THE USE OF COVARIATION INFORMATION IN THE · Attribution of Emotion ..* Ill Kelley's (1967)...

THE USE OF COVARIATION INFORMATION IN THE

CAUSAL ATTRIBUTION OF OTHERS' EMOTION

Heidi L. Evre

B.Sc., Utah State Universitv, 1998

THESIS SUBkETED IN PARTML FULFILLMENT OF THE

REQUIREMENTS FOR THE DEGREE OF

MASTER OF ARTS

in the

Department of Psychology

O Heidi L. Eyre 2000

SIMON FUSER UNIVERSITY

April2000

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Attribution of Emotion ..* I l l

Kelley's (1967) covariation theory as operationalized by Orvis, Cunningham. and

Kelley (1975) is considered one of the prevailing models of causal attribution.

With one notable exception (hIcArthur, lY2) . no one has exarnined the

attribution of emotion within this framework. The present study extended the

findings of McArthur by having participants make causal attributions for four

emotions (anger, happiness, depression, and anxiety) embedded within an

interpersonal context. The sarnple consisted of 155 male and female native

English-speaking Canadian undergraduates. Results supported Orvis et al.3

(1975) predictions for the person and stimulus attributions. There was less

support for the circumstance attributions, and the least amount uf support was

found for the person x stimulus attribution. Discussion focused on design and

analysis limitations, applications of the current study to other realms in emotion,

and the need for a more extensive examination of: other emotions.

Attribution of Emo tion

DEDICATION

1 would like to dedicate rny thesis to my closest friends and family: Katlin, Mom,

Dad, Tamara, kcky , Jeni fer, and Alana. Without their ceaseless support,

devotion, and love I would not have been able to accomplish this considerable

task. I camot thank them enough for being there for me.

Attribution of Emo tion v

ACKNOWLEDGEMENTS

I would like to thank Demis Krebs for being willing to take me on as a student

rnid-stream and Kim Bartholomew for being there by rny side through the

tvhole process. 1 would also like to thank Cathy McFarland and the members of

the social area seminar for their insighthl comments on mv thesis proposal. I

am grateful to Laura MacKav, Tina Niwinska, and Chris Newitt for their help

collecting data. Finally, I would like to thank Tamara Ferguson for her insightful

comments on a drait of my thesis.

Attribution of Emotion

TABLE OF CONTENTS

................................................................................................................. introduction 1

.......................................................................... Ovenriew of the Present $tudy 5

Hypotheses ........................................................................................................... 7

......................................................................................................................... Method 9

............................................................................................................ Participants 9

.............................................................................................................. Procedure 10

Results ....................................................................................................................... 11

Data Analyses ....................................................................................................... 11

.............................................................................................. Person Attributions 13

........................................................................................... Stimulus Attributions 13

................................................................................. Circumstance X ttributions 14

.......................................................................... Person + Stimulus Attributions 15

.................................................................................................................... Discussion 16

............................................................................................. Summary of Results 16

..................................................................... Limitations and Future Directions 19

.................................... Appendix A Causal Attribution Questionnaire - Form 1 24

Appendiu B Lndividual Emotion Results Tables .................................................... 29

.................................................................................................................... Re ferences 35


LIST OF TABLES

vii

Table 1 Mean Attribution Ratings for the Covariation hiormation . . 7 3 Conditions ................................................................................................... ,,

Table 2 Percentage of Person, Stimulus, Circumstance, and Person +

Stimulus Attributions Made by Participants When hsked to

......................................................................... Make a Single Attribution 23

Table 3 blean Attribution Ratings for the Four Emotions in Predicted

....................................... Covariation Information - Attribution Pairs 29

Table 4 ivlean Attribution Ratings by Covariation Pattern and Emotion

(Part 1). ........................................................................................................ .30

Table 5 Mean Attribution Ratings by Covariation Pattern and Emotion

.......................................................................................................... (Part 2) 31

Table 6 Percentage of the Person, Stimulus, Circumstance, and Person +

Stimulus Attributions Made by Participants When h k e d to

......................................... blake a Single Attribution for Eaîh Emotion 33

Attribution of Emo tion 1

The Use of Covariation information in the Causal

Attribution of Others' Emotion

How do ùbservers arrive at a causal attribution? That is, how do

individuals deçide ruhy a given event has occurred? According to Kellev (1967:

1973), individuals use the principle of covariation when they have access to

multiple instances oi the same or similar events. The principle is looselv based

on an analysis of variance mode1 containing three types of covariation

information: consensus, consistency, and distinctiveness. For example, let's say

John and Bill are in a bar, and John hits Bill. Kellev states that individuals use

covariation information to determine whether the event was caused by

something about John (person), Bill (stimulus), the particular circumstance, or

some combination of the three. Three pieces oi information corne together to

inform this decision of "why." In the majoritv of studies, this information is

presented to subjects as either high or low (cf. PvlcArthur, 1972). One piece of

information that is taken into account is the distinctiveness of the behavior; that

is, how does the person (John) behave toward other stimuli (individuals hi the

bar) in this situation? John's behavior would be considered highly distinctive if

he only hit Bill and not other people. Another piece of information that may be

taken into account is consistencv (i.e., what happens to the behavior when the

same person and stimulus interact across time?). If John hits Bill every time they

go to the bar together, John's behavior would be highly consistent. The third is

consensus, that is, how do other people react to the stimulus? If Steve, Randy,

and Mark (others who frequent the same bar) also hit Bill, John's behavior would

be highly consensual (see Hansen & Donoghue, 1977; Wells & Harvey, 1977 for

discussions on the importance of consensus information).


