International Journal of Cognitive Therapy, 2(2), 188–205, 2009© 2009 International Association for Cognitive Psychotherapy

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AARDEMA ET AL.QUANTIFICATION OF DOUBT

The Quantification of Doubt in Obsessive-Compulsive DisorderFrederick AardemaFernand-Seguin Research Center, Montreal Concordia University, Montreal University of Montreal

Kieron P. O’ConnorFernand-Seguin Research Center, Montreal University of Montreal

Marie-Claude Pélissier and Marc E. LavoieFernand-Seguin Research Center, Montreal

Obsessive-Compulsive Disorder (OCD) is a debilitating psychiatric disorder char-acterized by high levels of pathological doubt. The current article investigates the cognitive process of doubt in OCD as the dynamic interplay between the impact of possibility and reality-based information. An experimental reasoning task was designed to measure changes in level of doubt by alternately presenting participants with possibility and reality-based information. People with OCD were hypoth-esized to be more affected by possibility-based information leading to higher levels of doubt. Results confirmed these expectations, and showed that as compared to nonclinical controls, those with OCD were more affected by possibility-based in-formation. The impact of possibility-based information, and levels of doubt, related robustly to symptom severity. As expected, the relationship between the impact of possibility and symptom severity could be explained by inferential confusion, but not by any other cognitive domains, thereby confirming the convergent validity of the current experimental manipulation.

Obsessive-Compulsive Disorder (OCD) is a debilitating psychiatric problem caus-ing the sufferer to perform time-consuming physical or mental rituals aimed at neu-tralizing anxiety-provoking thoughts about harm to self or others. It is often referred to as “the doubting disease,” and for good reason, because obsessions almost always take the form of a doubt (Janet, 1903). For example, the person leaves the house, and

The study was supported with a Fellowship Award from the Fonds de la Recherche en Santé Québec (FRSQ) to the first author and Grant No. MOP67059 from the Canadian Institutes of Health Research (CIHR) to the second and fourth author. We would also like to thank the associate editor Dr. David A. Clark and the anonymous reviewers for their helpful comments and suggestions in the preparation of the final manuscript.Address correspondence to Frederick Aardema, Centre de Recherche Fernand-Seguin, 7331 Hochelaga, Montréal, Québec H1N 3V2, Canada. E-mail: faardema@crfs.rtss.qc.ca

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then thinks: “I might have left the door unlocked,” or alternatively, the person touches a pole in the train, and then thinks: “I might have been contaminated.” Consequently, the person engages in various forms of compulsive behavior like frequent washing or checking in order to neutralize the distress caused by the doubt.

Although cognitive theories have noted the presense of doubt as a factor in main-taining OCD (Dar, Rish, Hermesh, Taub, & Fux, 2000; Van den Hout & Kindt, 2003a, 2003b), it has so far not been systematically explored, or indeed, operational-ized as a distinct process in OCD. Typically, cognitive theories of OCD emphasize the role of beliefs (i.e., intolerance to uncertainty, inflated responsibility, need for control), or faulty information processing (i.e., attentional bias, problems with error detection, reality monitoring ability) in exacerbating anxiety (see Frost & Steketee, 2002). But doubting is distinct from information gathering, or the inability to tolerate future uncertainty. In doubt, information that is already acquired is put into question. In-deed, those with OCD have a tendency to be much more influenced than nonclinical controls when faced with given alternative conclusions during inductive reasoning (Pélissier & O’Connor, 2002; Pélissier, O’Connor, & Dupuis, 2008).

One approach to understanding obsessional doubt is to view it as a product of prior reasoning (see O’Connor, Aardema, & Pélissier, 2005). In particular, the rea-soning that gives rise to obsessional doubts is often highly subjective in nature. The person with OCD may see the door is locked, yet he/she continues to doubt on the basis of possibilities that support the notion that the door still might be open (e.g., Perhaps there is dust in the lock making it not work properly; I felt the door lock, but perhaps I did not turn the key sufficiently). In other words, people with OCD distrust reality—the world of the senses—and favor subjective possibilities that negate the senses. Cognitive confidence may be compromised as well, where the person distrusts perception, memory, and attention (Hermans et al., 2008). These two inferential com-ponents; dismissing reality and favoring hypothetical possibilities (i.e., the obsessional doubt), together constitute an inferential confusion where the person gives credibility to a possible state of affairs even though contradictory evidence is coming through the senses.

The concept of inferential confusion has to be differentiated from threat-related appraisals or beliefs. Of course, threat is an inherent part of obsessions, and as such inferential confusion often pertains to threat-related inferences. As a process, however, inferential confusion is distinct from threat, since it specifically deals with the highly subjective manner in which threat-related inferences come about in OCD. Even if obsessions often contain threat (e.g., I might be in danger . . . ), it is only the element of inferential confusion that is particularly relevant to OCD (e.g., I might be in dan-ger . . . even though I see and sense nothing to support it). Indeed, empirical data has shown that inferential confusion is factorially distinct from overestimation of threat, and relates independently to obsessive-compulsive symptoms in an OCD sample (Aar-dema, O’Connor, & Emmelkamp, 2006). A more recent study in a nonclinical sample found items from the inferential confusion to conglomerate with a limited amount of threat-related items reminiscent of inferential confusion (e.g Even when I’m careful ac-cidents may happen) (Aardema, Radomsky, O’Connor, & Julien, 2008). Once again, however, inferential confusion was independently related to obsessive-compulsive symptoms while controlling for overestimation of threat (and responsibility).

