Does treatment preference affect outcome in a randomized trial of a mindfulness intervention versus cognitive behaviour therapy for social anxiety disorder?
Bibliographic record
Abstract
Research suggests that treatment preference may affect outcome of randomized clinical trials, but few studies have assessed treatment preference in trials comparing different types of psychosocial interventions. This study used secondary data analysis to evaluate the impact of treatment preference in a randomized trial of a mindfulness-based intervention adapted for social anxiety disorder (MBI-SAD) versus cognitive behaviour group therapy (CBGT). Ninety-seven participants who met DSM-5 criteria for SAD were randomized. Prior to randomization, twice as many participants expressed a preference for the MBI-SAD over CBGT. However, being allocated or not to one's preferred treatment had no impact on treatment response. Additionally, with the exception of perception of treatment credibility, treatment matching had no impact on treatment-related variables, including treatment initiation, session attendance, homework compliance, satisfaction with treatment and perception that treatment met expectations. In sum, despite the greater preference for the mindfulness intervention in this sample of participants with SAD, we found little evidence of preference effects on our study outcomes. Findings should be viewed as preliminary and require replication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.073 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".