Obsessive–compulsive disorder is associated with less of a distinction between specific acts of omission and commission

Journal of Anxiety Disorders 24 (2010) 893–899

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Journal of Anxiety Disorders

Obsessive–compulsive disorder is associated with less of a distinction between specific acts of omission and commission Jedidiah Siev a,b,∗ , Jonathan D. Huppert c , Dianne L. Chambless b a b c

Department of Psychiatry, Massachusetts General Hospital/Harvard Medical School, 185 Cambridge Street, 2nd Floor, Boston, MA 02114, USA Department of Psychology, University of Pennsylvania, 3720 Walnut Street, Philadelphia, PA 19104, USA Department of Psychology, The Hebrew University of Jerusalem, Mt. Scopus, Jerusalem 93509, Israel

a r t i c l e

i n f o

Article history: Received 28 October 2009 Received in revised form 15 June 2010 Accepted 15 June 2010 Keywords: Obsessive–compulsive disorder Omission bias Cognitions Thought-action fusion Responsibility Moral reasoning

a b s t r a c t Individuals with obsessive–compulsive disorder (OCD) seem to judge harm caused actively and passively as morally equivalent. In contrast, people generally choose harm by omission over harm by commission, a propensity known as omission bias. Two studies examined the hypothesis that OCD is associated with less omission bias. In Study 1, with a student population, symptoms of OCD and related cognitions were negatively associated with omission bias about washing and checking scenarios targeting common OCD fears. In contrast, neither symptoms nor cognitions related to OCD were associated with general omission bias. In Study 2, individuals with self-reported OCD evinced less omission bias about washing and checking scenarios than did individuals without OCD. Again, general omission bias was not related to OCD. These results support the idea that individuals with elevated OCD symptoms distinguish less than others between acts of omission and commission for harm relevant to general OCD concerns. © 2010 Elsevier Ltd. All rights reserved.

1. Introduction Individuals with obsessive–compulsive disorder (OCD) tend to perceive thoughts as more consequential than do others (e.g., Rachman, 1997; Salkovskis, 1985). This tendency may be directly related to compulsive behavior because following an intrusive thought or obsession, someone with OCD may feel the need to take preventive measures to counteract the possibility of the feared consequence. Failure to prevent anticipated harm may be seen as equivalent to causing harm, and patients then see themselves as responsible for preventing harm. Hence, one can view compulsive behavior as stemming from both beliefs about the importance of thoughts and the perceived equivalence of failure to prevent harm and active infliction of harm. In sum, the individual with OCD: (a) experiences a distressing thought, (b) believes the thought to be of consequence, (c) believes that not preventing the feared consequence would be like causing it and perceives a personal responsibility to do something about it, and (d) ritualizes. This paper reports two studies that examine the hypothesis that individuals with OCD view failure to prevent harm as more similar to causing harm than do others.

∗ Corresponding author at: Department of Psychiatry, Massachusetts General Hospital/Harvard Medical School, 185 Cambridge Street, 2nd Floor, Boston, MA 02114, USA. Tel.: +1 617 643 3065; fax: +1 617 643 3080. E-mail addresses: [email protected] (J. Siev), [email protected] (J.D. Huppert), [email protected] (D.L. Chambless). 0887-6185/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.janxdis.2010.06.013

Clinical experience suggests that individuals with OCD often assign themselves equal moral responsibility for causing indirect or passive harm as they do for active harm. For example, individuals who fear their house burning down seem to act as if their failure to ensure the house is safe would be equivalent to intentionally burning the house down. Therefore, they compulsively check appliances, outlets, etc. Indeed, some researchers have proposed that individuals with OCD weigh acts of omission and commission more equally than do others (Wroe & Salkovskis, 2000). In the literature on decision making and heuristics, omission bias refers to the general tendency for people to choose harm by omission over similar harm by commission (Ritov & Baron, 1990). For instance, most people judge actively killing someone as worse than passively, albeit intentionally, allowing someone to be killed. Individuals with OCD, however, are characterized as having an inflated sense of responsibility (e.g., Salkovskis et al., 2000) and a tendency to view thoughts and intentions as equivalent to behavior (thought-action fusion [TAF]; e.g., Shafran, Thordarson, & Rachman, 1996), both of which may be related to the tendency to judge passive inaction that leads to a negative outcome as similar to active behavior. Increases in OCD symptoms may therefore be associated with decreases in the tendency to exhibit omission bias. In fact, some have identified the absence of omission bias as part of inflated responsibility (Obsessive Compulsive Cognitions Working Group, 1997).1

1 We recognize the controversy about the label, “bias,” in the absence of a deviation from a clear normative standard (e.g., Connolly & Reb, 2003), and that this