Since the early conceptualizations of an inference-based approach to OCD (O’Connor & Robillard, 1995, 1999; O’Connor, 2002; see also Aardema & O’Connor, 2003, 2007), the concept of inferential confusion, and its particular relevance to OCD,

190 AARDEMA ET AL.

has been supported in a number of different empirical studies. Psychometric studies in both clinical and nonclinical samples have consistently shown moderate to strong relationships between inferential confusion and obsessive-compulsive symptoms inde-pendently of negative mood states and other belief measures (Aardema, Kleijer, Trihey, O’Connor & Emmelkamp, 2006; Aardema, O’Connor, Emmelkamp, Marchand, & Todorov, 2005; Aardema, Radomsky, et al., 2008; Emmelkamp & Aardema, 1999; Wu, Aardema, & O’Connor, in press). In fact, inferential confusion as a process is able to substantially account for relationships between obsessive beliefs (as measured by the Obsessive Belief Questionnaire; OBQ) and obsessive-compulsive symptoms, while obsessive beliefs are unable to account for the relationship between inferential confusion and OCD symptoms (Aardema, O’Connor et al., 2006). In addition, those with OCD score significantly higher on inferential confusion than those with another anxiety disorder suggesting inferential confusion is particularly relevant to OCD (Aar-dema, O’Connor, et al., 2005). Indeed, change in inferential confusion predicts suc-cessful treatment outcome in those with OCD (Aardema, Emmelkamp, & O’Connor, 2005; Aardema, Wu, et al., 2008). Most crucially, a small-scale clinical trial showed that inference-based therapy is more effective than traditional cognitive behavior ther-apy if there is a strong investment in the obsessional doubt (O’Connor, Aardema, Bouthillier, et al., 2005). Experimental studies have also supported a role of reasoning in the generation of obsessional inferences. In particular, that those with OCD tend to doubt more after generating reasons in favor of a possible state of affairs, and rely on more remote information when reaching a conclusion (Pélissier & O’Connor, 2002; Pélissier, O’Connor, et al., in press). Likewise, unlike cognitive intrusions found in the normal population, obsessions are reported to occur more frequently out of context, and without any direct link to sense data to support the doubt (O’Connor, Julien, and Aardema, 2006; Julien, O’Connor, & Aardema, 2009).

While the generation of possibilities during subjective forms of reasoning can certainly have an adaptive and creative purpose, problems arise when possibility-based information weighs down too heavily and negates one’s sense of reality. In particular, in the case of OCD, one would expect an overall higher impact of possibility at the expense of reality during reasoning. For example, a person with OCD who sees the door is locked, while investing in the possibility that the lock might be broken, will end up with a high level of doubt that the door is properly locked. Indeed, several key parameters can be derived from a possibilistic model of obsessional doubting (see O’Connor & Aardema, 2005). Firstly, there is the combined impact of possibility and reality-based information on level of doubt. Secondly, there is the separate impact of possibility and reality-based information on level of doubt. Thirdly, there is the evo-lution of doubt over time as an individual considers reality and possibility-based in-formation. These parameters are measurable within an experimental task designed to assess the impact of possibility and reality on reasoning in both OCD and non-OCD populations. Predictions would be: (1) People with OCD doubt more than nonclinical controls after considering reality and possibility-based information; (2) People with OCD will rely more on possibility-based information as compared to nonclinical con-trols, leading to higher levels of doubt for those with OCD; and (3) The impact of possibility-based information, and levels of doubt will relate significantly to OCD severity.

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meThod

Participants

OCD Group. Participants in the OCD group were recruited through referrals to our research clinic, followed by a two-stage process using telephone screening inter-views and by initial questionnaires returned by post. Baseline diagnosis used three structured interviews to provide adequate description of clinical features. First, all patients were diagnosed using the Anxiety Disorders Interview Schedule for DSM-IV, a structured interview that diagnoses anxiety disorders and exclusionary conditions (Brown, DiNardo, & Barlow, 1994). Second, participants were administered the clini-cian version of the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS; Goodman, Price, Rasmussen, Mazure, Delgado, et al., 1989; Goodman, Price, Rasmussen, Mazure, Fleischman et al., 1989). Positive response to any of these screens led to use of appro-priate sections of the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I; Spitzer, Williams, Gibbon, & First, 1991) to complete the differential diagnosis. Entry criteria were: (a) a primary diagnosis of OCD, (b) no evidence of suicidal in-tent, (c) no evidence of current substance abuse, and (d) no evidence of current or past schizophrenia, bipolar disorder, or organic mental disorder. The final group consisted of fifty participants (26 males, 24 females). The average age was 37.8 years (SD = 10.8; range 19-64). All major subtypes of OCD, including those with either overt or covert symptoms were represented in the total sample. Educational levels were distributed as follows: 2.8% primary education, 22.2% secondary education, 30.6% post-secondary preparatory college (CEGEP), and 44.4% university education. The marital status of participants was as follows: 52.8% married or cohabitating, 22.2% single, 16.7% separated/divorced, and 8.3% widowed.

