A Programme of Research on the Role of Implicit Cognition in OCD Research. Emma Nicholson and Dermot Barnes-Holmes

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A Programme of Research on the Role of Implicit Cognition in OCD Research Emma Nicholson and Dermot Barnes-Holmes

Measuring OCD Measuring OCD is difficult due to its heterogeneity and high comorbidity with other disorders (Clark, 2004) Improving assessment and diagnosis is critical for both research and practice Assessment ranges from diagnostic interviews to family-report questionnaires to self- report s Self-report measures are problematic as OCD is very idiosyncratic and may not be accurately captured by self-reports

Measuring OCD The number and diversity of measures have created a confusing picture of the role of cognitive phenomena in OCD (OCCWG, 1997) The following programme of research aimed to develop an adequate implicit measure of OCD which would circumvent the issues which arise from the use of self-report measures A series of studies were conducted which explored the role of disgust in the aetiology of OC tendencies

The Present Research I will outline 6 parts of this programme of research: 1. Testing the ability of the IRAP to assess Disgust Propensity and Sensitivity in a non-clinical sample 2. Methodological Issues 3. Assessing obsessive beliefs in relation to disgust and contamination using the IRAP 4. Comparing clinical vs control samples with Propensity and Sensitivity IRAPs 5. A new dimension to disgust research 6. Using the IRAP to predict treatment outcome (ongoing research)

Part 1: Preliminary Research Two IRAPs were designed to each measure Disgust Propensity and Disgust Sensitivity Propensity is the initial disgust response and sensitivity is the appraisal the response If they could be assessed it would be useful in demonstrating that such responses occur on a continuum rather than as two separate responses N=33 undergraduate students

Disgust Propensity IRAP Measured initial feelings toward the disgust-eliciting stimuli

Study 1: Disgust Sensitivity IRAP Measured their response or appraisal to the initial feeling/thought

Disgust Propensity IRAP Disgust Sensitivity IRAP

Behavioural Approach Tasks Spider Hip Replacement Surgery Poop Cookie Socio-Moral

Correlation Analysis Disgust Propensity IRAP Disgust Sensitivity IRAP *p.05 ** p.01 ***p.001 BATs OCI-R Depression (DASS) Obsessing (OCI-R).09.40*.41*.49**.23 -.47**.41*.45*.32.39* Washing Concerns (OCI-R) BATs: Behavioural Approach Tasks OCI-R: Obsessive-Compulsive Inventory Revised DASS: Depression, Anxiety and Stress Scale

Predicting Avoidance Behaviour Hierarchical multiple regression analysis Anxiety (DASS) Disgust Sensitivity IRAP R 2 =.07 R 2 change =.18* Avoidance Behaviour Step 1: Beta = -.27, p =.18 Step 2: Beta = -.43, p =.03

Key Findings from Study 1 Both Propensity and Sensitivity IRAPs were related to OC tendencies Disgust Propensity was related to Obsessing behaviour Disgust Sensitivity was related to Washing Concerns The most critical finding was the Sensitivity IRAP predicted avoidance behaviour while the Propensity IRAP did not

Part 2: Methodological Issues First, it was deemed important to determine whether alterations to the 2009 IRAP procedure affect D-IRAP scores Two studies were conducted which used identical stimuli but in the 2009 and 2012 versions of the IRAP The target stimuli were the sensitivity from the previous study but with more contamination-focused pictorial stimuli Each study had different behavioural tasks

Trial-Types

.35.3 2009 IRAP 2012 IRAP.25.2.15.1 Anti-Contaminatio /Pro-Pleasant.05 0 Contamination/ Distressing Contamination/ Clean/ Positive Distressing,,.,,. Clean/ Positive

.35.3.25.2.15.1.05 0,,,.., Disgust/Positive Pleasant/Positive Disgust/Distressing Pleasant/Distressing F (33) = 3.08, p =.03

Part 3: Obsessive Beliefs OCCWG (1997; 2005) identified six cognitive belief domains of OCD excessive responsibility/overestimation of threat; perfectionism/intolerance of uncertainty; over-importance of thoughts/need to control thoughts Three studies conducted to explore these beliefs in the context of disgust and contamination

Six Obsessive Beliefs

Results RT p =.56 PC p =.43 CC p = 50 Anti-Disgust /Pro-Pleasant

Contamination RT

Self-Reports PI p =.48 Contamination p =.52 Anti-Contamina /Pro-Clean DS-R p =.51

Behavioural Task Comb BAT p = -.39 Anti-Contamina /Pro-Clean

Contamination PC

Self-Reports CC p =.41 CC p =.39 CC p =.41 DG p =.48 FMPS p =.55 PI p =.48 DG p =.51 DG p =.40 FMPS p =.45 Anti-Contamin /Pro-Clean

Behavioural Tasks Comb BAT p = -.39 Comb BAT p = -42 Anti-Contamin /Pro-Clean

Key Findings Firstly, they demonstrate the use of the IRAP as a measure of obsessive beliefs in the context of disgust and contamination Secondly, they reveal the precision that can be achieved with the IRAP with regards to targeting highly specific relational responding as it pertains to OCD. Context was important here because obsessive beliefs are not always prevalent in every aspect of an individuals life (Hasse et al., 2013)

