Cognitive Behavioural Analysis System of Psychotherapy for Treatment-Resistant Depression: Adaptation to a Group Modality
Bibliographic record
Abstract
Studies researching psychotherapeutic interventions for treatment-resistant depression (TRD) are quite new to the field. The Cognitive Behavioural Analysis System of Psychotherapy (CBASP) is the only model developed specifically to treat the chronically depressed patient. While empirical evidence indicates that CBASP is an effective treatment for chronic depression, little is known about its adaptation to a group modality. Treating these patients in a group approach would have the added benefits of being cost-effective and providing in vivo previously avoided interpersonal situations for practising social skills and role-plays. This single arm study asks whether CBASP adapted to a group modality can be effective. All patients received 12 CBASP group therapy sessions with two to four individual preparatory sessions before the group. Our results suggest that CBASP group treatment demonstrated positive effects on patient outcomes. Specifically, patients showed significant decreases in symptoms of depression and the use of emotion-oriented coping, as well as increases in overall social adjustment and interpersonal self-efficacy when compared to pretreatment levels. However, patients did not achieve normative levels in these areas by the end of treatment. These pilot results are encouraging and support further study of the effectiveness of CBASP group treatment with a control group.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".