A cognitive intervention for negative beliefs about losing control: impact on other cognitive domains and OCD symptoms
Bibliographic record
Abstract
Purpose Beliefs about losing control have been proposed as a novel cognitive domain in OCD. Despite increasing evidence that links these beliefs with OCD symptoms, it is unclear whether interventions targeting beliefs about losing control lead to symptom improvement. This study sought to develop and test the impact of a brief cognitive intervention for beliefs about losing control on OCD-relevant appraisals and symptoms in a sub-clinical OCD sample. Methods A total of 35 sub-clinical participants were recruited based on self-reported OCD symptoms and beliefs about losing control, and randomly assigned to receive a 1-hour CBT session targeting beliefs about losing control (intervention) or sleep hygiene (control). Beliefs about losing control, and OCD symptom were assessed at baseline and one week after the intervention using self-report questionnaires. Appraisals of losing control and OCD-relevant appraisals were also assessed using daily monitoring forms during the two-week intervention period. Results There was a significant interaction between condition and time on appraisals of losing control and OCD-relevant appraisals measured by the daily monitoring forms, with those in the intervention condition showing greater reductions from baseline to follow-up compared to those in control condition. There were no significant interaction effects on beliefs about losing control or OCD symptoms measured using standardized self-report questionnaires. Conclusions These results suggest that incorporating strategies targeting beliefs about losing control into CBT for OCD may be warranted, however more time and/or sessions is/are likely required to achieve broader symptom improvement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".