Cognitive-Behavioural Social Skills Training: Mediation of Treatment Outcomes in a Randomized Controlled Trial for Youth at Risk of Psychosis: L’entraînement aux compétences sociales cognitivo-comportementales : variables médiatrices des résultats thérapeutiques dans le cadre d’un essai clinique randomisé pour les jeunes présentant un risque de psychose
Bibliographic record
Abstract
OBJECTIVES: Currently, there are no effective treatments for functional outcomes (i.e., role and social) and negative symptoms for youth at clinical high-risk (CHR) for psychosis. Investigations into possible mechanisms that may contribute to the improvement of functioning and negative symptoms are needed in CHR research to help inform psychosocial treatments. The present study examined whether functioning and negative symptoms were mediated by asocial beliefs, defeatist beliefs, self-efficacy, maladaptive schemas, anxiety, depression, social cognition, or attenuated psychotic symptoms (APS) in a large clinical trial. METHODS: = 203; 104 females; 99 males) were recruited as part of a three-site randomized control trial comparing group cognitive-behavioural social skills training (CBSST) versus a supportive therapy group. Mediation analyses were conducted to test the relationships between treatment group, mediators (asocial beliefs, defeatist beliefs, self-efficacy, maladaptive schemas, anxiety, depression, social cognition, and APS), and outcome (social and role functioning, and negative symptoms). The mediation analyses employed conditional process path analysis via ordinary least squares regression. RESULTS: At the end of treatment, but not 12-month follow-up, more severe APS were found to mediate the impact of treatment on negative symptoms, and social and role functioning. The greater the severity of APS, the less likely that CBSST would result in improvement in negative symptoms and social and role functioning. Many of the other variables showed significant associations with social (less for role) functioning and negative symptoms but did not mediate the effect of treatment on these outcomes at the end of treatment or 12-month follow-up. CONCLUSIONS: There were no significant mediators except for APS at the end of treatment. Since more severe APS may result in participants being unable to fully participate in therapy and thus limit their gains, clinical implications may include offering some individual therapy to prepare these young people to benefit from the group treatment.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".