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Wroe and Salkovskis (2000) presented participants with hypothetical scenarios in which potential harm was caused by passive inaction, and manipulated degree of premeditation by altering the extent to which the actor consciously considered the possibility of harm. They considered inaction in the context of conscious awareness of potential harm and perceived responsibility to be equivalent to active commission. They found that patients with OCD were less likely to differentiate between premeditated and non-premeditated inaction than were anxious and non-clinical controls. However, this difference was found only for scenarios related to OCD patients’ semi-idiographic concerns (and not in scenarios about which they were least concerned). These findings support the notion that individuals with OCD view unintentional inaction which leads to harm as similar to intended harm through inaction. However, these data do not speak directly to whether individuals with OCD view judgments about true action versus inaction similarly, a tendency that may extend beyond domains of semi-idiographic concern. Whereas Wroe and Salkovskis labeled intentional inaction as commission, individuals in general evince an omission bias even when the actor is consciously aware of the possible harm that will result from inaction (e.g., Ritov & Baron, 1990). In a recent study, Franklin, McNally, and Riemann (2009) had individuals with or without OCD resolve moral dilemmas by choosing either actively to cause one death in order to save many others, or not to cause any deaths actively, but in so doing, passively to allow many people to die. Although not labeled as such, this study essentially examined general omission bias for hypothetical scenarios unrelated to OCD, similar to the non-idiographic portion of Wroe and Salkovsis’ study. The results did not reveal any group differences between those with and without OCD, suggesting that individuals with OCD are not more likely to judge all types of omission as similar to commission. The present two studies were designed to examine further the relationship between omission bias and OCD symptoms and cognitions, where omission bias denotes the tendency to favor harm caused by inactive, passive omission to that caused by active, overt commission. Scenarios were constructed to measure both omission bias about typical obsessive fears (contamination/washing and harm/checking), and general, non-OCD-related omission bias, and all measures were administered without attention to participants’ idiographic domains of concern. These procedures allow one to evaluate whether OCD symptoms and cognitions are associated with less omission bias (a) in general, (b) only when relevant to typical OCD concerns (but not contingent upon idiographic fears), (c) only when related to idiographic concerns (e.g., contamination for washing symptoms), or (d) none of the above. The first study was conducted with a non-clinical sample, following previous research supporting the utility of investigating OCD processes in analogue samples with self-report symptom measures (e.g., Burns, Formea, Keortge, & Sternberger, 1995; Mancini, D’Olimpio, Del Genio, Didonna, & Prunetti, 2002). The second study extended the investigation to an OCD sample. 2. Study 1 2.1. Method 2.1.1. Participants In Study 1, participants were undergraduate students from the University of Pennsylvania who completed study measures via the internet and received course credit for their participation. Partic-

controversy is particularly salient when the “biased” behavior is associated with more, not less, adaptive behavior. Nevertheless, we use the term “omission bias” with reference to a specific literature and as a term of convenience.

ipants were included if they were missing fewer than 20% of the items for each study measure, and completed the ratings for all of the OCD-relevant commission and omission scenarios. In total, 342 participants were included and 45 excluded. For those who were included, missing data were estimated as the mean item score for a participant on a given measure. For measures with validated subscales, the mean item score for each subscale was used. The mean age of the sample was 19.23 (SD = 2.52), and 67% of the participants were female. Approximately 65% were White, 21% Asian or AsianAmerican, 5% African-American or Black, and 9% other or unknown. 2.1.2. Measures 2.1.2.1. Obsessive–Compulsive Inventory—Revised. The Obsessive– Compulsive Inventory—Revised (OCI-R) is an 18-item self-report measure of OCD symptoms (Foa et al., 2002). Individuals rate the degree to which they have been distressed or bothered by various symptoms within the past month on a scale of 0 (Not at all) to 4 (Extremely). Normative data suggest that the OCI-R has excellent psychometric properties, including test-retest reliability, convergent validity, and internal consistency, as well as sensitivity and specificity in discriminating individuals with OCD from those without (Foa et al., 2002). In addition, the OCI-R has been shown to be psychometrically sound in student populations (Hajcak, Huppert, Simons, & Foa, 2004). The measure yields a total score and six subscales that assess washing, checking, obsessing, ordering, neutralizing, and hoarding. In this study, analyses were conducted using the total score as well as the washing and checking subscales. Internal consistency for the total score has ranged from ˛ = .81 to .93 in OCD, anxious, and non-anxious samples (Foa et al., 2002; Huppert et al., 2007), and was .91 and .93 in the present two studies. Internal consistency for the washing and checking subscales ranged from ˛ = .65 to .89 in the earlier studies, and from ˛ = .63 to .91 in the present studies. 2.1.2.2. Depression Anxiety Stress Scales. The short version of the Depression Anxiety Stress Scales (DASS-21; Lovibond & Lovibond, 1995) is a 21-item self-report measure that yields three subscales: Depression, Anxiety (which primarily measures panic-like symptoms), and Stress. Individuals rate on a scale of 0 (Did not apply to me at all) to 3 (Applied to me very much, or most of the time) how much statements endorsing symptoms of depression, anxiety and stress applied to themselves over the past week. The DASS-21 has demonstrated good psychometric properties in clinical and nonclinical populations, with high internal consistency for each scale ranging from ˛ = .82 to .94 (Antony, Bieling, Cox, Enns, & Swinson, 1998; Henry & Crawford, 2005). In the present two studies, ˛ = .87 and .92 for Depression, ˛ = .75 and .86 for Anxiety, and ˛ = .84 and .89 for Stress. 2.1.2.3. Thought-Action Fusion Scale. The Thought-Action Fusion Scale (TAFS) is a 19-item questionnaire designed to measure the TAF construct in relation to OCD (Shafran et al., 1996). For each item, participants rate agreement on a 0 (Disagree Strongly) to 4 (Agree Strongly) scale. Factor analyses yielded three subscales in non-clinical undergraduate and community samples (Shafran et al., 1996). Questions that comprise the Moral subscale target the belief that thoughts are morally equivalent to action. The Likelihood-Other and Likelihood-Self scales assess the belief that thinking about something makes it more likely to happen, either to others or oneself. All subscales have good or excellent internal consistency in the normative data (˛ between .75 and .96 for all scales in all samples; Rassin, Merckelbach, Muris, & Schmidt, 2001; Shafran et al., 1996) and as observed in the present study2 (˛ = .92

