value of 0.172 indicates the two maps are significantly different from one another.
Discussion
Chemesthetic stimuli are particularly difficult to work with due to long decay
times, possible sensitization and desensitization, and the highly fatiguing nature of these
compounds. This work shows that with the appropriate considerations, free sorting can be
successfully conducted with a number of chemesthetic stimuli in a reasonable amount of
time. The results presented here also show that participants can attend to the task and can
reliably differentiate between a number of sensations that in the colloquial context may
all be called “spicy” or “cooling”.
Design Considerations for Stimulus Delivery
There are a number of difficulties when working with chemesthetic agents. Cross-
and self-sensitization and desensitization phenomena (Cliff & Green, 1996; Dessirier,
O'Mahony et al., 2001; Green, 1989; Green, 1991; Green & Hayes, 2003; Green & Hayes,
2004; Jancso, Kiraly et al., 1977; Klein, Carstens et al., 2013; Prescott, 1999; Simons,
Carstens et al., 2003) and differing temporal profiles these compounds (e.g. different
onset times and decay rates) make designing a single session study complex. As previous
work shows, stimulus concentration and interstimulus interval can significantly influence
whether sensitization or desensitization is observed, so additional precaution in working
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with chemesthetic compounds is necessary (Green, 1989; Green, 1991; Prescott &
Stevenson, 1995a; Prescott & Stevenson, 1996a; Simons, Carstens et al., 2003).
To account for these difficulties, we delivered stimuli on swabs to multiple oral
regions while limiting the total amount of stimulus in the mouth, and made the tasting
protocol sufficiently long to allow for sensation onset prior to assessment. To ensure
sufficient decay between samples, we used a minimum interstimulus interval of at least
three minutes with rinsing ad libitum, even when retasting. The total sample number (11)
was selected to allow participants to complete the entire task in a single one-hour session.
In an effort to maximize the number of chemesthetic stimuli that were assessed and
ensure that stimuli that spanned a range of various chemesthetic sensations were
represented in the sample set, we included two prototypical tastants in the sample set.
Based on previous literature suggesting that some individuals report bitter side tastes
from capsaicin, we included quinine as one of the prototypical tastants (Green & Hayes,
2003; Green & Hayes, 2004). Pilot testing was used to choose concentrations that were
sufficient to evoke sensations rated as “moderate” on the gLMS. Concentrations were
high enough to elicit sensation but low enough that sensation dissipated within three
minutes. Finally, the tasting order was counterbalanced across participants to prevent any
systematic bias due to sample carryover. Collectively, we show that with an appropriately
designed protocol, it is possible to conduct sorting and mapping with chemesthetic agents.
In addition to precautions taken to limit area of stimulation and to maximize time
between stimuli, the presentation order of the stimuli was counterbalanced. Theoretically,
if there was meaningful cross sensitization or desensitization by any of the stimuli, we
would expect the consensus between individuals in each of the cohorts to drop, as the
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effects would not have been consistent across individuals with the different presentation
orders. Comparing the results presented here with stress values from sorting studies
conducted using stimuli that do not sensitize or desensitize (words on cards (Bertino &
Lawless, 1993), plastic pieces (Faye, Brémaud et al., 2004), odors (Lawless, 1989), and
grape jellies (Tang & Heymann, 2002), we see lower stress in solutions from both the
nose open and nose pinched cohorts (0.017 and 0.002, respectively). Collectively, the
stress values and the fact that the stimuli differentiated across several axes indicate that
the stimulus concentrations selected, the rinse protocol and the three minute interstimulus
intervals were sufficient to avoid cross sensitization or desensitization that might interfere
with the task.
When participants had all of their senses available to them, they appeared to use
chemesthetic qualities as their primary criteria for sorting. These groupings tended to
follow a biological basis, in agreement with the common assumption that activation of
common receptors should elicit similar perceptual qualities (Bennett & Hayes, 2012;
Bryant & Mezine, 1999; Sawyer, Carstens et al., 2009). However when comparing the
nose open and nose pinched groups, it is obvious that perception in the nasal cavity
(either olfaction or nasal chemesthesis) was a significant criteria as well, providing
important information to participants in the event that the qualities were either reliant on
nasal airflow (e.g. cooling in eucalyptol), were difficult to feel (e.g. numbing associated
with eugenol), or were unique (e.g. buzzing associated with huajiao).
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Nose open
In total, the nose open group generated 24 unique attributes for the 11
chemesthetic stimuli. Of these, 11 attributes were significant and there were two
opposing attribute dimensions that described the sample space, the burning-cooling axis
and the drying-numbing axis. For convenience, we refer to the ends of these axes as
burning, cooling, drying, and warming, respectively, but in actuality, the perceptual space
was described using additional attributes that regression analysis showed were similar.
As would be expected, naïve assessors in the nose open group used burning, spicy,
sharp, and pricking/stinging to describe sensations associated with allyl isothiocyanate,
zingerone, and capsaicin, in contrast to eucalyptol and menthol, which were described as
anesthetizing/numbing and cooling. The observation that terms like puckering, sour, and
drying/astringent fell on similar vectors is not surprising, as organic acids are known to
produce astringent sensations (Thomas & Lawless, 1995). Notably, the descriptor warm
was relatively isolated on the plot (lying closest to minty), but orthogonal to the burning
dimension. This finding potentially contradicts the assumption that warming is merely a
less intense version of hot and burning, indicating instead that warming and hot/burning
sensations are perceptually distinct.
In these participants, allyl isothiocyanate, capsaicin, and zingerone all fall in the
burning region of the plot as might be expected, given that each of these compounds have
previously been described as producing hot, burning, and stinging sensations (Caterina,
Schumacher et al., 1997; Dessirier, O'Mahony et al., 1998; Green, 1991; Green & Shaffer,
1993; Karrer & Bartoshuk, 1991b; Karrer & Bartoshuk, 1995; Prescott, Allen et al., 1993;
Prescott & Stevenson, 1996a; Prescott & Stevenson, 1996b). However, while these
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samples fall in the same region of the perceptual map, it is striking to note that in cluster
analysis, allyl isothiocyanate only joins the capsaicin/zingerone cluster only at the highest
level of the dendrogram. Previously, in both human behavioral and cell culture work, it
has been suggested that compounds that elicit perceptually similar sensations would share
common receptors, while compounds that elicit perceptually distinct sensations would
elicit sensation via different mechanisms (Bennett & Hayes, 2012; Bryant & Mezine,
1999; Sawyer, Carstens et al., 2009). Given that capsaicin and zingerone activate the
TRPV1 receptor (Caterina, Schumacher et al., 1997; Szallasi & Blumberg, 1999;
Tominaga, Caterina et al., 1998; Vriens, Appendino et al., 2009), it is expected that they
would show perceptual similarities and that they would be grouped together. Historically,
AITC has been thought to be exclusively a TRPA1 agonist (Bandell, Story et al., 2004;
Jordt, Bautista et al., 2004; Story, Peier et al., 2003), though more recent data indicates
that AITC may somehow sensitize TRPV1 through TRPA1 activation (Bautista, Jordt et
al., 2006), or that it may act directly on TRPV1 (Alpizar, Boonen et al., 2013; Everaerts,
Gees et al., 2011; Ohta, Imagawa et al., 2007). Even though the mechanism has not been
definitively identified, a large body of work shows that there is some type of interaction
between the TRPA1 and TRPV1 receptors (Alpizar, Boonen et al., 2013; Bautista, Jordt
et al., 2006; Doerner, Gisselmann et al., 2007; Eckert III, Julius et al., 2006; Fischer,
Balasuriya et al., 2014; García-Martínez, Humet et al., 2002; García-Sanz, Fernández-
Carvajal et al., 2004; Salas, Hargreaves et al., 2009; Simons, Carstens et al., 2003;
Staruschenko, Jeske et al., 2010; Zurborg, Yurgionas et al., 2007). Considering the
“common receptor-common sensation” hypothesis, dual activation of TRPA1 and
TRPV1 by AITC would explain the large distance on the dendrogram from the
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zingerone-capsaicin cluster and the close proximity on the perceptual map to this cluster
of typical TRPV1 agonists.
At the opposite end of this first axis, near cooling and anesthetizing/numbing lays
the menthol-eucalyptol cluster. Both menthol and eucalyptol activate TRPM8 and
produce predominantly cooling sensations (McKemy, Neuhausser et al., 2002; Peier,
Moqrich et al., 2002). While cooling is the sensation commonly associated with menthol,
prior work paradoxically describes it as being warming (Green, 1985; Hatem, Attal et al.,
2006). Interestingly, millimolar concentrations of menthol have shown activation of
TRPV3 (Karashima, Damann et al., 2007; Macpherson, Hwang et al., 2006; Vogt‐Eisele,
Weber et al., 2007), a receptor that are implicated in the perception of warmth (Chung,
Im et al., 2014; Peier, Reeve et al., 2002; Xu, Delling et al., 2006). TRPA1 has been
identified as a cold receptor (Bautista, Jordt et al., 2006; Karashima, Damann et al., 2007;
Story, Peier et al., 2003), though this channel’s role in cold sensing is debated (Bandell,
Macpherson et al., 2007). Menthol has been shown to block TRPA1 at submillimolar
concentrations, which, if TRPA1 is responsible for cold-sensing, could account for the
sensation of warmth that is elicited by menthol. Additionally, activation of both TRPV3
and TRPM8 by menthol would account for the placement of menthol at the approximate
midpoint between the cooling and warming regions of the perceptual map.
The fourth cluster, eugenol and cinnamaldehyde, associates with the warm region
of the plot. Previously, eugenol has been described using a number of descriptors,
including numbing, tingling, warming, burning, stinging, and pricking (Cliff & Heymann,
1992; Green, 2002; Klein, Carstens et al., 2013; Wise, Wysocki et al., 2012). As with
other chemesthetic agents, eugenol activates a number of TRP receptors in vitro in a
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concentration dependent manner, which may account for its diffuse perceptual nature.
Among the receptors that are reportedly activated by eugenol are TRPA1, TRPV1, and
TRPV3 (Bandell, Story et al., 2004; Vogt‐Eisele, Weber et al., 2007; Xu, Delling et al.,
2006; Yang, Piao et al., 2003). In contrast, cinnamaldehyde is thought to be a strict
TRPA1 agonist (Bandell, Story et al., 2004; Bautista, Jordt et al., 2006; Calixto, Kassuya
et al., 2005; Karashima, Damann et al., 2007; Macpherson, Hwang et al., 2006; Talavera,
Gees et al., 2009; Xu, Delling et al., 2006). Again, given the common receptor common
sensation assumption, that cinnamaldehyde and eugenol both activate TRPA1 means it is
not entirely unexpected that they share common perceptual space. It is notable that AITC,
another TRPA1 agonist does not share space on the perceptual map but is the closest
neighbor to the eugenol-cinnamaldehyde cluster on the dendrogram. Additionally,
cinnamaldehyde and eugenol shared descriptors that reference their association with
baking and brown spices, indicating that there is likely a learned association of these two
stimuli arising from the frequent concurrent use of cinnamon and cloves in culinary
applications, distinct from their activation of TRP channels.
The fifth and sixth clusters, huajiao and citric acid, and carvacrol and quinine,
respectively, are more difficult to interpret. The huajiao/citric acid cluster is diffuse, with
huajiao positioned along the anesthetizing/numbing, cooling axis and citric acid along the
puckering, sour, astringent/drying axis. The placement of huajiao on the map and
association with anesthetizing/numbing descriptions are expected, as this placement is
consistent with prior reports that hydroxyl-alpha-sanshool (the compound primarily
responsible for the sensation elicited by huajiao) and its derivatives elicit numbing and
tingling sensations (Klein, Carstens et al., 2013). Similarly, it is unsurprising that citric
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acid was described as puckering and sour. On this basis, these two compounds would not
seem to be similar enough to be grouped together, at least initially. However, it is
possible that citrusy/lemon-like associations of these compounds likely resulted in
participants grouping these stimuli. A key component in the aroma of huajiao is limonene,
a compound that is also a key component in the aroma of orange juice (Jiang and Kubota
2004; Yang 2008). Indeed, huajiao was described as having a distinct lemon taste by
some participants (data not shown) and citric acid is associated with citrus aromas via
learned associations. We should also note that our participants had some difficulty
describing the sensation elicited by huajiao, generating 17 different descriptors to
describe this sample. Additional work with isolated compounds (e.g. hydroxy-alpha-
sanshool or synthetic analogues like isobutylalkenyl amide) is warranted.
The final cluster, carvacrol and quinine, appeared to be the cluster of compounds
described as bitter. Both of these compounds were difficult for participants to describe
with any consensus, with 14 distinct attributes generated for carvacrol and 10 attributes
for quinine. It is surprising that participants had such difficulty describing quinine, a
prototypical bitterant, as participants were aware that they could use taste qualities as
descriptors. Examining the dendrogram, this cluster’s closest neighbor is the capsaicin-
zingerone cluster, indicating that some individuals may have also experienced bitterness
from these two compounds, a finding that would align with previous work (Green &
Hayes, 2003; Green & Hayes, 2004).
Nose pinched
Both to allow comparison to previous work (Cliff & Heymann, 1992), and because a
sufficient number of individuals in the nose open cohort used descriptors referencing
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aromas, we conducted a second experiment where a new cohort of participants completed
the sorting task while wearing nose clips. The clips served to occlude the nasal passages
and minimize any ortho- or retronasal odors that may influence the participants
For the nose pinched map, a three-dimensional solution was found to be most
appropriate, as the third dimension greatly enhanced interpretability. Overall, there were
35 distinct attributes generated by this group. Significant attributes included burning, hot,
spicy, pricking/stinging, refreshing, cooling, and ‘nothing’. In general, there were three
representative dimensions. The first dimension was ‘burning’, consistent of the
descriptors burning, spicy, hot, and pricking/stinging. The second was ‘cooling’,
consisting of cooling and refreshing, and the third dimension consisted of the attribute
participants denoted as ‘nothing’. It is interesting to note that the nose pinched cohort
generated more attributes than the nose open cohort. A possible explanation for this may
be that when individuals are less certain about the identity of the origin of the sensation
(i.e. mustard or cinnamon), they are more inclined to use more terms to describe what
they perceive. Indeed, more individuals in the nose open group attempted to identify the
food that the compound was associated with (data not shown).
Agglomerative hierarchical clustering of the nose pinched cohort’s data indicated that
two large groups were present in the perceptual space. Crudely, these two clusters map
onto the participants ability or inability to readily identify a taste or chemesthetic
sensation. The first cluster, with distinct perceptual qualities, contains citric acid,
cinnamaldehyde, zingerone, capsaicin, carvacrol, menthol, and allyl isothiocyanate
(AITC). This cluster encompasses over half of the plot, covering the regions described by
the burning and cooling vectors. The second cluster includes huajiao, eugenol, eucalyptol,
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and quinine; this cluster falls on the region of the plot characterized by the descriptor
‘nothing’. In contrast to the nose open group, the nose pinched group had far fewer
groups. Also, it is notable that the stimuli put into the nothing group by the nose pinched
cohort are the same stimuli the participants in the nose open cohort tended to cluster
together based on olfaction rather than chemesthesis. It is possible that assessors used
olfaction as a sorting criterion in lieu of perceiving any chemesthetic sensation. However,
this seems unlikely, as even in the nose pinched condition, assessors provided attributes
for these stimuli that were chemesthetic in nature (e.g. anesthetizing/numbing, cooling,
pricking/stinging, and tickling/tingling). We did not expect these striking differences
between the nose open and nose pinched cohorts, but it does suggests our participants
were likely attending to more than just the chemesthetic properties of the stimuli when
conducting the sorting task. Accordingly, future work should carefully consider whether
to use nose clips, depending on the question of interest.
Concerning some of the more volatile components, such as eugenol, cinnamaldehyde,
eucalyptol, and AITC, where nasal perception may have played a role in the sorting task
(in the nose open cohort), there were differences between descriptors generated by the
nose open and nose pinched cohorts. In all cases where attributes describing nasal
perception seemed to play a significant role in the sorting decisions of study participants,
such as with eugenol, AITC, and cinnamaldehyde, these descriptors were absent in the
nose pinched cohort. For stimuli such as capsaicin, where we expect no nasal perception,
there was no difference between the nose open and nose pinched cohorts. Interestingly, in
the nose pinched cohort, cinnamaldehyde was not described as warming by any of the
study participants. It may be possible that since there was a general tendency in the nose
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pinched cohort to use the term “hot” more often (7 individuals used the term in the nose
open cohort while 37 individuals used the term in the nose pinched cohort), that the
“warming” description was interpreted as “hot” by these individuals, but this finding
merits further investigation.
Conclusions
As discussed above, the nose open cohort appeared to group samples based
primarily on the chemesthetic or taste sensation, although olfaction appeared to
contribute as well. This perceptual map was roughly based on the underpinning
biological mechanisms; consistent with the hypothesis that compounds that share similar
perceptual properties activate common receptors (Bennett & Hayes, 2012; Bryant &
Mezine, 1999; Sawyer, Carstens et al., 2009). Many chemesthetic agents activate
numerous receptors in cell culture studies but it is important to consider several important
factors when interpreting cell-based evidence with respect to human behavioral data.
Foremost is the potential for different levels of expression and differing sensitivity of
receptors across species or cell preparations (Bandell, Macpherson et al., 2007; Klein,
Sawyer et al., 2011; Riera, Menozzi‐Smarrito et al., 2009). Recently, the presence of
heteromeric dimers and tetramers in native systems has been explored and the findings
suggest that again, the cell culture data needs to be interpreted cautiously to avoid being
overly reductionist, as heteromers show altered functionality that cannot be replicated in
heterologously expressed systems (Cheng, Yang et al., 2012; Fischer, Balasuriya et al.,
2014). While cell culture work is critical to elucidate molecular mechanisms, behavioral
85
work is indispensable as it provides insight into how our perceptions relate to these
molecular mechanisms within the whole organism.
Even though we did observe a few instances where olfactory input and learned
association appeared to influence the participants’ sorting decisions (i.e. the pairing of
eugenol, in cloves, and cinnamaldehyde, in cinnamon, or the pairing of huajiao with citric
acid), the perceptual map from the nose open cohort did tend to follow the putative
biological mechanisms believed to underlie these sensations. In the nose pinched cohort
only two clusters appeared, indicating that the map did not readily relate to the biological
interpretation observed in the nose open map. There are a number of factors that suggest
that conducting the task with a nose clip on was not as easy for participants to complete
as without nose clips, including the higher variance in the nose pinched cohort, lower
level of consensus regarding attributes, and the presence of only two clusters.
Overall, this study suggests free sorting procedures can be successfully completed
using chemesthetic agents with naïve participants with all senses available to them. In
designing this study we took into account a number of considerations to reduce the
potential for cross- or self-sensitization and desensitization to occur while still evoking
sufficiently intense chemesthetic sensations. These design considerations include the
delivery method, concentrations, tasting method, and interstimulus interval. Compared to
working with tastants and odorants, the number of stimuli that can be used for a sorting
task is significantly lower when working with chemesthetic agents, but it remains feasible.
We also demonstrate that naïve participants without prior training can consistently
differentiate between the perceptual qualities of different chemesthetic agents.
86
Acknowledgments
This manuscript was prepared in partial fulfillment of a Doctor of Philosophy degree by
N.K.B. The authors of this manuscript would like to thank Dr. Christopher Simons for his
donation of a huajiao extract to be used in the experiment, Laura Boone and Meghan
Kane for assistance with data collection, and all of our participants for their time and
involvement in the study.
Funding
This work was supported by funds from the Pennsylvania State University, United States
Department of Agriculture Hatch Project PEN04332 funds and a National Institutes of
Health grant from the National Institute National of Deafness and Communication
Disorders [DC010904] to JEH.
87
Supplemental Figures
Supplemental Figure 2-1. Scatterplot matrix of the perceptual map generated by the nose-pinched cohort.
88
Supplemental Figure 2-2. Setup used for the sorting task for both cohorts.
89
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Chapter 3
Perception of chemesthetic stimuli in groups who differ by culinary experience.
Abstract
Generally, in the English language, there is a limited lexicon when referring to the
sensations elicited by chemesthetic stimuli like capsaicin, allyl isothiocyanate and
eugenol, the orally irritating compounds found in chiles, wasabi and cloves, respectively.
Experts and novices have been shown to use language differently, with experts using
more precise language. Here, perceptual maps and word usage are compared across three
cohorts: culinary experts with formal training, naïve individuals with high Food
Involvement Scale (FIS) scores, and naïve individuals with low FIS scores. We
hypothesized that expertise, whether informal experiential learning or formal culinary
training, would have a significant influence on the outcome of a sorting task completed
with a descriptive portion conducted with chemesthetic stimuli. The low- and high-FIS
cohorts generated significantly similar maps, though in other respects the high-FIS cohort
acted as an intermediate between the low-FIS and expert cohorts. The high-FIS and
expert cohorts generated more attributes but behaved more idiosyncratically than the low-
FIS group. Overall, the expert group with formal culinary training differed from the two
naïve cohorts both in the perceptual map generated using MDS as well as the mean
number of attributes generated. Present data suggest that both formal training and
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informal experiential learning result in lexical development, but the level and type of
expertise also have significant influence on the outcome of a sorting experiment.
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Introduction
Sorting is one approach within a family of methods commonly used to generate
perceptual maps. Perceptual mapping techniques provide information about basic
attributes and common characteristics that are relevant to the assessors, regardless of
whether those assessors are trained or untrained participants. In a sorting task, assessors
evaluate a group of stimuli and create groupings of the stimuli based on perceived
similarities and dissimilarities. Prior work has suggested that napping (or projective
mapping), a related technique where participants place samples on a large sheet of paper
such that similar samples are closer together and dissimilar samples are farther apart, may
provide better product differentiation (King, Cliff et al., 1998; Nestrud & Lawless, 2011)
but there are significant drawbacks to the napping method when compared to sorting.
Specifically, the ad libitum retasting that is common in napping precludes the use of
highly fatiguing samples, such as chemesthetic stimuli like capsaicin, zingerone, and
menthol. Recently, we demonstrated that it is possible to conduct sorting with
chemesthetic stimuli if the necessary precautions are taken to minimize carryover and
desensitization (Byrnes, Nestrud et al., 2013).
Generally, there can be substantial semantic confusion surrounding the sensations
elicited by chemesthetic compounds (Bennett & Hayes, 2012). It is not uncommon to
hear sensations that are easily distinguishable, such as those caused by chili peppers and
horseradish, all colloquially referred to as being “spicy” or “hot” in spite of clear
differences between them. Historically, one major advantage of using similarity-based
judgments is that they avoid what Schiffman and colleagues termed “linguistic
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contamination” (Schiffman, Reynolds et al., 1981). In the present study, we explored the
role of formal culinary training on the ability of assessors to differentiate between and
describe the sensations elicited by a broad set of chemesthetic agents. We chose to
compare individuals with formal culinary training to naïve assessors as we reasoned
culinary training would enhance an individual’s personal lexicon regarding these various
chemesthetic sensations.
Previous work conflicts as to whether consumers are able to generate perceptual
maps comparable to those generated by trained panelists or individuals with expertise
(Barcenas, Elortondo et al., 2004; Cartier, Rytz et al., 2006; Chollet & Valentin, 2001;
Faye, Brémaud et al., 2004; Faye, Brémaud et al., 2006; Gains & Thomson, 1990;
Giacalone, Ribeiro et al., 2013; Guerrero, Gou et al., 1997; Kennedy & Heymann, 2009;
Lawless & Glatter, 1990; Nestrud & Lawless, 2010; Pagès, 2005; Perrin, Symoneaux et
al., 2008; Risvik, McEwan et al., 1997; Roberts & Vickers, 1994). Importantly, the
existing reports test the consensus of these configurations using a number of different
methods, including sorting (Cartier, Rytz et al., 2006; Lawless & Glatter, 1990), napping
(Kennedy & Heymann; Nestrud & Lawless, 2010), and free-choice profiling (Gains &
Thomson, 1990; Guerrero, Gou et al., 1997), they use a variety of different definitions of
“expert” (cf. (Chollet & Valentin, 2001; Guerrero, Gou et al., 1997; Lawless & Glatter,
1990; Nestrud & Lawless, 2010)), and use a number of different stimuli, such as odorants
(Lawless & Glatter, 1990), leather (Faye, Brémaud et al., 2006), beers (Giacalone,
Ribeiro et al., 2013), and cheddar cheeses (Roberts & Vickers, 1994). A few key
differences have been identified between experts or trained panelists and untrained
assessors that may account for differences in the maps generated using perceptual
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mapping techniques. These include the differences in memory and language use between
experts and non-experts, different focus as a result from training, and the acuity of trained
versus untrained participants regarding small product differences.
It has been proposed that experts may perform tasks differently than untrained
assessors due to superior memory abilities which result in less of an impairment by a
delay between samples and better ability to cope with the memory load required in tests
with repeated tasting of samples (Almeida, Cubero et al., 1999; Chollet, Valentin et al.,
2005; Nestrud & Lawless, 2010; Parr, White et al., 2004). Additionally, dissimilarities
between experts and novices have also been attributed to differential use of language.