Depending on the configuration of the covariation information,

attributions can be made to the person, the stimulus, the circumstance, or some

combination thereof (e.g., Hansen, 1980). Orvis, Cunningham, and Kelley (1975)

developed the template matching model of covariation which was based on

Kelley's covariation theory and, in part, on the attributional patterns described

by McArthur (1972). Although several attribution researchers have made

modifications to Omis et al.'s model, the predictions do not radically diverge for

the patterns under study in the present thesis (cf. Forsterling, 1989; Hilton, Smith,

& Kim, 1995; Jaspars, 1983). The template matchhg model states that stimulus

attributions are made in the presence of high distinctiveness (the actor did riot

respond in tlus manner in response to other stimuli), high consistency (the actor

generallv responded to this stimulus in the same fashion across tirne/ modalities),

and high consensus (most people responded in the same fashion toward the

stimulus as the actor) information. A person attribution (often referred to as a

dispositional attribution) is made when one received low distinctiveness (the

actor responded in this m m e r in response to other stimuli), high consistency

(the actor generally responded to this stimulus in the same fashion across

time/modalities), and low consensus (others did not respond in the same manner

toward the stimuli as the person did) information is present. The other type of

attribution made is something about the circumstance, which is hallmarked by

low consistency information (i.e., it only happened this once) and is most clearly

seen in conjunction with high distinctiveness and low consensus information.

As mentioned above, the three types of information can also be combined

to form complex attributions such as person + stimulus, peson + circumstance,

stimulus + circumstance, and penon + stimulus + circumçtance. There has been

Little empirical support for the person + circumstance, stimulus + circumstance,

Attribution of Emotion 3

and person + stimulus + circumstance attributions as operationalized by Orvis

and colleagues (e.g., McArthur, 1972; Orvis et al., 1975). Participants who were

presented covariation information hvpothesized to correspond to these complex

attributions tended to make main effect attributions (i.e., person, stimulus, or

circumstance) instead cf the cornplex attributioil predicted. The cne corn plex

attribution which participants did make is the person + stimulus attribution (e.g.,

in Orvis et al., 1975, participants made the predicted person + stimulus attribution

56% of the time). The information pattern in the template matching mode1

which corresponds to a person + stimulus attribution is low distinctiveness, high

consistencv, and high consensus.

EvIcArthur (1972) conducted the first empirical test of Kelley's theory. She

postulated that the causal attribution made rnav be a function of both the type of

covariation information the participant is given and the verb category.' The verb

types that she investigated were emotions, opinions, accornplishments, and

actions. In her experimental design, McArthur provided participants with brief

scenarios depicting four ernotional events (e.g., "Paul is enthralled with the

painting," McArthur, 1972, p. 174). She then paired these four emotion scenarios,

plus four of each other verb type (opinions, accornplishments, and actions), with

the eight differing covariation patterns that can be created bv combining

dis tinctiveness (high/low), consistency (high/low), and consensus (high/ low)

Although McArthur explicitlv labels her emotion words as verbs, they are

actually adjectives (e.g., "Sue is nfinid of the dog."). For purposes of continuity,

the term "verb" will continue to be used in reference to McArthurts study.

However, when explaining the design of the current study, the correct term

"adjective" will be used.


information. In short, every participant completed a 16-item questionnaire

which contained each of the 16 verbs being investigated paired with one of the

eight covariation information patterns. The attributions the participants made

were measured using a multiple choice format. That is, participants could select

rvhether it was (a) something about the person, (b) something about the

stimulus, (c) something about the particular circumstances, or (d) some

combination of a, b, and c (and they were asked to specify the combination).

McArthur found that across verb type, the highest proportion of stimulus

attributions were made in the high distinctiveness, high consistency, and high

consensus condition. The greatest proportion of person attributions were made

in the low distinctiveness, high consistencv, and low consensus condition. The

majoritv of the circumstance attributions were made when there was low

consis tency. However, the high dis tinc tiveness, low consistency, and low

consensus condition showed the greatest number of circumstance attributions

ovemll. Finallv, two separate conditions showed high person + stimulus

attributions. These were the low distinctiveness, high consistency, and high

consensus condition and the high dis tinctiveness, high consis t enq , and low

consensus condition. The first of these two patterns is what was predicted by

Omis and colleagues (1975) and this pattern produced a significantly higher

proportion than the second pattern (P = .35 vs. P = 23, p < .01). In short, the

results were in line with Orvis et ale's template matching predictions.

As for her results with emotion verbs, she found that person and person +

stimulus attributions were made the least often to emotion verbs as compared

with other verbs. On the other hand, stimulus and circumstance attributions

were made the most often in conjunction with emotion verbs.


Qverview of the Present Studv

The primary goals of the present studv were to examine two questions

regarding the application of covariation theory to the causal attribution of

rmotion: (a) Within ernotion scenarios, do participants rate the predicted

attributions significantly higher than the non-predicted attributions? (b) When

participants are given a multiple choice format and told to pick the single best

causal attribution, do they choose the predicted attributions significantly more

often than the non-predicted attributions? A third question, which was

exploratory in nature, was also addressed: (c) Do the results found in (a) and (b)

hoid true for each individual emotion?

Although Mcilrthur began the investigation into causal attribution of

emotion, she left many questions unanswered. First, McArthur only examined

four of the myriad possible ernotions.' She also relied on a single dependent

variable - picking îhe single best causal attribution. Third, she used asocial

scenarios which may not be the most appropriate format for emotional events.

She also presented the covariation information in an order which led participants

to under-utilize consensus information (Kassin, 1979; Ruble & Feldman, 1976).

These issues were addressed in the current study.

The emotions used in this study were anger, anxiety, happiness, and

depression. These emotions were chosen because they are represented within

many models of "prototypical" or "basic" emotions (Averill, 1994; Ekrnan, 1994;

Hupka, Lenton, & Hutchinson, 1999; Russell, 1997; Russell & Barrett, 1999;

Scherer, 1994; Shweder, 1994). Depression was chosen instead of sadness

' McArthur (1972) only named two of the four emotions she analyzed in her

study; they were enthrallment m d fear.


because within Russell's (1997) circumplex model, it is located farther away from

anger and anxiety, thus allowing for a more broad coverage of the arousal

spectrum (i.e., anger and anxietv have a high degree of arousal whereas

depression has a low degree of arousal).

