ORIGINAL ARTICLE

Using Cognitive Bias Modification to Deflate Responsibilityin Compulsive Checkers

Jessica R. Grisham • Lauren Becker •

Alishia D. Williams • Alexis E. Whitton •

Steve R. Makkar

� Springer Science+Business Media New York 2014

Abstract Cognitive-behavioural models of compulsive

checking posit a dominant role for beliefs regarding one’s

responsibility to prevent harm. In the current study we

employed a computerised cognitive bias modification of

interpretation (CBM-I) paradigm to target and modify

responsibility biases in a sample of undergraduate students

with high levels of checking symptoms (N = 100). Par-

ticipants were randomly assigned to either a positive

(decrease responsibility bias) or negative (increase

responsibility bias) CBM-I training condition. Relative to

participants in the negative training condition, participants

in the positive training condition demonstrated reduced

responsibility bias in a subsequent interpretive bias test.

Positive training also resulted in more adaptive physio-

logical responding during a responsibility stressor task.

There were no differential effects of CBM-I training,

however, on observed or self-reported checking or self-

reported responsibility beliefs. In light of these mixed

findings, we outline future avenues for improving the

efficacy of CBM-I training targeting responsibility biases.

Keywords Obsessive–compulsive disorder � Cognitive

bias modification � Responsibility � Checking

Introduction

Cognitive-behavioural theories of obsessive–compulsive

disorder (OCD) emphasise the importance of dysfunctional

beliefs in the formation and maintenance of obsessions

(e.g., Arntz et al. 2007). According to this framework,

intrusive thoughts are experienced by most people, but

develop into obsessions when they are appraised as posing

a threat for which the individual is personally responsible

(Rachman 1997; Salkovskis 1996). Over the past two

decades, correlational evidence has provided support for

the hypothesised association between inflated responsibil-

ity beliefs and OCD symptoms. Individuals with OCD tend

to score higher on measures of responsibility relative to

both non-anxious control participants (e.g., Foa et al. 2001;

Freeston et al. 1993) and anxious individuals (Foa et al.

2001; Salkovskis et al. 2000).

Checking is the most commonly reported OCD symptom

in both community (Fullana et al. 2009) and clinical samples

(Samuels et al. 2006). Prototypical examples include

checking to ensure that doors are locked, checking that gas

taps or electrical appliances are turned off, and checking that

cigarettes and matches are properly extinguished (Rachman

2002). Although inflated responsibility was originally

hypothesised to underlie all types of OCD symptomology,

there is evidence that maladaptive responsibility appraisals

may be more closely linked to checking than to other com-

pulsions. In a study investigating the intensity of perceptions

of responsibility in individuals with OCD, patients with

checking compulsions felt more personally responsible and

had greater urges to rectify hypothetical scenarios where

These data were presented at the World Congress for Behavioural

Therapies in Lima, Peru in July 2013.

J. R. Grisham (&) � L. Becker � A. E. Whitton

School of Psychology, University of New South Wales, Sydney,

NSW 2052, Australia

e-mail: jessicag@unsw.edu.au

A. D. Williams

The Clinical Research Unit for Anxiety and Depression, School

of Psychiatry, University of New South Wales, Sydney, NSW,

Australia

S. R. Makkar

The Sax Institute, Sydney, NSW, Australia

123

Cogn Ther Res

DOI 10.1007/s10608-014-9621-0

there was a potential for harm than non-checking OCD

patients (Foa et al. 2002).

Several experiments have examined the causal role of

responsibility in checking behaviour by experimentally

manipulating responsibility among participants. Perceptions

of responsibility can be manipulated using manual classifi-

cation tasks in which the participant is led to believe that any

error on their part could potentially result in harm coming to

others. Using a variation of this task in which participants were

required to sort pills according to colour, participants induced

to feel responsible engaged in more checking behaviours and

hesitations, experienced more anxiety and reported more

preoccupation with errors than those who were not made to

feel responsible (Ladouceur et al. 1995). This association

between responsibility and checking has been replicated in

several studies with non-clinical samples (e.g., Bouchard et al.

1999; Ladouceur et al. 1997; Mancini et al. 2004).

Beliefs reflecting an inflated sense of responsibility may

act as a type of cognitive bias. Cognitive biases involve

preferentially processing threatening information, via

either increased allocation of attention (attentional bias) or

rapid assignment of threatening appraisals to ambiguous

information (interpretive bias). In the context of inflated

responsibility beliefs, cognitive biases may involve the

tendency to interpret ambiguous situations as containing

the potential for harm that one has a responsibility to

prevent. For example, an individual with a responsibility

bias may encounter a tangled electric cord and interpret

this situation as one in which she is responsible for pre-

venting a fire. There is evidence to suggest that such biases

are not completely automatic or fixed, but may be modified

by repeated practice in rehearsing more adaptive interpre-

tations of ambiguity (Mathews 2012).

Recent advances in the development of implicit meth-

ods, such as cognitive bias modification (CBM), have

allowed us to target attentional processes (CBM-A) or

interpretive biases (CBM-I). Although the efficacy of

CBM-I as a method of training healthier interpretations has

been relatively well established in several anxiety disorders

(Amir et al. 2009; Bowler et al. 2012; Brosan et al. 2011),

few researchers have applied this paradigm to the treatment

and investigation of OCD. One notable exception is Cler-

kin and Teachman (2011), who provided preliminary evi-

dence that interpretive biases may be effectively modified

via CBM-I training among undergraduate students high in

obsessive–compulsive (OC) symptoms. Participants read

textual descriptions of OC-relevant situations in which

completion of a final word fragment disambiguated sce-

narios in a manner consistent with either a negatively-

biased interpretation or a more benign interpretation.