While untrained assessors tend to use vague, less specific terms, experts and trained
panelists reported use language more precisely and efficiently (Chollet & Valentin, 2001;
Clapperton & Piggott, 1979; Faye, Brémaud et al., 2004; Gains & Thomson, 1990;
Guerrero, Gou et al., 1997; Lawless, 1984; Solomon, 1990). Importantly, describing the
precision of word usage by experts and trained panelists refers to both the specificity and
repeatability of the words. Solomon argues that the precise use of language allows for
more subtle discrimination between samples (Solomon, 1990), a view supported by
literature showing better discrimination in experts and trained panels compared to
untrained assessors (Lawless, 1984; Risvik, McEwan et al., 1997; Roberts & Vickers,
1994; Tang & Heymann, 2002; Torri, Dinnella et al., 2013). While trained assessors may
be better at identifying small differences between samples, it is also observed that
training or expertise may shift the way that these assessors attend to the task (Delarue &
Sieffermann, 2004; Roberts & Vickers, 1994; Torri, Dinnella et al., 2013). For example,
Roberts and Vickers showed that trained dairy judges tend to focus on defects in cheeses,
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rating primarily negative qualities, versus assessors not trained in dairy judging, who
rated both positive and negative attributes (Roberts & Vickers, 1994) . Likewise, Torri
and colleagues (Torri, Dinnella et al., 2013) showed wine experts tended to generate
napping configurations that were equivalent to quality assessments while consumers
tended to sort based on hedonic criteria. Overall, it is unclear whether experts act in a
way that is more reproducible or more idiosyncratic than consumers as past reports
conflict (Barcenas, Elortondo et al., 2004; Nestrud & Lawless, 2008b; Torri, Dinnella et
al., 2013); we wished to explore this further here.
Importantly, we recognize that not all “experts” are equal. The training the one
receives to become a wine expert and dairy judging expert are clearly different from one
another, which is different than the training that one would receive during a culinary
education, and this trainings is different still from the training that descriptive analysis
panelists receive. Prior work done comparing naïve assessors to experts shows similar
effects whether the “experts” are trained as descriptive analysis panelists or as expert
assessors for commodity evaluation.
The Food Involvement Scale (FIS) is a measure of involvement with food in an
overall sense, focusing not just on preparation and eating of food but also procurement
and disposal of food (Bell & Marshall, 2003). Bell and Marshall conceived of the FIS as
a general measure in which involvement is defined as the level of importance of food in
someone’s life. The scale measures involvement with food across five different stages:
acquiring, preparing, cooking, eating, and disposal, and factor analysis indicates the
individual scale items load onto two subscales: preparation and eating (FIS-PE) and set
up and disposal (FIS-SD). While an individual’s moods or cravings may change
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throughout the day, making them more or less likely to want to prepare a meal versus
dine out, Food Involvement is more similar to a personality trait in that it does not vary
from moment to moment (Marshall & Bell, 2004). Marshall and Bell reported individuals
with higher FIS scores show finer discrimination between food items in sensation and
hedonic ratings (Bell & Marshall, 2003), although pilot work from our lab suggests this
may not be a robust effect (Byrnes, Allen et al., 2013). Regardless of differences in
sensory acuity that may potentially exist across groups with different expertise (see
discussion in (Hayes & Pickering, 2012), we anticipate that as with a number of other
experiences, greater involvement with food will serve as a type of informal training and
that individuals with higher FIS scores will have more personal lexical development than
individuals with lower FIS scores. To test the effect of formal training, we recruited a
group of individuals with culinary training as a cohort of experts. We hypothesized that
the expert cohort would perform a sorting task with chemesthetic stimuli similarly to the
highFIS and lowFIS cohort in terms of the MDS coordinates that were generated, but that
in the descriptive portion of the task, where participants describe the groups that they
have formed during the sorting task, the experts would perform significantly better than
two cohorts of naive assessors, regardless of FIS score.
Materials and Methods
Overview
This study was performed in three separate groups of individuals. All conditions,
stimuli, and instructions were the same in each group. All data were collected with the
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approval of the Penn State University Institutional Review Board; all participants
provided informed consent.
Participants
Participants were recruited from the Penn State campus and the surrounding area
in State College, Pennsylvania as well as through the Culinary Institute of America, in
Hyde Park, New York. To be eligible, individuals needed to be non-smoking, fluent
English speakers between 18 and 55 years old, with no known food allergies or defect of
taste or smell. Additional exclusion criteria included being pregnant or nursing, taking
prescription medication for any chronic pain condition, having known difficulties
swallowing, or a history of thyroid irregularities. As perceptual maps from sorting
stabilize with around 25-30 participants (Faye, Brémaud et al., 2006; Lawless & Horne,
2000), we tested ~30 participants in each group. To qualify for the expert cohort,
participants were culinary students beyond their second year of instruction, or instructors
who had already attained a degree from a culinary institution.
Stimuli
Samples were prepared in ethanol (95%, USP, Koptec, King of Prussia, PA), with
the exception of citric acid and quinine, which were prepared in reverse osmosis (RO)
water. All samples were Food Grade (FG), Food Chemical Codex (FCC), Kosher, or U.S.
Pharmacopeia (USP). Eugenol (12.2mM), menthol (38.4mM), allyl isothiocyanate
(0.36M), zingerone (vanillylacetone; 59.7mM), quinine (4.1mM), cinnamaldehyde
(0.12M), and carvacrol (0.27M) were obtained from SAFC (St. Louis, MO), citric acid
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(112mM) from J. T. Baker (Phillipsburg, NJ), capsaicin (100uM) from Sigma, eucalyptol
(0.65M) from International Flavors and Fragrances (Union Beach, NJ), and huajiao
extract (red fraction; 5% w/w) was a gift from Dr. Christopher Simons (Givaudan,
Cincinnati, OH). The stimuli concentrations used in this experiment were adapted from
previous literature on oral delivery chemesthetic compounds. The final concentrations
were determined to elicit similar levels of sensation intensity when delivered using our
tasting protocol (Byrnes et al., under review).
Procedure
Stimuli were prepared as stock concentrations and kept up to three weeks. Cotton
swabs were saturated in stock solution and dried, cotton end up, with the wooden shaft
pressed into blocks of florist’s foam. Solutions in ethanol were dried for three hours and
solutions in water were allowed to dry for 10 hours. Swabs were tagged with three-digit
blinding codes and stored in plastic zip-top bags for up to one week.
Stimuli were presented using the same methodology described previously (Byrnes
et al., under review). Briefly, samples were presented in glass culture tubes, with two
swabs in a tube for each stimulus. Participants pumped 10 ml RO water (held at 35C) into
a new medicine cup and held the swab in the water until rehydrated. They then rolled the
swab across their tongue three times, making sure to cross the center line, then rubbed the
swab against the roof of their mouth three times, breathed in through their mouth three
times, allowing air to pass over the tongue, and finally touched the tip of their tongue to
the roof of their mouth three times. Prior to rinsing with water (RO water at 35C)
participants placed the sample into the group they thought was appropriate or they
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formed a new group. A three-minute interstimulus interval was enforced, and participants
rinsed ad libitum (at least twice) until no lingering sensation was perceived. Retasting
was allowed, provided that the participants followed the protocol as if they were tasting a
new sample. All samples and rinse water were expectorated.
As placeholders during sorting, participants used poker chips that had been
labeled with three-digit codes corresponding to the blinding codes on the swabs.
Participants were instructed to form groups of the samples based on perceived similarities
and dissimilarities, however the participants determined the specific criteria on which
these grouping were formed without any input from the experimenter. Study participants
were told at the beginning of the session that they did not need to name the groups that
they formed. After they had tasted all of the samples and decided on a final configuration,
participants input their groupings into a web-based card-sorting program, Websort,
(UXPunk, Chicago, IL, USA; subsequently purchased by Optimal Workshop, Wellington,
NZ and renamed OptimalSort; http://www.optimalworkshop.com/optimalsort.htm) and
they were asked to provide a description of each group.
In addition to the stimuli, participants were given a notepad and pen to keep notes,
a sheet with the sampling directions outlined, and a list of possible descriptors.
Participants were reminded that this list was not a comprehensive list but could serve as a
starting point if they wished to reference it. The list of words included anesthetizing,
astringent, biting, bitter, burning, buzzing, cooling, drying, hot, irritating, itching,
metallic, numbing, pricking, puckering, salty, sharp, sour, spicy, stinging, sweet, swelling,
tickling, tingling, umami/savory, and warming. No definitions were provided. These
words were chosen as a compilation of words previously applied to chemesthetic agents
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(Albin & Simons, 2010; Bennett & Hayes, 2012; Cliff & Heymann, 1992) with the
addition of the five prototypical tastes to the list. The list was presented in alphabetical
order for all participants.
After the participants completed the sorting task, which lasted roughly an hour,
they completed an online personality questionnaire consisting of Arnett’s Inventory of
Sensation Seeking (AISS; (Arnett, 1994) and the Food Involvement Scale (FIS; (Bell &
Marshall, 2003).
Data Analysis
Multidimensional scaling (MDS) was performed using The R Statistics Package
(R Foundation for Statistical Computing). In R, we used the smacof library for MDS, the
agnes function in the cluster library for cluster analysis, and the FactoMineR (Husson, Lê
et al., 2007) library to calculate normalized RV coefficients to compare the perceptual
maps (see below).
Data from the free sorting task was converted into a dissimilarity matrix and
submitted to MDS. To determine the appropriate number of dimensions for the
perceptual mapping solution, we used a Scree plot with Kruskal’s stress values as a
function of the number of dimensions in the MDS solution. The appropriate number of
dimensions was chosen as the point when an increase in dimensionality did not
meaningfully decrease the stress of the solution or did not aid in the interpretation of the
configuration. Generally, a Kruskal’s stress level below 0.1 is considered an acceptable
model fit (Krzanowski & Marriott, 1994).
The RV coefficient (Robert & Escoufier, 1976), a multivariate generalization of
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Pearson’s R2, is commonly used as a measure of similarity between the multivariate
configurations of the cohorts. Here, we used the normalized RV (NRV) coefficient
because the number of stimuli in a group and dimensions in the perceptual map can
influence the RV coefficient (Nestrud & Lawless, 2008a). The NRV is interpreted
similarly to a z-score, with a large score (>2) indicating significant similarity between the
maps. The coeffRV function in FactoMineR also computes a p value that tests for
significant similarity when comparing the perceptual maps.
Multiple regression was used to associate the descriptors that participants
generated in the last step of the experimental protocol with the stimuli coordinates from
the perceptual map. This allows us to visualize which attributes were significantly
associated with what stimuli as attribute vectors in the perceptual maps, similar to
(Schiffman, Reynolds et al., 1981). The six most frequently used attributes for each
stimulus were used for regression analysis and descriptors with p-values less than 0.1
were considered significant in the regression.
Agglomerative hierarchical cluster analysis was conducted for each cohort. In
keeping with previously reported studies (Faye, Brémaud et al., 2004), we used
agglomerative hierarchical clustering methods here with Ward’s minimum variance
method as the linkage criteria. A plot of amalgamation distance versus joining order was
used to determine the appropriate number of clusters for each cohort. On this joining
distance plot, large jumps in the amalgamation distance indicate items being joined in
that step have increased dissimilarity as compared to previously joined items (See
(Lawless, 2013) for further explanation).
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Results
Panelist demographics
Non-expert participants were split into high and low Food Involvement Scale
(FIS) groups via a median split. Scores on the FIS for the low FIS cohort ranged from 44
− 66, with the mean score equal to 57.3 (+/- 1.2 SE). For the high FIS group, scores
ranged from 67 to 81 with the mean score 72.3 (+/- 14.5 SE). The expert cohort’s FIS
scores ranged from 58 to 84 with mean 72.8 (+/-1.2 SE). There was a significant effect of
cohort on mean FIS scores (F2, 79 = 59.8, p < 0.0001). The expert and high FIS cohorts
showed significantly higher scores on the FIS scale than the low FIS group (both p’s <
0.0001); however, there was no significant difference in the FIS scores between the high
FIS and expert cohorts (p = 0.956). This effect was present in both of the FIS subscales,
Setup and Dining (FIS-SD; F2, 79 = 11.91, p < 0.0001) and Preparation and Eating (FIS-
PE; F2, 79 = 44.33, p < 0.0001).
Mean age of each of the cohorts was roughly 28 years old (lowFIS: 27.8 +/- 1.7
years old, highFIS: 28.0 +/- 5.7 years old, experts: 29.9 +/- 2.2 years old). There was no
significant difference in the mean age of the cohorts (F2, 79 = 0.41, p = 0.662). The lowFIS
and expert cohorts were roughly 50% male (53.8% and 54.8%, respectively), while the
highFIS cohort was 32% male.
Low FIS cohort
Figure 3-1 shows the two-dimensional MDS configuration for assessors with low
scores on the Food Involvement Scale (FIS). As determined using a Scree plot, a two-
dimensional solution was most appropriate for this data (stress = 0.008).
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Figure 3-1. Perceptual map of 11 chemesthetic compounds sorted in a free sorting task by 26 assessors with low Food Involvement Scale scores. Regression was performed to regress descriptors generated by participants onto the perceptual map. Stimuli include allyl isothiocyanate (AITC), capsaicin (CAP), carvacrol (CARV), cinnamaldehyde (CINN), citric acid (CA), eucalyptol (EUCA), eugenol (EUG), huajiao (HJ), menthol (MEN), quinine (Q), and zingerone (ZING). The lowFIS cohort generated 35 unique attributes in total, of which 18 were
submitted to regression, and eight were significant in regression analysis. The significant
attributes were savory, herbaceous, puckering/sour, anesthetizing/numbing, cooling,
warming, spiced, and spicy. There were two roughly orthogonal axes in Figure 3-1. The
first axis opposes attributes cooling and anesthetizing/numbing with the attribute spicy.
Along the second axis, the attribute puckering/sour opposes the attributes warming and
spiced. There is a third unipolar axis that falls between the attribute vectors for
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puckering/sour and spicy. This dimension is made up of the attributes savory and
herbaceous.
Agglomerative hierarchical cluster analysis of the sorting data shows two large
clusters in the data generated by the lowFIS group (Figure 3-1). The group containing
allyl isothiocyanate, huajiao, citric acid, and quinine takes up the space in the plot
covered by the puckering/sour and savory-herbaceous vectors. The second cluster is a
diffuse group extending over the space in covered by the attributes cooling,
anesthetizing/numbing, warming, spiced, and spicy. The agglomerative coefficient for
this two-dimensional configuration is 0.82, indicating a strong clustering structure.
High FIS cohort
The two-dimensional MDS solution determined to be the best model for the
data generated by naïve assessors with high FIS scores is shown in Figure 3-2. Stress for
this two-dimensional model was 0.008.
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Figure 3-2. Two-dimensional perceptual map similar to Figure 3-1, except participants were from the high FIS score group (n = 25).
Although only two attributes were significant in regression, the high FIS group
generated 56 unique attributes, of which 20 were submitted to regression. The two
significant attributes lay on one opposing axis with the attribute astringent/drying on one
end and the attribute herbaceous on the other end. Agglomerative hierarchical clustering
indicates that there are three clusters for this cohort (agglomerative coefficient = 0.75).
The three clusters observed consisted of menthol, cinnamaldehyde, eugenol, and
zingerone in the first cluster, eucalyptol and quinine in the second cluster, and capsaicin,
carvacrol, allyl isothiocyanate, huajiao, and citric acid in the third cluster.
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Expert cohort
Figure 3-3. Two-dimensional perceptual map similar to Figures 3-1 and 3-2, but for the expert cohort (n = 32).
The perceptual map for the expert cohort (n = 32) is shown in Figure 3-3 (stress =
0.014). The experts generated 54 unique attributes during the sorting task. Of these, 19
were submitted to regression, and only two attributes were significant in regression. The
two significant attributes, cooling and anesthetizing/numbing, make up a single unipolar
axis. Cluster analysis showed three distinct groups were present in the sorting solution of
the expert cohort. The agglomerative coefficient, 0.82, indicates a strong clustering
structure. The three clusters observed are made up of citric acid, huajiao, eucalyptus, and
menthol in cluster 1, quinine, eugenol, and cinnamaldehyde in cluster 2, and carvacrol,
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capsaicin, zingerone, and allyl isothiocyanate in cluster 3.
Comparing perceptual maps between cohorts
Normalized RV coefficients (NRVs) were calculated between the cohorts to provide a
statistical measure of the similarity of the perceptual maps – by convention, the maps are
considered significantly similar if the p value for the NRV falls below 0.05. The
perceptual map generated from the expert cohort’s data failed to reach significant
similarity for both the low and high FIS groups (expert versus lowFIS: NRV = 1.47, p =
0.08, expert versus highFIS = 1.12, p = 0.13). The highFIS and lowFIS cohorts’
perceptual maps were significantly similar to each other (NRV = 2.15, p = 0.03).
To explore if there were differences in the way that assessors in the different cohorts
performed the task, we examined mean number of groups formed, mean number of
attributes generated, and amount of overlap in the attributes that were used. Four levels of
overlap were determined ranging from high (3) to none (0). An assessor who used the
same term to describe more than two groups, or used three words twice or more was
determined to have high overlap. Medium overlap was when the same terms were used in
two groups or two words were used two or more times, low overlap was when assessors
reused one word, and no overlap was when there were no descriptors that were reused.
No significant difference was observed in the number of groups formed (F2,78 = 1.732, p
= 0.184) or the amount of overlap (F2,78 = 0.883, p = 0.418). There was a significant
difference in the mean number of attributes generated by assessors in each cohort (F2,78 =
10.10, p = 0.0001). Tukey’s HSD indicated the expert cohort generated significantly
more attributes than both the high FIS (p = 0.013) and low FIS (p = 0.0001) cohorts. No
significant difference was observed in the mean number of attributes generated between
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the low FIS and high FIS cohorts (p = 0.358).
Table 3-1. Summary of how three cohorts used descriptors differently. Cohort Touch sensations Tastes / foods Aromas / non-food sensations
LowFIS 15/35 (43%) 11/35 (31%) 5/35 (14%)
HighFIS 18/56 (32%) 26/56 (46%) 12/56 (22%)
Experts 19/54 (35%) 24/54 (44%) 11/54 (21%)
Table 3-2. Mean number of attributes generated and mean number of groups formed by each cohort. Superscript letters indicate statistically significantly different values (p < 0.05).
Cohort Mean number of attributes (+/- SE)
Mean number of groups formed (+/- SE)
LowFIS 7.69 ± 0.58a
5.5 ± 0.4a
HighFIS 9.04 ± 0.66
a
6.3 ± 0.2a
Experts 11.80 ± 0.71
b
6.2 ± 0.3a
The low FIS cohort generated 35 unique attributes during the descriptive portion of
the sorting task. Seen in Table 3-1, of these 35 attributes, 43% (15 of 35 descriptors) were
terms that described touch sensations, 31% (11 of 35 descriptors) were terms that referred
to tastes, such as bitter or salty, or specific foods, such as “salsa” or “black licorice”, 14%
(5 of 35 descriptors) were terms that referred to other sensations, such as aromas or non-
food items (I.e. “leathery”, “oily”, and “refreshing”), and 12% (4 of 35 descriptors) were
descriptors that referred to the intensity of other stimuli in the sample set (i.e. “Less
intense version of 587” or “perfect mix of other two groups”). The high FIS cohort
generated 56 unique descriptors during the descriptive portion of the sorting task. Of
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these 56 attributes, 32% (18 of 56 descriptors) referred to touch sensations, 46% (26 of
56 descriptors) referred to tastes or specific foods, and 22% (12 of 56 descriptors)
referred to other sensations, such as aromas. The expert cohort generated 54 unique
descriptors during the descriptive portion of the experiment, generating a significantly
higher mean number of attributes per sample than either the highFIS or lowFIS cohort
(Table 3-2). Of these, 35% (19 of 54 descriptors) referred to touch sensations, 44% (24 of
54 descriptors) referred to tastes or specific foods, and 21% (11 of 54 descriptors)
referred to other sensations, such as aromas. In the high FIS and expert cohorts, no
assessors utilized descriptors that referenced the intensity of the other stimuli.
Comparing the cohorts using Arnett’s Inventory of Sensation Seeking (AISS;
Arnett 1994) there was no significant effect of cohort on overall AISS score (F2,79 = 1.75,
p = 0.18) or the Intensity Seeking subscale scores (AISS-IS; F2,79 = 0.238, p = 0.79),
though there was a significant effect on the scores on the Novelty Seeking subscale
(AISS-NS; F2,79 = 4.79, p = 0.011). The assessors in the expert cohort were significantly
lower in their AISS-NS scores than either the low FIS (p = 0.046) or high FIS cohorts (p
= 0.017). As there are two questions that pertain to food in the AISS-NS, we removed
these questions and conducted the analysis again. Upon removing these questions the
effect between the low FIS and expert cohorts was no longer significant (p = 0.120),
though the high FIS cohort’s AISS-NS scores remained significantly higher than the
expert cohort (p = 0.002).
Discussion
Comparing the cohorts’ ability to complete the sorting task, the results here agree
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with prior reports that level and type of expertise have a significant influence on the
outcome of perceptual mapping techniques such as sorting. Specifically, assessing
perceptually complex stimuli such as chemesthetic compounds, we expected the formally
trained expert cohort to perform significantly differently than both cohorts of naive
assessors regarding the descriptive portion of this test due to their theoretically expanded
lexicon regarding foods. Somewhat surprisingly, the highFIS cohort showed similarities
with both the lowFIS and expert cohorts, suggesting that formal training did not
differentiate cohorts as distinctly as originally hypothesized but rather, informal
experience also has large influence in assessor’s approach to completing the sorting task.
While the perceptual maps appear very different between the three cohorts on visual
inspection, only the expert cohort’s map is significantly different from the lowFIS and
highFIS cohorts’ maps based on the NRV coefficient. Currently, there are conflicting
reports regarding the ability of untrained assessors to generate maps similar to those by
trained or expert assessors using perceptual mapping techniques. Some literature
proposes untrained assessors cannot generate maps that are comparable to maps
generated by experts (Barcenas, Elortondo et al., 2004; Nestrud & Lawless, 2010; Pagès,
2005; Perrin, Symoneaux et al., 2008; Risvik, McEwan et al., 1997) while other findings
suggest untrained assessors are able to generate product maps comparable to those
generated by trained or expert assessors (Chollet, Lelièvre et al., 2011; Faye, Brémaud et
al., 2004; Faye, Brémaud et al., 2006; Lawless & Glatter, 1990; Tang & Heymann, 2002).
It is possible that these contradictory results arise from differences in the methodology
performed (e.g. napping, sorting or free choice profiling), type of training or degree of
expertise of the trained/expert cohorts, and the type of stimuli used and size of perceptual
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differences between the stimuli within the sample set; these possibilities are discussed in
more detail below. The incongruence between the maps of the expert and naive assessors
suggests that the expert cohort may be either a) attending to the sorting task differently or
b) actually perceiving the stimuli in a different way than the naive assessors. Indeed,
during data collection, we informally noted that a number of the assessors in the expert
cohort seemed to treat the task as an identification task, asking after the session if they
had correctly identified the sensations’ culinary sources; this behavior was never
observed with the naive assessors.
Generally, the clusters observed from the three cohorts did not obviously follow the
underlying receptor biology, as might be expected based on previous results (Byrnes et
al., under review). The lowFIS cohort generated two clusters, which can be interpreted as
a group that refers to touch sensations (e.g. numbing) and a group that refers to non-touch
sensations (e.g. sour). The cluster containing carvacrol, eugenol, eucalyptol, zingerone,
capsaicin, menthol, and cinnamaldehyde covers the area of the plot that is described by
attributes referring to touch sensations, such as spicy, cooling, numbing, etc., while the
other cluster, citric acid, huajiao, quinine, and allyl isothiocyanate covers the area of the
plot covered by attributes referring to non-touch sensations, such as savory and sour. It
was expected that the lowFIS group might have more difficulty discriminating between
samples for two reasons, the first having to do with FIS scores and the second to do with
the lexicon of these assessors. Previous work with the FIS has suggested that individuals
with higher scores on the FIS have higher sensory acuity than those individuals with
lower scores (Bell & Marshall, 2003). Given these findings, it is expected that lowFIS
individuals might have more difficulties discerning the perceptual differences between
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the chemesthetic sensations elicited by the stimuli in the sample set, irrespective of the
descriptors they provided, which would result in fewer clusters on the final map, as
shown Figure 3-1. Further, even if lowFIS assessors were able to pick apart these
differences, we expected they would have a smaller food-related lexicon with which to
describe the samples, which would create difficulties during the descriptive portion of the
task. Contrary to our hypothesis, the lowFIS cohort did not appear to have more difficulty
completing the sorting task as a group (stress = 0.008, agglomerative clustering
coefficient = 0.82) than the highFIS cohort (stress = 0.008, agglomerative clustering
coefficient = 0.75). They did however generate fewer clusters, indicating that as a group,
fewer differences were perceived between samples than the highFIS cohorts.
For the highFIS and expert maps, three clusters were observed, though these
clusters are difficult to interpret due to the low number of attributes that were significant
in regression analysis. The clustering structure from the expert cohort does offer some
clues, as there are general trends, though since we did not explicitly ask assessors to
specify their criteria for making decisions, these speculations should be interpreted
cautiously. In the expert cohort’s map, the first cluster, citric acid, huajiao and menthol,
lies along the cooling-anesthetizing/numbing axis, possibly grouped together due to the
common “refreshing” feeling that they elicit. The second cluster, made up of capsaicin,
zingerone, allyl isothiocyanate, and carvacrol, and the third cluster, made up of eugenol,
cinnamaldehyde, and quinine, occupy regions of the plot not characterized by any
significant attributes, thus it is not possible to interpret what the experts used as their
criteria for grouping these stimuli together. It is interesting to note however, that the
second cluster encompasses most of the stimuli associated commonly with cooking
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savory dishes (e.g. chile peppers, mustard, ginger), while the third cluster includes the
stimuli often used in baking applications (e.g. cloves, cinnamon).
