The effectiveness of an online short-format Recovery College model: a co-learning model to support mental health
Bibliographic record
Abstract
BACKGROUND: Our societies are facing mental health challenges, which have been compounded by the Covid-19. This event led people to isolate themselves and to stop seeking the help they needed. In response to this situation, the Health and Recovery Learning Center, applying the Recovery College (RC) model, modified its training program to a shorter online format. This study examines the effectiveness of a single RC training course delivered in a shortened online format to a diverse population at risk of mental health deterioration in the context of Covid-19. METHODS: This quasi-experimental study used a one-group pretest-posttest design with repeated measures. Three hundred and fifteen (n = 315) learners agreed to take part in the study and completed questionnaires on wellbeing, anxiety, resilience, self-management, empowerment and stigmatizing attitudes and behaviors. RESULTS: Analyses of variance using a linear mixed models revealed that attending a RC training course had, over time, a statistically significant effect on wellbeing (p = 0.004), anxiety (p < 0.001), self-esteem/self-efficacy (p = 0.005), disclosure/help-seeking (p < 0.001) and a slight effect on resilience (p = 0.019) and optimism/control over the future (p = 0.01). CONCLUSIONS: This study is the first to measure participation in a single online short-format RC training course, with a diversity of learners and a large sample. These results support the hypothesis that an online short-format training course can reduce psychological distress and increase self-efficacy and help-seeking. TRIAL REGISTRATION: This study was previously approved by two certified ethics committees: Comité d'éthique de la recherche du CIUSSS EMTL, which acted as the committee responsible for the multicenter study, reference number MP-12-2021-2421, and Comité d'éthique avec les êtres humains de l'UQTR, reference number CER-20-270-07.01.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".