Results indicated that participants who were trained to

interpret ambiguity in a benign manner later endorsed

fewer negative interpretations of novel ambiguous

scenarios. Critically, these effects extended to subjective

OC experiences, as participants in the positive training

condition reported (at trend level) fewer urges to engage in

neutralising acts in response to a stressor task after con-

trolling for baseline negative affect.

Although the findings were promising, Clerkin and Teach-

man’s (2011) study included a symptomatically heterogeneous

OC sample and targeted six different biases characteristic of the

OCD belief domains defined by the Obsessive–Compulsive

Cognitions Working Group (OCCWG 1997). In the absence of

multiple outcome measures, this lack of specificity is prob-

lematic because each of these belief domains have been shown

to influence various OCD symptom dimensions differently. For

example, whereas inflated responsibility appraisals signifi-

cantly predict OCD checking symptoms, the belief domain of

perfectionism is more strongly associated with the symmetry

subtype of OCD (Wheaton et al. 2010). Clerkin and Teach-

man’s (2011) heterogeneous CBM-I training program was

intended to ensure that all participants would have some of their

key obsessional biases modified; however, the effects of

training were difficult to quantify across participants as the

stressor task tapped only the ‘importance of thoughts’ belief

domain. The authors acknowledged the limits of employing a

general measure of emotional vulnerability and behaviour

change and recommended that future studies restrict CBM-I

training to the modification of one or two specific biases,

depending on the person’s idiographic symptom profile

(Clerkin and Teachman 2011). Consistent with this recom-

mendation, Yiend et al. (2011) used CBM-I to specifically

modify perfectionism biases, although this experiment was

conducted with unselected healthy volunteers.

Two recent studies have further extended Clerkin and

Teachman’s work by using CBM-I to target multiple OC

belief domains (Beadel et al. 2014; Williams and Grisham

2013). Both studies included three behavioural tasks to

assess changes in OC belief domains, although only Beadel

et al. (2014) included a behavioural task for responsibility

beliefs. In this task, Beadel and colleagues examined both

overestimation of threat and inflated responsibility by asking

participants to touch a ‘‘contaminated’’ pen and clean it for

the next participant. In contrast, the current study attempted

to use a behavioural stressor test for responsibility that would

not be influenced by participants’ concurrent contamination

concerns. Further, although the findings of Beadel et al.

(2014) and Williams and Grisham (2013) were promising

with respect to beliefs and interpretative bias, both found

limited or no impact of CBM-I training on behavioural tasks.

One possibility is that because both studies used CBM-I to

target multiple belief domains simultaneously, the effect of

the training on behaviour was somewhat diluted. In the

current study, we attempted to amplify the effect of CBM-I

training on inflated responsibility by targeting only this

specific OC belief domain.

Cogn Ther Res

123

Thus, in the current study, we used a single session of

positive or negative CBM-I training to manipulate

responsibility bias, then examined the effects of CBM-I

training on responsibility interpretation bias, checking

symptoms and responsibility beliefs. We also assessed

behavioural and physiological responses to a responsibil-

ity-relevant stressor in which participants ostensibly sorted

sweets to prevent an allergic response in a fictional future

participant. We measured checking behaviour during the

stressor task, as well as heart rate (HR) and heart rate

variability (HRV). HR was used as a physiological indi-

cator of levels of state anxiety during the stressor (Miu

et al. 2009), whereas HRV was included as a biomarker of

adaptive emotion regulation in response to the stressor

(Appelhans and Luecken 2006; Thayer and Lane 2000,

2009). Evolutionarily informed theories of HRV suggest

that high-frequency HRV facilitates effective responding to

socially and emotionally-relevant changes in the environ-

ment (Denson et al. 2011). Inclusion of behavioural and

physiological indices from the stressor task was critical in

order to rule out possible demand characteristics that may

influence self-report measures of beliefs and symptoms.

We made several key predictions regarding the impact of

positive and negative CBM-I training targeting responsibility.

First, we hypothesised that CBM-I training would alter the

interpretation of novel ambiguous material in a training-

congruent direction. Specifically, those in the positive con-

dition would interpret ambiguous information in a manner

consistent with a decreased sense of responsibility, whereas

those in the negative condition would interpret ambiguous

information in a way consistent with an increased sense of

responsibility. In accordance with prior research, we expected

these effects to occur independently of training-related

changes in mood and state anxiety. Second, we predicted that

participants in the positive training condition would report

decreased responsibility beliefs and compulsive checking

symptoms following training, whereas those in the negative

training condition would show increased responsibility

beliefs and checking symptoms. Third, we predicted that

relative to participants in the negative condition, those in the

positive condition would demonstrate a more adaptive

response to a stressor task in which they felt responsible for

preventing harm, as indicated by less checking behaviour,

decreased heart rate, and increased heart rate variability.

Method

Participants

High-checking undergraduate students from the University

of New South Wales (n = 100) were recruited based on

their responses to the checking subscale of the Padua

Inventory-Washington State University Revision (PI-R-

CHCK; Burns et al. 1996), which was administered as a

part of a larger pre-screening battery to 1,100 students.

With respect to the ethnic composition, the majority of

these students identified as either Anglo/European

(36.5 %) or Asian (35.3 %). Smaller percentages of the

sample identified as Middle Eastern (5.8 %), Indian (5 %),

or Indigenous Australian (1.5 %). Finally, a portion of

participants were classified as Other (14.9 %) or declined

to answer (1 %).

Participants scoring C10 on the PI-R-CHCK were

invited to participate based on the cut-off scores previously

established by Cuttler and Graf (2009). The final sample

reported checking symptoms (M = 19.32, SD = 6.00) that

were comparable to those reported in previous research

with clinically diagnosed OCD participants (Burns et al.

