Depression, anxiety, and personal recovery outcomes after group vs individual transdiagnostic therapy: a brief report
Bibliographic record
Abstract
Unified Protocol for Transdiagnostic Treatment of Emotional Disorders (UP) is an evidence-informed treatment utilizing Cognitive Behavioural Therapy (CBT) treatment principles. UP has demonstrated promising treatment effects comparable to single disorder protocol across several mental disorders. Its impact on personal recovery in anxiety and depression has not been examined. This study compares clinical and personal recovery outcomes of UP treatment for depression and anxiety disorders when delivered in a group vs. individual format. Retrospective chart review of outcomes was conducted for outpatients receiving 12-week individual (n = 65) and group (n = 62) UP treatment in a specialized psychiatric hospital. Descriptive and repeated measures ANOVA analyses were conducted on outcomes on Overall Depression Severity and Impairment Scale, Overall Anxiety Severity and Impairment Scale, Recovery Assessment Scale administered pre and post treatment. On average, participants in both group and individual UP treatment showed improvements in anxiety, depression, and recovery scores. Greater proportion of group participants showed improvements on two interpersonal-focused domains of personal recovery. Results indicate group UP treatment is comparably effective compared to individual UP in improving clinical and recovery outcomes, and treatment modality affects the degree of personal recovery. Overall findings offer important clinical promise of UP treatment as a transdiagnostic treatment option for individuals with anxiety and depression.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".