Generally, the significant attributes on each of the MDS plots associated with the
expected stimuli. For example, on the lowFIS cohort’s map, cooling and
anesthetizing/numbing point towards menthol and eucalyptol, spicy points towards
capsaicin and zingerone, and puckering/sour points towards citric acid. In addition to
looking at the significant attributes, examining the number and type of attributes
generated by each cohort provides interesting information. As a group, the lowFIS cohort
generated relatively few unique attributes, only 35, compared to the 56 and 54 unique
attributes generated by the highFIS and expert cohorts, respectively. Although there were
large differences in the number of unique attributes generated by the cohorts, roughly 20
attributes were submitted to regression for each cohort (see methods). From the
regression analysis, eight attributes were significant in the lowFIS group while only two
were significant in both the highFIS and expert cohorts, indicating that there was higher
consensus in the attributes used to describe stimuli in the lowFIS cohort than in the
highFIS or expert cohorts. Prior reports in the literature conflict on this point: some show
that trained panelists use more terms to describe the product space (Chollet, Lelièvre et
al., 2011) while others show that experts tend to use fewer words (Nestrud & Lawless,
2008b). Our study suggests that both findings may be true. Here, we show experts do not
use significantly more terms to describe the product space than a cohort of highFIS
individuals who lack formal culinary training, and both the expert and highFIS cohorts
use significantly more terms to describe the product space than the lowFIS cohort, who
lack formal culinary training and food involvement. Again, it appears that type of
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expertise and training may play a significant role. Another area of debate is the level to
which trained panelists, experts, and untrained assessors are consensual in their
descriptors. Some work suggests that trained panelists and experts tend of use more
precise descriptions of samples where untrained panelists tend to use less specific terms
(Clapperton & Piggott, 1979; Faye, Brémaud et al., 2004; Gains & Thomson, 1990;
Gawel, 1997; Guerrero, Gou et al., 1997; Lawless, 1984), while other work suggests that
chefs use fewer, more idiosyncratic words (Nestrud & Lawless, 2008b). Our work shows
that highFIS individuals tended to use more attributes than the lowFIS group but that
there was more consensus within the lowFIS cohort than either the highFIS or expert
cohorts as evidenced by the lower number of significant attributes, suggesting that these
two cohorts are more idiosyncratic in their descriptions.
Interestingly, the distribution of the generated attributes was different between the
lowFIS cohort and the highFIS and expert cohorts. The expert and highFIS cohorts were
again very similar in the distribution of the attributes that they generated, with roughly
33% of the attributes referring to chemesthetic sensations (32% highFIS, 35% expert),
roughly 45% of the attributes referring to tastes or specific foods (46% highFIS, 44%
experts) and roughly 22% of the attributes referring to other sensations such as aroma
(22% highFIS, 21% experts). On the other hand, of the lowFIS cohort’s attributes, 43%
referred to chemesthetic sensations, 31% referred to tastes or specific foods, 14% referred
to other sensations such as aromas, and 12% referred to the sensations elicited by other
stimuli in the sample set (e.g. “perfect mix of other two groups” or “less intense version
of 587”).
Overall, the highFIS and expert cohorts tended to behave similarly in the number of
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unique attributes that were generated per assessor, and the number of attributes that were
significant in regression. While these two cohorts generated more than 1.5 times the
number of unique attributes than the lowFIS group did, the low number of attributes
recovered from regression suggests that there was more idiosyncratic behavior within
these two high FIS cohorts. Evidence for this behavior is also shown by the lower
agglomerative coefficient of clustering analysis for the highFIS group versus experts and
lowFIS cohorts and the higher Kruskal’s stress of MDS configurations of the expert
cohort versus the highFIS and lowFIS assessors (Nestrud & Lawless, 2010). Conflicting
reports exist regarding whether experts and trained or untrained assessors use more or
less descriptors and if the experts and trained assessors are more precise or more
idiosyncratic than untrained assessors. A number of studies suggest that trained assessors
and experts tend to be more precise in their descriptions, using words more efficiently,
while untrained panelists tend to use more ambiguous terms (Chollet & Valentin, 2001;
Clapperton & Piggott, 1979; Faye, Brémaud et al., 2004; Gains & Thomson, 1990; Gawel,
1997; Guerrero, Gou et al., 1997; Lawless, 1984). However, Nestrud and Lawless
(Nestrud & Lawless, 2008b) compared chefs to untrained assessors using a napping
procedure to evaluate citrus juices and found that chefs tended to use fewer, unique terms
and behaved more idiosyncratically when compared to consumers.
The difference in these findings are likely due to differences in the type of training
and expertise that the various experts and trained assessors in each of the studies or to the
type of testing methodology employed in the studies. Notably, Nestrud and Lawless
(Nestrud & Lawless, 2008b) collected their expert data at the same culinary school used
here, using chefs with an average of 20 years of experience; accordingly, it seems
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possible that culinary training may not place the same emphasis on linguistic consensus
as other types of formal training (e.g. wine expertise, descriptive panels).
Previous work suggests that the performance differences may be due to superior
memory abilities of experts such that they are less impaired by delays between samples
and may be able to better handle the increasing load on memory as sample number
increases (Almeida, Cubero et al., 1999; Chollet, Valentin et al., 2005). The current study
was not designed to explore these issues as they relate to differences between experts,
trained panelists, and untrained assessors, but rather, the difference in the level of training
and experience on the way that assessors complete the sorting task. Existing literature
suggests that experts perform better on tasks such as perceptual mapping because they are
able to describe their perception with more precise formal language, can discriminate
better, and perceive more dimensions (Chollet, Lelièvre et al., 2011; Roberts & Vickers,
1994; Solomon, 1990; Tang & Heymann, 2002; Torri, Dinnella et al., 2013). Roberts and
Vickers (Roberts & Vickers, 1994) showed significant differences in the way that judges
trained in the ADSA methods, trained panelists, and untrained assessors perceived
cheeses as formal training of dairy judges resulted in a shift of these judges’ focus as they
were trained to focus on defects. It has also been proposed that not just the kind of
expertise but also the level of expertise with a sample type significantly influences their
product differentiation ability (Barcenas, Elortondo et al., 2004; Maitre, Symoneaux et al.,
2010) and that compared to untrained assessors, experts and trained subjects tend to use
non-hedonic criteria for sample differentiation (Delarue & Sieffermann, 2004). Indeed,
present results agree with prior findings, as the non-formally trained assessors with food
involvement scores similar to those with formal training generated similar numbers of
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unique attributes, used similar numbers of groups during the sorting task, and generated
the same number of clusters on the MDS map. The expert cohort did however appear to
have less difficulty grouping the stimuli than the highFIS cohort, as evidenced by a
higher agglomerative clustering coefficient, consistent with expectations as this cohort is
formally trained and has the highest level of training and expertise of all cohorts in the
present study.
Conclusion
Our results suggest type of expertise as well as type of training are important factors
to consider when interpreting perceptual maps. While the highFIS group lacked formal
culinary training, they tended to behave similarly to the formally trained chefs and
culinary students in their use of descriptors. The two groups with high FIS scores tended
to be more descriptive in the number of terms that they used to describe samples but there
was less consensus regarding these descriptors. A priori, we expected the culinary experts
to have better consensus in their descriptors, similar to wine experts, but during data
collection it became clear that a number of the experts approached the task as an
identification task, trying to identify the food or spice that the stimulus was derived from.
The fact that some assessors in the expert cohort were attending to the task differently
could be the source for some of the variation observed in attribute consensus.
Interestingly, while the highFIS cohort performed similarly to the expert cohort regarding
attribute generation, this cohort performed similarly to the lowFIS cohort with regard to
the configurations of the perceptual maps.
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Funding
This work was supported by a National Institutes of Health grant from the National
Institute of Deafness and Communication Disorders [DC010904] to J.E.H., United States
Department of Agriculture Hatch Project PEN04332 funds, and funds from the
Pennsylvania State University.
Acknowledgments
This manuscript was prepared in partial fulfillment of a Doctor of Philosophy degree at
the Pennsylvania State University by N.K.B. The authors would like to thank Meghan
Kane, Laura Boone, and Geneva Bonny for their help with data collection, and all of the
participants at Penn State and the Culinary Institute of America for their participation in
this study. We would especially like to thank Chris Loss for his involvement in the
project as well as for coordinating the research collaboration with the Culinary Institute
of America at Hyde Park, NY.
124
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Chapter 4
Personality factors predict spicy food liking and intake
Abstract
A number of factors likely affect the liking of capsaicin-containing foods such as
social influences, repeated exposure to capsaicin, physiological differences in
chemosensation, and personality. For example, it is well known that repeated exposure to
capsaicin and chilies can result in chronic desensitization. Here, we explore the
relationship between multiple personality variables – body awareness/consciousness,
sensation seeking, and sensitivity to punishment, and sensitivity to reward – and the
liking and consumption of capsaicin-containing foods. As expected, a strong relationship
was found between liking of spicy foods and frequency of chili consumption. However,
no association was observed between frequency of chili consumption and the perceived
burn/sting of sampled capsaicin. Nor was there any association between perceived
burn/sting of capsaicin and any of the personality measures. Private Body Consciousness
did not relate to any of the measures used in the current study. Sensation Seeking showed
positive correlations with the liking of spicy foods, but not non-spicy control foods.
Sensitivity to Punishment showed no relation with frequency of chili consumption, and
nonsignificant negative trends with liking of spicy foods. Conversely, Sensitivity to
Reward was weakly though significantly correlated with the liking of a spicy meal, and
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similar nonsignificant trends were seen for other spicy foods. Frequency of chili
consumption was positively associated with Sensation Seeking and Sensitivity to Reward.
Present data indicate individuals who enjoy spicy foods exhibit higher Sensation Seeking
and Sensitivity to Reward traits. Rather than merely showing reduced response to the
irritating qualities of capsaicin as might be expected under the chronic desensitization
hypothesis, these findings support the hypothesis that personality differences may drive
differences in spicy food liking and intake.
Keywords: individual differences, SPSRQ, AISS, PBC, sensation seeking, food
preference
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Introduction
Spicy foods are a mainstay of many culinary foodways around the world. In western
industrialized nations, many individuals enjoy and seek out spicy foods while others do
not. The basis of this individual variation has long captivated culinary psychologists and
other food researchers. The first systematic work was conducted by Rozin and Schiller
who found that liking of the orally irritating qualities of capsaicin can be learned with
repeated exposure in humans (Rozin, 1990b; Rozin & Schiller, 1980). Subsequent work
suggests intake of these foods is not merely an academic curiosity, as capsaicin and other
pungent spices are also bioactive compounds that may influence health (e.g. (Ludy &
Mattes, 2011a; Skulas-Ray, Kris-Etherton et al., 2011). Additionally, understanding the
influences of ingestive behavior may help elucidate the factors that promote healthy
dietary practices (Saliba, 2009).
Capsaicin consumption is also of interest due to biological effects that have important
implications for obesity and wellness. A number of studies demonstrate the ability of
capsaicin and related compounds to promote negative energy balance through increased
energy expenditure (Ludy & Mattes, 2011a; Ludy, Moore et al., 2012; Matsumoto,
Miyawaki et al., 2000; Yoshioka, Imanaga et al., 2004; Yoshioka, Lim et al., 1995;
Yoshioka, St-Pierre et al., 1999; Yoshioka, St-Pierre et al., 1998), increased fat oxidation
(Lim, Yoshioka et al., 1997; Ludy & Mattes, 2011a; Westerterp-Plantenga, Smeets et al.,
2005; Yoshioka, Lim et al., 1995; Yoshioka, St-Pierre et al., 1998), and the ability to
suppress orexigenic sensations (Ludy & Mattes, 2011a; Westerterp-Plantenga, Smeets et
al., 2005; Yoshioka, Imanaga et al., 2004; Yoshioka, St-Pierre et al., 1999). The primary
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deterrent in utilizing capsaicin for these beneficial effects is large variability in liking and
thus consumption. It is well established that in the absence of economic and availability
constraints, liking is the primary determinant of food choice (Cowart, 1981; Duffy, Hayes
et al., 2009; IFIC, 2011; Randall & Sanjur, 1981; Rozin & Zellner, 1985; Schutz, 1957).
Numerous reasons have been proposed to explain the consumption of foods that elicit
oral pungency and irritation, sensations that are otherwise aversive. These include social
and associative factors linked with culture (Rozin & Schiller, 1980; Stevens, 1990),
repeated exposure to a specific type of cuisine (Logue & Smith, 1986b), and
physiological differences such as taste phenotype (Duffy, 2007; Duffy & Bartoshuk,
2000) or oral anatomy (Bartoshuk, 1993; Miller & Reedy, 1990). It has been proposed
that desensitization due to frequent capsaicin exposure, a well-documented phenomenon
(Cowart, 1981; Karrer & Bartoshuk, 1991a; Lawless, Rozin et al., 1985; Stevenson &
Prescott, 1994), is partially responsible for the variation in reported sensitivity to and
liking of the burn of capsaicin. Humans can learn to like the burn with exposure to
gradually increasing levels (Logue & Smith, 1986b; Rozin & Schiller, 1980). However,
other work suggests only a slight desensitization is observed with chronic use and that it
is not just the loss of sensation that is associated with liking of the burn (Rozin & Rozin,
1981; Rozin & Schiller, 1980). This suggests chili liking is not merely a case of increased
tolerance with repeated exposure, but rather that there is an affective shift towards a
preference for oral burn that is not found in chili dislikers (Rozin & Schiller, 1980;
Stevenson & Yeomans, 1993a). Genetics can explain individual differences in sensation
and diet (e.g., Hayes et al 2011; (Perry, Dominy et al., 2007); thus, variability in
capsaicin response could result from polymorphisms in TRPV1, though solid evidence
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for this theory is limited (Park, Lee et al., 2007; Snitker, Fujishima et al., 2009). The
present work is part of a larger study designed to explore influences of TRPV1 genetics
on oral sensations.
In addition to cultural and biological variables, it has been proposed that personality
may play a large role in determining responsiveness to and liking of chili containing
foods (Stevens, 1996). In Mexico, chili pepper consumption is linked with strength,
daring, and masculine personality traits (Rozin & Schiller, 1980). Among American
college students, eating chili peppers has been linked with a number of “benignly
masochistic” and thrill-seeking activities, such as riding roller coasters, gambling, and the
consumption of substances such as alcohol and coffee. Each of these experiences, like
chili peppers, are initially aversive yet individuals learn to enjoy them, perhaps due to the
appreciation that the perceived risk is harmless (Rozin & Schiller, 1980). This
“constrained risk” may be what makes chili consumption thrilling for some individuals.
One of the most widely used personality constructs in the food literature is sensation
or novelty seeking. The Sensation Seeking Scale (SSS), first developed by Zuckerman,
was based on the conceptualization of sensation seeking as “the need for varied, novel
and complex sensations and experiences” (Zuckerman, 1964). This trait is also
characterized by the willingness to seek out these experiences regardless of the associated
physical and social risks (Arnett, 1994; Dawe & Loxton, 2004; Zuckerman & Neeb,
1979). The scale was initially developed to measure overall sensation seeking, and after
refinement, four factors emerged which measure specific constructs of sensation seeking.
These include thrill and adventure seeking (TAS), experience seeking (ES), boredom
susceptibility (BS), and disinhibition (DIS) (Zuckerman, 1996). A number of weaknesses
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of Zuckerman’s Sensation Seeking Scale have been identified by Arnett and others (see
methods). Given these critiques, Arnett (Arnett, 1994) developed a newer measure than
captures the same underlying construct (Ferrando & Chico, 2001b) while avoiding these
flaws.
Miller’s Private Body Consciousness (PBC) scale purportedly measures self-
awareness and self-consciousness by asking about state changes that are observable only
by the individual, such as heart rate or hunger pangs (Miller, Murphy et al., 1981).
Individuals with high PBC reportedly have enhanced ability to identify and detect
differences in sensory properties of food due to their supposed increased sensitivity to
sensory stimuli (Jaeger, Andani et al., 1998; Miller, Murphy et al., 1981; Stevens, 1990;
Ueland, 2001a). PBC has also been linked with sensitivity to pain (Ferguson & Ahles,
1998; Martin, Ahles et al., 1991) and irritation caused by spicy foods (Stevens, 1990).
Specifically, pilot data suggests high PBC participants rate the burn of piperine and
capsaicin more intensely than low PBC counterparts; however, PBC only associates with
chili use among frequent users (Stevens, 1990).
Gray’s neuropsychological theory of personality (Reinforcement Sensitivity Theory;
RST), states that two basic brain systems control behavior and emotions (Corr, 2004;
Franken, Muris et al., 2006; McNaughton & Gray, 2000; Pickering, Diaz et al., 1995).
The Behavioral Approach System (BAS) is activated by stimuli associated with reward
and termination of punishment while the Behavioral Inhibition System (BIS) is activated
by both punishing and new (i.e. unconditioned) stimuli and the termination of reward
(Caseras, Avila et al., 2003b; Dawe & Loxton, 2004; Franken, Muris et al., 2006; Gray,
1987). Numerous scales have been proposed to measure these constructs, but the
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Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) appears to
be the best operationalization of the BIS/BAS model (Caseras, Avila et al., 2003b;
Torrubia, Avila et al., 2001).
The current study had a number of objectives. First, we explore the relationship
between personality variables and individuals’ response to the burn / sting of capsaicin
utilizing a number of personality measurements including Private Body Consciousness,
Sensation Seeking, and Sensitivity to Punishment and Sensitivity to Reward. The second
objective was to determine the relationship between personality factors and the liking of
different spicy foods, looking at not only spicy meals in general but also the hedonic
ratings of spicy foods that vary in energy density. The final aim was to explore the
theorized relationship between Sensation Seeking and frequency of chili consumption.
Materials and Methods
Overview
Present data were collected as part of a larger, ongoing study of the genetics of oral
sensation. This multisession study involved one-on-one testing across 4 days; only data
from the first day are reported here. Participants completed a food-liking questionnaire
and rated the intensity of sensations from sampled stimuli, including capsaicin. After
leaving the laboratory, participants filled out an online survey that included several
different personality measures. This questionnaire also asked participants to report their
frequency of consumption of foods containing chili peppers.
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Participants
Participants were recruited from the Penn State campus and the surrounding area. To
be eligible, individuals needed to be non-smoking, fluent English speakers between 18
and 45 years old, with no known defect of taste or smell. Additional exclusion criteria
included pregnancy, taking prescription pain medications, the presence of lip, cheek, or
tongue piercings, or prior diagnosis with a disorder involving either a loss of sensitivity
or chronic pain. Qualified participants were asked not to eat or drink within 1 hour of
testing and were asked to abstain from eating hot and spicy foods for at least 48 hour
prior to testing.
Data from 97 participants (24 men) are reported here. . Ages of panelists ranged from
18 to 45 (mean 27.65). Self reported race and ethnicity were collected according to the
1997 OMB Directive 15 guidelines; our sample included 9 Asians, 8 African Americans,
79 Caucasians, and 1 not reported. Three individuals identified themselves as being
Latina or Latino, 94 responded as being not Latina or Latino.
Measuring Sensation Intensity
All intensity ratings were collected on a generalized Labeled Magnitude Scale
(Bartoshuk, Duffy, Green et al., 2004a) presented via Compusense five Plus, version 5.2
(Guelph, Ontario, Canada). Prior to rating samples, participants were oriented to using a
list of 15 imagined or remembered sensations that included both oral and non-oral items
(Hayes, Allen et al., 2012). Both the scale instructions and orientation procedure
encouraged participants to make ratings in a generalized context (See Appendix for scale
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and directions). The top of the scale was labeled as the “strongest imaginable sensation of
any kind”. For each sample, participants were asked to rate sweetness, bitterness,
sourness, burning/stinging, savory/umami, and saltiness.
Sampled Stimuli
Participants were presented a series of six food grade stimuli, including potassium
chloride, acesulfame potassium, sucrose, quinine, capsaicin, and a mix of monosodium
glutamate and inosine monophosphate, but only capsaicin data are reported here. All
stimuli were presented as 10 mL aliquots in plastic medicine cups at room temperature.
Participants rinsed twice with room temperature reverse osmosis (RO) water prior to the
first stimulus and ad libitum between each subsequent stimulus.
Participants received 25 uM capsaicin samples, as previous work in our laboratory
indicated this would produce a mean burn in between ‘strong’ and ‘very strong’ on the
gLMS (Hayes, Allen et al., 2012). After swirling the sample in his or her mouth for three
seconds and expectorating, but prior to rinsing, participants were asked to rate all six
sensation qualities using a gLMS. Only burning / stinging data are used here. Capsaicin
samples were prepared by diluting a 2.5 mM stock (0.076g capsaicin, natural, Sigma-
Aldrich, St. Louis, MO, in 100 mL 95% ethanol, USP, Koptec, King of Prussia, PA) with
RO water to 500 mL. The final ethanol concentration was 1%.
Measuring Food Preference
During the laboratory visit, participants completed a generalized Degree of Liking
(gDOL) questionnaire. The gDOL used here is a 63 item hedonic survey with 27 foods
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and 20 alcoholic beverages. Critically, it includes 16 non-food experiences to help
generalize the affective responses outside of a context solely focused on food. Affective
ratings were collected on an unstructured, horizontal visual analog scale, with the ends of
the scale being labeled ‘strongest disliking of any kind’ (left side) and ‘strongest liking of
any kind’ (right side); the midpoint of the scale was labeled ‘neutral’. Similar instruments
have been used to study associations between food liking and health outcomes ((Duffy,
Hayes et al., 2009) and taste phenotype (Pickering, Jain et al.). Here, we analyzed
affective ratings for six of the 27 food items on the gDOL. The primary outcome measure
was liking of ‘the burn of a spicy meal’. Secondary measures, liking for ‘spicy Asian
food’ and ‘spicy and/or BBQ spare ribs’, were also included to tentatively disentangle
perceived pungency from energy density. We also identified three non-spicy foods with
similar mean liking and variability on the gDOL, ‘skim milk’, ‘hot dogs’, and ‘cotton
candy’ (aka candy floss), to control for non-specific effects of personality on food liking.
Web-based questionnaire
After leaving the laboratory, participants completed a web-based personality survey
that combined the Private Body Consciousness (PBC; Miller, Murphy et al. 1981), the
Arnett Inventory of Sensation Seeking (AISS; Arnett 1994), and the Sensitivity to
Punishment and Sensitivity to Reward Questionnaire (SPSRQ; (Torrubia, Avila et al.,
2001). To assess intake frequency, we used an updated version of the question used by
Lawless and colleagues (Lawless, Rozin, & Shenker, 1985); specifically, we asked “how
often do you consume all types of chili peppers in foods including Mexican, Indian,
Chinese, Thai, Korean, and other foods that contain chili pepper and cause tingling or
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burning. Answers were recorded on a 7-point category scale (never, <1/month, 1-3/month,
1-2/week, 3-4/week, 5-6/week, 1/day, 2+/day). These values were recoded as yearly
frequency (e.g. 1-3/month=24, 3-4/week=182, 1/day=365, etc.) and quarter root
transformed prior to analysis.
Personality Measures
Miller’s PBC scale is a 5 item instrument that asks participants to characterize how
aware they are of changes in their internal state using a 5 point Likert scale (0 -
Extremely Uncharacteristic to 4 - Extremely Characteristic). The items are summed to
create an overall score. Miller originally defined high and low PBC individuals as the top
and bottom 40% of the sample respectively (Miller, Murphy et al., 1981); here, we used
PBC as a continuous variable to avoid throwing away the middle 20%.
The best-known measure of sensation seeking is Zuckerman’s Sensation Seeking
Scale-V (SSS-V) questionnaire. However, Arnett and others have identified a number of
weaknesses of Zuckerman’s scale. There are a number of items on the SSS-V that,
although relevant when the scale was initially developed, have become very dated (e.g. “I
would like to make friends in some of the ‘far-out’ groups like artists or ‘hippies”). The
SSS-V also includes items directly addressing alcohol and drug use, sexual behavior,
illegal activities, and various activities that break social norms. This often results in
criteria contamination when the SSS-V is used in studies focused on these behaviors.
Additionally, there are a number of criteria that focus on physical strength, endurance,
and exertion, factors confounded with age. Some individuals might also find the forced
choice response method of the SSS frustrating or difficult to complete as they feel that
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the response options do not accurately represent them. Based on these criticisms (Arnett,
1994; Haynes, Miles et al., 2000), we use Arnett’s Inventory of Sensation Seeking
(AISS) instead; the AISS is a 20 item alternative to the Zuckerman scale that improves
upon the SSS-V by deemphasizing risk behavior and removing age dependent, culturally
dated, and norm-breaking items. For the remainder of the manuscript, we use sensation
seeking (lower case) when referring to the overall construct, and Sensation Seeking
(capitalized) when referring to its operational measurement here via the AISS.