2

The TAFS and RAS were only analyzed in Study 1.

J. Siev et al. / Journal of Anxiety Disorders 24 (2010) 893–899

for Moral, ˛ = .93 for Likelihood-Others, and ˛ = .88 for LikelihoodSelf). The wording of two questions that refer to obscene gestures, thoughts, or remarks in church was altered slightly to include other places of worship.

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What is the largest number of debilitating strokes caused by the drug at which the government should give the new drug to all patients? 0; 100; 200; 300; 400; 500; 600; 700; 800; 900; 1,000

2.1.2.4. Responsibility Attitude Scale. The Responsibility Attitude Scale (RAS) is a 26-item questionnaire that assesses attitudes or beliefs about responsibility (Salkovskis et al., 2000). Individuals indicate their agreement, on a 1 (Totally Agree) to 7 (Totally Disagree) scale, with statements about (inflated) responsibility. Salkovskis et al. (2000) reported excellent psychometric properties for the RAS in the validation study. Internal consistency in that study was ˛ = .92 and in the current study was .94. In this study, the RAS was scored so that higher scores indicate stronger endorsement of beliefs associated with OCD. Analyses were performed on the mean item score for each participant and therefore missing data were not imputed (N = 306 for the reliability analysis).

2.1.2.5. Scenarios. Participants were presented with 12 scenarios. Eight were composed of action and inaction variants of four hypothetical vignettes that were constructed such that participants imagined themselves as target individuals who cause or fail to prevent harm, and rated the degree to which they would be responsible. The four vignettes were designed with the intention of producing two each for contamination/washing and harm/checking. For example, the following is the commission variant of one contamination/washing scenario: You are walking with your young niece when her pacifier falls into a dirty puddle. You pick it up and give it back to her. The next day, your niece is sick. How responsible would you be for this outcome? (1–7) In contrast, following is the omission variant for that scenario: You are walking with your young niece when her pacifier falls into a dirty puddle. You put it in the back of the stroller. A few minutes later, you see her mother, who didn’t notice it fall, hand the pacifier back to her, and don’t say anything. The next day, your niece is sick. How responsible would you be for this outcome? (1–7) All scenarios are provided in Appendix A. The original questionnaire also included two vignettes designed to tap scrupulosity; these proved to have poor psychometric properties and were therefore eliminated. The difference between the responsibility rating in the commission and omission variants of each vignette was the measure of omission bias. The scenarios were presented to all participants in separate commission and omission blocks, separated by two self-report symptom measures, and participants were randomized to receive the commission or omission block first. Four additional scenarios were adapted from Baron and Ritov (2009), and measured relative preference for non-OCD-related harm by inaction over a lesser degree of harm of the same type caused by action. All were presented as dilemmas facing the government, such that a certain negative outcome is given if the government does nothing, but can be prevented by governmental intervention at the cost of other, similar harm. Participants indicated up until what cost the government should intervene. All scenarios are provided in Appendix A, and the following is one example: If the government does nothing, 1,000 emergency patients in government hospitals will suffer debilitating strokes. Giving a new drug to all emergency patients would prevent 1,000 debilitating strokes but would itself cause other debilitating strokes.