Recent attributional research hao also illustra ted the use fulness of

including continuous rating scales instead of simply relving on multiple choice

answers (e.p., Hilton, Smith, & Kim, 1995). Xlthough multiple choice ratings give

the most concise representation of an attributional outcome (e.g., it was the

stimulus), they do not make as fine-grained distinctions as do continuous rating

scales (e.g., Hewstone, 1983). Both types of scales were used in the present study

to give a more complete picture of the attributional process.

hlso as mentioned above, McArthur's scenarios were primarily asocial

(Hewstone & Jaspars, 1983). That is, they involved an interaction between a

person and an object (e.g., Paul is enthralled with the painting), rather than two

people (e.g., Paul is enthralled with Emily). Although Hewstone and Jaspars

(1983) found that there was no difference between social and asocial action verbs,

the results for emotions may be different because most emotions occur within

interpersonal contexts (cf. Parkinson, 1995,1996). Accuracy and coordination in

the decoding and communication of emotion is essential in the lacilitation of

interpersonal relationships. Emotions are often used to clarify the meaning and

intent of speech, to persuade, and to draw others ernotionally near (Parkinson,

1995). Thus, in the current study, emotion words were placed in the type of

interpersonal context in which they would be likely to occur.

There has been some dispute within the literature as to the importance of

consensus information (e.g., Kassin, 1979; McArthur, 1976). Even McArthur's

original results indicated that participants did not utilize consensus information

Attribution of Ernotion 7

as much as they did distinctiveness and consistency. However, Wells and

Harvey (1977) later pointed out that the statistical method McArthur used

(calculating the percentage of variance accounted for by each covariation piece)

was not sound and thus McArthurfs results would need to be replicated across

several studies before drawing the conclusion that con~ensus was utilized les .

Also, Ruble and Feldman (1976) demonstrated that when consensus information

is placed last, the elfect of consensus is actually strengthened. Their research

demonstrated that individuals make the predicted attribution most often when

information is presented in the following order: distinctiveness, consistency, and

consensus.

Hv DO theses

Al1 hvpotheses in this study for the various information patterns were

derived from Orvis, C u ~ i n g h a m , and Kelleyfs (1973) template matching mode1

and McArthurfs (1972) empirical results. The main hvpotheses are listed below.

Of secondary interest was the exploratory study of the individual emotion

results. No specific predictions were made for these, but the general pattern of

results are presented in brief.

Person Attributions

(1) Person attributions for the emotions expressed would be made to a

greater extent in the low distinctiveness, high consistency, and 10 w

consensus condition than in any of the other information conditions.

(2) Within the low distinctiveness, high consistency, and low consensus

information condition, ratings of person attributions would be

significantly higher than ratings of stimulus or circumstance

attributions.

At tribution of Emotion 8

(3) When participants are asked to pick the single best causal

attribution, person attributions would be made more frequently than

person, circumstance, or person + stimulus attributions within the low

distinctiveness, high consistency, and low consensus information

condition.

Stimulus Attributions

(1) Stimulus attributions for the emotions expressed would be made to

a greater extent in the high distinctiveness, high consistency, and high

consensus condition than in any of the other information conditions.

(2) Within the high distinctiveness, high consistency, and high

consensus information condition, ratings of stimulus attributions

rvould be significantlv higher than ratings of person or circumstance

attributions.


attribution, stimulus attributions would be made more frequently than

person, circumstance, or penon + stimulus attributions within the high

dis tinc tiveness, high consis tency, and high consensus information

condition.

Circumstance Attributions

(1) Circumstance attributions for the emotions expressed would be

made to a greater extent in the high distinctiveness, low consistency,

and low consensus condition than in any of the other information

conditions.

(2) Within the high distinctiveness, low consistencv, and low consensus

information condition, ratings of circumstance attributions would be

significantly higher than ratings of stimulus or circumstance


attributions.


attribution, circumstance attributions would be made more frequently

than person, stimulus, or person + stimuius attributions within the

high distinctiveness, loiv consistency, 2nd lorv consensus information

condition.

Person + Stimulus Attributions

(1) Since there was not a person + stimulus rating scale, it was not

appropriate to examine whether these attributions would be made to a

greater extent in the low distinctiveness, high consistencv, and high

consensus infonnation condition.

(2) W ithin the low distinctiveness, high consis tencv, and high

consensus information condition, ratings of person and stimulus

attributions would be significantlv higher than ratings of circurnstance

attributions.


attribution, penon + stimulus attributions would be made more

frequently than person, stimulus, or person + stimulus attributions

within the low distinctiveness, high consistency, and high consensus

information condition.

~Method

Partici~ants

Introductory psychology undergraduate students from Simon Fraser

University were recmited through the subject pool board (where students sign

up for research participation). Students were given course credit for their

participation. One hundred fifty-five native English speakers were culled from


an initial pool of 226 students. Native speakers were chosen for this study

because it involved interpreting subtle grammatical nuances that may not be

picked up by non-native speakers. Of these 153,94.8% had lived in Canada for

more than 10 vears. There were 51 males (32.9%) and 104 females (67.1%). The

age range rras 17 tu 46 vears with ri mem ripe of 70.3 Feus. European

Canadian students comprised 63.2% of the sample, Asian students 20.6%; 7.19'0

were East hdian and 8.49'0 were of other ethnic background.