Nonclinical Controls. Participants in the nonclinical group were recruited from several sites (hospital staff, university students, working population) by advertising in the employee newspaper of the hospital staff on site, as well as announcements on public boards of three major universities and then screened by questionnaire. The nonclinical group consisted of a total of 22 participants (5 males, 17 females). Aver-age age was 39.6 (SD = 14.8; range 20-69). Educational levels were as follows: 4.5% primary education, 27.3% secondary education, 27.3% 30.6% post-secondary prepa-ratory college (CEGEP), and 40.9% a university education. Marital status was: 40.9% married or cohabiting, 36.4% single, and 22.7% divorced or separated. Comparing the demographic variables of the nonclinical controls with the OCD group revealed an overall difference in gender distribution (p < 0.05). However, no differences were found on any of the other demographic variables.

measures

The Inference Processes Task was specifically designed for the current study to measure changes in level of doubt on the basis of reality and possibility-based information. It builds on formal reasoning tasks investigating doubt in OCD where as task introduc-ing alternative possibilities to a logical conclusion proved to be a useful analogue to inducing doubt in both OCD and control subjects (Pélissier & O’Connor, 2002; Pélissier et al., 2009). In particular, the current task represents an ecologically valid analogue of OCD, which measured doubting as an ongoing, dynamic process, rather

192 AARDEMA ET AL.

than by one static measurement as in previous reasoning tasks. During the task, the person was presented with two written scenarios leading up to a particular inference. The first scenario consisted of a semi-typical OCD-related narrative, which related the possibility that he/she may have caused an accident while driving a car across a busy intersection.

OCD relevant scenario: You’re on your way to work with the car. This morning you read about an accident where a truck driver unknowingly drove over someone, and left the scene of the accident without realizing. You wonder how it is possible that someone could not notice this while driving. As you drive along, you come across an intersection and come to a halt at the stoplight. It is quite busy, with a lot of people on the other side of the intersection waiting to cross the street. You notice a group of young people, boys and girls, chasing each other, running on and off the street. As the light turns green you start to accelerate. Then, just as you pass the intersection you hear a scream and feel a bump!

The second scenario was a non-OCD related narrative, which related the possibility that there may be a bus strike while waiting for a bus. It was chosen specifically for being unrelated to any typical, or even semi-typical, OCD related worry.

Non-OCD relevant scenario: You are on your way to a restaurant for an evening out with your friends. You have decided to take the bus to save some money even though the possibility of a bus strike was announced on the news yesterday. Once you arrive at the bus stop you wait for 20 minutes with several people standing beside you and still no bus has arrived. Then you overhear something about “a strike.” Soon afterwards most of the people around you disappear.

Following each of these scenarios, the person was asked to rate how anxious they would feel if the scenario would really occur on a scale ranging from 0 to 100 (How anxious would you feel in the above situation using the following scale?). In addition, following the presentation of the OCD-related scenario, the participant was asked to rate the probability that an accident had occurred on a scale from 10 to 100 (What do you consider to be the probability that an accident has happened under these cir-cumstances using the following scale?). Likewise, following the presentation of the non-OCD relevant scenario, the participant was asked to rate the probability that there was a bus strike on a scale ranging from 10 to 100. (What do you consider to be the probability that there is a bus strike under these circumstances using the following scale?). Higher scores thus indicated a greater level of doubt with regards to the idea that no accident had happened, or that there was no bus strike.

These initial scores formed the baseline for the subsequent manipulation of level of doubt regarding a state of affairs in reality by introducing separate pairs of reality and possibility-based information. For example, after rating the probability concern-ing the occurrence of an accident in the OCD relevant scenario, the person was pre-sented with a separate piece of reality-based information congruent with the idea that no accident had happened (R1): You look in your rear view window and see a pothole in the street. Next, the participant again rated the probability concerning the idea of an ac-cident having occurred while taking into account this reality-based information. Then, the participant was asked to turn the page and presented with a piece of possibility-based information (P1) that could potentially negate the previous piece of reality-based information: Perhaps the pothole wasn’t deep enough to have caused the bump you felt earlier. And once again, the person was asked to rate the probability of an accident

QUANTIFICATION OF DOUBT 193

having occurred. This process was repeated up to presenting the participant with two additional pairs of reality and possibility-based information (R2, P2, R3, P3) in both the OCD related and neutral scenario (see Table 1):

The sequence of each three pairs of reality and possibility-based information was alternated with each participant using six separate versions of the questionnaire. So while each pair of reality and possibility-based information was kept intact, the order of the pairs was alternated in different versions of the questionnaire. Different versions of the questionnaires were alternated consecutively for each new participant.

The Inferential Confusion Questionnaire (ICQ; Aardema, O’Connor, et al., 2005) is a 15-item questionnaire measuring a tendency to negate reality in favor of a hypo-thetical possibility. Typical items include: “I often know a problem exists even though I don’t have visible proof ”; “I am sometimes more convinced about what might be there than by what I actually see”; “Even if I don’t have any actual proof of a certain danger, my imagination can convince me otherwise.” Items are rated on a 5-point scale (1 = strongly disagree to 5 = strongly agree). The ICQ is a unidimensional measure that has been validated in nonclinical and clinical populations with people with OCD scoring significantly higher than anxious and nonclinical controls. As well, inferential confusion as measured by the ICQ was related to treatment outcome while showing divergent validity with measures of general distress (Aardema, Emmelkamp, & O’Connor, 2005). The scale possesses good inter-item reliability (Cronbach’s α = 0.85).

The Padua Inventory (PI; Sanavio, 1988) is a self-report measure that consists of 60 items that measures both classic compulsive checking and cleaning behavior as well as various types of obsessions, including impulsions. Items are rated on a 5-point scale (0 = not at all to 4 = very much), according to the degree to which respondents are disturbed by the given thought or behavior (e.g., “I find it difficult to touch garbage or dirty things”). Studies with the PI have reported good reliability for the total scale (α = .90-0.94) as well as convergent and discriminant validity with high correlations with other measures of OCD and moderate correlations with anxiety and depression (Sanavio, 1988, Sternburger & Burns, 1990; Van Oppen, 1992).

