Stratégies d’engagement, faisabilité et impact potentiel d’une intervention de groupe cognitive comportementale pour la psychose au sein d’une équipe de suivi intensif dans le milieu
Bibliographic record
Abstract
Objectives The study aims to document the strategies used to facilitate the engagement of participating receiving assertive community treatment (ACT) to a group cognitive-behavioral therapy for psychosis (CBTp) given for the first time in that context, and to describe the feasibility of this intervention with these consumers and the involved clinicians.Methods A group CBTp of 24 sessions has been delivered. Participants were recruited from both teams ACT of Laval, Quebec. Different strategies were elaborated and documented in order to promote participants' engagement to the therapy. Participants had to fill in the following questionnaires: Self-Esteem Rating Scale - Short Form; Brief Symptom Inventory; and Social Provision Scale before and after the therapy.Results The descriptive data show that the strategies from the Positive reinforcement category were the most used, closely followed by Materials and services, and then by the strategies that aim to compensate Memory problems. Participants showed up on average at 76% of the sessions. Four participants on eight had an improvement on their global self-esteem score, 3 improved on social support and 3 improved their global severity index of the BSI symptoms.Conclusion The information gathered could be very important for other ACT teams that wished to carry out a CBTp among the targeted customer base. These consumers could particularly benefit from this group CBTp considering it could diminish social isolation and marginalization often lived by individuals with severe mental illness.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".