What do you really need? Self- and partner-reported intervention preferences within cognitive behavioural therapy for reassurance seeking behaviour
Bibliographic record
Abstract
BACKGROUND: Reassurance seeking (RS) in obsessive compulsive disorder (OCD) is commonly addressed in cognitive behavioural therapy (CBT) using a technique called reducing accommodation. Reducing accommodation is a behaviourally based CBT intervention that may be effective; however, there is a lack of controlled research on its use and acceptability to clients/patients, and case studies suggest that it can be associated with negative emotional/behavioural consequences. Providing support to encourage coping with distress is a cognitively based CBT intervention that may be an effective alternative, but lacks evidence regarding its acceptability. AIMS: This study aimed to determine whether support provision may be a more acceptable/endorsed CBT intervention for RS than a strict reducing accommodation approach. METHOD: Participants and familiar partners (N = 179) read vignette descriptions of accommodation reduction and support interventions, and responded to measures of perceived intervention acceptability/adhereability and endorsement, before completing a forced-choice preference task. RESULTS: Overall, findings suggested that participants and partners gave significantly higher ratings for the support than the accommodation reduction intervention (partial η2 = .049 to .321). Participants and partners also both selected the support intervention more often than the traditional reducing accommodation intervention when given the choice. CONCLUSIONS: Support provision is perceived as an acceptable CBT intervention for RS by participants and their familiar partners. These results have implications for cognitive behavioural theory and practice related to RS.
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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 | 0.003 | 0.015 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".