Clustering change patterns among learners of an online Recovery College in Quebec
Bibliographic record
Abstract
Introduction: Recovery Colleges (RCs) are educational hubs offering free courses on mental health, well-being, and recovery through mutual and transformative learning. These co-learning spaces bring together individuals with diverse backgrounds-such as those with lived experience of mental illness, family members, and mental health practitioners-to collaboratively produce knowledge on mental health topics. Studies have shown RC participation leads to improvements in several psychosocial dimensions (e.g. mental health literacy, empowerment, well-being, reduced anxiety, stigma) and healthcare utilization. However, the methodological approach of averaging outcomes across all participants can mask important individual differences in experiences and outcomes, which is particularly significant given the heterogeneity of RC learners. In light of these limitations, this study aims to explore the heterogeneity of change among RC learners by identifying different trajectories of change and exploring their determinants. Methods: The study adopts a quasi-experimental longitudinal design with repeated measures, utilizing data from 353 participants recruited from a French-language RC in Quebec, Canada. Data were collected at three time points: baseline (T0) prior to program participation, one-month post-program (T1), and three to four months post-program (T2). The study uses clustering techniques to identify distinct patterns of change across participants, focusing on key outcome measures such as well-being, anxiety, resilience, empowerment, and stigma. Results: The results identified three distinct clusters of change trajectories. The largest cluster (Cluster A) demonstrated moderate improvements in well-being, anxiety reduction, and slight increases in empowerment and resilience. Cluster B, characterized by participants with higher baseline well-being and lower stigma, showed improvements in empowerment and a slight reduction in stigma, often linked to participants with clinical backgrounds, such as healthcare practitioners. Cluster C, primarily composed of participants with clinical levels of anxiety and lower baseline empowerment, exhibited significant reductions in anxiety and increases in empowerment over time. Discussion: This study contributes to a more nuanced understanding of the diverse outcomes associated with RC participation and highlights the importance of tailoring RC programs to meet the heterogeneous needs of learners. It also reinforces the role of empowerment as a central mechanism of change within the RC model, suggesting that empowerment fosters not only personal growth but also improved well-being and reduced stigma.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".