A multisite longitudinal evaluation of Canadian clubhouse members: Impact on hospitalizations and community functioning.
Bibliographic record
Abstract
OBJECTIVE: The Clubhouse model of psychosocial rehabilitation supports the personal recovery of individuals with severe mental health challenges. To date, there has never been a multisite, longitudinal study examining the outcomes of Clubhouse members in Canada. Therefore, the purpose of the present study was to longitudinally assess the psychosocial outcomes and hospitalization rates of Clubhouse members from six Clubhouses across Canada. An exploratory aim of this study was to assess the psychosocial impact of the COVID-19 pandemic on Clubhouse members. METHOD: The present study used a participatory approach with six accredited Clubhouses across Canada. A total of 462 Clubhouse members consented to participate in the study. Members completed a questionnaire battery every 6 months over a 2-year period (five data points total). The last three data points were collected during the COVID-19 pandemic. Primary outcomes included community functioning, measured by the Multnomah Community Ability Scale, and self-reported hospitalization rates. Data were analyzed using multilevel growth models. RESULTS: The results of the analysis indicated stability over the study period in community functioning and rates of hospitalization. Subscales of community functioning, including interference in functioning and behavioral problems improved over the course of the study, while adjustment to the community and social competence remained stable. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: The consistency in outcomes across the study is notable, due to the worldwide impact of COVID-19 on mental health. Clubhouses may have had a buffering effect for members, in that membership diminished the impact of the pandemic on mental health. (PsycInfo Database Record (c) 2024 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".