As in this example, all responses ranged from 0 to 100% of the default harm caused by inaction, and were presented in 10% increments. The ratio of the response choice over the total harm represents the degree of omission bias such that smaller ratios denote greater omission bias, and ratios that approach one signify relative utilitarianism, in which the individual makes a moral decision with the primary goal to maximize the utility of the overall outcome. The eight omission bias scores derived from the aforementioned scenarios (four commission–omission difference scores for the OCD-related scenarios; four ratios from the non-OCD-related scenarios) were subjected to a principal components analysis with varimax rotation. The Kaiser criterion and an examination of the scree plot converged to suggest a two factor solution. The first factor was composed of the scores for the four non-OCD-related scenarios (factor loadings > .75; all other factor loadings < .03). The second factor included the ratings of the four scenarios intended to measure omission bias related to contamination/washing and harm/checking (factor loadings > .57; all other factor loadings < .06). Single composite omission bias scores were calculated for each factor by averaging the ratios for the non-OCD-related scenarios and adding the difference scores for the OCD-related scenarios, yielding separate scores for (a) general, non-OCD-related omission bias (˛ = .79), and (b) contamination/washing and harm/checking omission bias (˛ = .78). 2.2. Results Preliminary analyses demonstrated that participants favored harm by omission to harm by commission, as evidenced by choices of government intervention in the general scenarios, and ratings of responsibility in the OCD-relevant ones. The mean composite omission bias score for the general scenarios was 0.46 (SD = 0.30), indicating that the group believed on average that the government should intervene only if their actions would cause less than half the harm that would result from inaction. The mean omission bias scores for each of the four general scenarios ranged from 0.37 to 0.50. Participants assigned more responsibility to acts of commission than omission for all OCD-relevant scenarios. The mean of the contamination/washing and harm/checking composite score (i.e., the sum of four difference scores between ratings of responsibility for commission and omission) was 3.94 (SD = 4.64), equivalent to a mean of 0.99 per difference score composing the summed composite. Means for individual OCD-relevant scenarios ranged from 0.46 to 1.23 (paired samples t-tests all significant, ps < .001). Means and standard deviations of symptom and cognitive measures were approximately consistent with normative data from similar, non-clinical samples. For OCI-R, M = 14.48, SD = 10.91; for TAFS-Moral, M = 10.44, SD = 8.91; for TAFS-Likelihood-Others, M = 2.01, SD = 3.03; for TAFS-Likelihood-Self, M = 2.30, SD = 2.82; for RAS, M = 4.45, SD = 1.00. 2.2.1. Correlations The primary purpose of this investigation was to examine whether omission bias is related to OCD symptoms. Of secondary interest was the relationship between omission bias and cognitions associated with OCD. Indices of omission bias were correlated with symptom and cognitive measures (Table 1). Analyses revealed that for washing and checking scenarios, omission bias was signifi-

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Table 1 Correlations (r) between indices of omission bias, OCD symptoms (OCI-R), and cognitive measures (TAFS, RAS). TAFS W/C-OB Washing/Checking Omission Bias (W/C-OB) General Omission Bias (G-OB) OCI-R-total TAFS-Moral TAFS-Likelihood-Others (L-O) TAFS-Likelihood-Self (L-S) RAS

–

G-OB

OCI-R

Moral

L-O

L-S

RAS

−.03 –

−.15** .09 –

−.19*** .04 .36*** –

−.23*** .03 .40*** .63*** –

−.21*** −.03 .35*** .55*** .67*** –

−.13* −.04 .34*** .49*** .37*** .35*** –

Note. OCI-R = Obsessive–Compulsive Inventory—Revised; TAFS = Thought-Action Fusion Scale; RAS = Responsibility Attitude Scale. * p < .05. ** p < .01. *** p < .001.

