Joint Crisis Plan in Mental Health Settings: A Reflective Process More than an Intervention Tool?
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Coercion in mental health is challenged, prompting reduction interventions. Among those, the Joint Crisis Plan (JCP), which aims to document individuals' treatment preferences in case of future de-compensation, regardless of the potential loss of discernment, has been identified as a key path to study. Identified challenges related to its implementation highlight the need to adapt this intervention to the local context. Considering that in Quebec (Canada), the JCP is not widely used, but the scientific literature supports its adoption and corroborates its potential impact on reducing coercion, this study evaluates the feasibility, acceptability, and preliminary outcomes of the JCP among psychiatric and forensic inpatient settings. METHODS: A pilot mixed-methods study was conducted through 16 individual interviews with inpatients and healthcare providers, combined with a pre-post analysis of seclusion and restraint use and the violence prevention climate (VPC) based on healthcare providers' (n = 57) and inpatients' perspectives (n = 53). RESULTS: = 0.40) in the VPC was identified based on healthcare providers' perspectives. Qualitative findings are also insightful to understand the acceptability and feasibility of the JCP use. A tension emerged between the perspectives of inpatients and healthcare providers: while inpatients valued the reflective process of completing the plan, providers focused more on its technical aspects. CONCLUSIONS: The results support the integration of the JCP into patient care pathways, as it provides a tool to amplify patients' voices, promote patient empowerment, facilitate open dialog on alternatives to coercion, and foster more collaborative and humane 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 | 0.070 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".