The Beck Depression Inventory-II (BDI; Beck, Steer, & Garbin, 1988) is a 21-item measure designed to assess the severity of depressive symptoms experienced by re-

TABLE 1. Pairs of Reality and Possibility-Based Information in the OCD Relevant and Non-OCD Relevant Scenario.

OCD relevant scenario Non-OCD relevant scenario

R1 “You look in the rear-view mirror and see a pothole in the road.”

“At the end of the street you see a bus driving on what appears to be a different route.”

P1 “The pothole may not have been deep enough to cause the bump.”

“Maybe the bus was out of service since you could not see whether there were any people in it.”

R2 “You turn your head and see no one lying on the street.”

“A person tells you he took the bus earlier in the day.”

P2 “You may not have seen everything, because it’s quite crowded.”

“The strike may have only started later in the day.”

R3 “You watch the expressions on people’s faces and see no emotion that might indicate an accident.”

“You call the information service and get an auto-mated message with no mention of any strike.”

P3 “The lack of expression in people’s faces may have been shock.”

“Maybe the bus company doesn’t give out this type of information that quickly.”

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spondents during the two weeks previous to completion. The BDI is a reliable (α = .92) and valid measure (Beck, Steer, & Garbin, 1988)

The Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988) is a 21-item anxiety symptom checklist rating symptom intensity for the last week on a 0-3 scale. The original instrument shows high internal consistency (α = 0.91), good test-retest reliability (r = 0.75), moderate convergent validity (r = 0.51) and good discriminant validity (r = 0.25) (Beck, Epstein, et al., 1988).

The Obsessive Belief Questionnaire—44 (OBQ-44; Obsessive Compulsive Cog-nition Working Group, 2005) has been developed collaboratively by the Obsessive Compulsive Cognition Working Group (OCCWG). The OBQ-44 assesses belief domains considered relevant to OCD, and consists of three subscales, namely (1) Responsibility/Threat; (2) Perfectionism/Certainty and 3) Importance/Control. The subscales are reliable (alpha 0.89-0.93), and significantly predict OCD symptomatol-ogy (OCCWG, 2005).

ResulTs

mean scores and standard deviations on Questionnaire measures in the groups

Means and standard deviations of the questionnaires in the OCD group and nonclini-cal control group are shown in Table 2.

TABLE 2. Mean scores and Standard Deviations of Questionnaire Measures

OCD Group (n = 50) Non-Clinical Controls (n = 22)

Mean SD Mean SD

Padua Inventory 84.99 43.49 22.05 11.26

-Contamination 17.30 12.22 6.50 3.58

-Checking 14.65 9.10 4.18 3.49

-Mental Control 30.65 14.74 6.23 4.15

-Impulses 3.79 5.13 0.77 1.54

Inferential Confusion Questionnaire 46.60 15.41 36.18 11.82

Obsessive Beliefs Questionnaiire-44

-Responsibility/Threat 55.71 24.04 — —

-Perfectionism/Certainty 74.98 20.33 — —

-Importance/Control 37.74 14.42 — —

Beck Anxiety Inventory 14.49 11.81 6.27 7.03

Beck Depression Inventory 17.49 11.12 5.69 3.76

QUANTIFICATION OF DOUBT 195

Fig 1A. Impact of Reality (R1 to R3) and Negating Possibility Based Information (P1 to P3) on Level of Doubt in the OCD Related Scenario.

20

30

40

50

60

70

80

B R1 P1 R2 P2 R3 P3

N

o A

ccid

ent

A

ccid

ent

OCD Group (n=50 )

Non-Clinical Group(n=22)

Fig 1B. Impact of Reality (R1 to R3) and Negating Possibility Based Information (P1 to P3) on Level of Doubt in the Non-OCD Related Scenario.

20

30

40

50

60

70

80

Base R1 P1 R2 P2 R3 P3

No

Bus

Str

ike

B

us S

trik

e

OCD Group (n= 50)

Non-Clinical Group(n= 22)

FIGuRE 1A & B.

changes in level of doubt

Level of doubt was measured in the form of probability estimates at seven separate time periods, following the initial scenario to establish baseline levels of probability (B), and subsequent to the presentation of each separate piece of reality-based infor-mation (R1, R2, R3) and possibility-based information (P1, P2, P3).

OCD Related Scenario (see Figure 1a). Repeated measures of analysis showed a significant linear effect across the different time periods in the OCD related scenario, F (6,65) = 52.38, p < 0.001; Partial Eta Squared = 0.69, as well as an interaction effect that approached significance, F (6,65) = 2.11, p = 0.06; Partial Eta Squared = 0.16. Test of within subjects contrasts showed a strong linear effect as well, F (1,70)

196 AARDEMA ET AL.

= 78.11, p < 0.001; Partial Eta Squared = 0.53, including a significant interaction effect, F (1,70) = 6.32, p < 0.05; Partial Eta Squared = 0.08. In addition, a strong significant 6th order effect, which as intended by the experimental manipulation, sug-gested a fluctuating pattern in levels of doubt for all participants (five bends), F (1,70) = 52.38, p < 0.001; Partial Eta Squared = 0.43. There was no difference in the degree of fluctuation between the groups as evidenced by a nonsignificant 6th order interaction effect, F (1,70) = 0.05, p = 0.82); Partial Eta Squared = 0.00. Directly comparing baseline (B) with end point (P3) in repeated measures revealed an overall decrease in level of doubt, F (1,70) = 76.67, p < 0.001; Partial Eta Squared = 0.53, as well as an interaction effect where the OCD group decreased significantly less than the nonclinical control group in level of doubt following three pairs of reality and possibility-based information, F (1,70) = 4.03, p < 0.05; Partial Eta Squared = 0.05. This interaction effect remained significant when controlling for baseline anxiety, F (1,69) = 3.85; p < 0.05; partial eta squared = 0.05.

