Psychosocial group therapy interventions for patients with physical disabilities: A scoping review of implementation considerations.
Bibliographic record
Abstract
OBJECTIVE: Group therapy is an intervention that that has been well-studied in patients with medical illness and shown to optimize patients' wellbeing and mental health resource utilization. However, its implementation and effectiveness have not been adequately studied in those with physical disabilities. This review addresses current gaps by synthesizing the literature to examine implementation considerations in the use of psychosocial group therapy for anxiety and depression in individuals with physical disabilities. METHOD: This review adhered to Arksey and O'Malley's methodological framework and the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews Checklist. Studies were identified through MEDLINE, EMBASE, PSYCINFO, and CINAHL. Included studies were qualitative, quantitative, or mixed methods research on participants with a physical disability, and undergoing psychosocial group therapy to address anxiety/depression. RESULTS: = 27) reported high adherence rates (80%-99%), and a large proportion found group therapy led to improvements in their samples on a range of outcomes. CONCLUSION: Group therapies to address anxiety and depression are diverse, widely used, effective, and well-adhered to. This review may help practitioners develop, implement, and evaluate group programming for individuals with physical disabilities to address anxiety and depression. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.016 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".