The Impact of Modifying Interpretive Bias on Contamination-Related Obsessive–Compulsive Symptoms
Bibliographic record
Abstract
Abstract Cognitive-behavioural models of obsessive–compulsive disorder (OCD) propose that a tendency to negatively interpret ambiguous thoughts and situations plays a key role in maintaining the disorder. Moreover, some researchers have proposed that negative interpretive biases may share a common processing mechanism with attentional biases, with changes in one predicted to lead to changes in the other. The current study examined whether training positive (i.e., adaptive) interpretive bias of contamination-related OCD concerns using a cognitive bias modification paradigm (CBM-I) would lead to reductions in contamination concerns, as well as changes in contamination-related attentional bias. Undergraduate students with high levels of contamination-related OCD symptoms were randomly assigned to receive either positive ( n = 31) or neutral ( n = 33) CBM-I training. Participants in the positive training condition, relative to the neutral training condition, showed a significantly greater increase in positive interpretive bias, significantly less within-session behavioural avoidance of contaminants, and significantly reduced contamination-related cognitions (at one-week follow-up). Contrary to expectations, CBM-I training did not differentially impact attentional bias nor self-reported contamination-related OCD symptoms. We discuss future directions in applying CBM-I to contamination-related OCD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".