To obtain further insight into these results post-hoc repeated measures analyses were conducted following the principle of Fisher’s protected tests, in which any num-ber of post-hoc analyses may be conducted to follow-up a significant main effect or interaction (Carmer & Swanson, 1973). Results of the post-hoc repeated measures analyses controlling for baseline anxiety induced by the scenario are represented in Table 3. In addition, means and differences between groups at each specific time point are represented in Table 4 (corrected for unequal variances where necessary).

For the OCD scenario, looking at the impact of reality-based information at the different time points, (B1 to R1, P1 to R2, P2 to R2), a conflicting pattern emerged

TABLE 3. Group differences (OCD versus non-clinical controls) in the Impact of Reality and Possibil-ity Controlled for Baseline Anxiety (repeated measures of variance)

F Error df Partial Eta Squared p

OCD Related Scenario

Impact of Reality

B to R1 2.24 69 0.04 0.09

P1 to R2 4.27 69 0.06 0.04

P2 to R3 4.64 69 0.06 0.04

Impact of Possibility

R1 to P1 1.13 69 0.02 0.29

R2 to P2 0.87 69 0.01 0.35

R3 to P3 7.15 69 0.09 0.01

Non-OCD Related Scenario

Impact of Reality

B to R1 2.18 68 0.03 0.15

P1 to R2 2.2 68 0.03 0.14

P2 to R3 2.65 68 0.04 0.11

Impact of Possibility

R1 to P1 1.53 68 0.02 0.22

R2 to P2 0.02 68 0 0.9

R3 to P3 0.11 68 0 0.74

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with the OCD group relying significantly less on reality-based information from P1 to R2, and significantly more on reality-based information from P2 to R3 (see Table 4 for mean scores). However, with regards to the impact of possibility-based information the OCD group differed significantly from nonclinical controls from R3 to P3 by re-lying more on possibility-based information than nonclinical controls. No significant differences were observed in the impact of possibility-based information from R1 to P1 and from R2 to P2. Nonetheless, level of doubt at the time points P2 and P3 were significantly higher for those in the OCD group. There were no significant differences in level of doubt at baseline.

Non-OCD Related Scenario (see figure 1b). Repeated measures of analysis of the non-OCD related scenario showed a significant linear effect, F (6, 64) = 17.47, p < 0.001; Partial Eta Squared = 0.62, but no significant interaction effect across the dif-ferent time periods, F (6,64) = 1.01, p = 0.43; Partial Eta Squared = 0.09. Test of within subjects contrasts showed a significant linear effect as well, F (1, 69) = 26.83, p < 0.001; Partial Eta Squared = 0.28, but no significant interaction effect, F (1,69) = 0.87, p = 0.36; Partial Eta Squared = 0.01. In addition, a strong significant 6th order effect (five bends) was observed for all participants, F (1, 69) = 39.92, p < 0.001); Partial Eta Squared = 0.43, but there was no difference in the degree of fluctuation between the groups as evidenced by a nonsignificant 6th order interaction effect, F (1,69) = 1.59, p = 0.21; Partial Eta Squared = 0.02. Directly comparing baseline (B) with end point (P3) with repeated measures analyses revealed an overall decrease in level of doubt, F (1, 69) = 36.90, p < 0.001; Partial Eta Squared = 0.35, but no significant interaction effect, F (1, 69) = 1.08, p < 0.30; Partial Eta Squared = 0.02.

TABLE 4. Group differences (OCD versus non-clinical controls) at the different time points for the OCD related and non-OCD related scenario

Nonclinical Controls Mean

SD

OCD Group Mean

SD

t

p

OCD Related Scenario

B 65.46 18.45 68.80 25.29 0.56 0.58

R1 49.55 20.35 43.00 24.76 1.09 0.28

P1 54.09 17.64 52.00 25.79 0.40 0.69

R2 30.45 16.47 40.00 24.16 1.95 0.06

P2 37.73 16.60 51.40 28.14 2.57 0.01

R3 27.27 13.16 29.80 18.57 0.58 0.57

P3 32.37 16.60 48.00 28.71 2.92 0.01

Non-OCD Related Scenario

B 55.46 16.54 69.18 22.72 2.54 0.01

R1 39.55 18.64 45.10 26.47 1.01 0.32

P1 46.36 17.87 59.80 26.57 2.50 0.02

R2 35.91 18.94 39.39 26.17 0.56 0.58

P2 45.46 20.41 50.61 25.28 0.84 0.40

R3 29.55 21.93 34.08 26.45 0.70 0.49

P3 40.00 20.47 47.35 26.28 1.16 0.25

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Controlling for baseline anxiety continued to show a nonsignificant interaction effect, F (1, 68) = 0.68; p = 0.45; partial eta squared = 0.01.

