A qualitative exploration of a community-based singing activity on the recovery process of people living with mental illness
Bibliographic record
Abstract
Introduction This study first aims to qualitatively explore the benefits of a community-based singing activity taking place in Montreal, Canada. The second aim is to identify the activity’s essential components that potentially explain these benefits. Method An exploratory evaluative design involving qualitative descriptive methods was used. Thirteen individuals with various mental illnesses, the voice teacher and the activity coordinator participated in a group interview. Findings Four main benefits emerged from the participants’ interviews: (1) rediscovering identity and gaining self-confidence; (2) resuming and engaging in meaningful occupations and projects; (3) learning to collaborate with others and improving social skills; (4) improving physical condition and cognitive skills. The essential components of the activity were identified as: a normalizing environment and the absence of stigma; high expectations and support for participants; teacher-led stress relief exercises and activities; the use of singing as an activity to express emotions and stimulate cognitive functions. Conclusion This community-based singing activity appears to have contributed to the recovery process of its participants. There is a clear role for occupational therapists to promote, facilitate and support such activities outside traditional mental health services, since the participants were looking for occupational participation opportunities in normalizing community contexts.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".