Challenges in Implementing Recovery-Based Mental Health Care Practices in Psychiatric Tertiary Care
Bibliographic record
Abstract
Despite increased interest in the concept of recovery, not enough is known about the challenges of implementing recovery models in mental health care settings. Findings are presented from a 3-year feminist ethnographic study that followed recently deinstitutionalized women and men as they moved into psychiatric tertiary care facilities in British Columbia where a psychosocial rehabilitation model based on recovery principles was implemented. We found that inconsistent staff training and stretched community supports have resulted in uneven implementation that does not yet maximize opportunities for people's recovery. Further, care is organized and delivered in ways that emphasize individual needs as opposed to social and collective needs based on factors such as gender, ethnicity, and culture. These findings indicate that greater political will, as measured in commitments to community-based mental health services, is required to fully realize the philosophy of recovery and equitable mental health care.
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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 | 0.046 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.010 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".