Again, to obtain further insight into these results for the non-OCD related sce-nario post-hoc analyses were conducted (see Table 3 and 4). However, results showed that neither the impact of reality-based information (B to R1, P1 to R2, P2 to R3), nor the impact of possibility-based information (R1 to P1, R2 to P2, R3 to P3) dif-fered between the OCD group and nonclinical group. The only significant differences between the groups occurred immediately following the presentation of the non-OCD related scenario (B), and immediately following the presentation of possibility-based information at P1.

group differences in the cumulative impact of Possibility and Reality

Repeated measures of analysis showed that the combined cumulative impact of real-ity and possibility-based information significantly differed between those with OCD and nonclinical controls in the OCD scenario (P3-B). However, does the cumula-tive impact of possibility alone differentiate between those with OCD and nonclini-cal controls? Likewise, despite the conflicting pattern in the impact of reality-based information, is there a difference between those with OCD and nonclinical controls in the cumulative impact of reality-based information? To answer these questions, we calculated the cumulative impact of possibility-based information by adding any changes in level of doubt over time that were due to the presentation of possibility-based information, (P1 – R1) + (P2-R2) + (P3 –R3). The same type of calculation was used to determine the cumulative impact of reality-based information (multiplied by -1 in order to obtain a positive value), -1 * ((R1 – B) + (R2- P1) + (R3 – P2)).

For the OCD scenario, analysis of variance (ANOVA) revealed a significant dif-ference in the cumulative impact of possibility-based information between the groups (F (1, 70) = 4.37; p < 0.05; Partial Eta Squared = 0.06] with the OCD group (M = 38.60; SD = 47.16) scoring higher than nonclinical controls (M = 16.82; SD = 18.36). These results became even stronger when controlling for baseline levels of anxiety and baseline levels of doubt immediately preceding the impact of possibility-based information (R1 + R2 + R3), F (3, 68) = 5.25; p < 0.05; Partial Eta Squared = 0.07. No significant differences were observed in the cumulative impact of reality-based information. In fact, the OCD group scored higher (M = 59.40; SD = 47.36) than nonclinical controls (M = 50.00; SD = 31.32) on the cumulative impact of reali-ty-based information (albeit not significantly so). For the non-OCD relevant scenario, no significant differences were observed in either the cumulative impact of possibility and the cumulative impact reality-based information. However, there was a trend for those with OCD to be more affected by reality-based information in the non-OCD related scenario, F (1, 69) = 2.69; p < 0.10; Partial Eta Squared = 0.04.

The Relationship of Reality and Possibility with ocd severity

Does the impact of reality and possibility relate to OCD symptoms, and are these relationships independent of distressed mood? To investigate the relationship between the impact of reality and possibility with OCD severity a number of regression analy-

QUANTIFICATION OF DOUBT 199

sis were carried out. The analyses were limited to the OCD group alone to avoid any potential artificial inflation in the magnitude of relationships, and to conserve power, no multiple regression analysis was performed for non-OCD relevant scenario. As well, we only performed multiple regression analysis in those instances where (a) the combined cumulative impact of reality and possibility (P-B), (b) the cumulative im-pact of possibility, (P1 – R1) + (P2-R2) + (P3 –R3); or (c) the cumulative impact of reality-based information, -1 * (R1 – B) + (R2- P1) + (R3 – P2) related significantly to OCD severity. Inspection of the correlation matrix revealed that only the combined cumulative impact of reality and possibility (r = 0.39; p < 0.01), and the cumulative impact of possibility (r = 0.29; p < 0.05) were significantly related to OCD severity in the OCD related scenario. The cumulative impact of reality was not significantly related to OCD severity in the OCD related scenario. In the non-OCD related sce-nario, only the combined cumulative impact of reality and possibility was significantly related to OCD severity (r = 0.42; p < 0.01).

Initially, this led to two separate regressions analysis for the OCD-related scenario (I.A and II.A) where the primary objective was to determine whether the combined cumulative impact of reality and possibility, and the cumulative impact of possibil-

TABLE 5. Beta weights of the multiple regression analyses predicting OCD severity in the OCD Group1

OCD Scenario

A B

I. Combined Cumulative Impact of Reality and Possibility

- Baseline of Level of Doubt (B) 0.36* 0.25

- Baseline Anxiety 0.24 -0.04

- BAI 0.05 0.08

- BDI 0.09 0.12

- Combined Impact of Reality and Possibility (P3 – B) 0.45*** 0.27

- ICQ Inferential Confusion - 0.31†

-OBQ Responsibility/Threat - -0.03

- OBQ Perfectionism/Certainty - 0.21

-OBQ Importance/Control of Thoughts - 0.06

II. Cumulative Impact of Possibility

- Baseline Levels of Doubt (R1 + R2 + R3) 0.05 0.02

- Baseline Anxiety 0.12 -0.03

- BAI 0.22 0.06

- BDI 0.25 0.22

- Cumulative Impact of Possibility [(P1-R1) + [P2-R2) + (P3-R3)] 0.29* 0.15

- ICQ Inferential Confusion - 0.41*

-OBQ Responsibility/Threat - 0.03

- OBQ Perfectionism/Certainty - 0.28†

-OBQ Importance/Control of Thoughts - -0.05

Note. †p < 0.10; *p < 0.05; ***p < 0.001. BAI = Beck Anxiety Inventory; BDI = Beck Anxiety Inventory; ICQ = Inferential Confusion Questionnaire; OBQ = Obsessive Belief Questionnaire. 1Regression I.A: F = (5, 44) = 6.99; p < 0.001; Multiple R = 0.67; R Square = 0.45. Regression I.B: F = (9, 40) = 4.51; p < 0.001; Multiple R = 0.71; R Square = 0.51. Regression II.A: F = (5, 44) = 4.56; p < 0.01; Multiple R = 0.59; R Square = 0.35. Regression II.B: F = (9, 40) = 4.08; p < 0.01; Multiple R = 0.70; R Square = 0.49.

200 AARDEMA ET AL.

ity alone, predicted OCD severity in the OCD-related scenario while controlling for baseline anxiety, general distress (BAI and BDI), and baseline levels of doubt. In both cases, OCD severity as measured by the PI acted as the dependent variable. Both multiple regression analyses begin with the same correlation matrix to a substantial degree with a combined total of seven separate predictors. As such, there were more than seven times as many cases as predictors; a sufficient level of power for the current analysis. Beta weights of these analyses are represented in Table 5 (I.A and II.A).