Gray’s BIS/BAS model has been operationalized via the Sensitivity to Punishment
and Sensitivity to Reward Questionnaire (SPSRQ; (Torrubia, Avila et al., 2001), which
has two subscales. The SP subscale items measure an individual’s response to situations
involving punishment, cues for failure, or frustrative non-reward (Cooper & Gomez,
2008; O'Connor, Colder et al., 2004; Torrubia, Avila et al., 2001). The SR subscale
measures reactivity to reward in a number of situations. Unlike the BAS, which is
associated with sensitivity to conditioned cues for general reward and non-punishment,
the SR subscale items focus on a number of specific rewards, such as money, sexual
partners, and social status and approval (Cooper & Gomez, 2008; Dawe & Loxton, 2004;
O'Connor, Colder et al., 2004; Torrubia, Avila et al., 2001). It has also been highlighted
that while measures of novelty and sensation seeking are measures of general impulsivity,
SR is a measure of planned approach to rewarding stimuli (Dawe & Loxton, 2004). Here,
we use the 48 item English language SPSRQ from O’Connor and colleagues (O'Connor,
Colder et al., 2004), a translation of the original Catalan language scale developed by
Torrubia et al.
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Statistical Analysis
All data were analyzed using SAS 9.2 (Cary, NC). Pearson correlations were
calculated using proc corr and descriptive statistics were obtained via proc univariate.
Raw (non-normalized) data were used for the intensity and affective ratings. Significance
criteria was set at alpha = 0.05.
Results
In our cohort, self reported chili intake (annualized) showed wide variation
(interquartile range [IQR]: 24-182 times per year) with an average consumption
frequency of 107.5 ± 16.4 (mean ± standard error) times per year. The perceived intensity
of capsaicin burn was also variable (IQR: 14.5 -43.0), with a mean of 29.5 ± 2.2. Liking
of the three spicy items on the gDOL (possible range -100 to +100) showed similar mean
scores and interquartile ranges: spicy meal had a mean of 18.4 ± 4.0 and IQR of 0 to 50;
spicy Asian food had a mean of 27.5 ±4.7 and IQR of 5 to 61; spicy/BBQ spare ribs had a
mean of 28.0 ±4.7 and IQR of -1 to 58. The difference in mean liking scores for the
various spicy foods highlights that numerous aspects of the foods influence liking scores,
including energy density, and the presence of other compounds that might be considered
“spicy”.
Suitable variability was also observed in the personality measures. Out of a total
possible range of 0 to 24, SP scores in this cohort ranged from 2 to 20 (IQR: 6 to 13). SR
scores ranged from 3 to 23 (IQR: 7 to 13). AISS scores ranged from 35 to 76 (IQR: 48 to
61), out of a total possible range of 20 to 80.
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The burn/sting of capsaicin was not directly related to personality
There were no significant relationships observed between any of the personality
measures used in this study and perceived intensity of a 25µM capsaicin stimulus: PBC
(r= -0.06, p= 0.60), AISS (r= -0.11, p= 0.34), SP (r= 0.11, p= 0.31), and SR (r= 0.04, p=
0.68).
Liking was related to intake
As shown in Figure 4-1, a strong positive correlation was observed between the liking
of a spicy meal and reported chili intake (r= 0.58, p< 0.0001). Similar positive
relationships (not shown) were observed for the other two spicy foods on the liking
survey, although the relationship was not as strong for spicy/BBQ ribs (r= 0.28, p< 0.01)
as for spicy Asian food (r= 0.58, p< 0.0001). This may reflect that ribs are often
consumed with tangy, flavorful sauces that may or may not contain capsaicin.
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Figure 4-1. Relationship between self-reported liking of a spicy meal and yearly chili intake. Individuals were asked to rate how much they like or dislike a spicy meal on a generalized hedonic scale. Participants reported their intake of chili-containing foods on a 7-point scale, ranging from “never” to “two or more times a day”. This intake frequency was converted to an annualized frequency and quarter root transformed. The r-value reported on the figure is the correlation between liking scores for a spicy meal and yearly chili intake (quarter root transformed).
Intake did not relate to perceived intensity
Contrary to expectations, we did not observe any evidence to support chronic
desensitization with habitual intake. No relationship was found between reported intake
and the intensity of burning and stinging elicited by 10mL of 25uM capsaicin (r= 0.10,
p= 0.89).
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PBC did not relate to other measures
No significant relationships were found between PBC scores and liking of spicy
meals (r= 0.03, p= 0.79) or either of the other two spicy foods on the gDOL, spicy Asian
food (r= 0.06, p= 0.59) and spicy/BBQ ribs (r= 0.03, p= 0.75). Also, there was no
evidence for a relationship between PBC and annual chili intake (r= -0.06, p= 0.57).
Personality measures correlated with each other
Between the personality scales used in this study, no significant correlations were
found between PBC and any other measure (AISS, and both SPSRQ subscales). AISS
showed a significant negative correlation with the SP subscale (r= -0.51, p< 0.0001) and
a significant positive correlation with the SR subscale (r= 0.46, p< 0.0001). The SP and
SR subscales were independent from each other (r = -0.11; p= 0.31). Correlations across
the measures are summarized in Table 2-1.
Table 4-1. Correlation matrix of personality measures used in the present study. Private Body Consciousness (PBC) showed no correlation with any of the other measures used. Arnett’s Inventory of Sensation Seeking (AISS) showed significant correlations with both subscales of the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ). The SP and SR subscales of the SPSRQ were not correlated with each other. Bolded values are significant at p < 0.0001.
AISS SP SR
PBC -0.09 0.10 -0.04
AISS -0.51 0.46
SP -0.11
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AISS related to liking and intake
As Figure 4-2 shows, Sensation Seeking (measured via Arnett’s Inventory) was
significantly related to the liking of a spicy meal (r= 0.50, p < 0.0001). Significant
positive correlations were also found between Sensation Seeking and the liking of spicy
Asian food (r= 0.45, p < 0.0001) and the liking of spicy/BBQ ribs (r= 0.25, p = 0.02).
Figure 4-3 shows that Sensation Seeking was positively related to intake frequency of
chilis and chili-containing foods (r= 0.39, p = 0.0001).
Figure 4-2. Strong positive relationship between scores on the Arnett Inventory of Sensation Seeking and self-reported liking of a spicy meal. Sensation Seeking was measured using Arnett’s Inventory of Sensation Seeking (1994).
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Figure 4-3. Strong positive relationship between annualized chili intake and scores on the Arnett Inventory of Sensation Seeking and self-reported liking of a spicy meal.
SPSRQ was related to liking and intake frequency
The Sensitivity to Punishment subscale showed a negative relationship with the liking
of spicy meals (r= -0.19, p= 0.06; Figure 4-4) and nonsignificant negative relationships
with the liking of spicy Asian food (r= -0.14, p= 0.19) and spicy/BBQ ribs (r= -0.09, p=
0.39). SP showed no relationship with intake frequency (Figure 4-5). As shown in Figure
4-4, the Sensitivity to Reward subscale was positively correlated with the liking of spicy
meals (r= 0.23, p= 0.03). A nonsignificant, positive relationship was observed between
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SR and the liking of spicy Asian foods (r= 0.18, p= 0.08). Likewise, a nonsignificant,
positive relationship was seen between SR and the liking of spicy/BBQ ribs (r= 0.13, p=
0.22). As shown in Figure 4-5, SR showed a weak positive relationship with intake
frequency (r= 0.23, p= 0.03).
Figure 4-4. Relationships between Sensitivity to Punishment, Sensitivity and Reward, and liking of a spicy meal. Sensitivity to Reward showed a significant positive correlation with the liking of a spicy meal. In contrast, Sensitivity to Punishment showed a nonsignificant trend towards a negative relationship with spicy meal liking.
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Figure 4-5. A moderate positive relationship was observed between yearly chili intake and Sensitivity to Reward.
Personality effects on liking were generally limited to spicy foods
To control for non-specific effects of personality on food liking, we tested whether
any of the personality traits described above correlated with the liking or disliking of
three foods: skim milk, cotton candy, and hot dogs. These foods were chosen from the list
of the 27 foods on the gDOL because they are diverse in taste quality and had similar
liking scores (mean and variance) to the three spicy foods used in the study. None of the
personality measures were a significant predictor of spicy food liking (p’s > 0.14), with
one exception: Private Body Consciousness was weakly correlated with liking for skim
milk (r =0.27; p =0.01).
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Discussion
The general aim of this study was to determine what relationships existed between
personality variables and liking of spicy food. The burning/stinging sensation produced
by capsaicin, a major deterrent for many individuals, did not show a direct relationship
with any of the personality measures used in this study. PBC showed no association with
any of the other variables tested and did not correlate with any of the other personality
measures used. Sensation Seeking and Sensitivity to Reward both showed positive
relationships with the liking of a spicy meal, spicy Asian food, and spicy/BBQ spare ribs
as well as with chili intake frequency. Sensitivity to Punishment showed negative
correlations with the liking of spicy foods and showed no relationship with chili intake
frequency. Overall, the personality measure assessing sensation seeking behavior showed
a strong relationship with the liking and a moderate association with the intake of chili-
containing foods, while sensitivity to reward showed significant but weak relationships
with the liking and intake of capsaicin-containing foods.
Liking related to intake
Liking of a food is one of the primary drivers of food intake (Duffy, Hayes et al.,
2009; Eertmans, Baeyens et al., 2001a; IFIC, 2011) in meals both in and outside the
home. Here we observed a strong positive correlation between the liking of a spicy meal
and chili intake frequency, which supports this assertion. A moderate and weak
relationship was also found between intake and liking of the two other spicy foods on the
gDOL, spicy Asian and spicy/BBQ spare ribs, respectively. The associations between
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liking of a spicy meal and chili intake fall within the range of correlations previously
reported between liking and intake measures (Bell & Tepper, 2006; Duffy, Hayes et al.,
2009; Raynor, Polley et al., 2004). These findings also support Rozin’s observation of the
positive relationship between use and liking of chili peppers (Rozin, 1990b; Rozin &
Schiller, 1980).
Reported intake did not relate to burn intensity
While a strong relationship was observed with liking and intake, there was no
relationship observed between chili intake frequency and perceived burning/stinging, a
finding that appears to contradict the well documented phenomenon of capsaicin
desensitization (Stevenson and Prescott 1994, Karrer and Bartoshuk 1991, Cowart 1987,
Lawless et al. 1985). The current study was not designed to pull apart the reason for the
absence of this relationship, but we can speculate about several potential explanations for
this result. It is possible that the results are due to a reporting error and that there are
several individuals reporting frequent chili use who have a daily intake of capsaicin that,
while frequent, is low enough that it does not induce desensitization. Likewise, an
individual who is sensitive to the burn of capsaicin who consumes very low levels of
capsaicin on a regular basis might still perceive the food as “spicy”, resulting in a high
reported annual chili intake, while another individual, who is very tolerant to the burn of
capsaicin may consume high levels of capsaicin relatively infrequently, resulting in a low
intake frequency. In this situation it is possible that the low dose-high frequency
consumer does not consume enough capsaicin to induce desensitization while the high
dose-low frequency consumer does reach the desensitized state. Desensitization can
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occur after frequent application of low concentrations capsaicin as well as after a single
high concentration dose (Green 1989, Karrer and Bartoshuk 1991) and desensitization is
reversible. Here, the amount of capsaicin consumed was not assessed; thus it is possible
that the minimum dose, or dosing frequency, necessary to achieve chronic capsaicin
desensitization was not reached by some participants regardless of frequency of chili
intake.
Another hypothesis, as suggested by Rozin, is that any desensitization is expected to
be slight (Rozin & Schiller, 1980). This is consistent with the idea that frequent chili
users increase their consumption of chilis not because they fail to sense the burn but
rather that they come to enjoy the burn produced by the chilis (Stevens, 1990). This
hypothesis would suggest that there exists some difference (perhaps personality) between
the individuals who come to enjoy the burn of chilis and those who do not learn to like
this sensation. The present analysis is not powered for the moderator analysis required to
tease apart this question.
PBC did not relate to other measures
No significant relationship was found between PBC scores and the intensity of
burning and stinging produced by a 25uM capsaicin; this conflicts with prior reports that
high PBC individuals are more sensitive to the irritation of piperine and capsaicin
(Stevens, 1990). This previous work suggests that the difference in sensitivity to
capsaicin and piperine between a high and low PBC individual varies throughout regions
of the mouth. The area with the largest difference in sensitivity to both capsaicin and
piperine was the tip of the tongue. It is possible that with whole mouth stimulation, as in
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the present study, the differences in sensitivity between individuals with high and low
PBC scores are not seen.
Additionally, no relationship existed between PBC score and liking of spicy meals in
this study. Conflicting literature exists for the link between PBC and food choice
(Kahkonen, Tuorila et al., 1997; Solheim & Lawless, 1996; Stevens, 1990). It is possible
that a relationship is not seen because the personality construct of PBC may not be
associated with food choice. It is also possible that there is an interaction of this
personality construct with one, or many, of the other factors important in determining
food choice, which may explain these inconsistent results. Further exploration into this
topic is warranted.
Personality measures correlated with each other
In agreement with previously reported literature, the SP and SR subscales were
independent from each other. Significant negative and positive correlations were
observed between AISS and SP and SR scales, respectively. We are unaware of prior
work comparing these measures in the same individuals.
Sensation seeking is related to liking and intake
A strong positive correlation was seen between the liking scores of spicy meals and
Sensation Seeking. This finding confirms prior literature linking sensation seeking and
enjoyment of spicy foods, though this specific operationalization of sensation seeking,
AISS, has not been used previously with food. This may explain why the correlation is
stronger than has previously been reported with other sensation seeking measures (see
175
methods for a discussion of the flaws in other measures of sensation seeking). Recently,
Ludy and Mattes did not find a relationship between sensation seeking as measured with
a brief 4-item measure of sensation seeking in 25 individuals (Ludy & Mattes, 2012);
their inability to find a relationship may reflect the low power in their sample, or
imprecision of a brief personality survey. Additionally, we used more contemporary
methods to assess food liking (i.e. a generalized scale on a survey that included non-food
items) than many previous studies, which may have deattenuated correlations compared
to prior work. The AISS measure also showed moderate positive relationships with the
measure of liking of a spicy Asian meal and a weak but significant positive relationship
with the liking of spicy/BBQ spare ribs. (The weaker relationship with spicy/BBQ ribs is
discussed below). High AISS scores were moderately associated with chili intake,
accounting for roughly 15% of variation in intake frequency of chili-containing foods,
highlighting the important role that personality factors play in determining consumption
of spicy foods. Notably, Sensation Seeking did not associate with liking for non-spicy
control foods, indicating this effect is specific to spicy foods and not the result of a
general affective shift for food.
SPSRQ related to linking and intake
Sensitivity to Reward was associated with liking of a spicy meal. While AISS is a
general measure of sensation seeking and SR is a measure of sensitivity to more specific
type of rewards, the two scales are correlated. Due to the strong relationships of AISS
with SR and with the liking of spicy meals, a correlation between SR and spicy meals
might be expected. Nonetheless, it interesting that liking of spicy foods shows correlation
176
with a personality construct thought to measure responsivity to rewards such as money,
sex, and social status. This finding seems to supports Rozin’s hypothesis that the
consumption of chilis is linked with an individual’s perception among peers, or
“machismo” and the perception of strength (Rozin, 1990b). Positive (albeit
nonsignificant) trends were also found between liking of spicy Asian foods and
spicy/BBQ ribs and sensitivity to reward. It is tempting to speculate that this could reflect
a lower ‘machismo’ factor for these foods, but additional work is needed to formally test
this idea. Finally, in spite of a significant negative correlation between AISS and SP,
there was no evidence of a relationship between liking of spicy meals and Sensitivity to
Punishment. We believe this is the first time SP and SR have been applied in research on
food choice.
Rozin suggested that one of the reasons that Americans might like spicy foods is the
association of chili pepper with calorically dense, high fat foods such as barbecue, hot
wings, and American Mexican foods (Rozin, 1990b). While this was proposed at a time
when the typical middle American diet incorporated far fewer spices and spicy foods than
today, the present gDOL questionnaire included a number of different types of spicy
foods to determine if reported liking was potentially influenced by energy density.
Recently, we reported that liking for a spicy meal was predictive of biomarkers
associated with lower cardiovascular risk (Duffy, Hayes, Sullivan, & Faghri, 2009), but
this may not reflect a causal physiological mechanism for capsaicin (e.g., increased
satiety) as spicy foods can also vary dramatically in energy density (cf. buffalo chicken
wings versus a vegetable based stir-fry).
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Here, participants were asked to rate their liking of non-specific ‘spicy meals’ as well
as two more detailed items, ‘spicy Asian food’ assessing a group of lower calorie, lower
fat spicy foods, and ‘spicy and or BBQ spare ribs’ to target a high fat, high calorie food.
As discussed earlier, there were a number of situations in which correlations of varying
strengths and significance were observed between the three spicy foods and a specific
personality trait. Disparities in the relationships between the different personality scales
and liking of spicy meal, spicy Asian foods, and spicy/BBQ spare ribs may be due to
differences in the interpretations of the items on the gDOL. For example, when asked
about ‘spicy Asian foods’ participants may have included orally irritating compounds
which do not activate or cross desensitize TRPV1 receptors, such as allyl isothiocyanate
found in wasabi, in their definition of “spicy”. Further research in this area to elucidate
the conceptualization of the term “spicy” and its identity in a number of different cultures
would be useful in determining the cause of this variation. Additionally, exploration of
other orally irritating compounds and any link with these personality traits would help to
understand the nature of the affective shift from disliking to liking the irritation.
In this vein, spicy/BBQ spare ribs showed a significant positive association that was
only slightly less than that observed for non-specific ‘spicy meals’ in relation to sensation
seeking behaviors. Conversely spicy meals showed significant relationship with
Sensitivity to Reward while spicy BBQ did not. As with the implicit complexities of the
spicy Asian meal item, delving into the source of this variation between BBQ and the
other two spicy foods is beyond the scope of the present study. Still, it seems possible
that the frequent inclusion of sugar in BBQ sauces and the high fat content of the BBQ
itself, reduces the perception of capsaicin in these foods due to physicochemical (Lawless,
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Hartono et al., 2000) and cognitive factors (Stevens & Lawless, 1986). Additionally, the
wide variety of BBQ among regions in the US (vinegar sauces versus tomato sauces
versus dry rubs) introduces a complication not accounted for in the present study design.
Conclusion
The relationships presented in this study confirm that liking or disliking of spicy
foods is not solely determined by an individual’s sensitivity to capsaicin but that
personality factors exist that influence and the affective response to the initially aversive
burning/stinging sensation of capsaicin.
Sensation Seeking and Sensitivity to Reward were strongly linked with the liking of
all of the spicy foods measured here, and with reported chili intake. Although sensation
seeking behavior has been previously linked with the liking of spicy foods, this study
provides new insights into personality variables that play a role in food choice.
Significant positive associations were found between Sensation Seeking and the
liking of spicy meals, including spicy Asian foods and spicy/BBQ spare ribs, though the
relationships varied in strength. Sensitivity to Reward showed a significant relationship
only with the liking of a spicy meal. The inconsistency in relationships between the
personality measures and liking scores for the three spicy foods included on the gDOL
cannot be determined in this study (AISS was predictive of all three foods, compared to
SR, which only correlated with one). Further exploration into the source of these
differences is essential to fully understand the drivers of food choice with chemesthetic
compounds.
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It is clear from present data that personality variables influence the liking of spicy
foods and food choice. Notably however, we did not observe any relationships between
the liking of non-spicy foods and the personality measures that correlated with spicy food
liking, suggesting that individuals with high scores in these traits do not show an overall
affective shift toward food. Individuals who were higher in Sensation Seeking and
Sensitivity to Reward also report consuming capsaicin containing foods more frequently.
The relationships presented here, while indicative that personality variables are related
with food choice and liking, are only associations. In the future, structural equation
modeling could be utilized to better characterize the nature of the relationships between
these variables.
Funding
This work was supported by a National Institute of Health National Institute National
of Deafness and Communication Disorders grant [DC010904] to J.E.H.
Acknowledgements
This manuscript was completed in partial fulfillment of the requirements for a
Doctorate of Philosophy at the Pennsylvania State University by N.K.B. The authors
warmly thank Alissa L. Allen and Meghan Kane for their assistance with data collection
and our study participants for their time and participation.
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Chapter 5
Personality Influences Liking and Intake of Spicy Foods Differently in Men and
Women.
Abstract
It has been proposed, and only minimally explored, that personality factors may play
a role in determining an individual’s sensitivity to, and preference for, capsaicin
containing foods. The study presented, as part of a larger on-going project, aimed to
further explore this relationship and the differences in the various methods of measuring
personality factors. Participants rated liking of a number of foods and sensations in a
laboratory setting. After the session, panelists filled out an online personality survey,
which combined Arnett’s Inventory of Sensation Seeking (AISS) and the Sensitivity to
Punishment-Sensitivity to Reward Questionnaire (SPSRQ). Previously we reported
strong and moderate correlations between the liking of a spicy meal and the personality
constructs of Sensation Seeking (AISS) and Sensitivity to Reward (SPSRQ), respectively.
Here, we replicate prior findings in new participants, and then we use moderation models
to explore the nature of the relationship between personality traits, perceived intensity of
the burn of capsaicin, and the liking and consumption of spicy foods. Limited evidence of
moderation was observed in the cohort, however differential effects of the personality
traits were seen men versus women. In men Sensitivity to Reward associated more
185
strongly with liking and consumption of spicy foods, while in women, Sensation Seeking
associated more strongly with liking and intake of spicy foods. The results presented here
suggest that there may be different motivations for consuming spicy foods, where men
may respond more to extrinsic factors, while women may respond more to intrinsic
factors. These differences indicate that in men and women, there may be divergent
mechanisms leading to the intake of spicy foods.
Keywords: Sensation Seeking, capsaicin, food choice, food preference, moderation, AISS,
SPSRQ, Project GIANT-CS, individual differences
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Introduction
It is well accepted that liking of a food drives intake (Cowart, 1981; Duffy, Hayes et
al., 2009; Randall & Sanjur, 1981; Rozin & Zellner, 1985; Schutz, 1957). In the absence
of economic and availability constraints, liking may be the single most important
determinant of food choice, in meals eaten both in and outside the home (Eertmans,
Baeyens et al., 2001b; IFIC, 2014). Although healthfulness is the second most important
criteria in determining food choice (IFIC, 2014), and capsaicin intake has been linked
with a number of health benefits (Ludy & Mattes, 2011a; Ludy, Moore et al., 2012;
Matsumoto, Miyawaki et al., 2000; Westerterp-Plantenga, Smeets et al., 2005; Yoshioka,
Imanaga et al., 2004; Yoshioka, Lim et al., 1995; Yoshioka, St-Pierre et al., 1999), the
burning and stinging sensation elicited by capsaicin is often a strong deterrent to the
consumption of capsaicin containing foods. Assuming the hedonics of burn are a major
determinant of spicy food intake, the question then becomes, what factors cause some
individuals, but not others, to enjoy of this burning sensation?
Factors that reportedly influence food liking include physiological differences such as
taste phenotype (Duffy & Bartoshuk, 2000; Duffy, Lanier et al., 2007) or oral anatomy
(Bartoshuk, 1993; Miller & Reedy, 1990), as well as prior exposure and familiarity with
spicy foods (Logue & Smith, 1986b; Ludy & Mattes, 2011b; Rozin & Schiller, 1980;
Stevenson & Yeomans, 1993b). Moreover, humans can learn to like the burn of capsaicin
with repeated exposure (Rozin, 1990b), and acute and chronic desensitization to
capsaicin in and outside the laboratory are well-documented phenomena (Green &
George, 2004; Green & Hayes, 2003; Karrer & Bartoshuk, 1991b; Lawless, Rozin et al.,
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1985; Stevenson & Prescott, 1994). Thus, it is conceivable that the higher usage levels
typically observed among frequent chili users is due to greater tolerance (i.e. reduced
burn intensity). However, Rozin and others have suggested that any effect of
desensitization on liking of capsaicin is small, and that the affective shift from disliking
to liking is attributable to other factors (Rozin & Rozin, 1981; Rozin & Schiller, 1980;
Stevens, 1996).
Another factor known to play a role in determining the liking of spicy foods is
personality. The liking of chili peppers and “unusual spices” has been linked with
personality characteristics such as strength and daring and with thrill and adventure
seeking behaviors (Rozin & Schiller, 1980; Stevens, 1996; Terasaki & Imada, 1988).
Rozin and Schiller (1980) also reported in interviews with rural Mexican villagers
(N=13), when the interviewees were asked to determine which of two hypothetical
identical twins was female, which was stronger, which was less intelligent, etc., given the
information that one of the twins ate chili and the other did not. A majority of the
respondents identified the twin that ate chili as stronger, though they responded that none
of the other attributes could be determined just by knowing which twin consumed chili.
Rozin and Schiller hypothesized that this attribution of strength to the chili eater might
have been related to the Mexican idea of machismo, indicating that traits of daring and
masculinity. No difference in the preference for spicy foods between men and women
was found in the Mexican sample, possibly due to the prevalence of chili in the diet of the
region. Rozin later reported that enjoyment of certain activities, which he classified as
masochistic, such as amusement park rides, dangerous sports, and gambling, were linked
with the liking of chili peppers (Rozin, 1990b). However, the link to sensation seeking
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was an inference based on a common theorized ‘constrained risk’ across these activities,
as Rozin never directly associated measures of sensation seeking with chili liking or
intake. Notably, this early work was conducted primarily in the 1980s, when the average
consumption of capsaicin and chili peppers was much lower than current estimates
(Govindarajan & Sathyanarayana, 1991; Lucier, Pollack et al., 2006).