cantly, negatively associated with OCD symptoms, suggesting that individuals with more OCD symptoms were more likely to view acts of omission and commission as similar, although the effect was small. Omission bias for those scenarios was also negatively associated with TAF, as evident from all three TAFS subscales, and inflated responsibility, as measured by the RAS. General omission bias was not associated with any symptom or cognition measure. To evaluate specificity of these findings to OCD symptoms, OCIR scores were simultaneously entered with all three DASS-21 scales (Depression, Anxiety, and Stress) as predictors of omission bias for washing and checking. Regression diagnostics examining potential measures of influence, multicollinearity, and heteroscedasticity were not concerning. None of the scales independently predicted omission bias. The effect of Anxiety was a non-significant trend (ˇ = −.15, t [326] = −1.76, p = .08), and the other scales were nonsignificant (for OCD, ˇ = −.05, t [326] = −0.72, p = .47; for Depression, ˇ = .05, t [326] = 0.73, p = .46; for Stress, ˇ = −.02, t [326] = −0.26, p = .80). Hence, there does not appear to be a specific relationship between omission bias and OCD symptoms in a non-clinical sample. 2.2.2. Semi-idiographic presentation Post hoc analyses were conducted to investigate further the extent to which omission bias was associated with participants’ semi-idiographic OCD presentation. Indices of omission bias relevant to washing and checking were separately correlated with the OCI-R washing and checking subscales (which correlated with each other, r = .56, p < .001). Thus, two theoretically derived omission bias indices (washing and checking) were constructed from the previously described scenarios, without combining the washing and checking scenarios. These analyses revealed that omission bias for checking was slightly more strongly related both to OCIR washing (r = −.15) and checking (r = −.16) than was omission bias for washing (r = −.11 and −.09 for OCI-R washing and checking, respectively). Overall, there was little evidence to suggest a unique relationship between idiographic symptom presentation and domain of omission bias. 2.3. Summary Results of Study 1 indicate that OCD symptoms were associated with less omission bias for scenarios relevant to typical OCD concerns in a non-clinical sample, but not general omission bias. The magnitude of the overall effect was small, however, and did not remain significant when controlling for anxiety, stress, and depression. It is possible that the correlation would be larger and more robust in a clinical sample.

3.1. Method 3.1.1. Participants Clinical participants were recruited from various internet support groups and organizations for OCD,3 and had the option of entering a raffle for a $25 gift certificate for their participation via the internet. A comparison group of participants were recruited from a pool of individuals who had previously agreed to be contacted about judgment and decision making research participation opportunities, and were each compensated $3 for their participation via the internet. Missing data were handled as in Study 1. The following criteria were set to increase the likelihood that participants in the OCD group in fact had OCD and those in the comparison group did not. Classification in the OCD group required self-identification as having OCD and a score of 4 on at least one non-hoarding item on the OCI-R. A score of 4 on at least one item appears to be the most sensitive and specific decision-rule to identify OCD patients based on the OCI-R (J. Wood, personal communication, February 25, 2007), and the requirement of a nonhoarding item follows recent empirical evidence and theory that call into question the categorization of hoarding as an OCD subtype (cf. Rachman, Elliott, Shafran, & Radomsky, 2009; Saxena, 2007). In contrast, classification as non-OCD required self-identification as not having OCD and no score of 4 on any OCI-R item (conservatively including hoarding items). In total, 103 participants with OCD and 106 participants without OCD composed the sample. The mean age of the entire sample was 37.23 (SD = 11.85), and 79% of the participants were female. Approximately 88% were White, 5% Asian or Asian-American, and 7% other or unknown. 3.1.2. Measures The study procedure was identical to that in Study 1 (see Section 2.1.2 for descriptions of symptom measures, including internal consistency in both samples). 3.1.2.1. Scenarios. Participants were presented the same scenarios described in Study 1 (see Section 2.1.2.5). The result of a principal components analysis of the omission bias scores was similar to that in Study 1. Again, the Kaiser criterion suggested a two factor solution, although examination of the scree plot was also consistent with a possible three factor solution. Because the Eigenvalue for the third factor was small (0.78) and the two factor solution was consistent with Study 1, the Kaiser criterion was utilized. In this sample, the first factor was composed of the scores for the four non-OCD-related scenarios (factor loadings > .74; all

3. Study 2 The aim of Study 2 was to extend Study 1 to an OCD population.

3

A complete list of which is available upon request from the first author.

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Table 2 Means (standard deviations), test statistics, and effect sizes for symptom measures and demographics by group. OCD group OCI-R-total DASS-21-Depression DASS-21-Anxiety DASS-21-Stress Age % Female

35.57 (13.33) 11.32 (5.29) 9.23 (4.76) 13.42 (4.22) 31.27 (9.18) 79%

Non-OCD group 9.52 (8.81) 4.32 (4.13) 2.77 (3.13) 5.59 (3.69) 43.12 (11.27) 80%

t (p)

Effect size (d)

16.71 (<.001) 10.69 (<.001) 11.63 (<.001) 14.30 (<.001) −7.79 (<.001)

2.31 1.48 1.61 1.98 −1.15

Note. OCI-R = Obsessive–Compulsive Inventory—Revised; DASS-21 = Depression Anxiety Stress Scales.

