Transdiagnostic cognitive-behavioral group therapy for anxiety disorders: Therapists’ perception of group management in community-based care
Bibliographic record
Abstract
Introduction Cognitive-behavioral therapy (CBT) is recognized as an effective treatment for anxiety disorders. Transdiagnostic group CBT (tCBT) targets cognitive and behavioural intervention strategies common to anxiety disorders. tCBT allows the treatment of a larger number of patients simultaneously and therapists only need to master a single intervention protocol. However, tCBT may present several challenges for therapists, particularly regarding group management. Objectives To explore therapists’ perceptions and experience of group management during tCBT for mixed anxiety disorders. Methods A qualitative study embedded in a randomized controlled trial of group tCBT (Roberge & Provencher; CIHR, 2015-2021). Semi-structured interviews were conducted with 18 of the 21 therapists to document their perceptions and to identify improvements for tCBT delivery. The data were analyzed using a deductive approach and based on the interactive cyclical process of data reduction, display and conclusion drawing. Results Therapists raised the challenge of the heterogeneous characteristics of participants’ anxious profile, since they had to be creative to provide exercises that were suitable for a whole group. Exposure exercises, a key component of tCBT, were particularly affected by the composition of the groups. Previous group animation experience and the ability to establish a therapeutic alliance from a group perspective were important facilitators. Co-therapy also facilitated the intervention, since it allowed the therapists to be more vigilant to group dynamics and favored the organization of tCBT. Conclusions This study highlights the importance of exploring therapists’ perceptions and experience about group management in order to identify facilitators and barriers of group tCBT in community-based care. Disclosure No significant relationships.
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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 | 0.017 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".