Elsewhere, personality measures used previously have been criticized for containing
gender and age-biased items, as well as for the response style employed by the scales
(Arnett, 1994; Haynes, Miles et al., 2000). Recently, we reported strong positive
correlations between the personality variable Sensation Seeking, as measured with
Arnett’s Inventory of Sensation Seeking (AISS; (Arnett, 1994), and the liking of some
types of spicy food (Byrnes & Hayes, 2013). We also observed a more modest positive
relationship between spicy food liking and the Sensitivity to Reward subscale of the
English language version (O'Connor, Colder et al., 2004) of Torrubia and colleagues’
Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ; (Torrubia,
Avila et al., 2001). These findings complement existing literature on the links between
personality traits and orally irritating foods, by suggesting that multiple different
personality constructs may influence an individual’s affective response to chili-
containing foods. However, not all studies study support an association between
personality and liking of spicy foods (e.g. (Ludy & Mattes, 2012), but these results may
be due to measurement error in brief measures of personality or small sample sizes.
The main objective of the present work was to test the hypothesis that personality
modifies the relationship between the perceived burn of capsaicin and the liking/disliking
of spicy foods. To formally test this, we constructed a model to test whether personality
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moderates the relationship between capsaicin burn and spicy food liking, using standard
guidelines established by Baron and Kenny (Baron & Kenny, 1986). In a moderation
model, the outcome variable is regressed onto the predictor and moderator variables as
well as onto a multiplicative interaction term of the predictor and the moderator. This
interaction term is included in the model to test the influence of the putative moderator
(personality trait) on the relationship between the predictor (burn) and outcome (liking),
seen in Figure 5-1. If the interaction term accounts for a statistically significant amount of
variance in the outcome variable, this is evidence of moderation. Here, our moderation
model tests whether the relationship between the perceived burn of a 25uM capsaicin
stimulus and reported spicy food liking systematically varies across individuals as a
function of personality.
Based on our recent work showing strong to moderate correlations between Sensation
Seeking (r = +0.50) and Sensitivity to Reward (r = +0.23) and spicy food liking, we
hypothesized that these personality traits would moderate the relationship between the
perceived burning/stinging of 25uM capsaicin and the reported liking/disliking of spicy
foods. Secondary aims of this study were to assess the moderation of the relationship
between liking and intake of spicy foods by personality. Additionally, we aim to explore
the role of gender in these relationships, given the possible association of masculine traits
with the consumption of spicy foods.
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Figure 5-1. Visual representation of moderation models to be tested in this protocol. Model 1 depicts the potential moderation of the relationship between perceived intensity of burning/stinging of a 25uM capsaicin sample and liking of spicy foods by personality traits. Model 2 depicts potential moderation by personality of the relationship between liking and intake of spicy foods.
Methods
Overview
Similar to our previous report (Byrnes & Hayes, 2013), these data were collected as
part of a larger, ongoing study of the genetics of oral sensation (Project GIANT-CS).
Briefly, data were collected in one-on-one testing across multiple days, but only data
from the first laboratory session and a follow-up online survey is reported here. During
the first session, participants completed a food-liking questionnaire and rated the intensity
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of sensations from sampled stimuli, including capsaicin. After leaving the laboratory,
participants filled out an online survey that included several different personality
measures, and intake.
Participants
Participants were recruited from the Penn State campus and the surrounding area. To
be eligible, individuals needed to be non-smoking, fluent English speakers between 18
and 45 years old, with no known defect of taste or smell. Additional exclusion criteria
included being pregnant or breastfeeding, taking prescription pain medications, the
presence of lip, cheek, or tongue piercings, or prior diagnosis with a disorder involving
either a loss of sensitivity or chronic pain. Participants who qualified were asked not to
eat or drink within 1 hour of testing and were asked to abstain from eating hot and/or
spicy foods for at least 48 hours prior to testing.
Present data are a superset of the cohort (n = 97) described previously (Byrnes &
Hayes, 2013); here, we report data from 246 participants (99 men). Participant ages
ranged from 18 to 45 (mean 25.9). Self reported race and ethnicity were collected
according to the 1997 OMB Directive 15 guidelines. The present analysis included 35
Asians, 6 African Americans, and 172 Caucasians; 33 individuals did not report a race.
Regarding ethnicity, 12 individuals identified themselves as being Latina or Latino, 203
responded as being not Latina or Latino, and 31 did not report an ethnicity.
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Measuring Sensation Intensity
A general Labeled Magnitude Scale (Bartoshuk, Duffy, Green et al., 2004a) was used
to collect all intensity ratings. Prior to rating any sampled stimuli, participants were
oriented to the scale using a list of 15 imagined or remembered sensations that included
both oral and non-oral items (Hayes, Allen et al., 2013). Both the scale instructions and
orientation procedure encouraged participants to make ratings in a generalized context
that was not limited to food or oral sensations. The top of the scale was labeled as the
“strongest imaginable sensation of any kind.” For each sample, participants were asked to
rate sweetness, bitterness, sourness, burning/stinging, umami/savory, and saltiness. All
data were collected via Compusense five Plus, version 5.2 (Guelph, Ontario, Canada).
Sampled Stimuli
A 10 mL aliquot of 25 uM capsaicin was presented to participants as part of a series
of six food grade stimuli; other food-grade stimuli included potassium chloride, quinine
HCl, Acesulfame potassium, a MSG/IMP blend, and sucrose (see (Allen, McGeary et al.,
2013)). Presentation order was counterbalanced in a Williams Design to minimize
carryover effects. This capsaicin concentration and volume were selected as they evoke
burning sensations above ‘strong’ on a general Labeled Magnitude scale (gLMS) in sip
and spit experiments (e.g. (Hayes, Allen et al., 2013). Capsaicin was first dissolved in
ethanol and then diluted to volume as described previously (Byrnes & Hayes, 2013). All
stimuli (10 mL) were presented in plastic medicine cups at room temperature.
Participants rinsed twice with room temperature reverse osmosis (RO) water prior to the
first stimulus and then ad libitum between each subsequent stimulus; a minimum
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interstimulus interval of 30 seconds was enforced, and the experimenter did not provide
the next sample until the participant reported all sensations from the previous stimulus
were gone. After swirling a sample in his or her mouth for three seconds and
expectorating, but prior to rinsing, participants were asked to rate all six sensation
qualities (see above) for each stimulus; only burning/stinging ratings for capsaicin are
used here.
Measuring Food Preference
During the first visit to the laboratory, participants completed the generalized Degree
of Liking (gDOL) survey; similar generalized hedonic questionnaires have been
described elsewhere (Duffy, Hayes et al., 2009; Peracchio, Henebery et al., 2012;
Pickering, Jain et al., 2012b; Scarmo, Henebery et al., 2012). The version of the gDOL
used here is a 63-item survey with 27 foods and 20 alcoholic beverages (See Appendix A
for scale). This questionnaire differs from most previous food preference questionnaires,
in that it also includes 16 non-food items to generalize affective responses outside of a
context focused on food. Hedonic ratings were collected on a horizontal visual analog
scale, with the ends of the scale being labeled ‘strongest disliking of any kind’ (left side)
and ‘strongest liking of any kind’ (right side); the midpoint of the scale was labeled
‘neutral’. Here, we analyzed affective ratings for one of the spicy foods (‘burn of a spicy
meal’) of the 27 food items on the gDOL.
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Web-based questionnaire
After the first laboratory session, participants completed a web-based personality
survey that included items from the Private Body Consciousness (Miller, Murphy et al.,
1981), Arnett’s Inventory of Sensation Seeking (AISS; Arnett 1994), and the Sensitivity
to Punishment and Sensitivity to Reward Questionnaire (SPSRQ; (Torrubia, Avila et al.,
2001). For additional information on these measures see Byrnes and Hayes (Byrnes &
Hayes, 2013). For the remainder of this document, we use lower case letters when
referring to the general concept of sensation seeking, and use the phrase Sensation
Seeking (capitalized) or the abbreviation AISS when referring to scores on Arnett’s
Inventory (Arnett, 1994).
To assess typical intake, we adapted the question used previously by Lawless and
colleagues (1985). We asked participants ‘‘How often do you consume all types of chili
peppers in foods including Mexican, Indian, Chinese, Thai, Korean, and other foods that
contain chili pepper and cause tingling or burning?” Responses were recorded on an 8-
point category: scale (never, <1/month, 1-3/month, 1-2/week, 3-4/week, 5-6/week, 1/day,
2+/day) was used. These values were recoded as yearly frequency (e.g. 1-3/month=24, 3-
4/week=182, 1/day=365, etc.) and quarter root transformed prior to analysis to reduce
skew.
Statistical Analysis
All data were analyzed using SAS 9.2 (Cary, NC). All assumptions of multiple
regression were assessed and met after log transformation of the variable measuring
yearly chili intake. No multicollinearity was noted between variables, so no centering was
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performed. T-tests were conducted in SAS 9.2 comparing men and women on the various
personality measures, liking of spicy foods, and annual intake of chilis using proc ttest
with a Satterthwaite approximation of standard error. Significance criteria was set at
alpha = 0.05.
Moderation was tested using the method from Baron and Kenny (1986). To test for
moderation, personality was used in the model as an additional predictor of the outcome
variable (liking) along with burn (the main predictor). A multiplicative interaction term
(predictor × moderator; here, burn × personality) was included in the regression model in
addition to the predictors of burn and personality (3 predictors in total). A significant
interaction term was taken as evidence of moderation. See Figure 5-1 for a visualization
of this model
Results
Our participants showed wide variation in self-reported chili intake frequency
(interquartile range [IQR]: 24-182 times per year), with a mean consumption frequency
of 130± 12 (mean ± standard error) times per year. Ratings of the perceived burning and
stinging of a 25uM capsaicin sample were variable (possible range 0 to 100, IQR: 17.0-
48.0), as were the liking scores for ‘burn of a spicy meal’ collected on a generalized
hedonic survey (possible range -100 to 100, IQR: 0-52). We also observed sufficient
variation in scores on the various personality measures to allow for further analyses. Out
of a total possible range of 20 to 80, AISS scores ranged from 35-77 (IQR: 49.5-61.0). SP
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scores ranged from 0 to 23 (IQR: 6.0-13.0) and SR scores ranged from 1 to 23 (IQR: 8.0
– 14.0), both scales have a total possible range of 0 to 24.
Relationship between perceived burn intensity of 25uM capsaicin, liking of spicy
foods, and yearly chili intake
Perceived burn intensity of the 25uM capsaicin sample showed significant negative
correlations with the liking of a spicy meal (r = -0.25, p < 0.0001), liking of spicy Asian
food (r = -0.17, p = 0.008), and liking of spicy and/or BBQ ribs (r = -0.19, p = 0.003).
Annual chili intake also positively correlated with the liking of spicy meals (r = 0.37, p <
0.0001), liking of spicy Asian food (r = 0.41, p < 0.0001), and liking of spicy and/or BBQ
ribs (r = 0.22, p = 0.001). Annual chili intake and perceived burn intensity did not show a
significant correlation (r = -0.05, p = 0.46).
In men, perceived burn intensity correlated with the liking of all spicy foods (meals: r
= -0.28, p = 0.005, Asian: r = -0.25, p = 0.01, BBQ: r = -0.23, p = 0.03), while only liking
of spicy meals correlated with annual chili intake (meals: r = 0.28, p = 0.01). In women,
perceived burn intensity correlated with the liking of all spicy foods (meals: r = -0.24, p =
0.003, Asian: r = -0.15, p =0.08, BBQ: r = -0.18, p = 0.03). Annual chili intake positively
correlated with all 3 measures of spicy food liking (meals: r = 0.42, p < 0.0001, Asian: r
= 0.49, p < 0.0001, BBQ: r = 0.27, p = 0.003). There was no relationship between
perceived burn intensity and yearly chili intake in men or women.
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Relationship between personality traits and liking of spicy foods
In the full dataset, Sensation Seeking showed weak to moderate significant
correlations with the liking of spicy meals, spicy Asian food, and spicy and/or BBQ ribs
(meals: r = 0.37, p < 0.0001, Asian: r = 0.29, p < 0.0001, BBQ: r =0.16, p = 0.02).
Sensitivity to Reward showed weak significant correlations with the liking of spicy meals
and spicy Asian foods (meals: r = 0.18, p = 0.01, Asian: r = 0.16, p = 0.02). In the whole
sample, no moderation was observed in the models assessing moderation by personality
on the relationship between perceived intensity of burning/stinging of 25uM capsaicin
and liking of spicy meals, spicy Asian food, and spicy and/or BBQ ribs. There were
however significant main effects of Sensation Seeking and Sensitivity to Reward on the
liking of all spicy foods (AISS; meal: β = 0.27, p = 0.02, Asian: β = 0.31, p = 0.01, BBQ:
β = 0.26, p = 0.03, SR; meal: β = 0.24, p = 0.06, Asian: β = 0.32, p = 0.01, BBQ: β = 0.29,
p = 0.03).
Relationships between perceived burn intensity, liking of spicy foods, and
personality differ between men and women
In men, Sensation Seeking showed a moderate significant correlation with the liking
of spicy meals (r = 0.32, p = 0.004. The relationship between Sensitivity to Reward and
the liking of a spicy meal also showed a positive trend (r = 0.21, p = 0.06). In women,
Sensation Seeking showed significant moderate relationships with the liking of a spicy
meal (r = 0.34, p < 0.0001) and the liking of spicy Asian foods (r = 0.29, p = 0.001) while
Sensitivity to Reward showed no relationships with any of the spicy food liking measures.
Men also showed a significant relationship between Sensation Seeking and perceived
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burn intensity from sampled capsaicin (r = -0.24, p = 0.03) as well as a trend in the
relationship between Sensitivity to Punishment and perceived burn intensity (r = 0.21, p =
0.054). No such relationships were observed in women
In models testing moderation of the relationship between perceived burn intensity and
liking of spicy foods, a main effect of Sensitivity to Reward on liking of all spicy foods
was noted in men (Table 5-1; meal: β = 0.55, p = 0.02, Asian: β = 0.60, p = 0.01, BBQ: β
= 0.56, p = 0.03) as well as a moderator effect of SR on the relationship between
perceived intensity of burning and liking of spicy Asian foods (β = -0.96, p = 0.03). A
main effect of Sensation Seeking on the liking of a spicy meal (β = 0.28, p = 0.05) and
spicy Asian foods (β = 0.34, p = 0.02) was observed in women. No moderation of the
relationship between perceived burn intensity and the liking of spicy foods was observed
in women.
Table 5-1. Moderator effects of personality on the relationship between perceived intensity of burning/stinging and liking of spicy foods. Standardized regression coefficients are reported. * p<0.05, ** p<0.01, *** p<0.001
FULL COHORT (N=246) Spicy Meal Spicy Asian Foods Spicy/BBQ Spare Ribs BS -0.47 -0.02 0.245 AISS 0.27* 0.31** 0.26*
BS
x AISS 0.26 -0.12 -0.43 Model (3,212) Adj. R-Sq. 0.17*** 0.09*** 0.05**
BS -0.12 -0.04 -0.31* SP -0.003 0.05 -0.28
BS
x SP -0.15 -0.16 0.19 Model (3,214) Adj. R-Sq. 0.06** 0.02 0.024*
BS -0.18 0.04 0.041
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SR 0.24 0.32* 0.29*
BS
x SR -0.09 -0.28 -0.31 Model (3,214) Adj. R-Sq. 0.08*** 0.05** 0.046**
MEN (N=99) Spicy Meal Spicy Asian Foods Spicy/BBQ Spare Ribs BS -0.84 -0.52 -1.30 AISS 0.11 0.01 -0.21
BS
x AISS 0.58 0.29 1.05 Model (3,73) Adj. R-Sq. 0.14** 0.03 0.06
BS -0.14 -0.15 -0.10 SP 0.17 0.22 0.18
BS
x SP -0.25 -0.19 -0.22 Model (3,78) Adj. R-Sq. 0.05 0.04 0.02
BS 0.16 0.49 0.31 SR 0.55* 0.60* 0.51*
BS
x SR -0.61 -0.96* -0.72 Model (3,150) Adj. R-Sq. 0.13** 0.09* 0.08*
WOMEN (N=147) Spicy Meal Spicy Asian Foods Spicy/BBQ Spare Ribs BS -0.38 0.10 0.66 AISS 0.28* 0.34* 0.29
BS
x AISS 0.18 -0.23 -0.87 Model (3,150) Adj. R-Sq. 0.14** 0.08** 0.03
BS -0.10 0.05 -0.43* SP -0.02 0.09 -0.19
BS
x SP -0.16 -0.24 0.37 Model (3,150) Adj. R-Sq. 0.12 0.002 0.02
BS -0.32 -0.11 -0.04 SR 0.06 0.17 0.09
BS
x SR 0.11 -0.04 -0.16 Model (3,150) Adj. R-Sq. 0.04* 0.02 0.01
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Relationship between personality and reported yearly chili intake
Sensation Seeking and Sensitivity to Reward showed significant correlations with
reported chili intake in the full dataset (AISS: r = 0.16, p = 0.02, SR: r = 0.19, p = 0.005).
In models assessing possible moderation of the relationship between the liking of spicy
foods and yearly intake of chili-containing foods by personality traits, moderation was
observed only by some personality traits. In all 246 participants, main effects were noted
for liking of spicy meals and spicy Asian foods on reported yearly chili intake in the
moderation model with Sensitivity to Reward (Table 5-2; meal: β = 0.58, p = 0.002,
Asian: β = 0.53, p = 0.003). Sensitivity to Reward showed main effects on yearly intake
in all moderation models, Sensitivity to Punishment showed main effects on yearly intake
in the moderation models with spicy meals and spicy Asian foods, and Sensation Seeking
showed main effects in the model with spicy and/or BBQ ribs (See Table 5-2). No
moderation of this relationship was observed by Sensation Seeking or Sensitivity to
Reward. Sensitivity to Punishment showed moderation of the relationship between the
liking of a spicy meal and reported yearly chili intake (β =0.30, p = 0.02).
Table 5-2. Moderator effects of personality on the relationship between liking and intake of spicy foods. Main effects of spicy foods (spicy meal, spicy Asian foods, or spicy and or BBQ spare ribs), and personality (AISS, SP, or SR), are reported for each model as well as interaction effects of spicy food and personality. AISS is Sensation Seeking, SP is Sensitivity to Punishment, and SR is Sensitivity to Reward. Standardized regression coefficients are reported. Significant main effects of personality or liking of spicy foods and significant interaction effects are highlighted * p<0.05, ** p<0.01, *** p<0.001
FULL COHORT (N=246) Intake Intake Intake
Spicy Meal 0.52 Spicy Asian Foods 0.59 Spicy/BBQ Spare Ribs 0.45 AISS 0.11 AISS 0.15 AISS 0.29
Spicy Meal -0.1 Spicy Asian Foods -0.17 Spicy/BBQ Spare Ribs -0.25
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x AISS x AISS x AISS
Model (3,198) Adj. R-Sq. 0.22*** Model (3,196) Adj. R-Sq. 0.21*** Model (3,188) Adj. R-Sq. 0.12*** Spicy Meal 0.21 Spicy Asian Foods 0.34* Spicy/BBQ Spare Ribs 0.1
SP -0.07 SP -0.04 SP -0.1 Spicy Meal
x SP 0.30* Spicy Asian Foods
x SP 0.14 Spicy/BBQ Spare Ribs
x SP 0.18 Model (3,198) Adj. R-Sq. 0.22*** Model (3,196) Adj. R-Sq. 0.20*** Model (3,188) Adj. R-Sq. 0.05**
Spicy Meal 0.58** Spicy Asian Foods 0.53** Spicy/BBQ Spare Ribs 0.16
SR 0.24** SR 0.23* SR 0.21*
Spicy Meal x SR -0.17 Spicy Asian Foods x SR -0.13 Spicy/BBQ
Spare Ribs x SR 0.07 Model (3,198) Adj. R-Sq. 0.24*** Model (3,196) Adj. R-Sq. 0.24*** Model (3,188) Adj. R-Sq. 0.10***
MEN (N=99) Intake Intake Intake
Spicy Meal 0.86 Spicy Asian Foods 0.43 Spicy/BBQ Spare Ribs -0.36 AISS 0.26 AISS 0.31 AISS 0.19
Spicy Meal x AISS -0.59 Spicy Asian Foods
x AISS -0.26 Spicy/BBQ Spare Ribs x AISS 0.47
Model (3,77) Adj. R-Sq. 0.13** Model (3,77) Adj. R-Sq. 0.07* Model (3,75) Adj. R-Sq. 0.05
Spicy Meal 0.06 Spicy Asian Foods 0.26 Spicy/BBQ Spare Ribs -0.06
SP -0.29 SP -0.08 SP -0.24 Spicy Meal
x SP 0.39 Spicy Asian Foods x SP -0.07 Spicy/BBQ Spare Ribs x SP 0.25
Model (3,77) Adj. R-Sq. 0.14** Model (3,77) Adj. R-Sq. 0.02 Model (3,75) Adj. R-Sq. -0.01
Spicy Meal 0.79* Spicy Asian Foods 0.63 Spicy/BBQ Spare Ribs 0.14
SR 0.38** SR 0.52* SR 0.32 Spicy Meal
x SR -0.54 Spicy Asian Foods x SR -0.53 Spicy/BBQ Spare Ribs
x S -0.06
Model (3,77) Adj. R-Sq. 0.18** Model (3,77) Adj. R-Sq. 0.11** Model (3,75) Adj. R-Sq. 0.07*
WOMEN (N=147) Intake Intake Intake
Spicy Meal 0.29 Spicy Asian Foods 0.49 Spicy/BBQ Spare Ribs 0.74 AISS 0.01 AISS -0.01 AISS 0.28**
Spicy Meal x AISS 0.21 Spicy Asian Foods
x AISS 0.08 Spicy/BBQ Spare Ribs x AISS -0.48
Model (3,120) Adj. R-Sq. 0.24*** Model (3,118) Adj. R-Sq. 0.31*** Model (3,112) Adj. R-Sq. 0.12**
Spicy Meal 0.19 Spicy Asian Foods 0.3 Spicy/BBQ Spare Ribs 0.1
SP 0.05 SP 0.03 SP -0.03
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Spicy Meal x SP 0.37* Spicy Asian Foods
x SP 0.31 Spicy/BBQ Spare Ribs x SP 0.22
Model (3,120) Adj. R-Sq. 0.28*** Model (3,118) Adj. R-Sq. 0.34*** Model (3,112) Adj. R-Sq. 0.07*
Spicy Meal 0.41 Spicy Asian Foods 0.47* Spicy/BBQ Spare Ribs 0.17
SR 0.14 SR 0.09 SR 0.13 Spicy Meal
x SR 0.09 Spicy Asian Foods x SR 0.1 Spicy/BBQ Spare Ribs
x SR 0.13
Model (3,120) Adj. R-Sq. 0.26*** Model (3,118) Adj. R-Sq. 0.32*** Model (3,112) Adj. R-Sq. 0.09**
Relationship between liking of spicy foods, reported yearly chili intake, and
personality differ between men and women
No correlation between personality and yearly intake of chilis was observed in men
but in women, a significant correlation exists between Sensitivity to Reward and reported
yearly intake of chilis (r = 0.17, p = 0.04). In men, there were no observed main effects or
moderator effects of Sensation Seeking or Sensitivity to Punishment on the relationship
between liking and reported annual chili intake. Main effects of Sensitivity to Reward
were observed (Table 5-2; in model with spicy meal: β = 0.38, p = 0.01, in model with
spicy Asian foods: β = 0.52, p = 0.01), but no moderation was observed. In women, main
effects of Sensation Seeking on yearly chili intake in the model with spicy and/or BBQ
ribs (β = 0.28, p = 0.006), and a main effect of liking of Asian foods on yearly chili intake
in the model with Sensitivity to Reward (β = 0.47, p = 0.03) were observed. Sensitivity to
Punishment showed a moderator effect on the relationship between the liking of a spicy
meal and the yearly chili intake (β = 0.37, p = 0.03).
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Discussion
Here, we used a common statistical model, moderation, to explore the nature of the
relationships between the perceived burn of a 25uM capsaicin stimulus, remembered
liking of a spicy meals, reported yearly chili intake, and a number of personality traits.
These traits included Sensitivity to Punishment and Sensitivity to Reward (O'Connor,
Colder et al., 2004; Torrubia, Avila et al., 2001) and Sensation Seeking (as measured
with Arnett’s Inventory; (Arnett, 1994). This work builds on recent work from our
laboratory showing strong to moderate correlations between the liking of spicy foods and
some of these personality constructs (Byrnes & Hayes, 2013). Here, we extend this work
in a superset of the previous cohort, showing that the nature of the relationships that are
observed between perceived burning, liking, and intake differs between men and women.
Theoretically, the perceived intensity of burning/stinging sensation elicited by
capsaicin influences an individual’s liking of capsaicin-containing foods, which thus
influences his/her yearly intake of capsaicin-containing foods. In certain individuals, if
the appropriate dose is delivered, intake of capsaicin-containing foods can also influence
the perceived intensity of capsaicin through desensitization (Green & George, 2004;
Green & Hayes, 2003; Karrer & Bartoshuk, 1991b; Lawless, Rozin et al., 1985;
Stevenson & Prescott, 1994). There was no evidence of desensitization in men or women,
indicating that variables other than perceived intensity of the burning/stinging sensation
of capsaicin may be driving liking and consumption of spicy foods.
