Comparison of the Association Between Goal-Directed Planning and Self-reported Compulsivity vs Obsessive-Compulsive Disorder Diagnosis

Abstract

Importance: Dimensional definitions of transdiagnostic mental health problems have been suggested as an alternative to categorical diagnoses, having the advantage of capturing heterogeneity within diagnostic categories and similarity across them and bridging more naturally psychological and neural substrates.

Objective: To examine whether a self-reported compulsivity dimension has a stronger association with goal-directed and related higher-order cognitive deficits compared with a diagnosis of obsessive-compulsive disorder (OCD).

Design, setting, and participants: In this cross-sectional study, patients with OCD and/or generalized anxiety disorder (GAD) from across the United States completed a telephone-based diagnostic interview by a trained rater, internet-based cognitive testing, and self-reported clinical assessments from October 8, 2015, to October 1, 2017. Follow-up data were collected to test for replicability.

Main outcomes and measures: Performance was measured on a test of goal-directed planning and cognitive flexibility (Wisconsin Card Sorting Test [WCST]) and a test of abstract reasoning. Clinical variables included DSM-5 diagnosis of OCD and GAD and 3 psychiatric symptom dimensions (general distress, compulsivity, and obsessionality) derived from a factor analysis.

Results: Of 285 individuals in the analysis (mean [SD] age, 32 [12] years; age range, 18-77 years; 219 [76.8%] female), 111 had OCD; 82, GAD; and 92, OCD and GAD. A diagnosis of OCD was not associated with goal-directed performance compared with GAD at baseline (β [SE], -0.02 [0.02]; P = .18). In contrast, a compulsivity dimension was negatively associated with goal-directed performance (β [SE], -0.05 [0.02]; P = .003). Results for abstract reasoning task and WCST mirrored this pattern; the compulsivity dimension was associated with abstract reasoning (β [SE], 2.99 [0.63]; P < .001) and several indicators of WCST performance (eg, categories completed: β [SE], -0.57 [0.09]; P < .001), whereas OCD diagnosis was not (abstract reasoning: β [SE], 0.39 [0.66]; P = .56; categories completed: β [SE], -0.09 [0.10]; P = .38). Other symptom dimensions relevant to OCD, obsessionality, and general distress had no reliable association with goal-directed performance, WCST, or abstract reasoning. Obsessionality had a positive association with requiring more trials to reach the first category on the WCST at baseline (β [SE], 2.92 [1.39]; P = .04), and general distress was associated with impaired goal-directed performance at baseline (β [SE],-0.04 [0.02]; P = .01). However, unlike the key results of this study, neither survived correction for multiple comparisons or was replicated at follow-up testing.

Conclusions and relevance: Deficits in goal-directed planning in OCD may be more strongly associated with a compulsivity dimension than with OCD diagnosis. This result may have implications for research assessing the association between brain mechanisms and clinical manifestations and for understanding the structure of mental illness.

Figure 1.. Goal-Directed Planning Task

Goal-directed (model-based) planning was assessed using a 2-step decision-making task. In each trial, individuals were asked to select between 1 of 2 choices (top). On the basis of the depicted probabilities (70% or 30%) for each of these options, individuals would transition to a second stage, where they were again asked to choose between 2 options. These choices were rewarded (or not rewarded) with a 1-cent coin based on the current probability of reward assigned to that fractal. In the example trial depicted here, the leftmost fractal had a 34% chance of producing a coin. This probability changed slowly throughout the task, encouraging individuals to update their action preferences and regularly explore new options.

Figure 2.. Factor Analysis of 3 Transdiagnostic Dimensions: Compulsivity, Obsessionality, and General Distress

Each bar represents the loadings for each subscale onto the 3 factors (distress, compulsivity, and obsessionality). The height of each bar reflects its loading onto the relevant factor. Color codes indicate the questionnaire from which each subscale was drawn. DASS indicates Depression and Anxiety and Stress Scale; MCQ, Metacognitive Beliefs Questionnaire; OCI-R, Obsessive-Compulsive Inventory–Revised; SDS, Sheehan Disability Scale.

Figure 3.. Association Among Model-Based Planning Scores, Diagnostic Status, and Compulsivity

A, Bars display mean model-based planning scores (after controlling for age) by group, and dots indicate individual participant’s performance. No significant association was found for obsessive-compulsive disorder (OCD) (P = .18) or generalized anxiety disorder (GAD) diagnosis (P = .71) with model-based planning. The coefficients are from a regression model, specifically the interaction between reward and transition on stay behavior in the 2-step task. Scores below 0 were possible but rare (5 of 285 scores were below 0); scores close to 0 indicated a poor fit of the model to behavior. B, Scatterplot depicting the association between scores on the transdiagnostic compulsivity dimension and model-based planning ability, controlling for age. A significant negative association was found (P = .003). Individuals who had the highest self-reported compulsivity had the lowest scores on the test of model-based planning. Colors indicate the diagnoses for which each participant met the criteria (OCD, GAD, or combined OCD and GAD). C, Results are from a regression analysis comparing OCD diagnosis with the dimensional compulsivity factor in the same analysis. The association of OCD with model-based planning approached 0 when compulsivity was included in the same model (P = .91), whereas the association with compulsivity remained strong (P = .007). Error bars indicate SEs.