other factor loadings < .12). The second factor included the ratings of the four scenarios intended to measure omission bias related to contamination/washing and harm/checking (factor loadings > .61; all other factor loadings < .15). Internal consistency for the composite scores were ˛ = .82 for general, non-OCD-related omission bias, and ˛ = .78 for contamination/washing and harm/checking omission bias. 3.2. Results Means, standard deviations, and between-groups comparisons for symptom measures are presented in Table 2. As expected, the OCD group scored significantly higher than did the non-OCD group on symptom measures, and the effects were large. The OCD group was also significantly younger than the non-OCD group. However, age was not a significant predictor of omission bias scores when entered with OCD group status, nor was it significantly correlated with omission bias scores within either group (rs < .08, ps > .46), suggesting that group differences in omission bias are not attributable to differences in age. 3.2.1. Between-groups analyses The OCD group scored significantly lower than did the non-OCD group on the composite omission bias difference score for washing and checking scenarios, t (207) = −3.03, p = .003, with an effect size approaching medium in magnitude, d = −0.42. The groups did not differ significantly on general omission bias and the effect size was small, t (207) = 1.05, p = .30, d = 0.15. Considering that participants were categorized on the basis of OCD status, the present between-groups comparisons do not easily lend themselves to an examination of the association between omission bias and cognitions, and the TAFS and RAS were therefore not evaluated in Study 2. Because the groups differed on both OCD and other symptom measures, a follow-up analysis was run to evaluate the specificity of the between-group differences to OCD symptoms. In general, correlational analyses based on the combination of two samples can be misleading; however, inspection of the correlations between omission bias and symptom measures for the samples separately and combined, as well as examinations of the scatterplots, indicated a similar pattern in both samples (although correlations were somewhat smaller in magnitude in the non-clinical sample, probably because of restricted range). Therefore, scores on the OCI-R and all three DASS-21 scales (Depression, Anxiety, and Stress) were entered as simultaneous predictors of washing and checking omission bias to evaluate which symptoms were specifically associated with omission bias. Regression diagnostics were again not concerning. OCD and Anxiety symptoms significantly and independently predicted omission bias (for OCD, ˇ = −.24, t [203] = −2.14, p = .03; for Anxiety, ˇ = −.25, t [203] = −2.19, p = .03). The effect of Stress was a non-significant trend (ˇ = .21, t [203] = 1.72, p = .09), and Depression was non-significant (ˇ = −.02, t [203] = −0.18, p = .86). Hence, OCD and anxiety symptoms both appear to predict omission bias in this sample.

3.2.2. Semi-idiographic presentation For participants who reported having OCD, post hoc analyses were conducted to investigate further the extent to which omission bias was associated with semi-idiographic OCD presentation. As in Study 1, theoretically derived indices of omission bias relevant to washing and checking were separately correlated with the OCI-R washing and checking subscales (which correlated with each other among individuals who reported having OCD, r = .39, p < .001). Correlational analyses between omission bias and symptom scales indicated that checking symptoms were more highly correlated with both omission bias scales (r = −.20 for washing, and r = −.21 for checking omission bias), than were washing symptoms (rs = −.08 for both washing and checking omission bias). Hence, there is no evidence of specificity in terms of the relevance of idiographic concerns to judgments of omission bias in a self-identified clinical sample. 3.3. Summary In Study 2, individuals with OCD evinced less omission bias for scenarios relevant to typical OCD concerns than did a comparison group. The magnitude of the difference was almost moderate in size, and OCD symptoms predicted washing and checking omission bias independent of anxiety, stress, and depression. 4. Discussion The main purpose of this investigation was to examine the relationship between OCD symptoms and omission bias. The general tendency to favor acts of harm by omission to similar, or even smaller, acts of harm by commission is characteristic of most people. However, individuals with OCD seem to judge the failure to prevent harm as similar to causing harm actively. We sought to evaluate whether OCD symptoms are associated with less omission bias (a) in general, (b) only when relevant to typical OCD concerns (but not contingent upon idiographic fears), (c) only when related to idiographic concerns (e.g., contamination for washing symptoms), or (d) none of the above. Results of these studies support the second hypothesis, that OCD symptoms are related to less omission bias when relevant to typical OCD concerns. In Study 1, with a student population, symptoms of OCD were negatively associated with omission bias about washing and checking scenarios targeting common OCD fears. Moreover, TAF and inflated responsibility were also correlated negatively with omission bias about those scenarios. The magnitudes of these effects, however, were small. In contrast, neither symptoms nor cognitions related to OCD were associated with general omission bias. In Study 2, individuals who reported having OCD evinced less omission bias about washing and checking scenarios. The magnitude of the difference between individuals with and without OCD was moderate. Again, general omission bias was not related to OCD. In a non-clinical sample, the relationship between washing and checking omission bias and OCD symptoms was eliminated after controlling for symptoms of depression, anxiety, and stress. Indeed, none of the scales independently predicted omission bias