1996; Hermans et al. 2003). Five participants were exclu-

ded from analyses because they reported suspicion during

the debriefing regarding either the true purpose of the

training (i.e., increase or decrease responsibility) or the

deception involved in the sweet sorting task. Thus, the final

sample comprised 95 participants (75.8 % female) ranging

in age from 17 to 25 (M = 20.19, SD = 2.69), who were

randomly allocated to either the positive (n = 47) or neg-

ative training condition (n = 48).

Materials and Measures

Bias index (modified from Mathews and Mackintosh 2000)

The bias index assessed the extent to which training-

induced biases influenced the subsequent interpretation of

novel ambiguous information. Participants completed an

interpretive bias test immediately before and after CBM-I

training. First, participants were presented with ten novel

scenarios for which the level of responsibility remained

ambiguous. They then completed a brief filler task in which

they rated the pleasantness of 60 neutral images taken from

the International Affective Picture System (Lang et al.

2008).

After the filler task, participants were shown an identi-

fying title for each of the preceding ten scenarios. For each

title, four emotionally valanced disambiguated versions of

the scenario were created, two of which corresponded to

possible positive and negative interpretations of responsi-

bility (targets), and two corresponded to positive and

negative distracters that describe a slightly different event

to the original scenario (foils). Targets were included to

assess whether the CBM-I procedure produced specific

training-congruent changes in responsibility interpretive

bias towards novel material, whereas foils were used to test

whether CBM-I resulted in a more general positive

or negative interpretive bias toward novel material.

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Participants were asked to think back to the original sce-

nario and rate how similar each statement was to the ori-

ginal from 1 (very different in meaning) to 4 (very similar

in meaning). Similarity ratings were averaged, resulting in

a mean score for each of the four categories (positive tar-

get, positive foil, negative target, negative foil).

To obtain an index of interpretation bias before and after

CBM-I training, bias indices were calculated based on the

methodology of Clerkin and Teachman (2011). Target Bias

scores were calculated by subtracting mean similarity rat-

ings for negative target items from mean similarity ratings

for positive target items in order to indicate a negative

(inflated) versus positive responsibility bias across sce-

narios. Similarly, Foil Bias scores were calculated by

subtracting mean similarity ratings for negative foils from

mean similarity ratings for positive foils in order to indicate

an overall negative or positive interpretative bias.

Cognitive Bias Modification Training Items

The CBM-I task used in the present study was based on the

paradigm originally devised by Mathews and Mackintosh

(2000) and modified by Lang and colleagues (Lang et al.

2009; see also Whitton et al. 2013). The current CBM-I task

was designed to target interpretations of situations

potentiating responsibility for preventing harm. A total of 60

positive and 60 negative responsibility-based training items

were initially generated from a range of maladaptive beliefs

described in various self-report questionnaires, such as the

Responsibility Attitude Scale (Salkovskis et al. 2000), Inter-

pretation of Intrusions Inventory (Steketee and Frost 2001),

the Responsibility Interpretations Questionnaire (Salkovskis

et al. 2000), and responsibility training items used by Clerkin

and Teachman (2011). Potential items were pilot-tested as an

online questionnaire using the internet-based Amazon

Mechanical Turk interface in which participants (N = 129)

rated how responsible each scenario would make them feel if

it were true. Scenarios in which the negative version elicited

significantly more responsibility than the positive version

were included in the final CBM-I training paradigm, resulting

in a total of 32 positive and 32 negative items. See Fig. 1 for an

example CBM-I training item.

Thus the script-based training paradigm consisted of 32

sentences, each presented twice, which were designed to

either reduce responsibility bias (positive CBM-I training)

or increase responsibility bias (negative CBM-I training).

The CBM-I training task was programmed using E-prime

software (Versions 1.1.4.1, Pittsburgh: Psychology Soft-

ware Tools Inc.) and was presented to participants on a

desktop computer.

You see that someone has left a knife on the bench but do not put it away. If someone cuts themselves

you would feel

s o _ r y f o r t h e m a _ h a m e d o f y o u r s e l f

If someone cut themselves on the knife would you feel responsible?

NO YES

If someone cut themselves on the knife would you feel responsible?

NO YES

Answer NO Answer YES

CORRECT! INCORRECT

Answer YES Answer NO

INCORRECT CORRECT!

Press: ‘r’ Press: ‘s’

POSITIVE TRAINING CONDITION

NEGATIVE TRAINING CONDITION

Fig. 1 Example of positive and negative CBM training

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123

Participants were asked to read and imagine themselves

as the central character in a series of scenarios, each of

which consisted of a two sentence long statement presented

on the computer screen for 3 s, which had the final few

words missing. These missing words meant that the initial

sentence presented was ambiguous (e.g., ‘‘You notice a

piece of glass on the ground but do not stop to pick it up. If

someone injures themselves, you are…’’). The final words

subsequently appeared on the screen as a fragment for the

participant to solve, and remained on the screen for up to

30 s. Participants were instructed to use their understand-

ing of the preceding scenario to complete the word frag-

ment by filling in a single missing letter. When they knew

what the missing letter was, they were to press the advance

key and type in the letter. Fragments were constructed so

that there was only one solution that fit a possible inter-

pretation of the preceding statement.

Completion of this word fragment resolved the ambi-

guity of the preceding scenario in a way that served to

inflate the reader’s sense of personal responsibility in the

negative training condition (e.g., ‘‘_esponsible’’), and

decrease this sense of responsibility in the positive training

condition (e.g., ‘‘_lameless’’). By actively generating a

solution to this word fragment, participants were induced to

make an emotional interpretation consistent with either a

dysfunctional responsibility bias or a more benign inter-

pretation. The time taken for participants to complete each

word fragment was recorded throughout training, and

response latencies (in milliseconds) for each of the training

items were averaged to provide a single mean reaction time

score for each participant.