Confirming our prior findings (Byrnes & Hayes, 2013), we show here that perceived
burning/stinging intensity of sampled capsaicin is inversely related to liking of spicy
foods (spicy meals, spicy Asian foods, spicy and/or BBQ ribs). These relationships are
204
weak, suggesting that there may be other factors that impact an individual’s liking of
spicy foods. We also show that liking of spicy foods predicts annualized intake of
capsaicin-containing foods and that the personality traits Sensation Seeking, Sensitivity
to Reward, and Sensitivity to Punishment are related to the liking and intake of capsaicin-
containing foods. To elucidate the nature of relationships that exist between the perceived
burning sensation elicited by capsaicin, the liking of spicy foods, intake of these foods,
and personality traits, moderator analysis was conducted using the methods proposed by
Baron and Kenny (1986). Given the relationships observed in our previous study, we
hypothesized that Sensation Seeking and Sensitivity to Reward would moderate the
relationship between perceived burning/stinging intensity of capsaicin and liking of spicy
foods. However, we saw no moderation by Sensation Seeking and limited moderation by
Sensitivity to Reward. Sensitivity to Punishment also showed moderator effects. We did
observe evidence that the relationships between personality traits and the liking and
intake of spicy foods may be different between men and women.
In the sample as a whole, intensity of perceived burn negatively predicted liking of
spicy foods, which in turn positively predicted yearly intake of capsaicin-containing
foods. Additionally, the personality traits Sensation Seeking and Sensitivity to Reward
showed significant associations with liking and intake of chili-containing foods. Based in
these findings, along with our prior work (Byrnes & Hayes, 2013), it was expected that
differences in AISS and SR might account for some of the differences seen in liking of
spicy foods given the weak relationship between perceived burning/stinging intensity and
liking of spicy foods. The original hypothesis was that for individuals high in Sensation
Seeking and Sensitivity to Reward, the perceived burning/stinging intensity of capsaicin
205
would influence their liking of capsaicin less than in low Sensation Seeking or Sensitivity
to Reward individuals. Contrary to this hypothesis, no moderator effects were observed
for either trait in the full cohort.
Interestingly, the relationships between perceived burning/stinging, yearly intake of
chili-containing foods, and the liking of spicy foods, are different between men and
women. Overall, men show stronger negative correlations between perceived
burning/stinging intensity and liking of spicy foods, indicating that the burning/stinging
of capsaicin may be more of a deterrent in men. In women, stronger positive relationships
are noted between liking of spicy foods and yearly intake of chili-containing foods.
Moderator analysis was conducted, using personality traits as the potential moderators, to
explore if personality differences might be responsible for these discrepancies.
In moderator analysis conducted in the whole cohort, the only observed moderation
was the moderation of the relationship between liking and intake of spicy foods by SP.
AISS and SR showed significant main effects on all measures of liking and on yearly
intake of chili-containing foods, however no moderation was observed by either of these
traits in models assessing the relationship between burning/stinging intensity and liking
of chili-containing foods, and models assessing the relationship between liking and intake
of chili containing foods.
In men, SR appeared to play a larger role in the relationships between perceived burn
intensity, liking, and intake. In moderator models exploring the effect of burning/stinging
intensity of liking of chili-containing foods, significant main effects were observed for
SR on the liking of all of the spicy foods. The only moderator effect that was noted in
men was the moderation of the effect of burning/stinging intensity on the liking of spicy
206
Asian foods by SR. Additionally, in men, SR showed significant main effects on yearly
intake of chili-containing foods in models assessing moderation of the effect of liking on
yearly intake of chili-containing foods by personality traits.
Conversely, in women, AISS appeared to play a more prominent role. In models
exploring personality traits as moderators of the relationship between burning/stinging
intensity and liking of chili-containing foods and the relationship between liking and
intake of chili-containing foods AISS showed significant main effects. No moderation by
AISS was observed in either model. Interestingly, the moderation of the relationship
between liking and intake by Sensitivity to Punishment that is seen in the whole cohort
appears to be an effect that is driven by women as this effect is not observed in men.
Overall, the data indicate that Sensitivity to Reward and Sensation Seeking tap into
different aspects of what makes spicy food enjoyable. While the personality constructs of
Sensation Seeking and Sensitivity to Reward are correlated (Byrnes & Hayes, 2013;
Torrubia, Avila et al., 2001; Zuckerman & Neeb, 1979), they are not interchangeable
constructs (Scott-Parker, Watson et al., 2012; Torrubia, Avila et al., 2001). Indeed, our
study is not the first to report differential effects between the two scales (Mobbs, Crepin
et al., 2010; Scott-Parker, Watson et al., 2012).
Sensitivity to Reward, an operationalization of Gray’s Behavioral Approach System
(BAS), is composed of items that describe reactivity in situations that are predominantly
rewarding. The items on this subscale of the SPSRQ deal with specific rewards, such as
money, sex, social power, and approval (Caseras, Avila et al., 2003b; O'Connor, Colder
et al., 2004; Torrubia, Avila et al., 2001). AISS, on the other hand, is designed to assess
the tendency of an individual to enjoy novel or intense sensations in addition to the
207
tendency to seek out those sensations (Arnett, 1994; Zuckerman & Neeb, 1979). It has
been proposed that individuals high in trait sensation seeking have chronically lower
levels of cortical arousal than their low sensation seeking counterparts (Zuckerman,
2007). The key difference between high and low sensation seekers has to do with
response to arousing stimuli. High sensation seekers enjoy these experiences because the
stimulation brings them closer to their optimal level of cortical arousal, making the
stimuli pleasant. Conversely, low sensation seekers operate at a baseline level that is
closer to their optimal level of arousal, so these stimulating sensations push them beyond
this optimal level, and are thus unpleasant. Thus, AISS may tap into rewards that are
more biologically based, rather than socially based, as with SR.
In the 1980’s Rozin observed that in Mexican culture, chili consumption was socially
associated with strength, and possibly the Mexican idea of machismo (Rozin & Schiller,
1980). Notably, there were no significant sex differences regarding preference of chili
peppers in the Mexican sample, limiting the idea that there might be a social or sexual
significance in that culture. In the present sample, men rated the liking of all spicy foods
significantly higher than women (all p < 0.05). It is possible that the cultural association
of consuming spicy foods with strength and machismo has created a learned social
reward for men. While for women these social forces are not present, and thus intrinsic
factors may act as the primary motivation for consuming spicy foods. These conclusions
are tentative; as additional work is needed to better understand the sensations that
consuming spicy foods elicit and the biological bases that underlie the associated sensory
and affective responses.
208
Conclusions
In this study, we build upon earlier findings from our lab, showing empirical evidence
for the association between the personality traits Sensation Seeking and Sensitivity to
Reward and the liking and intake of spicy foods. Once again, significant associations
between these personality traits and the liking and intake of spicy foods were observed.
Given the possible association of liking and consumption of spicy foods with masculine
traits and machismo (Rozin & Schiller, 1980), we examined differences in the
relationships of personality traits with liking and intake of spicy foods between men and
women. In men, Sensitivity to Reward tended to show stronger effects than the other
personality measures, while in women, Sensation Seeking showed stronger effects than
the other personality measures. These results suggest that in men the consumption of
spicy foods may be more strongly motivated by extrinsic rewards, while women may be
motivated more strongly by intrinsic rewards. It is possible that these findings reflect
different social learning or reward of consuming spicy foods between men and women
This hypothesis is tentative, as further work is necessary to explore any possible
biological differences in neurological response to capsaicin that may play a role in
determining liking or disliking of capsaicin-containing foods. Additionally, work
examining perception of extrinsic rewards for consuming spicy foods may provide
insight into differences between men and women. Overall, this work suggests that
personality variables may influence the intake of spicy foods differently in men and
women, and that the relationship between the variables of personality, perceived
burning/stinging of capsaicin, liking of spicy foods, and consumption of spicy foods may
differ between men and women.
209
Funding
This work was supported by a National Institute of Health grant [DC010904] from
the National Institute National of Deafness and Communication Disorders to JEH, and
United States Department of Agriculture Hatch Project PEN04332 funds.
Acknowledgements
This manuscript was completed in partial fulfillment of the requirements for a
Doctorate of Philosophy at the Pennsylvania State University by NKB. The authors
warmly thank Alissa L. Nolden, Emma L. Feeney, and Meghan Kane for their assistance
with data collection, and our study participants for their time and participation.
210
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Chapter 6
Sensation Seeking, Sensitivity to Reward, and Risk Taking Personality Traits
Reflect Different Motivations for Consumption of Spicy Foods.
Abstract
Based on work done in the 1970’s through the early 1990’s, there is a widespread
belief that personality traits like sensation seeking are related to the enjoyment and intake
of spicy foods, though actual evidence supporting this is quite limited. Recently, we
showed strong to moderate correlations between remembered liking of spicy foods and
the personality traits of Sensation Seeking and Sensitivity to Reward. In the present study,
participants sampled strawberry jelly spiked with two concentrations of capsaicin to
estimate liking for sampled spicy foods. Additionally, we used a laboratory-based
behavioral measure of risk taking (the momentary Balloon Analogue Risk Task;
mBART) to complement a range of validated self-report measures of risk-related
personality traits. Here, we confirm prior results showing that Sensation Seeking is
significantly correlated with both remembered liking of an overall spicy meal and liking
of the burn of a spicy meal, and extend these findings to show a relationship with the
liking of sampled capsaicin stimuli. Other personality measures, including Sensitivity to
Punishment, Sensitivity to Reward, and the Impulsivity and Risk Taking subscales of the
Personality Inventory from the DSM-5 (PID-5) did not show significant relationships
with sampled or remembered liking of spicy foods. The behavioral measure of risk taking,
214
the mBART, also did not show a significant relationship with remembered or sampled
spicy food liking. Significant relationships were observed however between Sensitivity to
Reward, the Risk Taking subscale of the PID-5, and reported intake of spicy foods. Based
on the differences observed between the personality measures and liking and intake of
spicy foods, we propose that AISS may exert its influence on intake of spicy foods
through a different mechanism than SR and PID5-RT. We also suggest that AISS may
reflect motivations for consuming spicy foods that are more biologically based, while the
motivations for eating spicy foods measured by SR and PID5-RT are external.
215
Introduction
A number of reasons have been proposed to explain the individual differences in
consumption of foods that elicit sensations that are inherently aversive, such as capsaicin,
in chili peppers. There are biological reasons, such as genetic effects (Hayes, Wallace et
al., 2011; Kim, Neubert et al., 2004; Perry, Dominy et al., 2007; Törnwall, Silventoinen,
Kaprio et al., 2012), differences in oral anatomy (Bartoshuk, 1993; Miller & Reedy,
1990) and physiology (Duffy, 2007; Duffy & Bartoshuk, 2000), which may make
someone more or less sensitive to the sensations elicited by capsaicin on their first
encounter. Desensitization, an effect that may influence an individual’s sensitivity to
capsaicin after repeated encounters (Cowart, 1981; Green, 1996; Karrer & Bartoshuk,
1991b; Lawless, Rozin et al., 1985; Rozin & Schiller, 1980; Stevenson & Prescott, 1994),
is also proposed to influence reported liking of spicy foods. Conflicting reports on this
exist, as some researchers suggest that the supposed increased liking is merely an effect
of decreased sensitivity (Logue & Smith, 1986a; Logue & Smith, 1986b; Rozin, 1990a;
Rozin, 1990b; Rozin & Schiller, 1980), while other researchers suggest that the effects of
desensitization on liking are minimal (Rozin, Mark et al., 1981; Rozin & Schiller, 1980).
While there may or may not be differences in initial sensitivity to capsaicin that are
biologically based, it is suggested that there are actual affective differences to the
sensation that capsaicin elicits (Rozin & Schiller, 1980; Stevenson & Yeomans, 1993b).
Social and cultural effects have also been proposed to play a role in the development of
liking of spicy foods. Some work suggests that along the lines of the mere exposure
hypothesis (Zajonc, 1968), that repeated exposure to spicy foods and specific types of
216
cuisines increases the liking for these foods (Logue & Smith, 1986a). It is also possible
that cultural factors, such as the desire to be perceived as an adult, or the desire to be
involved in cultural customs influence the liking of spicy foods (Rozin & Schiller, 1980;
Rozin & Vollmecke, 1986; Stevens, 1990).
Additionally, certain personality traits have been associated with the liking of spicy
foods. Work beginning in the 1970’s and continuing through the early 1990’s associated
the liking of spicy foods and spices with personality traits such as sensation seeking and
thrill seeking (Kish & Donnenwerth, 1972; Logue & Smith, 1986b; Rozin, 1990b; Rozin
& Schiller, 1980; Stevens, 1990; Terasaki & Imada, 1988). While this work theorizes that
there is a link between trait sensation seeking and the liking of spices and spicy foods,
some of the work was not done with actual measures of personality or was not conducted
in a large enough group to allow for statistical analysis. In previous work from our lab
(Byrnes & Hayes, 2013) we showed empirically that strong significant correlations were
seen between sensation seeking (Arnett, 1994) and Sensitivity to Reward (Torrubia,
Avila et al., 2001), and the liking and intake of spicy foods, suggesting that individuals
high in sensation seeking and Sensitivity to Reward would tend to like spicy foods more
than individuals low in these traits. Conflicting reports of these relationships do exist
(Ludy & Mattes, 2012), though it is possible that the divergent findings result from a
small sample size or the use of a brief measure of sensation seeking that was developed
for use in adolescents (Hoyle, Stephenson et al., 2002). It is also possible that this
measure, while constructed from items on Zuckerman’s SSS-V, does not measure the
same overall construct that Zuckerman’s measure does.
217
There are a number of related traits including impulsivity, behavioral constraint,
disinhibition, thrill seeking and risk taking that are associated with risky behaviors, such
as alcohol and drug consumption, theft, risky sexual behavior, and risky driving
behaviors (i.e. drunk driving, speeding, not wearing a seatbelt, etc.); (Aklin, Lejuez et al.,
2005; Fernie, Cole et al., 2010; Greene, Krcmar et al., 2000; Grossarth-Maticek &
Eysenck, 1991; Hopko, Lejuez et al., 2006; Jonah, 1997; Lauriola & Levin, 2001;
MacPherson, Magidson et al., 2010; Marino, Rosen et al., 2013; Powell, Hardoon et al.,
1999; Stanford, Greve et al., 1996; Stout, Rock et al., 2005; Zuckerman, 2007). The
association of these traits with these behaviors classifies them as risk-related traits. While
there is contention in the field about where these traits fall in the hierarchical organization
of personality (e.g. (Costa & Mccrae, 1998; Eysenck, 1978; Zuckerman, 2002) and about
the exact definition of the related traits (e.g. (Arnett, 1994; Cloninger, 1987; Zuckerman,
1964), it is agreed upon that many of these traits are multidimensional (Dawe & Loxton,
2004; Evenden, 1999; Lauriola, Panno et al., 2013; Lejuez, Read et al., 2002). The
variety of conceptualizations of these traits has lead to an assortment of personality scales
designed to measure said traits.
Previously, the relatedness of the personality instruments designed to measure has
been assessed using correlations (e.g. (Torrubia, Avila et al., 2001; Zuckerman &
Cloninger, 1996), but this measure only provides information about the extent of overlap
between the instruments. Comparing the common behaviors that two personality scales
associate with provides more information as to whether the scales are measuring similar
dimensions of the specific trait. For example, if two scales that are designed to measure
218
impulsivity both associate strongly with the tendency of an individual to drive drunk, it is
likely that they measure similar dimensions of trait impulsivity.
Assessment of risk behaviors in the literature has often relied heavily on the use of
self-report instruments that measure constructs such as Sensation Seeking (Zuckerman,
Kolin et al., 1964), venturesomeness (Eysenck, 1978), impulsivity (Barratt, 1985;
Eysenck, 1978), and deficits in behavioral constraint (Tellegen & Waller, 2008). While
these constructs overlap with risk taking, none fully capture the multidimensional nature
of risky behavior. Additionally, limitations exist with self-report measures in that certain
individuals may not be able to provide an accurate report of their own behavior. It is also
possible that individuals perceive certain consequences or stigma associated with
reporting risky behaviors and this may also influence the fidelity of self-report measures
of risk taking. Using behavioral measures of risk taking, such as the Bechara Gambling
Task (BGT;(Bechara, Damasio et al., 1994), have their own set of advantages and
disadvantages (Lejuez, Read et al., 2002) and it has been suggested that the best approach
is to use both self-report and behavioral measures as they may provide complimentary
information (Meyer, Finn et al., 2001; Weiner, 2005).
One such behavioral measure is the Balloon Analogue Risk Task (BART). Scores on
this measure have been significantly correlated with relevant measures of risk-related
personality constructs including Sensation Seeking total score, Barratt Impulsiveness
total score, Eysenck Impulsivity subscale score, and the MPQ Behavioral Constraint
superfactor score (Holmes, Bearden et al., 2009; Hopko, Lejuez et al., 2006; Lejuez,
Aklin, Jones et al., 2003; Lejuez, Read et al., 2002). The BART also correlates well with
measures of real-life risky behavior, such as alcohol use, number of drugs used in the past
219
year, and smoking behavior (Lejuez, Read et al., 2002). This measure has seen limited
use in the field of food choice research (Lejuez, Read et al., 2002).
In addition to exploring the relationship between measures of personality, perceived
intensity of burning/stinging sensation, and liking and intake of capsaicin, we will also be
exploring the possibility that individuals exhibit different responses to varying levels of
capsaicin. In the sweet (Antenucci, 2014; Drewnowski, Henderson et al., 1997) and sour
(Molinier and Hayes, unpublished work) liking literature, multiple response types have
been observed. These responses, summarized by Drewnowski and colleagues (1997),
include inverted-U (Type I), linear increasing (Type II), linear decreasing (Type III)
responses, and a response style where no systematic change in response is observed
(Type IV) with increased concentration of stimulus. We hope to clarify whether reported
liking of increased capsaicin concentrations is attributed to decreased sensitivity (Logue
& Smith, 1986a; Rozin, 1990a; Rozin & Schiller, 1980) or whether some individuals
actually enjoy the pungency of capsaicin, regardless of the perceived intensity of
burning/stinging (Rozin, Mark et al., 1981; Rozin & Schiller, 1980).
Here, we will be expanding on previous work by examining the relationship between
liking of spicy foods and personality traits using a range of self-report and behavioral
measures of risk-related personality traits, including Arnett’s Inventory of Sensation
Seeking (AISS; (Arnett, 1994), the Sensitivity to Punishment and Sensitivity to Reward
Questionnaire (SPSRQ; (Torrubia, Avila et al., 2001), the Personality Inventory for the
Diagnostic and Statistic Manual of Mental Disorders-5 (PID-5; (Krueger, Derringer et al.,
2012), and the Balloon Analogue Risk Task (BART; (Lejuez, Read et al., 2002). We will
be further exploring the relationship between liking spicy foods and risk-related
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personality traits by utilizing multiple personality scales that may tap different
dimensions of risky behaviors as they relate to the liking and intake of spicy foods.
Additionally, we will be assessing how these personality measures relate to each other in
our sample. A secondary aim of the study is to examine whether participants show
different response types to varying capsaicin concentrations.
Materials and Methods
Participants
Data were collected from individuals recruited from the Pennsylvania State
University campus and surrounding area. To be eligible, potential participants had to be
nonsmoking, fluent English speakers between 18 and 55 years old, with no known
defects of taste or smell. Participants were ineligible to participate if they had cheek, lip,
or tongue piercings, had a history of a condition involving chronic pain or were on
prescription pain medications, were pregnant or nursing, or if they had an allergy to
spices or food components. Additional exclusion criteria included a known defect in taste
or smell or a history of choking or difficulty swallowing, and presence of a cold or upper
respiratory condition that might hinder his or her senses of taste or smell. Participants
were asked not to consume hot and spicy foods for 48 hours prior to the test and to refrain
from eating or drinking anything other than water in the hour prior to their testing session.
Data from 103 participants (26 men) are reported here. Ages of panelists ranged from
18 to 55, with 61% between the ages of 18-25, 13% between 26-35, and 12% between
36-45, 1% between 46-55, 13% did not respond. Self reported race and ethnicity were
collected with two separate questions, according to the 1997 OMB Directive 15
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guidelines. Our sample included 7 Asians, 80 Caucasians, and 16 not reported; 3
individuals identified as being Latina or Latino, and 86 indicated they were not Latina or
Latino. All data were collected with the approval of the local Institutional Review Board;
written informed consent was obtained, and participants were paid for their time.
Stimuli
All materials were food grade. Capsaicin (natural, Sigma-Aldrich, St. Louis, MO) and
allyl isothiocyanate (AITC; mustard oil, ≥ 93%, FCC, Sigma-Aldrich, St. Louis, MO)
were chosen as the time course of irritation is different and based on prior work, these
stimuli are perceptually distinguishable. Stock concentrations of capsaicin (2.20 mM) and
AITC were made in ethanol (95%, USP, Koptec, King of Prussia, PA) and stored at 4°C
for four weeks.
Previous work shows that while capsaicin and AITC elicit sensations that are both
referred to as spicy, the psychophysical functions for these stimuli are different
(McDonald, Barrett et al., 2010), and can be identified as distinct sensations (see chapter
2).
To help participants concentrate on the pungency elicited by the chemesthetic stimuli
and to avoid any expectancy effects from learned associations with certain foods (i.e.
salsa or mustard; (Prescott & Stevenson, 1995b), we chose a strawberry jelly matrix to
deliver the stimuli. Recent work by Törnwall and colleagues delivered capsaicin in a firm
strawberry-flavored gel cut into cubes that was made with pectin based jelly sugar
(Törnwall, Silventoinen, Kaprio et al., 2012). As firm gels with this texture would
typically be made with gelatin (e.g. Jell-O) in North America, we instead made a softer
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flowable jelly with the texture of akin to a fruit spread. To make these, we used sucrose,
pectin (100% natural Sure-Jell, Premium Fruit Pectin, Kraft Foods, Deerfield, Illinois,
U.S.A.), red food color (McCormick, Hunt Valley, Maryland, U.S.A.), imitation
strawberry extract (McCormick, Hunt Valley, Maryland, U.S.A.), and reverse osmosis
(RO) water. Jelly samples were prepared by combining 4.32 g flavoring, 642.50 g
sucrose, 1.47 g food coloring, and 283.90 g reverse osmosis (RO) water. Separately,
39.68 g pectin and 141.96 g RO water were brought to a boil over medium heat while
stirring constantly for one minute. The pectin mix was removed from heat, combined
with the sucrose mix, and stirred for three minutes, which was a sufficient amount of time
for all the sucrose to dissolve. To minimize variation between jelly samples within a
testing session, all samples used in a session were produced from a single batch of jelly.
The jelly was separated into five lots and spiked with the appropriate amount of capsaicin
or AITC stock to produce a blank, 3.0 µM capsaicin, 12 µM capsaicin, 0.05 mM AITC,
and 2.0 mM AITC samples. Duplicate samples came from same lot of spiked jelly to
eliminate differences between duplicates. Samples were mixed thoroughly and 3 g was
weighed into individual 1 ounce serving cups. Samples were capped, labeled with
randomly assigned three-digit blinding codes, and stored at 4°C for up to two weeks.
Previous work in our laboratory showed that a 25 µM capsaicin stimulus would
produce a mean burning/stinging intensity rating between “strong” and “very strong” on a
general Labeled Magnitude Scale (Hayes, Feeney et al., 2013). Pilot testing with the jelly
samples was conducted to intensity match the low capsaicin and low AITC stimulus, and
the high capsaicin and high AITC stimuli, respectively. This testing indicated that the low
concentrations (3 µM capsaicin and 0.5 mM AITC) were not significantly different from
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each other, producing a burning/stinging sensation that was rated near “weak” on a gLMS.
The high concentrations (12 µM capsaicin and 2.0 mM AITC) were significantly more
intense than the low concentration samples but were not significantly different from each
other, producing ratings around “moderate” on a gLMS.
Data Collection
All data were collected using Compusense version 5.2 (Guelph, Ontario, Canada).
Liking and intensity ratings for the sampled jellies were collected on one computer using
Compusense while a second computer running Compusense five Plus was used to collect
personality measures and remembered food liking ratings. Momentary BART (mBART)
data were collected using a custom software application (coded as specified by (Lejuez,
Read et al., 2002) presented on a Google Nexus 7 tablet (Google, Mountain View,
California, U.S.A.) running the Android operating system. This software was kindly
provided by R. Ross MacLean. (See Appendix for image of screen)
Prior to evaluating any stimuli, participants completed an orientation on how to use a
general Labeled Magnitude Scale (gLMS), followed by a warm-up exercise. Ratings on
the gLMS range from “No Sensation” on the left of the scale and “Strongest Imaginable
Sensation of Any Kind” on the right of the scale; intermediate labels (Barely Detectable,
Weak, Moderate, Strong, and Very Strong) are located along the scale (Bartoshuk, Duffy,
Green et al., 2004b; Green, Dalton et al., 1996). To encourage participants to make their
ratings in a generalized context, in the warm-up, participants rated the intensity of a list
of 15 remembered or imagined sensations that include both oral and non-oral items
(Hayes, Allen et al., 2013).