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for washing and checking when entered simultaneously, although the effect of anxiety was a non-significant trend. In a clinical sample, however, both OCD and anxiety symptoms remained significant predictors accounting for unique portions of the variance when other symptom measures were controlled. This analysis suggests a specific association between OCD symptoms and omission bias about washing and checking. It points, as well, to a specific relationship between panic-related somatic anxiety symptoms and omission bias about those scenarios, which was unexpected and is worthy of future attention. Anxiety is a core feature of OCD and symptoms of anxiety may account for some variance due to OCD symptoms. Future research comparing individuals with OCD and other anxiety disorders could elucidate this result. Wroe and Salkovskis (2000) demonstrated that people with OCD distinguished less than others between variably premeditated inactions that could cause harm, but only for scenarios they found most distressing. On the basis of that study, the authors concluded that omission bias is related to OCD only in the domains of particular OCD fear. There is a difference, however, between premeditated acts of omission and acts of commission, and it is possible that people with OCD distinguish less than others between harm caused passively (even if intentionally) and actively for other scenarios, as well. Indeed, in general, individuals tend to favor intentional, passive harm to similar active harm. Results of this investigation partially, but not entirely, support the conclusions of Wroe and Salkovskis (2000). In these studies, there was also no evidence for a relationship between OCD symptoms and general omission bias. However, there was an association between OCD symptoms and omission bias for washing and checking scenarios that, although representing typical OCD fears, were not specific to participants’ self-reported, semi-idiographic concerns. Furthermore, examination of OCI-R washing and checking subscales and omission bias for washing and checking scenarios (separately) did not reveal a differential effect based on type of symptom presentation and type of omission bias scenario. It is also worthy of note that Franklin et al. (2009) found a positive association between inflated responsibility and the tendency to prefer harm by omission versus harm by commission. Essentially their findings suggest a positive relationship between inflated responsibility and general omission bias, which stands in contrast with Study 1, in which inflated responsibility was negatively correlated with omission bias about washing and checking, and unrelated to general omission bias. Further investigation is necessary to account for this discrepancy. We referred to cognitive models of OCD (e.g., Rachman, 1997; Salkovskis, 1985; see Section 1) and suggested there may be utility in examining omission bias in that context. In particular, compulsive behavior can often be understood as stemming from the tendencies to attribute importance to thoughts, and to view harms by action and inaction as equivalent and oneself as responsible. Together these beliefs may motivate the individual with OCD to respond actively in some way to distressing obsessions. Hence, efforts to elucidate the role of omission bias in OCD may shed light on processes that maintain the disorder and may have treatment implications (e.g., unhelpful judgments are a potential target in cognitive therapy). Such a model suggests a complex interplay between cognitive and meta-cognitive tendencies that include TAF, omission bias, and inflated responsibility. These tendencies may be additive or interactive. One possibility is that a general belief that thoughts are equivalent to actions (i.e., TAF) causes one to view failure to prevent anticipated harm as similar to actively causing it (i.e., less omission bias). One may then perceive oneself to be responsible to prevent such harm (i.e., inflated responsibility) either as a direct consequence of believing that failing to do so would be equivalent to causing it or for other reasons. Together these factors may bridge the gap between an unpleasant intrusive thought and a compul-

sion. The directions of effects are unclear, however. In fact, Wroe and Salkovskis (2000) suggest that inflated responsibility leads to decreased omission bias, rather than vice versa. Future studies utilizing structural equation modeling may shed light on the potential causal chain involved in these processes, particularly with respect to omission bias. There are several caveats worthy of consideration in interpreting these findings. First, there are differences other than domain of harm between the scenarios designed to measure general omission bias and those constructed for OCD-relevant situations. One difference is that the former require prospective judgments, whereas the latter solicit post hoc responsibility ratings. Although previous research has revealed a sizable correlation between decisions about choosing harm by action versus inaction, and judgments about guilt for having caused harm after the fact (e.g., Baron, 1992), OCD symptoms may relate most strongly to feelings of guilt and responsibility for harm caused. This is especially likely considering a second difference: In the general scenarios, nothing could have been done to prevent harm altogether, whereas in the OCD-relevant scenarios, the actor could have prevented all harm that the actor could have anticipated. Certainly inflated responsibility about harm that could have been prevented is particularly characteristic of OCD (e.g., Salkovskis, 1996). A third difference is that the scenarios designed to measure general omission bias solicited judgments about how the government should act, whereas the OCD-relevant scenarios were personal and individual. Recommendations about governmental behavior could be influenced by political beliefs, although there is no reason to expect that such political beliefs differ by OCD symptom level. Second, in some scenarios there may have been a ceiling effect on participants’ ratings of responsibility for commissions, which could have limited the magnitude and range of commission–omission differences in those scenarios. Third, absent diagnostic interviews, the clinical status of participants who identified themselves as having OCD cannot be certain. Nonetheless, it is advantageous that the sample was not restricted to those who seek treatment as is often the case in psychopathology research, in that those seeking treatment may be atypical of the population of people with OCD at large. Fourth, because all variables were evaluated at the same time point, one cannot make a causal inference regarding the role of omission bias in leading to OCD symptoms or the functions of TAF and inflated responsibility. Unless the variables are assessed such that they follow each other temporally, their designation as independent and dependent variables is theory-driven but speculative. Overall, future research is required to replicate and extend these findings. Promising avenues might include (a) the use of various measures of omission bias, (b) attention to the role of inflated responsibility as minimizing or exaggerating the tendency to prefer inaction even when it results in greater harm than action, and (c) examination of the apparent relationship between panic-like symptoms of anxiety and omission bias. Studies employing behavioral measures of omission bias could be particularly useful in avoiding artifacts of scenario construction and limitations of selfreported ratings. Acknowledgment The authors wish to thank Jonathan Baron for helpful comments on, and suggestions about, constructing the scenarios and considering the data. Appendix A. Note: For the washing and checking scenarios, the commission variant is presented first, followed by the omission variant. Partici-