To ensure that participants understood all statements and

to reinforce the meaning of the disambiguated scenario, a

comprehension question randomly followed one from each

pair of scenarios. Participants were told that the questions

constituted a comprehension exercise and that they should

answer in a manner that was consistent with the informa-

tion in the preceding scenario, irrespective of whether this

aligned with their own personal beliefs. For example, the

correct response to the question ‘‘Are you at fault if

someone injures themselves on the glass?’’ would be ‘yes’

for the negative condition and ‘no’ for the positive condi-

tion. Participants received feedback to indicate whether

they had answered correctly or not, with the words ‘cor-

rect’ or ‘incorrect’ appearing after completion of each

question. Correct responses for each of the comprehension

questions were totalled to give a single training accuracy

score.

Responsibility Beliefs

To gauge the impact of CBM-I training on responsibility

beliefs, the Responsibility Attitudes Scale (RAS;

Salkovskis et al. 2000) was administered before and after

training. The RAS is a 26-item questionnaire designed to

measure general attitudes, assumptions, and beliefs about

responsibility. Each item describes a belief about respon-

sibility (e.g., ‘‘not acting to prevent danger is as bad as

making a disaster happen’’) that respondents rate on a

seven-point scale according to how much they agree with

the statement, from 1 (totally agree) to 7 (totally disagree).

The RAS has demonstrated good test–retest reliability

(r = .94) and excellent internal consistency (Cronbach’s

a = .92; Salkovskis et al. 2000). The internal consistency

of the RAS in the current study was .90.

Compulsive Checking Symptoms

To examine whether responsibility biases induced during

CBM-I training had downstream effects on compulsive

checking symptomology, the PI-R-CHCK was adminis-

tered at pre-screening and after training. The PI-R-CHCK

is a 10-item self-report measure of compulsive checking.

Respondents rate each item on a 5-point scale according to

the degree of disturbance caused by the thought or

checking behaviour, from 0 (not at all) to 4 (very much).

The scale has demonstrated good test–retest reliability

(r = .74; Burns et al. 1996) and good internal consistency

(Cronbach’s a = .88; Burns et al. 1996). The measure also

has good external validity and is able to discriminate

individuals with OCD from both healthy controls and

individuals with other anxiety disorders (van Oppen et al.

1995). The internal consistency of the PI-R-CHCK in the

current study was .76.

Sweet-Sorting Stressor Task

This manual classification task was adapted from the pill

sorting task developed by Ladouceur et al. (1995) and the

subsequent modifications employed by Reeves et al.

(2010). The experimenter presented participants with a jar

filled with six types of sweets (60 total), each with a small

identifying label. Two of the types of sweets contained

nuts, two of the types may have contained nuts, and two of

the types did not contain any nuts. The experimenter

informed participants that the next participant had a nut

allergy (see Procedure for additional details). The experi-

menter then provided instructions to sort the sweets based

on Reeves et al. (2010), providing no information regard-

ing who (if anyone) would check the sweets after they had

sorted them.

A web camera recorded performance during the manual

classification task and a blind independent assessor viewed

the videos to count the checking behaviours based on

behavioural indices employed by Arntz et al. (2007) and

Reeves et al. (2010). These behaviours included: (1)

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inspection of the ingredients list on the jar; (2) inspection

of a sweet in the participant’s hand for at least 1 s; (3)

emptying out one of the bowls; (4) changing a sweet from

one bowl to another; (5) close inspection of the contents of

a bowl; (6) final check by inspecting the contents of a bowl

after the final sweet had been classified. We summed the

number of checking behaviours to generate a total checking

score and calculated the time taken to complete the sorting

task in seconds.

Heart Rate

To measure physiological state anxiety during the sorting

task, participants were fitted with a ZephyrTM BioHarness

(Zephyr Technology, Auckland, New Zealand), to measure

heart rate (HR) and heart rate variability (HRV). HR was

calculated in beats per minute (BPM) and averaged across

the 4 min during both a baseline phase and the sorting task. In

the statistical analyses, the dependent variable was the

change in (average) heart rate during the sorting task relative

to baseline. Positive scores indicate an increase in heart rate

from baseline to sorting task, whereas negative scores indi-

cate a decrease. As an index of HRV, we employed the

widely utilised root mean square of successive differences

(RMSSD). This measure is highly correlated with the high

frequency component of the respiratory frequency range and

thus thought to primarily reflect vagal influence (i.e., para-

sympathetic activity; Mendes 2009; Goedhart et al. 2007).

Theory and research suggest that HRV is a biomarker of

adaptive emotional regulation (Appelhans and Luecken

2006; Thayer and Lane 2000, 2009).

Mood and Anxiety Measures

State mood and anxiety measures were used to assess

whether completion of the CBM-I paradigm would result

in training-congruent changes in mood or anxiety and to

control for any subsequent performance differences that

may have been a direct consequence of, or mediated by,

this mood change. Six visual analogue scales (VAS) were

developed based on those employed by Lothmann, Holmes,

Chan, and Lau (2011). In the present study, participants

rated three items corresponding to negative affect (upset,

distressed, guilty) and three items measuring state anxiety

(worried, nervous, scared) on 10 cm long scales with end

points at 0 cm = not at all [emotion] and 10 cm =

extremely [emotion]. Participants indicated how they were

feeling at the current moment by marking a point on the

line. Ratings were summed to produce a composite nega-

tive affect score and a composite state anxiety score for

each participant. The internal consistency of these sub-

scales in the current sample was .82 for negative affect and

.76 for state anxiety.