Procedure

Participants were given one of four questionnaires to complete that began

with demographic information and instructions (see Appendix A for a copy of

Form 1 of the questionnaire). The four forms were based on a Latin square

design similar to that emploved bv McArthur. Kirk (1968) describes the

fractional factorial Latin square design as having three variables. Two are within

subjects and one is between. The first within subjects variable is the covariation

pattern, which has four levels (HHH, LHL, LHH, HLL). The second within

subjects variable is the emotion, which also has four levels ( h g e r , Anxiety,

Depression, and Happiness). The questionnaire form is the between subjects

variable; it is also four levels (Form 1, Form 2, Form 3, and Form 9.' The four

forms with their respective emotion-covariation information (Distinctiveness,

Consistency, and Consensus) painngs were as follows:

Form 1: HHH-Anger; LHL-Dep ression; LHH-Happiness; HLL-hxiety

Forrn 2: LHL-Happiness; HLL-Anger; HHH-Anxiety; LHH-Depression

Form 3: LHH-Anxiety; HHH-Depression; HLL-Happiness; LHL-Anger

' Because each f o m contained unique information, an analysis examining the

differences between forrns was not possible.


F o m 4: HLL-Dep ression; LM-Anger; LHL-h i e ty; HHH-Happiness

Participants were given short statements about an emotion-eliciting event.

These statements contained the three pieces of covariation information along

with pieces of contextual information, such as the re!atiomhip between the

person and stimulus and where they were or what they were doing when the

emo tion occurred.

After participants read the brief scenarios, they were asked to make three

scale ratings which assessed the extent to which the emotion was due to the

person, stimulus, and circumstance (e.g., "To what extent do you believe that

Shawna's happiness in this case was due to somrthing nbori t Mnry?") . Ratings

were made on a 9-point scale which were anchored by the terrns "not at all" and

"very much so." Finallv, participants were asked, "If vou had to choose orrr

reason why [the target] felt [the emotion] in this particular circumstance, is it due

to sornething about: (a) [the person], (b) [the stimulus], (c) [the particular

circumstances], or (d) both [the person and the stimulus].

Resul ts

Da ta Analvse~

Because of the complexity of the Latin square design, each of the analyses

used and the table that is associated with those particular results will be

delineated first. The first set of analyses were repeated-measure ANOVAs

comparing the mean ratings of peson, stimulus, and circurnstance attributions

made in each of the covariation information conditions. These analyses are

illustrated in the columns of Table 1 and were done to address the first set of

predictions made for each attribution, namely, whether a given attribution was

made significantly more often in the predicted covariation information condition


than the other three information conditions (the predicted results in al1 of the

tables are italicized). Although the majority of the predictions in this study were

made a priori, pairwise comparisons were made using posthoc tests as a more

conservative estimate of the effects (Tukey's HSD for the between-subjects

analyses and pairwise repeated-measu res analyses for the tvi thin-subjects

analyses).

The second set of analvses, outlined in the roivs oi Table 1, were also

within-subjects ANOVAs designed to test whether there were significant

differences in the mean ratings of person, stimulus, and circumstance attributions

made within each of the covariation patterns (the second set oi predictions made

for each attribution).

Table 2 contains the results of the third set of analvses which were

conducted on the multiple-choice ratings made by participants (the third set of

predictions made for each attribution). Chi-square analyses were used to test

whether a' higher proportion oi person, stimulus, circumstance, or person +

stimulus attributions were made in each of the four information conditions.

Because the results for the individual ernotions were exploratory in nature

and not of primary interest in this thesis, the tables associated with them are

listed in Appendix B. Table 3 contains the predicted covariation - attribution

pairs and addresses the issue of whether the mean attribution rating for the

expected covariation pattern - attribution pair is sigruficantiy higher or lower

for any one of the four emotions examined. That is, it indicates whether the

results presented across emotions hold true for the individual emotions. Table 4

is the complement to Table 1 columns and it contains between-subjects ANOVAS

for eadi ernotion - attribution pair (as mentioned above, the post-hoc

comparisons were done using Tukeyts HSD test). Table 6 is the complement to

Attribution of Ernotion

the rows of Table 1 nnd contains repeated-measures analyses; Table 7 i s the

complement to Table 2.

Person Attributions

Based on Kelley's theorv and McArthurf s results, it was predicted that

peson attributions for emotions would be made most strcngly in the low

distinctiveness, high consistency, and low consensus condition when compared

to the three other information patterns. The first column of Table 1 illustrates

that, collapsed across the four emotions, person attributions were made the most

strongly in the LHL information pattern, as predicted, F (3,462) = 46.97, p c .001.

Within the LHL information pattern, respondents rated the person attribution

significantly higher than the stimulus or circumstance attribution, F (2,308) =

82.77, p < .O01 (see the first row of Table 1 for the rneans and standard

deviations). As illustrated in the fi rst row of Table 2, when respondents were

asked to select the single best causal attribution in the LHL information

condition~significantly more of hem made person attributions than stimulus,

circumstance, or person + stimulus attributions (55.48'30 vs. 9.0396, 20.6s0/0,

14.849/0, respectively).

As mentioned above, the analyses conducted on each of the emotions

were exploratory in nature and thus only the general pattern of results will be

delineated here. The tables associated with each of these analyses are listed in

Appendix B. First, for the LHL information condition, there were no significant

differences in the ascription of person attributions among the four emotions, F

(3,151) = 1.55, p > .O5 (see Table 3). As seen in Tables 4 through 6, the findings

denoted above held mie when each emotion was examined separately.

Stimulus Attributions

[t was also predicted that stimulus attributions would be made to a


greater degree in the high distinctiveness, high consistency, and high consensus

condition than in the three other information patterns. Stimulus attributions,

collapsed across emotions, were made to a greater extent in the HHH

information condition, F (3, -162) = 61.38, p < .O01 (see the second column of Table

1 for the means and standard deviations). The second row of Table 1 shows b a t

within the HHH information condition, individuals rated the stimulus attribution

significantly higher than person or circurnstance attributions, F (2, 308) = 82.72, p

c .001. As illustrated in Table 2, participants who were asked to pick the single

best causal attribution in the HHH information condition made stimulus

attributions more often than person, circurnstance, or person + stimulus

attributions (63.23% vs. 8.39%, 13.48%, and 12.90%, respec tively).

