Do anxiety and depression symptoms moderate the effect of motivational enhancement therapy as a pretreatment to dialectical behaviour therapy skills training? A follow‐up analysis of a pilot randomised controlled trial for youth
Bibliographic record
Abstract
AIM: We conducted a follow-up analysis of a pilot randomised controlled trial to examine whether baseline depression and anxiety symptoms moderated the impact of a motivational enhancement therapy (MET) pretreatment to dialectical behaviour therapy skill training (DBT-ST) for EA experiencing emotion dysregulation. METHODS: All participants completed a 12-week DBT-ST group intervention and participants in the MET/DBT-ST condition also completed a 4-week group MET pretreatment. Nineteen MET/DBT-ST participants and 26 DBT-ST only participants completed the treatment as per protocol. RESULTS: Baseline anxiety and depression symptoms moderated the impact of the MET pretreatment for participants' reductions in emotion dysregulation and psychological distress, respectively, at a 3-month follow-up: participants with more severe baseline symptoms benefited more from the pretreatment. However, baseline symptoms did not moderate the effect of MET immediately after treatment. CONCLUSIONS: These results identified for whom MET is most effective as a pretreatment for DBT-ST amongst a heterogenous sample of EA in a real-world setting.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".