Funnelled Debriefing

Prior to the complete debriefing, participants were probed

for suspicion regarding the sweet sorting task and the true

purpose of the study through three questions which the

experimenter asked at the conclusion of the study: (1) What

did you think the purpose of the experiment was?; (2) Did

anything about the experiment seem strange to you?;

(3) Did you have any questions about the part of the

experiment where you ate the sweet? Participants were

considered suspicious if they reported awareness of the

purpose of the CBM training or the deception involved

with the sweet sorting on any of these three questions.

Procedure

Participants were tested in individual sessions lasting

approximately 1 h. Participants arrived for a study osten-

sibly investigating the effect of cognitive factors and glu-

cose consumption on imagery and emotion. As part of the

deception, the experimenter informed the participant that

they would be required to consume a sweet later in the

study and asked if they had any food allergies.

The experimenter obtained written consent and fitted

participants with the BioHarness, which the experimenter

suggested would be used to measure their physiological

response to imagery. Participants completed the RAS and

the baseline interpretation bias test, in which they were first

presented with 10 ambiguous scenarios and their accom-

panying titles. They then completed the neutral images

filler task, which lasted approximately 6 min. Following

this, participants completed the baseline similarity rating

task and then rated their current levels of negative affect

and state anxiety on the mood visual analogue scales.

After completing baseline measures, participants

underwent either the positive or negative CBM-I training

paradigm. After CBM-I training, a second mood and anx-

iety rating was taken and participants were again presented

with the similarity rating task.

Following these ratings, the experimenter asked partici-

pants to select and consume one sweet from the large jar of

sweets, after which an alarm on the experimenter’s phone

went off, ostensibly signalling the arrival of the next par-

ticipant. The experimenter excused herself, explaining that

the study was running a little late and that she would need to

set up the next participant in another room. The experimenter

took the jar of sweets and left the room for 3 min, before

returning to the room with the jar appearing flustered. The

experimenter then informed participants that the next par-

ticipant had a nut allergy, and that she did not have time to

sort out which sweets would be safe for this participant to eat.

Participants were then asked to sort the sweets into two

groups—those that would be safe for her to eat (sweets that

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123

did not contain nuts) and those that would not be safe

(sweets that contained or may have contained nuts). The

experimenter then briefly left the room and returned with

two bowls for the participants to put the sweets in. As

initial piloting indicated that participants would require no

more than 3 min to classify all 60 of the sweets, the

experimenter subsequently left the room for 4 min,

allowing participants the opportunity to engage in any

checking behaviours.

After participants had finished sorting the sweets, they

again rated their current mood and state anxiety levels

before completing post-training self-report measures

including the RAS and the PI-R-CHCK. Finally, the

experimenter probed participants for suspicion, thanked

them, and debriefed them completely.

Results

Random Assignment

To establish whether random assignment of participants to

CBM-I training conditions was successful, the positive

(n = 47) and negative (n = 48) training conditions were

compared with respect to demographic characteristics,

checking symptoms, and pre-training responsibility bias.

There were no significant differences between the positive

and negative CBM-I conditions with respect to age (t =

-.60, p = .55) or gender (v2 = .09, p = .81). The training

conditions were also matched with respect to checking

symptoms on the PI-R-CHCK (t = .07, p = .94) and

interpretative bias as measured by their pre-training Target

Bias scores (t = .26, p = .79).

Training Accuracy and Reaction Time

We performed analyses of training accuracy scores to

determine whether participants understood the task. Out of

a potential score of 32, training accuracy overall was

extremely high for both conditions [positive CBM-I:

(M = 29.04, SD = 2.37); negative CBM-I: (M = 30.33,

SD = 2.54)]. An independent samples t test revealed that

training accuracy was significantly higher among the neg-

ative versus positive CBM-I condition, t(1, 93) = -2.56,

p = .01, g2 = .07. We also conducted an independent

samples t-test to compare reaction time in the two CBM-I

conditions. Again, there was a significant effect of CBM-I

training, such that participants in the positive condition

took longer to complete the word fragments

(M = 2,795.31, SD = 911.04) than those who completed

negative training (M = 2,237.78, SD = 459.40), t(1,

93) = 3.78, p \ .001, g2 = .13.

Effects of Cognitive Bias Modification

on Responsibility

Bias Index

To examine whether CBM-I training successfully modified

biases in the interpretation of novel ambiguous material,

we calculated pre- and post-training bias scores for targets

and foils. As previously noted, Target Bias scores reflected

ratings of positive versus negative interpretations of

responsibility and Foil Bias scores reflected ratings of

positive versus negative information more generally. We

conducted univariate GLM analyses with Time as the

repeated factor and condition as the within-subjects factor.

For Target Bias scores, there was no main effect of

Time, but there was a significant Time by Condition

interaction, F(1, 93) = 6.76, p = .01, gp2 = .07. Planned

comparisons revealed that Target Bias scores significantly

increased in the positive condition (reflecting a change

away from negatively valenced interpretations). The shift

in Target Bias scores in the negative condition was not

significant. Further, Target Biases changed significantly

more in the positive training condition relative to the

negative condition, [t(93) = 3.28, p = .02], corresponding

to a medium effect (Cohen’s d = .49, 95 % CI .08–.90).

For Foil Bias scores, there was no main effect of Time,

however the interaction of Time by Condition was signif-

icant, F(1, 93) = 5.17, p = .03, gp2 = .05. Planned com-

parisons revealed that Foil Bias scores also significantly

increased in the positive condition. The shift of Foil Bias

scores in the negative condition was non-significant.

Importantly, Foil Bias scores did not change significantly

more in the positive training condition relative to the

negative condition, t(93) = 1.62, p = .10, demonstrating

relative equivalence between the positive and negative

conditions for Foils.