M e n examining the results for the individual emotions, it is clear that

depression was significantly less likely to elicit a stimulus attribution in the HHH

information pattern as compared with the other three emotions, F (3, 151) = 3.63,

p < .O5 (see Table 3). When examining Tables 4 and 5, we see that stimulus

ratings in the HHH information condition were consistently higher than any of

the other attributions, even though this difference was not always statistically

signifiant in the post-hoc analyses. Finally, as demonstrated in Table 6, stimulus

attributions were made significantlv more often in the HHH information

condition across the four emotions.

Circumstance Attributions

It was predicted that circumstance attributions would be made to the

greatest extent in the high distinctiveness, low consistency, and low consensus

condition. The third column of Table I illustrates that when the results are

collapsed across emotions, circumstance attributions were made to a greater

degree in the HLL information condition, F (3,462) = 11.38, p c .001. However,


within the HLL condition, there was no difference between the person, stimulus,

person + stimulus, and circumstance means, F (2,308) = 1.65, p > .O5 (see the third

row of Table 1). When participants were asked to pick the single best causal

attribution in the HLL information condition, they made circumstance

attributions significantly more often than person, stimulus, or person 4 ~timului

attributions (45.81% vs. 19.35%, 26.45%, and 8.39%, respectively; see Table 2).

The results with the individual ernotions are slightly more mixed. As

demonstrated in Table 3, circumstance attributions were made to a lesser extent

in the depression scenarios and slightly more often in the happiness scenarios,

al though these ratings are not significantly different from the anviety and anger

ratings, F (3,151) = 3.27, p < .05. Tables 4 and 5 indicate the results for happiness

support the predictions. The results for anger and anviety are less strong, in that

the results are in the general direction predicted, although they are not

statistically significant. The emo tion of depression does no t support the

predictions at all.

Person + Stimulus Attributions

It was hypothesized that LHH mformation would give rise to person +

stimulus attributions. Since this study did not contain a person + stimulus rating

scale, it was not appropriate to compare whether peeon + stimulus attributions

were made to a greater degree in the LHH information condition (results which

had been presented in the columns of Table 1). However, when the rows of

Table 1 are examined, it is evident that when individuals were given LHH

information, they did not make significantly higher person and stimulus

attributions, F (2,308) = 1.75, p > .05. When participants were asked to make the

single best causal attribution in the LHH information condition, they did not pick

the person + stimulus attribution significantly more often than the other three


attributions (see Table 2). The proportion of person, stimulus, circums tance, and

person + stimulus attributions were nearlv equal across the four categories

(26.459/0,25.16%, 25.169'0, and 23.23%, respectively).

As to the issue of whether there is a difference in the degree to which

person and stimulus attributions are made for the four emotions, significantly

lower stimulus attributions were made to the emotion of depression than to the

other three emotions, F (3,151) = 16.47, p < .O01 (see Table 3). Also, significantly

lower person attributions were made to anger and anxiety than to depression or

happiness, F (3, 151) = 8.31, p < .001. When examining Table 5, it is apparent that

happiness is the only emotion which conforms to the expected pattern of

attributions (i.e., person and stimulus ratings were significantly higher than

circumstance ratings). Finally, as evident in Table 6, the person + stimulus

attribution was not chosen more ot'ten than anv of the other attributions,

regardless of emotion.

Discussion

Summarv of Resulrs

In sum, participants generally made the predicted attribution for the LHL

condition (person attribution) and for the HHH condition (stimulus attribution).

In tems of the HLL condition (circumstance attribution), the results were more

mixed. When participants had to choose the single best causal attribution in the

HLL condition, they usuallv chose the circumstance attribution. However, the

scale rating results were not as supportive as the discrete causal attribution

results. Finally, the results for the LHH condition did not generally support

Orvis et al.3 template matching model. That is, participants did not generally

choose the person + stimulus attribution in the LHH condition. The scale ratings

were only partially supportive, at best. Research within Kelley's paradigm has


typically shown mixed support, and the presen t resul ts do generaily replicate

other findings (see Forsterling, 1989 for a current review). That is, there was

strong support for the person and stimulus attributions, less support for the

circumstance attributions, and the least amount of support for the combined

attributions (Le., Ferson + stimulus).

Thus, it appears that individuals do, in some cases, use Kelley's covariation

principle effectivelv for the attribution of emotion. hdividuals in this study were

consistent in using the principle for determinhg person and stimulus

attributions. Participants were less consistent in arriving a t the predicted

circums tance

the predicted

information.

attribution in the case of HLL information and they rarely niade

person + stimulus attribution when presented with LHH

Further study is warranted to narrow down whether the

covariation information patterns are incorrect in the case of circumstance and

person + stimulus attributions or whether it is the application of these patterns to

the realm 'of emotions which are producing the contradictory attributions.

To briefly address the latter of these two possible explanations, 1 will

summarize the exploratorv emotion results. It appears that the emotion of

happiness, the oniy positive emotion examined in this study, produced results

that were rnost consistent with Orvis and colleagues' predictions. For example,

even though the results for anxiety, anger, and depression did not show support

for the person + stimulus attribution predicted by the template matching mode1

in the L H H information condition, happiness did show marginal support for this

attribution. Participants' ra tings of happiness also consis tently showed the

clearest support for the person, stimulus, and circumstance attributions. Because

this study only contained one positive emotion, it is not clear whether this

attributional pattern is unique to happiness or is likely to occur with other


positive emotions. However, because emotion research has demonstrated that

individuals discriminate less between various positive emotional states (e.g.,

elation vs. jov) as compared to negative states (e.g., frustration vs. rage; Ekman

& Davidson, 1994)) 1 would predict that the pattern found with happiness would

generalize to other positive emo tions.

Results for depression, on the other hand, rarely conformed to Orvis et

al.3 predictions. For depression, significan tly less stimulus attributions were

made cvithin the corresponding information conditions. This pattern is also

apparent in other conditions, such as the LHH condition. In short, it appears that

there is a person bias (or dispositional bias) present in participants' rating the

emotion of depression. Most likely, this stems from the term used because

"depression" implies more of a long-lasting, global, interna1 state, rather than a

transitory emotion aroused by situational pressures.