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In total, ten jellies were evaluated, with blank, low capsaicin concentration, high
capsaicin concentration, low AITC concentration, and high AITC concentration jellies all
evaluated in duplicate. Stimuli were presented in a pseudo-randomized order, such that
the first jelly that participants evaluated was always a blank jelly sample containing no
capsaicin or AITC. The presentation order of the remaining nine samples was
counterbalanced across all participants. Participants were instructed to rinse their mouths
with RO water prior to tasting the first sample, and between samples.
All jellies were sampled in the same manner. Participants were instructed to scoop the
entire jelly sample (3g) from the plastic cup with a plastic spoon and then to flip the
spoon over so that the jelly contacted their tongue before the spoon. They were instructed
to make sure that all the jelly was off of the spoon and then to use their tongue to move
the jelly around in their mouth for five seconds. They then expectorated the sample and
rated liking and intensity of the burning/stinging sensation before rinsing with RO water.
In the break between jelly samples participants completed personality instruments and
food liking surveys on a second computer. They were instructed to continue rinsing with
RO water while completing these surveys. A minimum of 3 minutes elapsed between
samples and participants were instructed not to sample the next jelly until they felt that
there was no lingering sensation from the prior sample. No water or jelly samples were
swallowed in this protocol.
Personality measures
The personality trait sensation seeking is characterized by the need for varied,
complex, and novel sensations, and the willingness to seek out these experiences
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regardless of possible associated physical and social risks (Arnett, 1994; Zuckerman,
Kolin et al., 1964; Zuckerman & Neeb, 1979). Arnett’s Inventory of Sensation Seeking
(AISS; (Arnett, 1994) is a scale designed to measure a construct similar to Zuckerman’s
Sensation Seeking. Arnett believed that intensity, rather than complexity, was a key
component to sensation seeking and he emphasized the role of environmental influences
on this personality trait. Arnett’s measure updated Zuckerman’s scale to exclude gender
and age biased questions, shortened the instrument to 20 questions, and did away with the
original response style of “yes” or “no”, which is considered somewhat frustrating and
difficult for some participants to respond with (Arnett, 1994; Haynes, Miles et al., 2000).
While some work shows that Zuckerman’s and Arnett’s scales measure the same
construct (Ferrando & Chico, 2001a), other work shows that, due to Arnett’s removal of
age-biased questions, differences between the scales may arise in older individuals
(Carretero Dios & Salinas Martínez de Lecea, 2008). We chose to use Arnett’s scale to
avoid these age-biases.
The Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) is a
scale originally developed in Catalan by Torrubia, Molto, and Caseras (Torrubia, Avila et
al., 2001) to measure the reactivity to and avoidance of rewarding and punishing stimuli.
Here, we use the English language version validated by O’Connor and colleagues
(O'Connor, Colder et al., 2004). Constructed to operationalize Gray’s Behavioral
Inhibition System (BIS) and Behavioral Activation System (BAS), this measure has been
linked with extraversion, impulsivity, and novelty seeking (Torrubia, Avila et al., 2001),
all traits that have previously been associated with liking of spicy foods (Blackburn,
1969; Corlis, Splaver et al., 1967; Eysenck, 1978; Franken & Muris, 2006). The SP
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subscale measures individual’s responses to situations involving punishment, cues for
failure, or frustrative non-reward (Cooper & Gomez, 2008; O'Connor, Colder et al., 2004;
Torrubia, Avila et al., 2001), while the SR subscale measures reactivity to reward,
specifically rewards pertaining to money, social status and approval, and sexual partners
(Cooper & Gomez, 2008; Dawe & Loxton, 2004; O'Connor, Colder et al., 2004; Torrubia,
Avila et al., 2001). Data applying the SPSRQ in a food context is limited, as our group
was the first to do so. Previously, we observed a positive correlation between scores on
the SR subscale and the liking of spicy foods (Byrnes & Hayes, 2013).
The PID-5 is a personality inventory for the Diagnostic and Statistic Manual of
Mental Disorders V (DSM-V) constructed by Krueger and colleagues (Krueger,
Derringer et al., 2012). The model operationalized maladaptive personality traits from the
DSM-5 in a condensed set of 25 traits that define 5 higher order domains: negative affect,
detachment, antagonism, disinhibition, and psychoticism (Krueger, Derringer et al., 2012;
Thomas, Yalch et al., 2013; Wright, Thomas et al., 2012). The structure, which resembles
Costa & McCrae’s Five-Factor Model (FFM; (Costa Jr & McCrae, 1992; De Fruyt, De
Clercq et al., 2013; Krueger, Derringer et al., 2012), replicates well and is robust across
samples (Wright, Thomas et al., 2012). For the present study, we selected two specific
subscales, Impulsivity and Risk Taking, from the Disinhibition domain, to explore how
these subscales associate with the other personality measures used here, as well as the
liking and intake of spicy foods.
The Balloon Analogue Risk Task (BART) is a laboratory-based behavioral measure
of risk-related constructs that provides a context in which actual risk taking behavior is
measured. This computerized task models real-world risky situations, in that riskiness is
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rewarded up to a point, but excessive riskiness often results in diminishing returns. In this
task, the participant plays a game where he or she presses a button to inflate a balloon on
a computer screen. Each time the participant pumps up the balloon and the balloon does
not pop, the participant receives a nominal cash reward into a temporary bank. After each
pump, the participant must choose whether to cash out his or her winnings on that balloon
and transfer to a permanent bank, which starts a new balloon, or to continue pumping up
the balloon via additional button presses. If the balloon pops, all money in the temporary
bank is lost and a new balloon is started. This game operationalizes risk taking, as each
successive pump on an individual balloon trial both increases the amount to be lost if the
balloon pops and decreases the relative gain from any additional pumps. Here, we used
the mBART, a version of the original BART that was adapted for use on mobile devices
such as tablets. Average adjusted pumps were calculated as the average number of times
that a participant pumped a balloon before collecting money, when the balloon did not
pop. To incentivize study participants as was done in the original BART work (Lejuez,
Read et al., 2002), we informed them at the start of the mBART task that they would not
be receiving the amount that they earned in their permanent “bank”; rather we would be
recording their total earned and that the top three earners would be recontacted after the
experiment was completed, with the top earner receiving $75 (USD), second place $50
(USD), and third place $25 (USD).
Measuring food liking
During the session, one of the measures that participants completed between jelly
samples was a generalized Degree of Liking (gDOL) survey (See Appendix B for scale).
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The gDOL used here is a 63-item affective survey with 47 food items (including ratings
of “your favorite food”, “your least favorite food”, “overall spicy meal”, and “burn of a
spicy meal”), three alcoholic beverages, and 13 non-food sensations. Responses were
collected using a bipolar, unstructured, horizontal visual analog scale (VAS), ranging
from “strongest disliking of any kind” (-100, left side) and “strongest liking of any kind”
(+100, right side), with the midpoint of the scale labeled “neutral” (0). Similar measures
have been used previously to measure associations between food liking and intake
(Byrnes & Hayes, 2013; Hayes, Sullivan et al., 2010), food liking and health outcomes
(Duffy, Hayes et al., 2009), and food liking and taste phenotypes (Pickering, Jain et al.,
2012b). This bipolar hedonic scale was also used to collect ratings of the liking of the
burning/stinging sensation experienced when sampling the jellies.
Follow-up web-based questionnaire
After leaving the laboratory testing session, participants completed a web-based
questionnaire that collected demographic data, including race, ethnicity, and gender, as
well as food intake frequency data. To assess intake frequency, we used an updated
version of the questionnaire originally developed by Lawless and colleagues (Lawless,
Rozin et al., 1985). Here, participants were asked to indicate how often they consumed
various foods on a survey. Response options consisted of a seven-point category scale
with the descriptors “never”, “1-10 times / year”, “1-2 times / month”, “1-3 times / week”,
“4-6 times / week”, “1-2 times / day”, and “more than 2 times / day”. The specific foods
on the follow-up survey included: wasabi, horseradish, spicy food, spicy brown mustard,
yellow mustard, spicy Korean food, non-spicy Korean food, spicy BBQ, non-spicy BBQ,
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spicy Mexican/Latin food, non-spicy Mexican/Latin food, spicy Thai food, non-spicy
Thai food, spicy Indian food (creates burning, hot, or stinging/pricking sensation), non-
spicy Indian food (can still be highly aromatic but does not create burning, hot, or
stinging/pricking sensation), Buffalo wing sauce (ex: Frank’s Red Hot), Tabasco sauce or
other hot sauces (excluding Sriracha), hot salsa, mild salsa, Sriracha (Rooster Sauce),
spicy Chinese food, and non-spicy Chinese food. Participants were asked, that if they had
never tried the food to refrain from making a rating. For analysis, these responses were
converted to an annualized measure, such that “never” became 0 (times per year), “1-2
times / month” became 12, “1-2 times / week” became 52, etc. up to “more than 2 times /
day”, which became 730.
Statistical analyses
One-way ANOVA showed that there was no significant effect of order and that all
sample duplicates had intensity ratings that were not significantly different from one
another. Thus, the duplicate means for the intensity and liking ratings were used for all
analyses. SAS 9.2 (Cary, North Carolina, U.S.A.) was used for all data analysis. Pearson
correlations were calculated using proc corr and descriptive statistics were generated
using proc means and proc freq. Difference scores were calculated for intensity and
affective ratings prior to analysis, such that the mean intensity and affective ratings for
blank samples were subtracted from the mean intensity and affective ratings for the
spiked samples. Importantly, because of this transformation, the ranges of possible values
for difference scores were larger than the original scale (-100 to 100 for intensity ratings
and -200 to 200 for affective ratings). Significance criteria was set at alpha = 0.05.
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Results
In this cohort of 103 individuals, perceived intensity for the low and high capsaicin-
spiked jelly samples (possible range -100 to 100) showed wide variation (3 µM capsaicin
[mean ± SE]: 7.00 ± 0.81, IQR: 1.75 – 11.50, range: 8.25 to 33.50; 12 µM capsaicin
[mean ± SE]: 22.79 ± 1.32, interquartile range [IQR]: 12.75 – 29.00, range: 1.50 to
72.00). Liking of the low and high concentrations of capsaicin-spiked jellies (possible
range -200 to 200) also showed wide variation in observed responses (3 µM capsaicin
[mean ± SE]: 13.58 ± 2.52, IQR: -1.00 – 29.50, range: –77.50 to 90.50; 12 µM capsaicin
[mean ± SE]: -11.57 ± 4.04, IQR: -33.50 – 13.00, range: -130.50 to 99.50). Liking scores
for measures of remembered liking measured on the gDOL) showed similar means and
IQRs: liking of an overall spicy meal [mean ± SE]: -30.80 ± 3.16, IQR: 13 – 52, range: -
81 to 98, liking of the burn of a spicy meal [mean ± SE]: 22.9 ± 2.97, IQR: 6 – 44, range:
-78 to 83. Self-reported yearly intake of spicy foods showed a variety of responses, from
never to once per day (mean ± SE: 73.05 ±9.87 times per year, IQR: 12 – 59, range: 0 –
365).
Perceived intensity for the low and high AITC-spiked jelly samples also showed wide
variation (0.05 mM AITC [mean ± SE]: 1.23 ± 0.49, IQR: 0.00 – 2.00, range: 14.5 –
27.0; 2.0 mM AITC [mean ± SE]: 3.22 ± 0.57, IQR: 0.00 – 5.00, range: -7.75 – 31.75).
Liking of the high and low concentrations of AITC-spiked jellies also showed wide
variation in observed responses (0.05 mM AITC [mean ± SE]: -9.02 ± 2.01, IQR: -19.5 –
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1.00, range: -71.50 – 40.00; 2.0 mM AITC [mean ± SE]: -14.69 ± 2.95, IQR: -23.00 –
0.50, range: -109.50 – 71.00).
Personality scores also showed sufficient variability across variability. Out of a
possible range of 20 to 80, observed AISS scores ranged from 31 to 70 (mean ± SE: 52.7
± 0.8, IQR: 47-58). SP and SR scales, both with a possible range of 0 to 24, showed
responses from 0 to 23 for SP (mean ± SE: 11.4 ± 0.5, IQR: 7-16), and 2 to 21 for SR
(mean ± SE: 11.7 ± 0.4, IQR: 8-14). Both subscales taken from the PID-5 questionnaire
showed satisfactory variability, with the observed PID5-Impulsivity subscale scores
ranging from 5 to 20 out of a possible 0 to 24 (mean ± SE: 9.5 ± 0.4, IQR: 6 – 12), and
the observed PID5-Risk Taking subscale scores ranging from 11 to 45, out of a possible
range of 0 to 56 (mean ± SE: 26.78 ± 0.83, IQR: 20 – 33). In our cohort, average adjusted
pumps on the mBART (mean ± SE: 30.7 ± 1.4, IQR: 19.3 – 40.3, range: 1.03 – 67.46).
Initially there was concern that study participants may not be properly incentivized,
as we did not pay study participants the amount they earned on the mBART, but instead
only paid the top three earners in the study. The results observed here however, indicate
that this reward scheme does function to appropriately incentivize study participants, as
participants did not behave in an overly risky way (in essence, “shooting the moon”). The
mean number of average adjusted pumps is similar to that reported in the original BART
manuscript (Lejuez, Read et al., 2002) and in more recent work (Hunt et al 2005).
Liking of AITC-spiked samples did not relate to other measures
Unlike the capsaicin-spiked jelly samples, no relationship was observed between
personality measures and perceived intensity or liking of either AITC spiked-jelly. No
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relationships were observed between liking of AITC-spiked samples and intake of spicy
foods, nor were relationships observed between perceived intensity of the jellies and
intake of spicy foods. Non-significant relationships were observed between liking of the
high AITC jelly and remembered liking of overall spicy foods (r = 0.18, p = 0.07) and a
non-significant relationship was observed between liking of the high AITC concentration
jelly and yearly intake of spicy foods (r = 0.21, p = 0.06).
Perceived intensity did not relate to yearly intake of spicy foods or personality traits
Perceived intensity of the 3 µM capsaicin-spiked jelly was not related to yearly intake
of spicy foods or to any of the personality traits. Perceived intensity of the 12 µM
capsaicin-spiked jelly also did not show any association to yearly intake of spicy foods or
personality measures.
Liking and intake of capsaicin-containing foods were related
As expected, remembered overall liking of a spicy meal and remembered liking of the
burn of a spicy meal showed significant relationships with reported intake of spicy foods
(r = 0.48, p < 0.0001 and r = 0.39, p = 0.0005, respectively). Liking of the 3 µM
capsaicin-spiked jelly was not correlated with yearly intake of spicy foods. Liking of the
high capsaicin concentration jelly was significantly correlated with yearly intake of spicy
foods (r = 0.35, p = 0.002).
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Remembered and sampled liking are related
Liking of the 3 µM capsaicin-spiked jelly did not relate to remembered liking of an
overall spicy meal or the liking of the burn of a spicy meal. Liking of the 12 µM
capsaicin-spiked jelly correlated with both remembered overall liking of a spicy meal (r =
0.49, p < 0.0001) and with remembered liking of the burn of a spicy meal (r = 0.45, p
<0.0001).
Personality related to liking and intake of capsaicin-containing foods
Liking of 3 µM capsaicin-spiked jelly did not show associations with any of the
personality measures tested here. The AISS showed significant correlations with liking of
the 12 µM capsaicin-spiked jelly (12 µM capsaicin-spiked jelly, r = 0.30, p = 0.002).
Replicating our prior finding in a separate cohort, AISS also showed significant
correlations with overall liking of a spicy meal (r = 0.23, p = 0.02) and liking of the burn
of a spicy meal (r = 0.24, p = 0.02), and yearly intake of spicy foods and AISS were
correlated (r = 0.33, p = 0.003). The SR subscale of the SPSRQ showed a significant
relationship with yearly intake of spicy foods (r = 0.27. p = 0.02). The Risk-Taking
subscale of the PID5 measure also showed significant correlations with yearly intake of
spicy foods (r = 0.31, p = 0.005). The SP subscale of the SPSRQ, the Impulsivity
subscale of the PID5, and the mBART did not show any correlations with the liking or
intake of spicy foods.
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Personality measures did not relate to liking of non-spicy foods
Three non-spicy foods were selected that showed mean liking scores and range of
liking scores that were similar to the reported overall liking of a spicy meal and the liking
of the burn of a spicy meal. These foods were fried chicken (mean liking ± SE: 32.73 ±
3.07, range: -89 to 99), hamburgers (mean liking ± SE: 33.16 ± 2.65, range: -78 to 100),
and doughnuts (mean liking ± SE: 33.86 ± 2.97, range: -81 to 100). None of the
personality traits showed significant correlations with the liking of these foods.
Additionally, the relationships between personality traits and the rated liking for “your
favorite food” (mean liking ± SE: -63.31 ± 27.49, range: -100 to 9) and “your least
favorite food” (mean liking ± SE: 71.91 ± 16.39, range: 32 to 100) were assessed. No
significant correlations existed between either of these measures and any of the
personality traits.
Personality measures related to one another
Both self-report and behavioral measures of personality were significantly correlated
with one another. These relationships are summarized in the correlation matrix shown in
Table 6-1.
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Table 6-1. Correlation matrix of personality measures. R-values are reported, with asterisks indicating p-values
AISS SP SR PID5-I PID5-RT Ave. adj. pumps
AISS --- -0.23* 0.44*** 0.39*** 0.61*** 0.30**
SP --- -0.03 -0.15 -0.36*** -0.13
SR --- 0.36*** 0.50*** 0.18
PID5-I --- 0.71*** 0.18
PID5-RT --- 0.30**
AISS = Arnett’s Inventory of Sensation Seeking, SP = Sensitivity to Punishment subscale
of the SPSRQ, SR = Sensitivity to Reward subscale of the SPSRQ PID5-I = Impulsivity
subscale from the PID5, PID5-RT = Risk Taking subscale from the PID5, ave. adj.
pumps = average adjusted number of pumps from the mBART. * p < 0.05, ** p < 0.01,
*** p < 0.001
Distinct response styles were observed regarding liking of capsaicin-spiked jellies
On a plot of liking versus intensity, the slope of the plotted line indicates the change
in liking between the low and high capsaicin concentrations over the change in perceived
intensity between the low and high capsaicin concentrations. Individuals were divided
into two groups based on whether the slope of this line was positive or negative (See
Figure 6-1). From this point on we call those with a positive slope (meaning they liked
the high concentration more than the low concentration) “capsaicin likers” and those with
a negative slope (meaning they liked the low concentration more than the high
concentration) “capsaicin dislikers”. Mean slope values for the capsaicin likers and
dislikers were significantly different from each other.
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Figure 6-1. Liking of the burning/stinging sensation in 3µM and 12µM capsaicin-spiked jelly versus perceived intensity of the burning/stinging sensation in 3 µM and 12 µM capsaicin-spiked jelly. On the left are capsaicin dislikers while on the left are capsaicin likers. Points on the plot indicate the location of the 3 µM capsaicin-spiked jelly sample on the plot. Along the x-axis, the labels, and corresponding values from the gLMS are plotted.
Mean scores for the personality measures, AISS, SP, SR, PID5-Impulsivity, PID5-
Risk Taking, and the number of average adjusted pumps, from the mBART were
compared between capsaicin likers and dislikers using Student’s t-test. No significant
differences were seen in SP, SR, PID5-Impulsivity, PID5-Risk Taking, and average
adjusted pumps. Capsaicin likers showed significantly higher scores on the AISS and
higher scores on the AISS-Novelty Seeking subscale than capsaicin dislikers.
Discussion
Here, we confirm earlier findings (Byrnes & Hayes, 2013) in a new group of
individuals, illustrating that these effects are robust. We also extend upon these findings,
showing that remembered and sampled liking for capsaicin-containing foods are related,
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and that both of these measures associate with reported yearly intake of spicy foods.
Once again, there was no association of personality traits with the perceived
burning/stinging sensation from a sampled capsaicin stimulus and there was no evidence
of desensitization in this cohort. Sensation Seeking, as measured by AISS, related to all
measures of liking of spicy foods, remembered and sampled, and to yearly intake of spicy
foods. No other personality measures were related any measures of liking of spicy foods.
Sensitivity to Reward and the Risk Taking subscale from the PID-5 questionnaire did
however correlate with reported yearly intake of spicy foods. A secondary aim of this
study was to explore whether individuals showed different response types, similar to
those that are seen with other stimuli (Drewnowski, Henderson et al., 1997). Here, we
showed that at least two types of responders exist and that significant differences exist
between the groups. The individuals who showed higher liking as the concentration of
capsaicin increased (capsaicin likers) showed higher AISS scores than the individuals
whose liking for the jellies decreased as capsaicin increased (capsaicin dislikers). Again,
no other personality traits significantly associated with the increasing or decreasing
trends in liking. Overall, the association of Sensation Seeking with liking and intake
suggests that for individuals high in Sensation Seeking, there may be a rewarding aspect
of capsaicin as a stimulus. Whereas for other personality constructs that associated only
with intake of spicy foods, the enjoyable aspect of consuming capsaicin may be related
more to the social aspect of consuming spicy foods.
Unlike the capsaicin-spiked jellies, the AITC-spiked jellies did not produce the
expected effects. This is perhaps due to the distinct aroma that AITC imparted on the
jellies. Some participants noted that the jellies spiked with AITC had an aroma similar to
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onions or garlic. This perceptible odor, which was not present in the capsaicin-spiked
jellies may have primed the participants and created an expectation that was incongruent
with the strawberry flavor of the jellies, influencing the liking of the jellies (Caporale,
Policastro et al., 2006; Cardello & Sawyer, 1992; Dalton, 1999).
In this cohort, perceived intensity of the burning/stinging sensation for the 12µM
capsaicin-spiked jelly provided better discriminatory ability between individuals
compared to the 3µM capsaicin-spiked jelly sample, so results with the 12µM capsaicin-
spiked jelly sample are discussed here.
While desensitization is a well-established phenomenon (Cowart, 1987b; Green,
1989; Karrer & Bartoshuk, 1991b; Lawless, Rozin et al., 1985; Prescott & Stevenson,
1995a), in this sample perceived intensity of 12µM capsaicin showed no relationship with
reported yearly intake of spicy foods indicating that there is no evidence of
desensitization. Rozin and colleagues showed that even though there are significant
differences in sensitivity to capsaicin between individuals who consume capsaicin
frequently and those that consume capsaicin infrequently, there is a large amount of
overlap between the groups and the effects on liking are slight (Rozin, Mark et al., 1981;
Rozin & Schiller, 1980).
Previously, we found that remembered liking of capsaicin-containing foods
associated with reported intake of spicy foods (Byrnes & Hayes, 2013). Here, we
replicate this finding and we also show that in addition to remembered liking of an
overall spicy meal, remembered liking of the burn of spicy foods is related to reported
intake of spicy foods. Additionally, we show here that this relationship is not limited to
measures of remembered liking. Liking of a sampled capsaicin stimulus (12µM)
239
significantly correlated with yearly intake of spicy foods, though the relationship between
liking and intake was slightly lower when using sampled liking (r = 0.35) versus
remembered liking (r = 0.48). Previous work suggests that remembered, or surveyed
liking is a good indicator of sampled liking (Hayes, Sullivan et al., 2010; Sharafi, Hayes
et al., 2013). To our knowledge, this is the first work assessing the relationship between
measures of remembered and sampled liking of capsaicin-containing foods. Here,
sampled liking shows correlations with remembered liking of an overall spicy meal (r =
0.49) and with the remembered liking of the burn of a spicy meal (r = 0.45). Initially,
these values may appear low, however considering that 1) “spicy” includes more than just
capsaicin-containing foods as previously shown (Cliff & Heymann, 1992), also see
chapters two and three), and 2) that these concentrations may be higher or lower than an
individual’s preferred concentration of capsaicin resulting in lower liking of the sampled
capsaicin stimuli compared to foods that are seasoned to the desired level by the
individual, we propose that remembered liking is a good indicator of sampled liking for
capsaicin-containing foods.
Personality related to liking and intake of capsaicin-containing foods
A number of personality traits showed significant associations with measures of
liking and intake of spicy foods. Importantly, none of the personality traits tested here
showed significant associations with liking of non-spicy foods, “your favorite food”, and
“your least favorite food”, indicating that the effects of personality observed here are not
generalizable to all foods.
240
The personality traits, Sensitivity to Punishment, the Impulsivity subscale of the PID-
5, and the number of average adjusted pumps from the mBART did not show a
relationship to any measure of liking of spicy foods or to yearly intake of spicy foods.
Previously, we hypothesized that the SP scale would be negatively correlated with the
liking of spicy foods, as the more sensitive an individual is to punishment, the less they
enjoy the burning/stinging of capsaicin; however, when this hypothesis was tested, no
relationship was observed (Byrnes & Hayes, 2013). Based on these prior findings, it was
not expected that SP would show a relationship to spicy food liking or intake.
Regarding the PID5-Impulsivity subscale, there may be a number of reasons why no
association was observed between impulsivity and spicy food liking. While impulsivity
and sensation seeking are related traits (Eysenck, 1978; Hur & Bouchard Jr, 1997;
Zuckerman, 1964), and have been associated with common behaviors, such as alcohol
and substance abuse, gambling, and drunk driving (Dawes, Tarter et al., 1997; Jaffe &
Archer, 1987; Stanford, Greve et al., 1996; Tarter, Kirisci et al., 2003), there is a key
difference between impulsivity and sensation seeking. This difference is that impulsivity,
unlike sensation seeking, has to do with the failure to inhibit behavior that will likely
produce negative consequences (Baumeister & Heatherton, 1996; Schalling, 1978).