Effects on Self-reported Emotion, Responsibility Beliefs,

and Compulsive Checking

To examine the effects of CBM-I training on self-reported

mood (negative affect, state anxiety), responsibility beliefs,

and compulsive checking symptoms, a doubly-multivariate

profile analysis was conducted using SPSS GLM (Ta-

bachnick and Fidell 2007). The between-subjects factor

was Condition (positive or negative CBM-I), the within-

subjects factor was Time (pre- or post-training), and was

treated multivariately. The dependent variables were neg-

ative affect, state anxiety, responsibility beliefs (RAS), and

compulsive checking (PI-R-CHK). The results are dis-

played in Table 1.

Overall, multivariate tests revealed a significant main

effect of Time on the combined dependent measures, F(4,

Cogn Ther Res

123

88) = 17.75, p \ .001, gp2 = .45; however the main effect

of Condition, F(4, 88) = 1.493, p = .21, gp2 = .06, and the

Condition by Time interaction, F(4, 88) = 1.423, p = .23,

gp2 = .06, were both non-significant. Follow-up univariate

tests for the main effect of time were conducted on each

dependent variable separately, using a corrected alpha level

of (0.05/4 = 0.0125). The results revealed that the main

effect of Time was only significant for compulsive

checking symptoms, F(1, 91) = 46.25, p \ .001,

gp2 = .34. Thus, irrespective of training condition, com-

pulsive checking symptom scores increased from pre- to

post-training.

Emotional and Behavioural Response to Stressor Task

We also examined the effects of CBM-I training on emo-

tional and behavioural responses during the sweet sorting

stressor task, in which participants were induced to feel

responsible for preventing harm. A MANOVA was con-

ducted using SPSS GLM with Condition (positive or neg-

ative CBM-I) as the between-subjects factor, and the

dependent variables consisting of the number of times

participants checked during the task (check_total), the

length of time it took participants to sort the sweets

(check_time), self-perceived responsibility (responsibility),

self-rated severity of potentially harmful consequences

during the sorting task (severity), post-task rating of neg-

ative affect (sorting_NA), and state anxiety (sorting_anx)

during the sorting task. Means and standard deviations for

the positive and negative CBM-I conditions are displayed

in Table 2.

Logarithmic transformations were performed due to

positive skewness in both conditions for check_total,

responsibility and severity ratings, sorting_NA, and

sorting_anx. MANOVA results revealed a non-significant

multivariate main effect of CBM-I condition for the

combined measures (F = 1.34, p = .25, gp2 = .09).

Examination of the univariate tests for all dependent

variables revealed non-significant main effects of CBM-I

condition (all ps greater than the corrected alpha value of

.008) (Fig. 2).

Effects on Physiological Responding During Stressor Task

To examine the downstream effects of CBM-I training on

physiological variables (i.e., heart rate and heart rate

Table 1 Pre- and post-training

ratings of negative affect, state

anxiety, responsibility beliefs

(RAS) and compulsive checking

symptoms (PI-R-CHK)

Variable Positive CBM-I Negative CBM-I

Pre-training Post-training Pre-training Post-training

M (SD) M (SD) M (SD) M (SD)

Negative affect 0.56 (0.05) 0.66 (0.06) 0.67 (0.05) 0.73 (0.06)

State anxiety 0.70 (0.06) 0.61 (0.06) 0.75 (0.06) 0.73 (0.06)

RAS 101.54 (2.98) 97.46 (3.72) 93.21 (2.95) 88.70 (3.68)

PI-R-CHK 19.07 (0.86) 25.30 (1.05) 19.19 (0.85) 24.06 (1.03)

Table 2 Dependent variables associated with the sweet-sorting

stressor task

Variable Condition

Positive Negative

M (SD) M (SD)

Time spent checking 3.73 (0.88) 3.83 (1.15)

Total # of checks 35.97 (23.65) 30.70 (14.44)

Post negative affect 3.99 (5.02) 5.24 (4.85)

Post state anxiety 4.27 (5.72) 5.53 (5.08)

Positive Training Condition

target foil-15

-10

-5

0

5

10

Bia

s

Pre-TrainingPost-Training

Negative Training Condition

target foil-15

-10

-5

0

5

10

Pre-Training

Bia

s

Post-Training

* *

*

*

Fig. 2 Pre and post-CBM-I responsibility biases for targets and foils

for participants in the positive and negative training conditions

Cogn Ther Res

123

variability) during the sweet-sorting task, a doubly-multi-

variate profile analysis was conducted using SPSS GLM

(Tabachnick and Fidell 2007). The between-subjects factor

was Condition (positive or negative CBM-I), the within-

subjects factor was Time (baseline and post-sorting task),

and was treated multivariately, and the dependent variables

were heart rate (HR) and heart rate variability (HRV). Means

and standard deviations are presented in Fig. 3.

There was a significant proportion of missing heart rate

data due to BioHarness equipment malfunction (35 % of

cases). Importantly, for both the positive and negative

CBM conditions, Little’s MCAR test [positive CBM:

v2(N = 2) = .90, p = .64; negative CBM: v2(N = 2) =

.78, p = .68], indicated that missing data was unrelated to

scores on a variable, and thus missing completely at ran-

dom. Because data was missing at random, analyses were

performed deleting cases with missing data on any mea-

surement occasion. The multivariate analysis revealed a

non-significant main effect of Condition (F \ 1), but a

significant main effect of Time, F(2, 56) = 12.25,

p \ .001, gp2 = .30, and a significant interaction between

Condition and Time, F(2, 56) = 4.74, p = .01, gp2 = .15,

on the combined physiological dependent measures. Fol-

low-up univariate tests were conducted to explore the

significant main and interaction effects involving Time.