The results for anxietv and anger were not consistent across the

attributional patterns. Ratings from these scenarios conformed to the predicted

results for the person and stimulus attributions, but were mixed for the more

complex circums tance and person + stimulus attributions. Further exploration

into these results is needed before one can speculate on the how these particular

emotions fit within this framework.

It is also important to note at this point that the rating scale results

typically showed that participants indica ted al1 three factors (person, stimulus,

and circurnstance) plaved a rok in the emotional situations. For example, al1 of

the means in Table 1 (excluding one) were over five, which was labeled as

"somewhat" due to the person, stimulus, or circumstance. So, although

participants did make the hvpothesized person and stimulus attributions to a

greater extent, they did not rule out the possibility that other factors (such as the


circumstance) may have been playing a role. in the case of the circumstance and

person + stimulus scenarios, participants did not single out a solitary cause, but

instead ratecl al1 three causes as equally likely. However, the rating scale results

for person and stimulus attributions did support the multiple choice results; the

only case in which the rating scale results did not match the multiple choice

results was in the case of circumstance attributions. Taking both of these results

into account, it appears that participants do have an idea about what the primarv

cause of a situation is, although they do not report the primary cause as the only

cause.

Limitations and Future Directions

One potential flaw with this studv is that the Latin square design does not

allow the studv of the interaction between the covariation information pattern

and the emotion. Although this design has been used yuite frequently in the

literature, it is cited in statistics textbooks as most usehl for exploratory studies

and studies in which one dors not expect to find an interaction (e.g., Kirk, 1968).

So, it would be prudent to study Kellev's theory within a fully crossed factorial

design. Nso, a person + stimulus rating scale would be wise to include in future

s tudies.

Another potential limitation of this study is that it lacks extemal validity.

As stated at the beginning of this thesis, I was testing whether individuals apply

Kelley's covariation principle to the attribution of emo tion. The next step to be

addressed is whether or not individuals actually do go through this process

when making attributions and what the limiting factors are. Although several

studies have been conducted to test Kelley's principle in more mundanely

realistic settings (cg., Ferguson, 1977; Ferguson & Wells, 1980; Major, 1980;

Smith & Miller, 1983), none has examined the causal attribution of emotion


within this framework. Given the present results, it appears that when you force

individuals into choosing only one cause, they do use the covariation process.

However, the rating scale results indicate the individuals actually make more

complex attributions and are often unwilling to rule out any causes. That is, it

appears that individuals sav. "It is most likelv x, but it could partlv be due to v

and 2." Participants also may be inferring traits or motivations that are not given

to them in the individual scenarios (e.g., hidden agendas, other personalitv traits,

etc.) Thus, there iç some evidence that for these type of emotion scenarios,

participants go through a more complex attributional process than the one

outlined by Kelley and colleagues.

Although no subjects indicated, either through written or verbal

comment, that thev did not understand the questionnaire, there is the possibility

that participants had a difficult tirne understanding the task or were not

rnotivated to focus their undivided attention on the task. Again, since the

majority of the results followed the hypotheses, it is unlikely that this was the

case for the majoritv of participants (or the results would have appeared more

random).

Also important to acknowledge is the confound between emotion and

scenario content. That is, it is difficult to generalize the results for the given

emotions since there was only one scenario per emotion. Future research should

include multiple scenarios for each emotion in order to better tap the emotional

experience.

Ferguson and Stegge (1998) also recently suggested that emotion should

be studied within the covariation framework. They emphasized the necessity of

this approach because the covariation information can be diagnostic of an

emotion's (ma1)adaptivity. That is, dispositional attributions may be indicative of


an individual's proclivity to experience a given emotion. For example, if Jocelyn

experiences guilt in the presence of many individuals, across multiple situations

over time, and no one else responds with guilt in these situations, one could

conclude the something about Jocelyn is driving these feelings of guilt. There are

manv studies which have used consistencv information to studv an emotion'ç

maladaptivitv, and Ferguson, Stegge, Evre, Vollmer, and Ashbaker (in press)

recently demonstrated a high correlation between children who respond with

guilt in low consensus situations (as opposed io high consensus situations) and

intemalizing symptoms. The current study shows that individuals do use al1

three pieces of covariation information when making attributions and thus

future research should address Ferguson and Stegge's hypothesis that al1 three

pieces of information can be used to assess an emotion's rnaladaptivity.

in sum, it appears that when individuals are given consensus, consistency,

and distinctiveness information in the manner prescribed by Kelley, they do

make sorne of the causal attributions in the direction he predicted. It is

interesting to h d thnt Kelley's predictions hold even w hen considering

emotional States. Future research should examine this process in more depth

and see where people's implicit stereotypes about emotion (e.g., gender-related

stereotypes of ernotion) and logical attribution models, such as Kelley's, diverge.

Subsequent studies done on emotion should also more thoroughly test Kelley's

mode1 against other covariation models (e.g., Jaspars, 1983; Forsterling, 1989).


Table 1,

Mean Attribution Ratings Made for the Covariation Information Conditions

kz!!l Stimulus Pattern Circums tance F-value

LHL 7.0Se (1.941 4.05d (2.41) 5.2Ia (2.20) 69.61"'

H H H 4.4lC (2.17) 7.36e (1.78) S.IOa (2.17) 32.72"'

HLL 5.30ab (2.23) 5.97b (2.31) 6.36b (2.24) 2.65

LHH 6.05tz (3.47) 5.67a (2.40) 5.52a (2.23) 1.75

Predicted Attributions for rach of the Distinctiveness, Consistencv. and Consensus Information

h t t ~ r n s : LHL - Person; HHH - Stimulus; MLL - Circumstance; LHH - Person + Stimulus

Note: F-vdues listed on the horizontal were computed on the columns; F-values listed on the

vertical were computed on the rorvs. Menns not sharkig a common subscript across a row or

column are signihcantly different. The scde range is 1 to 9 and high numbers indicate stronger

attributions.

