Developing a realist theory of psychosocial rehabilitation: the Clubhouse model
Bibliographic record
Abstract
Background Psychosocial rehabilitation is a service that supports recovery from mental illness by providing opportunities for skill development, self-determination, and social interaction. One type of psychosocial rehabilitation is the Clubhouse model. The purpose of the current project was to create, test, and refine a realist theory of psychosocial rehabilitation at Progress Place, an accredited Clubhouse. Method Realist evaluation is a theory driven evaluation that uncovers contexts, mechanisms, and outcomes, in order to develop a theory as to how a program works. The current study involved two phases, encompassing four steps: Phase 1 included (1) initial theory development and (2) initial theory refinement; and Phase 2 included (3) theory testing and (4) refinement. Results The data from this two-phase approach identified three demi-regularities of recovery comprised of specific mechanisms and outcomes: the Restorative demi-regularity, the Reaffirming demi-regularity, and the Re-engaging demi-regularity. The theory derived from these demi-regularities suggests that there are various mechanisms that produce outcomes of recovery from the psychosocial rehabilitation perspective, and as such, it is necessary that programs promote a multifaceted, holistic perspective on recovery. Conclusions The realist evaluation identified that Progress Place promotes recovery for members. Additional research on the Clubhouse model should be conducted to further validate that the model initiates change and promotes recovery outcomes.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.035 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".