For HR, the main effect of Time was not significant,

F (1, 57) = 2.75, p = .10, gp2 = .05, but the Condition by

Time interaction was significant, F(1, 57) = 7.42,

p = .009, gp2 = .12. Simple effect contrasts revealed that

participants in the negative CBM-I condition showed a

significant increase in HR from baseline to sorting task

(p = .009), whereas participants in the positive condition

did not show a significant change in HR between baseline

and sorting task (p = .45).

For HRV, the main effect of Time was significant, F(1,

57) = 18.08, p \ .001, gp2 = .24, and the Condition by

Time interaction was also significant, F(1, 57) = 4.14,

p = .047, gp2 = .07. Simple effect contrasts revealed that

participants in the positive CBM-I condition showed a

significant increase in HRV from baseline to sorting task,

p \ .001, whereas participants in the negative CBM-I

condition did not exhibit a significant HRV change

between baseline and sorting task, p = .13.

Discussion

The current investigation examined the effect of CBM-I

training targeting responsibility biases on interpretations of

ambiguous situations, self-reported responsibility, check-

ing symptoms, and response to a responsibility stressor task

among undergraduate students with high checking symp-

toms. To summarise our findings, positive CBM-I training

had the predicted effect of reducing the responsibility bias

on subsequent interpretations of ambiguous situations,

whereas there was no effect of negative CBM-I training on

subsequent interpretation bias. There were no training-

congruent changes on self-report measures or on checking

behaviour during the stressor task. However, participants in

the positive training condition demonstrated a significantly

more adaptive physiological response to the stressor task

relative to those in the negative training condition.

Beginning with performance on the training component

of the paradigm, it is interesting to note that although

training accuracy overall was extremely high for both

conditions, participants in the negative CBM-I condition

evidenced significantly higher training accuracy and sig-

nificantly faster reaction time to complete word fragments.

One possible interpretation of these findings is that they

reflect a pre-existing responsibility bias amongst high-

checking undergraduates. Because the positive training

condition presented interpretations that were inconsistent

with inflated responsibility, it may have been slightly more

difficult for high checking participants to adhere to and

complete relative to the negative training condition. This

explanation is speculative, however, and additional inves-

tigations with a low-checking group would be necessary to

confirm this possibility.

Heart Rate

Positive Negative0

20

40

60

80

100

Hea

rt R

ate

(bp

m)

Baseline

Sweet-Sorting

Heart Rate Variability

Positive Negative0

50

100

Baseline

Sweet-Sorting

HR

V*

A

*

B

Fig. 3 a Baseline and sweet sorting heart rate in beats per minute

(bpm) for participants in the positive and negative CBM-I condition.

b Baseline and sweet sorting heart rate variability (HRV) for

participants in the positive and negative CBM-I condition

Cogn Ther Res

123

Regarding the primary interpretation bias findings, the

positive training condition resulted in a significant shift

away from negatively valenced interpretations of the Tar-

get bias scores. Although Foil bias scores also shifted

significantly away from negatively valenced interpretations

in the positive training condition, the difference between

positive and negative training conditions for Foil bias

scores was non-significant, suggesting that positive CBM-I

training led to a specific decrease in responsibility bias,

rather than a decrease in negative interpretations more

generally. Moreover, there were no significant changes in

state anxiety or negative affect following training for either

CBM-I conditions, suggesting that this change in inter-

pretive bias occurred independently of training-congruent

changes in emotional state. Nonetheless, the shift in bias in

the positive condition was modest and the Target bias

remained negative overall.

With respect to the lack of a corresponding shift in the

negative training condition, one possible explanation is that

the negative condition was inherently less active for high-

checking participants because it was congruent with their

pre-existing biases, as suggested by greater accuracy and

faster completion time in this condition. High checking

participants may have been more actively engaged in the

positive condition, in which they were resolving scenarios

in a manner that was incongruent with their existing biases.

Indeed, past CBM-I research has suggested that training-

congruent biases are more effectively induced when par-

ticipants actively engage with information to resolve

ambiguity during training (Hoppitt et al. 2010; Mathews

2012; Mathews and Mackintosh 2000). If negative reso-

lutions were fairly consistent with participants’ thinking,

the negative condition may have served as control CBM-I

condition without training in opposite direction.

Contrary to prediction, there were no training congruent

changes with respect to self-reported responsibility or

compulsive checking symptoms. The failure of CBM-I

training to have differential effects on these self-report

measures may be due to the limited capacity of these

measures to detect changes immediately post-training,

when individuals have not yet had time to interact in their

usual environment outside of the lab. Future studies should

assess changes in symptoms and beliefs at a follow-up

assessment at least 1 week post-training.

The lack of effect of training on these measures may

also be attributable to the limited ‘‘dose’’ of CBM-I train-

ing in the current study, which comprised only 64 training

trials completed in a single 30-min session. It is likely that

this modest amount of training led to a slight shift in

interpretation of novel situations involving responsibility

without impacting the downstream symptoms resulting

from this bias. Past CBM-I research that has demonstrated

stronger effects on self-report measures has typically used

lengthier training programs with a much greater number of

training trials (e.g., Wilson et al. 2006), whereas other

studies that have failed to obtain generalisation of CBM-I

effects to self-report measures have also attributed these

findings to training brevity (e.g., Lester et al. 2011). A

recent review by MacLeod and Mathews (2012) recom-

mended that in order to enhance the impact of CBM-I

paradigms in real-world settings, CBM-I studies should

aim to deliver multiple, spaced training sessions and to

implement CBM-I paradigms outside of the laboratory.

