Évaluation de l’implantation d’un nouveau protocole de garde en établissement : profil de la clientèle, audit de dossiers et recommandations
Bibliographic record
Abstract
Since the 1990s, legislative reforms have been undertaken in many Western countries to reduce involuntary hospitalization. Studies examining fluctuation rates before and after the legislative reform show a general trend toward an increase rather than a decrease in involuntary hospitalization rates (de Stefano & Ducci, 2008). In Quebec, many reports have shown that consent for psychiatric evaluation and hospitalisation for people who present an imminent danger to themselves or to others is difficult to obtain due to clinical, legal, and ethical considerations. To facilitate this process, a new protocol was developed and implemented following the training of 335 health workers and 85 medical doctors in 6 hospitals. Our study evaluated this protocol and established a profile of people who had been hospitalized against their will. Using a retrospective analysis, we examined the files of 179 patients who underwent a psychiatric evaluation process during an involuntary hospitalization. This file analysis allowed us to develop a better profile of these people and determine whether the required forms were present and how adequately they were filled out by the professionals. We also conducted a study with the professionals responsible for applying the new protocol to get a better idea of its characteristics (relative advantage, compatibility, simplicity, reversibility and observability) as well as the principles of consent and the obstacles to its implementation.Our study showed that that half of the patients were diagnosed with schizophrenia or another psychosis. Fifty-four point two percent (54.2%) of the patients were males, 79% were single or separated and only 18,4% were working. At the time of their crisis situation, 30,7% were brought to the hospital by police officers and 19% were already hospitalized. The remaining patients were brought in by ambulance, family members or they came in by themselves. Professional opinion of the new protocol was positive however they did not rigorously enter the data required in the new forms. The new form was present in only 51% of files and when consent was given, it was only documented in 27% of the cases.These results highlight the need to improve the documentation process given in the protocol. It would be very useful to establish strategies to obtain this consent in light of the specific characteristics that make up this subgroup of people who have been hospitalized against their will. Legislation alone is not enough to invoke a change in the involuntary hospitalisation rate. The clinical and organisational context must also be actively prepared to receive this new practice. In order to do this, evaluative research could contribute to improving the level of implementation and be of benefit to people in crisis and those with mental disorders.
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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 | 0.617 | 0.593 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".