Results showed that the combined cumulative impact of reality and possibility, and the cumulative impact of possibility alone, significantly predict OCD severity while controlling for distress and baseline levels of doubt. In addition, baseline level of doubt (B) predicted OCD severity beyond the combined cumulative impact of reality and possibility-based information. None of the other control variables predicted OCD severity.

Following these initial regression analyses, an additional pair of multiple regres-sion analysis was carried out to determine whether cognitive domains could account for the relationship between the combined cumulative impact of reality and possibility with OCD severity (I.B), and the cumulative impact of possibility with OCD severity alone (II.B). We reran the same analyses (including controls), but this time, we also included the ICQ and OBQ belief domains as independent variables to the analysis. The additional regression analysis were justified on the basis that it only included the addition of four cognitive domains as independent variables, and relied to a substantial extent on the same correlation matrix, with almost five times as many cases as predic-tors. Beta–weights are represented in Table 5 (I.B and II.B).

The addition of the ICQ and OBQ belief domains to the regression analysis leads the overall cumulative impact of reality and possibility-based information to no longer significantly predict OCD severity. For the most part, this appears due to the addition of the ICQ, which showed a trend in the prediction of OCD severity (0.08). None of the OBQ belief domains significantly predicted OCD severity. The addition of all cognitive domains to the multiple regression analysis also led the cumulative impact of possibility alone to no longer significantly predict OCD severity. Again, this seemed mostly due to the addition of inferential confusion, which was the only cognitive do-main to significantly predict OCD severity. There was a trend for the OBQ subscale Perfectionism/Certainty to predict OCD severity, which may therefore to some extent account for the impact of possibility-based information.

TABLE 6. Relationship between Levels of Doubt at the different time points with OCD severity and Inferential Confusion in the OCD Group (n = 50)

B R1 P1 R2 P2 R3 P3

OCD Scenario

PI - Padua Inventory 0.31* 0.23 0.19 0.22 0.41** 0.49*** 0.60***

ICQ - Inferential Confusion 0.26 0.34* 0.43** 0.45** 0.42** 0.47*** 0.59***

Non-OCD related Scenario

PI - Padua Inventory 0.30* 0.20 0.29* 0.23 0.39** 0.29* 0.40**

ICQ - Inferential Confusion 0.21 0.00 0.15 0.18 0.38** 0.14 0.23

Note. *p < 0.05; **p < 0.01; ***p < 0.001; ICQ = Inferential Confusion Questionnaire; PI = Padua Inventory.

QUANTIFICATION OF DOUBT 201

evolution of doubt, inferential confusion and ocd severity

Because level of doubt at the end-point of reasoning explicitly takes into account the cumulative effects of the impact of reality- and possibility-based information, one would expect levels of doubt to be most strongly related to OCD severity at the end-point of reasoning. To test this hypothesis we calculated the correlations between level of doubt at the different time points and OCD symptoms. In addition, we calculated the relationship between levels of doubt with the ICQ. Correlations are presented in Table 6.

The importance of reasoning in doubt formation, and OCD severity, was cor-roborated by a progressive increase in the magnitude of correlations between level of doubt and obsessive-compulsive symptoms. In particular, for the OCD scenario, the relationship between level of doubt and OCD symptoms increased over time fol-lowing the presentation of possibility-based information (P1, P2, P3). At end-point levels of measurement (P3) level of doubt was most strongly associated with OCD severity. The ICQ was associated with levels of doubt at all time periods (except for the baseline), yet also most strongly related to level of doubt at end-point of reasoning. Correlations in the non-OCD related scenario tended to be lower, but once again, a progressive increase in the magnitude of relationships was observed after the presenta-tion of possibility-based information (P1, P2, P3). However, this time, the ICQ was not associated with level of doubt at any of the different time-points (with the excep-tion of P2).

discussion

Overall, the current results showed that doubt can be successfully operationalized ac-cording to the dynamic interplay between the impact of possibility- and reality-based information. The impact of reality and possibility varies over time and affects levels of doubt in an independent but cumulative fashion. Specifically, regarding the OCD related scenario, people with OCD maintained higher levels of doubt than nonclini-cal controls following the presentation of three pairs of reality- and possibility-based information. Moreover, post-hoc analysis controlling for baseline levels of anxiety pro-voked by the OCD-relevant scenario indicated that increased levels of doubt were mainly associated with the impact of possibility-based information in the later stages of reasoning (R3 to P3). Likewise, most differences between the OCD group and the nonclinical group occurred immediately after the presentation of possibility-based information with the OCD group showing higher levels of doubt than nonclinical controls (P2 and P3). In addition, the cumulative impact of possibility-based informa-tion across time points was significantly higher in those with OCD. We may therefore conclude that the impact of possibility-based information is an important quantifier of doubt that differentiates those with OCD from nonclinical controls.

No clear pattern emerged with respect to the impact of reality-based informa-tion and its effects on level of doubt. In one instance (P1 to R2), people with OCD were more influenced by reality-based information than nonclinical controls, while in another instance (P2 to R3) they were less influenced. No significant differences were observed between the groups immediately following the presentation of reality-based information (R1, R2 and R3). As well, those with OCD did not significantly differ

202 AARDEMA ET AL.

from nonclinical controls in the cumulative impact of reality-based information across time points. Overall then, the impact of reality-based information did not appear to contribute to higher levels of doubt in the course of reasoning for those with OCD. These results confirm the notion that what is possible for the individual with OCD is more problematic than what actually occurs. It is only when the imagination of the individual with OCD is triggered that problems seem to arise (Keen, Brown, & Wheatley, 2008; O’Connor & Aardema, 2005).