Turning to the stressor task, participants in both training

conditions evidenced a slight but significant increase in

checking symptoms from pre- to post-training. The sweet-

sorting stressor task, which they completed prior to the

post-training self-report measures, is likely to have primed

checking behaviour for all participants. However, the lack

of a differential CBM-I effect on checking may have been a

result of the perceived high level of risk associated with the

task. When participants were told that the next participant

had an allergy, they engaged in what may be considered a

socially and morally acceptable response of checking the

sweets thoroughly, regardless of their CBM-I training

condition. This lack of ambiguity in the behavioural task is

a limitation of the current study. Future studies should

employ a more ambiguous and lower risk situation (i.e.,

‘‘one of the next participants might have a mild allergy’’),

which may have better allowed responsibility biases to

emerge. In support of this possibility, Foa et al. (2002)

found that compulsive checkers felt more personally

responsible and reported greater urges to rectify hypo-

thetical scenarios than control participants, but only when

the degree of risk was ambiguous (low and moderate risk

scenarios). Interpretations of responsibility were equal in

scenarios where there was a high degree of risk for

potential harm. Other recent studies have also failed to find

a behavioural change associated with CBM-I (Lange et al.

2010; MacDonald et al. 2013; Teachman and Addison

2008; Whitton et al. 2013). As with self-report measures,

these studies and the current study may also have failed to

find an effect because a single session of CBM-I training is

insufficient to evoke behavioural change.

Despite the lack of difference in checking behaviour

during the stressor task, participants in the positive con-

dition appeared to demonstrate a more adaptive physio-

logical response to the stressor task relative to those in the

negative condition, with respect to both decreased HR and

increased HRV. Increased HRV in the positive condition

may be a physiological indicator of more adaptive, flexible

responding to environmental demands (Appelhans and

Luecken 2006; Thayer and Lane 2000, 2009). In the con-

text of the sweet-sorting stressor task, individuals who

interpreted the situation with a slightly decreased respon-

sibility bias may have been able to view the situation as

Cogn Ther Res

123

somewhat less threatening and respond more flexibly to

their arousal. Importantly, these physiological differences

are unlikely to be a result of exposure to more anxiety-

provoking scenarios in the negative condition because the

conditions did not differ with respect to state anxiety and

negative affect either after training or during the sorting

task.

There were several important limitations to the current

findings, including the nonclinical sample and the single

laboratory-based training situation. Future studies would

benefit from using CBM-I to target responsibility in a

clinical sample of individuals with OCD with primary

checking symptoms across multiple training sessions in

different contexts. In addition, we experienced equipment

difficulties that led to a loss of heart rate data for the

stressor task. However, even with the missing data the

sample size was adequate for our analyses. Further, with

respect to the physiological indices, we utilized RMSSD as

a measure of high frequency HRV. Although there is evi-

dence that RMSSD is highly correlated with the high fre-

quency component of the respiratory frequency Goedhart

et al. (2007), some have advised using more specific power

spectral analyses of the high frequency component

(Berntson et al. 2005). Thus, although we interpret our

HRV as a function of high frequency, some caution is

warranted.

Despite these limitations, the current study provides

some provocative initial findings and pathways for

extending this promising area of research. It seems that

CBM-I interventions may be tailored to target specific

interpretive biases and symptom profiles exhibited by

individual OCD clients. With regard to compulsive

checking, the modification of inflated responsibility beliefs

has long been considered to be a key strategy for reducing

checking symptomology in cognitive-behavioural therapy

(CBT) and changes in responsibility beliefs are often

observed after CBT (e.g., Ladouceur et al. 1996). These

methods may involve the use of pie charts to analyse the

allocation of responsibility between the patient and other

people, as well as practising the transfer of responsibility

first to the therapist, then to friends and relatives (for a

review, see Radomsky et al. 2010).

Unfortunately, changes in responsibility perceptions are

often vigorously resisted in therapy (Radomsky et al.

2010), which may stem from a lack of insight into these

maladaptive beliefs (Sookman and Steketee 2009). The

limited insight of OCD patients is unsurprising given that

responsibility biases may operate outside of conscious

control, traditional cognitive therapy techniques rely

heavily on the insight and awareness of the patient (Nez-

iroglu and Stevens 2002). If these biases may operate

outside of conscious control, inflated responsibility

appraisals may better lend themselves to implicit methods

of modification. CBM-I also does not require insight,

because the targeted bias does not need to be introspec-

tively accessible. For OCD checking patients who resist

challenging their responsibility beliefs, CBM-I may pro-

vide non-confrontational exposure to alternative standards

to responsibility. Further, change induced via an implicit

method may be less dependent on the availability of cog-

nitive resources (Baert et al. 2011). Thus, CBM-I training

may function to enhance or accelerate changes in respon-

sibility biases which have typically been associated with

symptomatic improvement following CBT (e.g., Haraguchi

et al. 2011).

In conclusion, in the current study we found some mixed

initial evidence supporting the application of CBM-I to

inflated responsibility biases among individuals displaying

compulsive checking symptoms. CBM-I training appeared

to be successful in modifying interpretive responsibility

biases in a more adaptive direction with possible down-

stream consequences for physiological response to a

stressor task. However, the effects of the implicit respon-

sibility modification did not generalise to self-reported

responsibility beliefs, compulsive checking symptomology

or to checking behaviour. Future studies may examine

various ways to increase the efficacy of this training pro-

gram with nonclinical and clinical samples. Overall, the

present study highlights the need for future research to

extend the breadth of CBM-I paradigms to novel OCD

belief domains.

Conflict of Interest Jessica R. Grisham, Lauren Becker, Alishia D.

Williams, Alexis E. Whitton and Steve R. Makkar declare that they

have no conflict of interest. The first author was supported in part by a

Discovery Project grant from the Australian Research Council

(DP0984560). The third author was supported by a National Health

and Medical Research Council of Australia Fellowship (630746).

Informed Consent Informed consent was obtained prior to partic-

ipation and approval was given by the UNSW Human Research

Ethics Advisory Panel.

Animal Rights No animal studies were carried out by the authors

for this article.

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