' p < .OS; *' p < .Ol; "'p < .O01


Table 2.

Percentage of Person, Stimulus, Circumstance, and Person + Stimulus

Attributions Made by Participants When Asked to Make a Single Attribution

Pattern P e m n Stimulus Circumstance Person .e Stimulus Chi Sq.

LHL 53.48 9.03 20.65 14.84 31 .QOM'

HHH 8.39 63.23 15.48 12.90 122.39"*

HLL 19.35 26.45 45.81 8.39 46.06***

LHH 26.45 25.16 25.16 23.23 0.33


Causal Attribution Questionnaire - Form 1

Your age:

~ o u r srx: laie ~ e r n d c

Plrase place a " 1 " ncxt to the erhnic group you idrntify with the most. If you identify with more thnn one p u p . rrink order the remainint groups you identify with.

hsian Europenn Cyiadiui First Nations E:ist Indian C] Other

Please place an "x" in the box next to the religious group you affiliate with the mas[.

Hindu Catholic Protestant [7 bluslim 0 Buddhist

Mormon (LDS) Athrist No rrligious affiliation Other religion

How many yevs have you l i v d in Canada? 0 less thon 1 0 1-5 5 - 10 more thnn 10

1s English your tirsr language? 0 Ycs [7

if English is POT your first language: How good is your çornmand of rhe Engiish Ianguage'? 0 Excellent G d Fair Poor

Your religion and ethnic group are being ask for gnly to make sure we accurately characterize the people piirticipating in the study.

This questionnaire contnins 3 numbcr of smtements which report the occumnce of somr emotion (which is

undrrlinrd). FoIlowing rach statrmrnr you will îïnd three items of infarmntion, a11 of which ripply to the

emotion reponcd. Your task is to decide, on the bûsis of the informacion given. whor probably caussd the

emotion to occur. You will be ctskrd to nte the extent to which you think the srnotion was criusrd by three

possible causes. Please circlr a number on the ratine scale (Irom 1 io 9). After rhat. you will be sked to

pick the mosr probable cause by çhoosing monp four alternatives. You can indicnte your choice by . .

çircling the lette[ next to the cause which you think is most probable.

Plrase give me your best estimate, but don't spcnd toa long on any one question. Xlso. once you have

completed a page. continue on to the next page and do nor go back to liny previous pages.

Thank you t'or your participation!


Katie and Emily are in the süme chemistry lab. One day, while talking with Emily during Inb, Katie becomes nnwv. You know that on that day Katie only felt angry around Emily and not around other Iab members; in the past when Katie and Emily have been in Iab together, Kntie has almost always felt angry around Emily; and 311 of the peopie in iüb feit angry when taiking with Ernily.

To what extent do you believe thrit Katic's anger in this case W;ZS due to 50rnemsz rrhaur K&'?

1 3 3 4 5 6 7 8 Y not at ri11 sornewhat vrry rnuch so

To whrit extent do you bclieve thrit Kritie's mger in bis case was due to somethirg about Fmily?

1 7 3 4 5 6 7 8 Y

not rit d l sornewhrit ver? much so

Ti, w h r i r extent do y o u btrlieve thrit Karie's ringer in this case was due to s ~ m e t h i n g about & paniculrir circurnst~ncr$?

1 - 7 3 4 5 6 7 8 Y not rit ; i I I somrw h a very rnuch so

If you had to choose one reuon why Kritie got ringry in this prinicular instance, is it due to somr thing about:

(3) Katitt

(b) Emily

(c) the puciculru circumstrinces

(d) both Kritie and Emily


A group of students, including Danielle and Kara, often study together. One day when Danielle and Kara are studying together, Danielle becomes de~ressed. You know that on that day Danielle also felt depressed rround al1 of the other members of the group; when they have studied together in the past, Danielle has almost dways felt depressed; and none of the other students who studied with Kara on that day felt depressed.

To whrit extent do you believe that Danielle's drpression in this case wris due to somethinv about Dmir llc'?

1 3 3 4 5 6 7 8 Y not rit dl some what very much 50

To whrit extent do you believe thrit Danielle's depression in this case w3s dur to something about &gg!

1 2 3 4 5 6 7 8 Y not iit 1\11 somewhrit very much 50

To whrit extrnt do you believr thrit Danielle's depression in this sase wris due to somrthing about the niirticulrir -;ince$?

1 t 3 4 5 6 7 8 9 not ; ~ t 311 somew hrit very much so

If you hrid to choose terison why Danidle felt depressed in this particulu instance, is it dur tn something about:

(a) Danielle

(b)

(c) the particulsu circumstrinces

(d) bah Danielle and Krin


Shawna and Mary are friends and one time when Shawna and Mary are talking, Shawna becomes hnogy. You know that on that d r y Shawna also felt happy around al1 of her other friends; in the past, Shawna has almost alwnys felt happy around Mary; and d l of their other friends felt happy around Mary on that day.

1 . To whi t extent do you believe thrit Shawnri's hrippinrss in this case wris due io scirnething ribout Shriwn;i9?

1 9 3 4 5 6 7 8 Y not rit rill some w hat very much so

2. T o whrit extent do you believe thtit Shawnri's happiness in this case wris due to somethinr about 31 3p '?

1 i 3 4 5 6 7 8 Y not rit dl sornew hrit very much 5 0

3 . To whrit extent do you belirve thrit Shriwnri's hrippiness i n rhis case was due to something about fie osiniçulrir circurnstance$?

i i 3 4 S 6 7 8 Y not rit 311 some w h3t vcrry much so

4. If you had ro choose reason why Shriwna felr happy in this puticular instance, is it dur to somrthing about:

(a) Shriwna

(b) Mvlan,

(c) the particulv circumstruices

(d) both S hawnû and Mary


One day when Erica and Linda they are hanging out together, Erica becomes anxious. You knuw that on thit day Erica only fek anxious around Linda and not around any of her other friends; when Linda and Ericû have hung out together in the past, Erice never felt ûnxious; and on that day none of their other friends felt anxious around Linda.