Impulsivity and sensation seeking are multidimensional traits that have been
conceptualized in a variety of ways (Evenden, 1999; Pickering & Gray, 1999). While
AISS and impulsivity are related, it is possible that the dimensions of AISS that associate
with liking spicy foods are not the dimensions that overlap with impulsivity. This may be
due to the fact that the PID-5 was developed as a personality inventory to help identify
241
clinically relevant populations, and compared to obtaining or using illicit substances,
capsaicin-containing foods come with very little associated risk.
AISS was the only construct that significantly related to any measure of liking of
spicy foods. Sensation Seeking was positively correlated with both measures of
remembered liking and sampled liking of capsaicin-containing foods. AISS was also
associated with yearly intake of spicy foods. While the correlations reported here are
lower than our previous work (Byrnes & Hayes, 2013), the findings in a new group of
participants confirm that the effects are robust. Unlike our previous work, SR did not
show a significant relationship with the measures of liking of spicy foods. However, SR
did show a significant correlation with yearly intake of spicy foods. Given our prior work
showing that the effects for SR are likely smaller than for SS (Byrnes & Hayes, 2013),
and the fact that the effects noted here for SS are smaller than prior findings, it is possible
that this cohort is not large enough to see any effect of SR. It is also possible that the
discrepancy between SS and SR reflects different motivations for the consumption of
spicy foods, a point that will be discussed below. Additionally, the Risk Taking subscale
of the PID5 questionnaire did not show significant relationships with measures of liking
of spicy foods, but did show significant correlations with yearly intake of spicy foods.
Prior literature examined the relatedness of personality measures, showing that a
number of the scales used here are correlated to one or more of the other scales used (e.g.
(Bornovalova, Cashman-Rolls et al., 2009; Torrubia, Avila et al., 2001; Zuckerman &
Cloninger, 1996). However, little such work has been done with the PID-5, since it is a
relatively new scale. Table 6-1 shows the relationships observed in this study between
242
each of the personality measures. Figure 6-2 visualizes the relationships between the
personality measures used in this study.
Figure 6-2. Diagram of significant correlations between personality variables used in this study. Dashed lines indicate negative relationships. Line thickness and darkness indicate strength of the correlation. * indicates association of personality measure with yearly intake of spicy foods and ** indicates association of personality measure with liking of spicy foods and yearly intake of spicy foods.
While a number of these personality traits are correlated to one another (see Table 6-1
and Figure 6-2), it is important to note that they may still be measuring different
constructs. The difference in trait sensation seeking as measured by AISS and risk taking
as measured by the PID5-Risk Taking subscale may be the reason that PID5-RT
243
associates only with intake of spicy foods, while AISS also associates with liking of spicy
foods. Additionally, this may be why PID5-RT shows a relationship to spicy food intake,
while another measure of risk taking, the mBART, does not show a relationship to any
measure of spicy food liking or intake, in spite of their being correlated to each other.
Previous literature using the BART links this measure of risk taking with behaviors such
as alcohol consumption, smoking, risky sexual behaviors, theft, and use of illicit
substances (Aklin, Lejuez et al., 2005; Lejuez, Aklin, Jones et al., 2003; Lejuez, Aklin,
Zvolensky et al., 2003; Lejuez, Read et al., 2002).
It is possible that, as discussed before, the risk associated with procuring and
consuming spicy foods is not comparable to the risk associated with behaviors such as
procuring and using illicit substances, binge drinking, or speeding while driving a car.
Similarly, the mBART is associated with AISS but not with PID5-Impulsivity and it is
possible that the dimensions of risk taking assessed by using mBART overlap with
dimensions of AISS, distinct from PID5-Impulsivity and spicy food liking. We suggest
that the differences between the association of these personality constructs with behaviors
show domain specificity. In other words, the dimension of one measure of impulsivity or
sensation seeking that are tapped by one measure associate with early- versus late-onset
alcoholism (Dom, Hulstijn et al., 2006), while another measure may tap dimensions
related to disordered eating (Dawe & Loxton, 2004; Loxton & Dawe, 2001), while yet
another may tap dimensions that associate with liking of spicy foods.
While sensation seeking, sensitivity to reward, and the PID5-RT are each related to
measures of spicy food liking and intake here, we suggest that they act through different
mechanisms. Based on the relationships between the variables of personality, spicy food
244
liking, and spicy food intake, we propose a mechanism by which these risk-related
personality traits act on liking and intake of spicy foods. While we did not conduct
regression analyses, we propose that the effect of sensation seeking may act on intake of
spicy foods through liking of spicy foods. It is possible that the effects of AISS reflect
more of an intrinsic motivation for the consumption of spicy foods. Perhaps the
individuals who are higher in trait sensation seeking tend to have a higher
neurobiological response to doses of capsaicin that results in increased liking or wanting
of capsaicin-containing foods. (For an overview of liking, wanting, and learning, see
(Berridge, Robinson et al., 2009).) Conversely, the data presented here shows that SR and
PID5-RT do not associate with liking of spicy foods, and thus, likely do not exert an
effect on intake of spicy foods through liking. Instead, we suggest that the differences in
effects of Sensation Seeking and Sensitivity to Reward and PID5-RT may reflect
motivation for consumption of spicy foods by external factors. While the BAS is a
measure of sensitivity to conditioned cues for reward and non-punishment, SR is a
measure of reactivity to a specific subset of rewards including social praise (Cooper &
Gomez, 2008; Dawe & Loxton, 2004; O'Connor, Colder et al., 2004).
245
Figure 6-3. Proposed path model for the effects of various personality traits on liking and intake of spicy foods. All values shown are correlations. On the far left, the correlations between the personality measures are shown. The triple line arrows indicate that these relationships have been previously shown. * p < 0.05, ** p < 0.01, *** p < 0.0001.
Previously, it was suggested that the apparent liking that is noted in “chili likers” was
merely an effect of desensitization (Cowart, 1981; Karrer & Bartoshuk, 1991b; Lawless,
Rozin et al., 1985; Stevenson & Prescott, 1994). In other words, it was proposed that
individuals who ate chili peppers were consuming enough capsaicin to induce
desensitization, and thus, the perceived intensity of capsaicin burning was lower, making
the sensation more pleasant, and thus, making capsaicin more liked. In our previous work
we saw no evidence of desensitization but showed strong associations between Sensation
Seeking and liking of spicy foods. Here we show these same effects, suggesting that high
246
sensation seekers may be more likely to actually enjoy the pungency of spicy foods more
than low sensation seekers. As seen in other, non-chemesthetic stimuli (Antenucci, 2014;
Drewnowski, Henderson et al., 1997), we show that at least two distinct types of
responses to capsaicin can be seen (Figure 6-1). Capsaicin likers, or the individuals that
like the high capsaicin jelly more than the low capsaicin jelly, showed positive slopes in
Figure 6-1. Conversely, capsaicin dislikers, or the individuals that like the low capsaicin
jelly more than the high capsaicin jelly, show negative slopes in Figure 6-1.
Between the capsaicin likers and dislikers, there is no significant difference between
the liking or perceived intensity of the low capsaicin concentration. However, the
capsaicin dislikers rated the burning/stinging sensation of the high capsaicin jelly
significantly more intense and the liking for the high capsaicin jelly significantly lower
than the capsaicin likers. The lack of difference between the two groups with regard to
the low capsaicin concentration indicates again that there is not desensitization in the
sample that might influence the liking of capsaicin. It is notable that at the low
concentration of capsaicin there is no significant difference in liking between the two
groups, with mean burning/stinging intensity ratings for both groups just above “weak”
on the gLMS. Instead, it is at the high concentration of capsaicin that differences between
the groups are observed. The fact that capsaicin dislikers show lower affective ratings for
the stimuli that they perceive as more intense is not surprising.
As with a number of other stimuli, it is noted that pleasure increases as intensity
increases to a certain point, after which pleasure decreases as intensity increases (Beebe-
Center, 1935; Coombs & Avrunin, 1977; Moskowitz, 1981; Moskowitz, Kluter et al.,
1974; Pfaffmann, 1980). This point, or range has been called the “bliss point”
247
(Moskowitz, 1981), and represents the level(s) of intensity to produce optimal liking. It is
likely that everyone has this inverted-U-style response to a range of stimuli but the curve
parameters (steepness of the rising phase, width of the plateau, steepness of the falling
phase), depend on the stimuli being assessed, and potentially environmental influences. It
is possible that the different response types that are seen to stimuli such as sweeteners
(Antenucci, 2014) are merely close-up snapshots of a portion of that person’s response
curve and is not indicative of his or her responses to a wider range of intensities of these
same stimuli. With this in mind, it is possible that the discrepancy in liking ratings
between capsaicin likers and dislikers are because we are sampling from different points
on their individual inverted-U function (see Supplemental Figure 6-1).
As shown previously, past experiences with pain significantly influence the use of a
gLMS (Bartoshuk, Duffy, Chapo et al., 2004; Stevenson & Prescott, 1994). The
difference in the perceived intensity of burning/stinging for the high capsaicin
concentration may also be due to the differences in previous experiences between the
capsaicin likers and dislikers. Capsaicin likers showed significantly higher AISS scores
than capsaicin dislikers. Specifically, the Novelty Seeking subscale of AISS was
significantly higher in the capsaicin likers than in dislikers. It is possible that capsaicin
likers, being more sensation seeking than capsaicin dislikers, have experienced a wider
range of burn intensities and overall sensation intensities, thus making the high capsaicin
concentration seem less intense in comparison. Conducting future work using
concentrations that are intensity-matched across individual participants rather than
concentration-matched may be able to better pull apart the relationship between
perceived intensity, liking, and sensation seeking.
248
Conclusions
In this study we examined the relationship between risk-related personality traits
and the liking and intake of spicy foods in a new group of people, confirming that our
previously reported results are robust. Additionally, we extend these findings, using a
variety of self-report personality measures, as well as a behavioral measure of risk taking,
to explore the effect of personality on liking of remembered and sampled spicy foods. We
utilized contemporary measures of personality and selected a variety of personality
measures that tap a range of dimensions associated with risk-related behaviors.
While all the personality measures correlated with one another, only AISS, SR,
and PID5-RT showed significant associations with intake of spicy foods and only AISS
showed significant relationships with measures of liking of spicy foods. Based on the
differences between AISS and SR and PID5-RT and the liking and intake of spicy foods,
we proposed a hypothetical model of how these personality measures may influence the
intake of spicy foods. While these measures are all related to intake of spicy foods, we
propose they may act through different mechanisms. As AISS, a measure of the
propensity of an individual to seek out and enjoy varied, novel, and complex experiences,
is associated with liking and intake of spicy foods, we suggest that sensation seeking may
influence the liking of capsaicin-containing foods, and thus, influence intake of these
foods. We also suggest that the effect of AISS may reflect intrinsic, or biological,
motivations to consume spicy foods, while the other measures, SR and PID5-RT reflect
external, or social, motivation for consuming spicy foods.
249
We showed that there are at least two distinct response types to the concentrations
of capsaicin used, empirically showing that certain individuals enjoy the pungent
sensation elicited by capsaicin. While this evidence supports the hypothesis that certain
individuals enjoy the burning sensation produced by capsaicin, there are inherent flaws
with using two measurements to classify a relationship. It is unlikely, given research with
other stimuli, that the hedonic response function to capsaicin is not an inverted-U,
however, testing with more than two samples is needed to better resolve these
relationships. Additionally, it is possible that the differences in liking between the
capsaicin likers and dislikers are partially influenced by the differences in perceived
intensity of the capsaicin stimuli. These differences may arise from variation in the
individual’s prior experiences with pain. Studies utilizing an array of intensity-matched
concentrations across individuals would provide insight into identifying different
responder types.
Overall, these findings suggest that the relationships between liking and intake of
spicy foods are robust. While further research is needed to elucidate the mechanisms, we
propose that risk-related personality traits may show differential effects on the liking and
intake of spicy foods and that they may act through different mechanisms. These findings
highlight the dual motivation system that may exist for the consumption of spicy foods.
250
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Funding
This work was supported by a National Institute of Health grant [DC010904] from
the National Institute National of Deafness and Communication Disorders to JEH.
Acknowledgements
This manuscript was completed in partial fulfillment of the requirements for a
Doctorate of Philosophy at the Pennsylvania State University by NKB. The authors
warmly thank Brianne Linne and Geneva Bonny for their assistance with sample
preparation and data collection, and our study participants for their time and participation.
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Supplemental Figures
Supplemental Figure 6-1. Liking versus Perceived Intensity for stimuli. The orange points lie along a hypothetical inverted-U-shaped function representing the relationship between liking and intensity across a range of concentrations. This plot highlights the possibility that sampling with two points does not provide adequate resolution to determine an individual’s hedonic response profile to capsaicin.
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Chapter 7
Conclusions and future work
To explore the relationships between liking of spicy foods and personality, the
perception of spicy foods, and the factors that can influence the perception of
chemesthetic stimuli, a number of related sensory experiments were conducted. The
findings presented here give greater insight into the study of perception, liking, and
consumption of spicy foods, and personality and experiential factors that can influence
these variables. The key experimental findings of these studies are:
1. Sensation Seeking, as measured by Arnett’s Inventory of Sensation Seeking, was
shown empirically, to associate with the liking and intake of spicy foods as
measure both by measures of remembered and sampled liking. These results were
replicated in two distinct cohorts and were not generalizable to all measures of
liking of non-spicy foods, indicating that they are robust and specific.
2. In a study utilizing related personality measures to examine the domains of each
trait that are associated with liking and consumption of spicy foods, two different
types of relationships were observed. Sensation Seeking was associated with
liking and intake of spicy foods while reward-related measures were associated
only with intake of spicy foods. These results suggest that the effect of sensation
seeking may act on intake through liking, reflecting a biological motivation for
consumption, while the effect of reward-related traits may be due to external
motivations for consumption, such as social reward.
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3. The observed relationships between personality variables and the liking of spicy
foods are different between men and women. In men the larger effect that is
observed with Sensitivity to Reward but in women, stronger effects are seen with
Sensation Seeking.
4. Two distinct responder types were observed when assessing the relationship
between perceived intensity and liking of sampled capsaicin stimuli. These
response types significantly associate with total scores on AISS and the Novelty
Seeking subscale. Higher scores on these measures correlated with increased
liking of higher concentrations of capsaicin.
5. Free sorting can be conducted with chemesthetic stimuli if the appropriate
precautions are taken. Additionally, naïve participants can consistently
differentiate the perceptual dissimilarities between chemesthetic agents.
6. Training, whether gained through experiential learning or formal culinary
coursework, significantly alters the way describe chemesthetic stimuli.
Participants with experiential and formal learning performed similarly regarding
attribute generation but participants without formal training performed similarly
in the sorting task. Formal training appeared to altered the way that participants
attended to the sorting task.
While these studies have strengthened the foundation of data based on the
theoretical relationships proposed by Rozin, this work has generated numerous questions
that need to be explored in future work. The differential effects that were observed
between Sensation Seeking and Sensitivity to Reward raised questions about the
279
dimensions of spicy food consumption that these dimensions tap into. Based on the
theoretical foundations of the personality scales, it is possible that the discrepancies
reflect intrinsic versus extrinsic motivational factors for the consumption of spicy foods,
which act through different mechanisms. However, these studies were not designed to
assess these questions. Here, we did not conduct path analysis or SEM due to the
relatively small sample size in the second study. Future work using these techniques to
test the proposed model would provide critical insight into the mechanisms through
which the personality measures exert their effects.
Additionally, the differences seen between men and women with regard to the
relationships between personality scales and liking of spicy foods would also be
interesting to explore in the future. We speculate, that along the lines of Rozin’s theorized
link between spicy food consumption and machismo, that there might be social pressures
or rewards that are more pertinent to men as compared to women that may act as drivers
for consumption. It is also possible that there are neurobiological differences between
men and women that could influence the biological response to capsaicin stimuli. No
significant differences were noted between the liking of spicy foods between men and
women in these studies, but it would be interesting to examine the differences in potential
motivational factors between men and women to explore the possibility that the effects of
personality on liking and intake of spicy foods may be moderated by gender.
In addition to the findings between sensation seeking and liking and intake of
spicy foods, the work showing two distinct response styles to varying capsaicin
concentration, and the association with Sensation Seeking adds an interesting dimension
to the interpretation of how personality influences the liking and intake of capsaicin.
280
Initially we showed, through regression that it is hypothesized that high sensation seekers
would be less deterred by the burning sensation of capsaicin, a point we build upon in
later experiments, showing empirical evidence that sensation seekers are more likely to
enjoy the sensation elicited by capsaicin. While we confirm this hypothesis, the question
regarding the origin of this effect still remains unanswered. We propose that it may be
due to the differences in maximal sensation intensity ever experienced in high sensation
seekers versus low sensation seekers, but we do not have a way of testing that in the
current dataset. Exploring this more, perhaps via altering the gDOL and gLMS to include
an item along the lines of ‘the strongest sensation that you have ever experienced’ would
be helpful. Additionally, future work exploring the relationship between hypergeusia,
Sensation Seeking, past experienced sensation intensity, and capsaicin sensitivity would
be interesting to explore if high sensation seeking hypergeusics tend to rate the intensity
of taste stimuli as less intense than low sensation seeking hypergeusics.
Finally, the confirmation that it is possible to conduct a sorting task using
chemesthetic compounds adds to the existing methodologies with which these difficult to
work with compounds can be assessed. While the two studies that we show here show
sufficient levels of agreement between participants, the method should be validated
further. Conducting validation studies using different participants and incorporating blind
duplicates would be useful in confirming the usefulness of this method for evaluating this
type of stimulus. Additionally, optimization studies where different lengths of the
interstimulus interval and number of samples to be evaluated would be informative to
take the technique even further.
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Appendix A
Generalized Degree of Liking Survey Scale and items used in Chapters 4 and 5
1. Hitting your funny bone 2. Raw carrots 3. Smell of freshly cut grass 4. Vanilla milkshake 5. Hamburger 6. Jumping into the ocean or pool
on a hot day 7. Ales (Bass, Sam Adams
Summer) 8. Sound of a car alarm 9. Your favorite cereal 10. Fried chicken 11. Buzz of fluorescent lights 12. Cinnamon rolls 13. Skim milk 14. Vodka or gin martini 15. Warm fire on a cold day 16. Bitter beers (IPAs, stouts) 17. Burn of a spicy meal 18. Malt liquor (Colt 45, Olde
English) 19. French fries 20. Walking barefoot on hot
pavement 21. Diet Coke or Diet Pepsi 22. Lagers (Bud, Stella Artois,
Heineken, Corona) 23. Cotton candy 24. Dry cider (Magners, Strongbow) 25. Very spicy or BBQ spareribs
26. Wind of your face on a winter day
27. Sweet white wine 28. Pizza 29. Fresh strawberries 30. Dry wine (red or white) 31. Fresh flowers 32. Scotch or whiskey (straight or
with ice) 33. Ice cream 34. Walking in the rain 35. Flavored malt beverages (Skyy
Blue, Smirnoff Ice, Mike’s) 36. Smell of dirty gym socks 37. Semi-sweet or off-dry white wine 38. Riding a rollercoaster 39. Vodka (straight or with ice) 40. Sound of a dentist drilling your
tooth 41. Spirits with soda (Rum n’ Coke,
7 & 7) 42. Doughnuts 43. Regular Coke or Pepsi 44. Cigarette smoke 45. Bacon 46. Fruity red wine 47. Hot dog 48. Very spicy Asian food 49. Brussels sprouts 50. Margaritas or daiquiris
282
51. Salty snacks (potato or tortilla chips, popcorn)
52. Shooters (lemon drop, Kamikaze)
53. Glare of headlights at night 54. Whole milk 55. Spirits with energy drinks
(Redbull & vodka) 56. American cheese
57. Spirits with juice or milk (White Russian, vodka and cranberry juice)
58. Cheesecake 59. Unsweetened grapefruit juice 60. Brandy or cognac 61. Brownies 62. Fortified wine (port) 63. Driving fast on a twisty road
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Appendix B
Generalized Degree of Liking Survey Items used in Chapter 6
1. listening to your favorite son 2. raw carrots 3. getting a papercut 4. vanilla milkshake 5. hamburger 6. cold wind on a winter day 7. wasabi 8. sound of a car alarm 9. your favorite food 10. fried chicken 11. spending time with your favorite
person/people 12. cinnamon rolls 13. skim milk 14. horseradish 15. warm fire on a cold day 16. light beer/mild lager 17. burn of a spicy meal 18. wearing a new soft sweatshirt 19. french fries 20. watching your favorite movie 21. Diet Coke/Pepsi 22. spicy brown mustard 23. yellow mustard 24. cotton candy 25. strongly flavored beers (stouts,
IPAs) 26. waiting on hold for a long period
of time for customer service 27. spicy Korean food 28. non-spicy Korean food 29. pizza 30. fresh strawberries 31. the smell of your favorite
cologne/perfume
32. spicy BBQ 33. non-spicy BBQ 34. ice cream 35. spicy Mexican/Latin food 36. non-spicy Mexican/Latin food 37. hard liquor/spirits (straight/neat) 38. spicy Thai food 39. non-spicy Thai food 40. donuts 41. regular Coke/Pepsi 42. spicy Indian food (burning) 43. non-spicy Indian food (can be
highly aromatic) 44. smell of cigarette smoke 45. your least favorite food 46. overall spicy meal 47. hot dog 48. Buffalo wing sauce (Frank's Red
Hot) 49. Brussels Sprouts 50. Tabasco sauce 51. salty snacks (potato/tortilla
chips/popcorn/pretzels) 52. hot salsa 53. mild salsa 54. glare of headlights at night 55. whole milk 56. American cheese 57. brownies 58. Sriracha (Rooster sauce) 59. cheesecake 60. unsweetened grapefruit juice 61. spicy Chinese food 62. non-spicy Chinese food 63. driving fast on a twisty road
Curriculum Vitae
Nadia K. Byrnes
EDUCATION 2014 Ph.D., Food Science, The Pennsylvania State University, University Park, PA 2011 M.S., Food Science and Technology, The Ohio State University, Columbus, OH 2009 B.S., Chemistry. The University of Rochester, Rochester, NY PUBLICATIONS Byrnes, N. K., Nestrud, M. A., and Hayes, J. E. (Under Review). “Perceptual mapping of chemesthetic stimuli in naïve assessors.” Chemical Senses. Byrnes, N. K., Loss, C. R., Hayes, J. E. (Under Review). “Perception of Chemesthetic stimuli in
groups who differ by culinary experience.” Food Quality and Preference. Byrnes, N. and Dalton, P. (In press). Psychology of Chemesthesis. In Chemesthesis: The
Sensations of Eating – Hot, Cold, Tingling, and Numbing, and How to Use Them in Food. Wiley.
Prescott, J., Hayes, J., and Byrnes, N. (In press). Sensory Science. In Encyclopedia of Agriculture and Food Systems. Elsevier.
Byrnes, N. K. and Hayes, J. E. (2013). “Personality factors predict spicy food liking and intake.” Food Quality and Preference. 28(1): 8.
Doran, T. E., Kamens, A. J., Byrnes, N. K., & Nilsson, B. L. (2012). “Role of amino acid hydrophobicity, aromaticity, and molecular volume on IAPP(20-29) amyloid self-assembly.” Proteins: Structure, Function, and Bioinformatics. 80(4): 1053.
SELECT PRESENTATIONS Oral Presentations Byrnes, N. “Chemesthesis, Capsicum, Szechuan: It's a Spicy World!” Symposium, Institute of
Food Technologists 2013, Chicago, IL Byrnes, N. and Hayes, J. E. ‘Some Like it Hot: The Science Behind Our Food Preferences.’
Research Unplugged Series, Penn State, University Park, PA Byrnes, N. ‘Understanding Personality as a Factor in Determining the Liking of Spicy Foods.’ 3rd
Annual Meeting Society for Sensory Professionals. Jersey City, NJ Poster Presentations Byrnes, N., and Hayes, J. (2014). ‘Risk Related Personality Traits and the Liking of
Spicy Foods.’ Society of Sensory Professionals 4th Biennial Meeting, Tucson, AZ. Byrnes, N., and Hayes, J. (2014). ‘Perception of Chemesthetic Stimuli in Groups who Differ in
Culinary Expertise.’ Association of Chemoreception Sciences 36th Annual Meeting, Bonita Springs, FL.
Byrnes, N., Nestrud, M., and Hayes, J. (2013). ‘Sorting and mapping of samples chemesthetic agents with naïve assessors.’ 10th Pangborn Sensory Science Symposium, Rio de Janeiro, Brazil.
Byrnes, N. and Hayes, J. (2012). ‘Personality Traits and the Liking of Spicy Meals: Mediator and Moderator Relationships.’ Society for Sensory Professionals 3rd Biennial Meeting. Jersey City, NJ.
Byrnes, N., Allen, A., & Hayes, J. (2012). ‘Revisiting personality factors, capsaicin intensity, preference for spicy foods, and intake.’ Association of Chemoreception Sciences 34th Annual Meeting, Huntington Beach, CA.