Multiple regression analysis revealed that both the combined cumulative impact of reality and possibility, and the cumulative impact of possibility alone, were sig-nificant predictors of OCD severity. These results held while controlling for baseline levels doubt, baseline levels of anxiety provoked by the scenario, and general distress. As expected, pre-existing levels of inferential confusion could explain the impact of possibility-based information, which confirms the convergent validity of the current experimental manipulation. Other cognitive domains could not significantly account for the relationship between the impact of possibility-based information and OCD severity. Perfectionism/Certainty, however, showed a trend in the prediction of OCD severity, and may therefore to some extent account for the relationship between the impact of possibility and OCD severity.

Other alternative cognitive explanations of doubt in OCD than those of inferen-tial confusion also do not match well with the current results. For example, none of the current findings are easily explained by a general lack of confidence that charac-terizes people with OCD during reasoning, since people with OCD did not appear to lack confidence in processing reality-based information. People with OCD even appeared to process reality-based information a little bit better than nonclinical con-trols in the non-OCD-related scenario. Likewise, a disconfirmation bias operating in OCD does not adequately explain the present findings very well, since it also would be expected to appear equally in making reality- and possibility-based decisions. In any case, obsessive-compulsive checkers do not display a disconfirmation bias despite reduced confidence (Dar, 2004). Neither are the current results easily explained by models of deficits in reality monitoring, which is generally defined as the ability to distinguish between external and internal sources of information (Johnson & Raye, 1981). Of course, a tenet of the inferential confusion model is that people with OCD treat possibilities as if they have any direct bearing on reality, and to that extent, they do not seem to differentiate between possibility and reality very well. However, people with OCD did not appear to have any problems processing reality-based information itself, nor do they show any deficits in reality monitoring ability (Hermans, Martens, De Cort, Pieters, & Eelen, 2003). The problem does not appear to be blurred percep-tual boundaries, rendering the person with OCD unable to discriminate between real and imagined precepts (Brown, Kosslyn, Breiter, Baer, & Jenike, 1994). Rather, the essential (cognitive) process lies in the impact of possibility at the expense of reality, which in turn leads the person with OCD to doubt reality (even while reality itself is adequately perceived and processed). The differential impact of reality and possibility among people with OCD also could potentially explain why they generally have in-sight into the senselessness of their obsessions (i.e., the normal impact of reality) while at the same time being unable to distance from the thought (i.e., the high impact of possibility) (i.e., ego-dystonicity). Possibly, the impact of reality-based information is more attenuated in ego-syntonic obsessions, or obsessions that resemble overvalued ideas or delusions.

QUANTIFICATION OF DOUBT 203

Further support for the current inference-based model was found in an investiga-tion of relationships between level of doubt at the different time points with OCD severity and inferential confusion. The strongest relationships of levels of doubt with OCD severity and inferential confusion were found in the later stages of reasoning for both the OCD-relevant scenario and the non-OCD-relevant scenario. These results underline the importance of measuring reasoning as a dynamic, continuous process, rather than by one-time, single measurements in time. Possibly, relationships might become even stronger if additional pairs of reality and possibility-based information were added to the current scenarios, since after all, the persistent nature of obsessions is a major characteristic of OCD. Future research will need to shed light on this is-sue.

It is also noteworthy that the importance of the impact of possibility-based in-formation was limited to the OCD scenario. This suggests that inferential confusion is domain specific, and that other variables might in turn underlie inferential confu-sion. For example, vulnerable self-themes in OCD have been proposed to underlie the domain specificity of OCD (see O’Connor & Aardema, 2007). Even so, while the interplay between reality and possibility, and its relevance to obsessive-compulsive symptoms appears to be domain specific, it is questionable whether the same results would be obtained with scenarios that are too idiosyncratic. One client for example, whose obsessions corresponded exactly to the automobile accident in the OCD-related scenario, spontaneously volunteered possibility-based information on each occasion he was presented with reality-based information (i.e., But perhaps . . . ). In these instances, prior reasoning had led to crystallization of the obsessional belief, often reflected by elevated scores at baseline, and no changes in subsequent measurements. Consequently, the opportunity to measure reasoning in action is missed. The same pattern might occur when a person fills in the test repeatedly with the effects of prior reasoning reflected in baseline measurement. These methodological issues could po-tentially be resolved in future studies through the exclusion, or separate analysis of those participants who show no fluctuation in levels of doubt, and where previous reasoning about the scenario has crystallized into belief.

One limitation of the current study is the absence of a psychiatric comparison group as well as the use of a relatively small nonclinical sample size. Nonetheless, the current study included a number of strict controls, and the present findings provide a coherent and robust level of empirical support to an inference-based approach to OCD, which holds that pathological doubting is the principal characteristic of OCD, which distinguishes OCD from nonclinical controls. Nevertheless, the current study would benefit from replication, which preferably would include a psychiatric control group, larger sample sizes, adaptation of the current tasks with more pairs of reality- and possibility-based information, and the addition of more scenarios to investigate reasoning processes in OCD.

The clinical implications of the current study are: (1) Assessment of obsessional doubt should form part of OCD evaluation; (2) This degree of doubt should be con-sidered a separate cognitive process; and (3) Cognitive therapy might successfully address doubt in order to alleviate symptoms.

204 AARDEMA ET AL.

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