To what extent do you believe that Erics's rinxiety in this case w u due to sornerhi~u about F r k ?

1 - 7 3 J 5 6 7 8 Y not at riIl somewhctt very much so

To whst extent do you believe t h a Ericri's rinxiety in this m e was due to ~omethinyabout I inda'!

1 a 7 3 4 5 6 7 8 9 not at di some w hst very rnuch so

To what extent do you belirvt: thrit Erica's anxiety in this case wris due to sornething about p;iniculnr c=trcumsr;uices?

1 a 7 3 4 5 6 7 8 9 not rit d I somewhat very rnuch so

if p u had to choose q~lf reaon why Ericri felt anxious in this particular instance. is i t due to somrrthing about:

a ) Erica

(b j Linda

(c) the pmicular circumstances

(d) both Ericri and Linda


APPENDE B

Individual Emotion Results Tables

Table 3.

Mean Attribution Ra tings for the Four Emotions in Predicted Covariation

Information - Attribution Pairs

4kkm î-mW ,Anxiety Depression Happiness F-va lu%

LHL. Person

HHH

S timulus

HLL

circurnstance 6.46ae (1.99) 6.59,b (2.45) 5.43a (2.44) 6.97b (1.70)

LHtI Person 5.30a (2.80) 4.Wa (2.15) 7.18t, (2.25) 6.Sb (2.06) 8.31"'

S tirnulus 6.63a (2.28) 6.1da (1.71) 3.64b (2.41) 6.3& (1.96) 16.47"*

. . . . . fornation Predicted At~but ions tor each of the Distinctiveness. Consistent nsensus in

-: LHL - Person; HHH - Stimulus; HLL - Circmtance; LHH - Person + Stimulus

Note: Menns with different subscripts across the row indicate sigruficant ciifferences

p < .Os; ** p c .01; ***p c ,001

Attribution of Emotim 30

Table 4.

Pvlean Attribution Ratings by Covariation Pattern and Emotion (Part 1)

Pattern

Person

Anger

Xnxiety

Dep ression

Happiness

skuudlu

h g e r

Xnxie ty

Depression

Happiness

Circumstance

h g e r

Anxie ty

De pression

Ha p p iness

LHL

7.001, (1.75)

6,771, (3.38)

7.59b (1.93)

6.85b (1.73)

4.89b (2.28)

4.97b (2.40)

1.98b (1.23)

4.74b (2.17)

5.27,b (2.04)

4.43a (1.99)

5.3& (2.44)

5.7Aa (2.15)

HHH

4.2Sa (1.98)

4.6Aa (2.70)

4.30a (1.93)

4.40a (2.06)

7.5ja (2.23)

7.67u (1.66)

6 . S L 3 (2.21)

7.63,1 (1.78)

4.98a (2.33)

4+03a (2.17)

5.9Za (1.83)

5.60a (1.80)

HLL -

5 . Z a (2.53)

6.3Zabc (2.39)

6,0OC (1.78)

5.9/b (2.04)

6.2Ic (2.41)

5.6Sb (2.50)

6.1& (2.14)

5.83bc (3.10)

6.64b (2.06)

6.391, (2.45)

5.43a (2.44)

6.97b (1.70)

LHH

5.20a (3.83)

4.94, (2.15)

7.18bc (2.35)

6.64b (2.06)

6.63aC (2.38)

6.Ub (1.71)

3.& (2.41)

6.3& (1.96)

4.57a (2.15)

5.92b (1.99)

5.9Sa (2.55)

5.57a (3.02)

Predicted Attributions for each of the Distinctiveness. Consistency, and Consensus Information

Patterns: LHL - Person; HHH - Stimulus; HLL - Circumstance; LKH - Person + Stimulus

Note: Means with different subscripts across the row indicate significant differences;

* p c -05; " p. c .01; "'p c .O01


Table 5 .

Mean Attribution Ratings by Covariation Pattern and Emotion (Part 2 )

Pattern DE

LHI,

Anger (1,361

Anxiety (1,34)

Depression (1,431

Happiness (1,3S)

HHH

Anger ( U 3 )

Anxiety (1,38)

Depression (1,36)

Happiness (1,34)

Hu h g e r (1,381

h x i e ty (1,43)

Depression (1,34)

Happiness (1,35)

LHH h g e r ( 1,341

Anxiety (1,35)

Depression (1.38)

Happiness (1,431

(Table 5. Continues)


Table 5. Continued

. . . . . - . predicted c\ttributions for ,aa~h of the ~ ) ~ ~ t s

F a t t a : LHL - Person; HHH - Stimulus; HLL - Circumstance; LHH - Person i Stimulus

O : Means with different subscripts across the row indicate signiiicmt differences

* p c .OS; " p c .al; "'p c .O01


Table 6.

Percentage of the Person, Stimulus, Circumstance, and Person + Stimulus

Attributions Made bv Participants When Asked to Make a Single Attribution for

Each Emotion

I2ul!xn x w

h g er (37)

Anxiety (35)

Depression (44)

Happiness (39)

HHH

.Lnger WU

.Anxiety ( 39 )

Depression (37)

Happiness (35)

HLL

&ger (39)

Anxiety (44)

De pression (35)

Happiness (36)

LHH

Anger (35)

Anxiety (37)

Depression (39)

Happiness (44)

Stimulus

18.92

17.14

0.00

2.56

56.82

71.79

36.76

68.57

35.90

25.00

20.00

25.00

54.29

24.32

5.13

20.45

Circ- Ferson + S t i m b Chi Sq.

(Table 6. Continues)


Table 6. Continued


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