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pants were instructed to imagine themselves in each situation and, following each scenario, rated: “How responsible would you be for this outcome?” on a 1 (Not Responsible) to 7 (Completely Responsible) scale. Washing and Checking Scenarios 1. a. You have the flu and sneeze into your right hand. Moments later your friend introduces you to someone who extends her right hand to shake yours. You accept it. Later you find out that the new acquaintance is in bed with the flu. b. Your friend has the flu and sneezes into her right hand. Moments later you introduce someone to your friend and that person extends her right hand to shake your friend’s. You don’t say anything. Later you find out that the other person is in bed with the flu. 2. a. You are walking with your young niece when her pacifier falls into a dirty puddle. You pick it up and give it back to her. The next day, your niece is sick. b. You are walking with your young niece when her pacifier falls into a dirty puddle. You put it in the back of the stroller. A few minutes later, you see her mother, who didn’t notice it fall, hand the pacifier back to her, and don’t say anything. The next day, your niece is sick. 3. a. You are getting ready to leave the house for the evening when you remember that you lit a candle upstairs. You decide not to do anything about it and just leave. A few hours later you return to find the house damaged by a fire that started from the candle. b. You are getting ready to leave the house for the evening and you have a feeling that someone might have lit a candle upstairs. You decide not to do anything about it and just leave. A few hours later you return to find the house damaged by a fire that started from a candle. 4. a. You are reading a book before going to sleep when you remember having left a window on the ground floor open earlier in the evening. You decide not to do anything about it and just continue reading. When you go downstairs in the morning you find that someone has burgled the front room of the house. b. You are reading a book before going to sleep and you have a feeling that someone might have left a window on the first floor open earlier in the evening. You decide not to do anything about it and just continue reading. When you go downstairs in the morning you find that someone has burgled the front room of the house. General Scenarios (adapted from Baron & Ritov, 2009) 1. If the government does nothing, 1,000 emergency patients in government hospitals will suffer debilitating strokes. Giving a new drug to all emergency patients would prevent 1,000 debilitating strokes but would itself cause other debilitating strokes. What is the largest number of debilitating strokes caused by the drug at which the government should give the new drug to all patients? 0; 100; 200; 300; 400; 500; 600; 700; 800; 900; 1,000 2. If the government does nothing, 20 fish species will become extinct due to naturally changing water levels. Building a dam would save 20 species of fish above the dam but cause other species to become extinct downstream. What is the largest number of species extinctions caused by the dam at which the government should build the dam? 0; 2; 4; 6; 8; 10; 12; 14; 16; 18; 20 3. If the government does nothing, 500 airline passengers will die from an accidental guided missile attack on a large jet. Directing

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a second jet into the path of the missile, to take the hit, would save the 500 passengers but cause other passenger deaths. What is the largest number of passenger deaths in the second jet at which the government should direct the second jet into the missile’s path? 0; 50; 100; 150; 200; 250; 300; 350; 400; 450; 500 4. If the government does nothing, 10,000 people will die from a new form of flu. A vaccine that causes a weaker form of flu will prevent these flu deaths by creating immunity, but the vaccine itself will cause other flu deaths. What is the largest number of flu deaths from the vaccine at which the government should vaccinate all those at risk? 0; 1,000; 2,000; 3,000; 4,000; 5,000; 6,000; 7,000; 8,000; 9,000; 10,000 References Antony, M. M., Bieling, P. J., Cox, B. J., Enns, M. W., & Swinson, R. P. (1998). Psychometric properties of the 42-item and 21-item versions of the Depression Anxiety Stress Scales in clinical groups and a community sample. 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