Part 4: Control vs Clinical Participants included 17 undergraduate students from NUI Maynooth (Mean age = 23.9) and 17 patients attending the OCD stream at St. Patrick s University Hospital Dublin for treatment for OCD (Mean age = 33) Therapeutic framework is based on CBT and Mindfulness Based Approaches IRAPs which were almost identical to that used in Nicholson & Barnes-Holmes (2012) were implemented Participants also completed a series of questionnaires (Padua Inventory, Obsessive-Compulsive Inventory, STAI, Disgust Scale and Disgust Propensity and Sensitivity Scale)

Disgust Propensity IRAP Measured initial feelings toward the disgust-eliciting stimuli

Disgust Sensitivity IRAP Measured their response or appraisal to the initial feeling/thought

Disgust Propensity.5.4.3 Control Clinical.2 Anti-Disgust /Pro-Pleasant.1 0 Disgust/ Bad Disgust /Good Pleasant /Bad Pleasant /Good,,,.., Mixed between-within between groups ANOVA for the DP-IRAP

.6 Disgust Sensitivity.5 Control.4 p =.07, n 2 =.09 p =.01, n 2 =.18 Clinical.3.2 Anti-Disgust /Pro-Pleasant.1 0 Disgust/ Distressing,,,.., Disgust/ Positive Pleasant/ Distressing Pleasant/ Positive Mixed between-within between groups ANOVA for the DS-IRAP

ROC Analyses-IRAP 74% of the time the IRAP correctly classified a participant as clinical or control Combined Pleasant Sensitivity trial-type produced a fair ability to classify group membership, AUC =.737, p =.02

ROC Analyses-Self-Report 64% of the time the Padua Inventory correctly classified the participants and clinical or control Scores on the Padua Inventory produced a poor ability to classify group membership, AUC =.639, p =.1

ROC Analyses-Self-Report 68% of the time the Padua Inventory correctly classified the participants and clinical or control Self-reported Obsessional Thoughts of Harm produced a fair ability to classify group membership, AUC =.68, p =.03

Mean D-IRAP Scores Comparing the High Scoring Controls with the Clinical Sample Clinical.45 Control.4.35.3.25.2.15.1.05 0 Combined Disgust Trial-Types,, Combined Pleasant Trial-Types Repeated Measures ANOVA for the Disgust Propensity IRAP

Mean D-IRAP Scores Comparing the High Scoring Controls with the Clinical Sample Clinical.5 Control.4.3.2.1 0 -.1 -.2 -.3.,.. Combined Disgust Trial-Types Combined Pleasant Trial-Types Repeated Measures ANOVA for the Disgust Sensitivity IRAP

Part 5: A New Perspective This study assessed changes to the target stimuli for the sensitivity IRAP Based on feedback from the participants Also, explored the finding with the Pleasant/Distressing in greater detail Discussions with the Debbie in St. Pat s brought about the idea for exploring an intolerance for causing disturbance/contamination We termed this Intolerance of Causing Mess (ICM) New Behavioural Tasks were designed to assess this finding

Target Stimuli for the DS-IRAP Target Stimuli

Behavioural Tasks

Results PI p =.41 Contamination p =.53 Contamination p =.49 DG p =.34 Four trial-types for the DP-IRAP

Results Comb BAT p = -.44 Comb BAT p = -.35 Four trial-types for the DP-IRAP

Contamination p =.41 Four trial-types for the DS-IRAP

Comb BAT p = -.31 # Comb BAT p = -.33 # Jenga p = -.50 Four trial-types for the DS-IRAP

Key Findings Jenga task correlated with and was predicted by the Pleasant/Distressing trial-type This finding is worth further exploration as similar findings are non-existent in the literature but form part of clinical practice

Part 6: Predictive Validity The final study of this research sought to determine the predictive validity of the DP and DS IRAPs Critically, we wanted to compare the IRAP to the most widely used measure in the literature, the Yale- Brown Obsessive Compulsive Scales (YBOCS) Data was collected from 26 patients attending the OCD stream of the anxiety programme in St. Patrick s Hospital Dublin

Quick reminder of the IRAPs Disgust Propensity IRAP Disgust Sensitivity IRAP

.7.6 Disgust Propensity IRAP In Treatment/Did not Complete.5 Discharged.4.3.2 Anti-Disgust /Pro-Pleasant.1 0,,.,,. Disgust/ Bad Disgust/ Good Pleasant/ Bad Pleasant /Good Assessment carried out during week 1 of the anxiety programme at St. Patrick s University Hospital

Disgust Sensitivity IRAP.8.7.6 In Treatment/Did not Complete Discharged.5.4.3 Anti-Disgust /Pro-Pleasant.2.1 0 Disgust/ Distressing,,,.., Disgust/ Positive Pleasant/ Distressing Pleasant /Positive Assessment carried out during week 1 of the programme at St. Patrick s University Hospital

Between-Group Effects Mann-Whitney U s to determine between groups differences across the trial-types

YBOCS

Key Findings 1. While the final study was limited by a relatively small sample size and uneven groups, the IRAP did outperform the YBOCS in terms of predicting outcome at 5 weeks 2. Once again the Pleasant/Distressing trial-type was the critical trial-type

Points for Discussion The opposing category can be critical even when there is no natural dichotomy to the behaviour in question There have been calls in the literature for a behavioural measure of OCD (Wheaton et al., 2010; Deacon & Abramowitz, 2005; Summerfeldt, 2004) While the IRAP was developed out of a long tradition of behavioural science, the findings are relevant to the wider cognitive-behavioural theories (e.g., Salkovkis, 1985)

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