Indicateurs de qualité des soins en santé mentale pour les approches centrées sur la personne et axées sur le rétablissement
Bibliographic record
Abstract
Objective Meeting the mental health needs of the population is a priority of the Quebec government. To do so, it is important to evaluate and improve the quality of mental health care in primary and community care settings, particularly with respect to person-centred and recovery-oriented care. The purpose of this study is to identify existing quality indicators that measure these dimensions, and to report on their strengths and weaknesses. Method A review of systematic reviews was conducted in MEDLINE, EMBASE, PsycINFO and CINAHL, using combinations of search terms related to the concepts of "mental disorders," "primary care," "health care quality," and "review." The review of titles and abstracts review was completed by single reviewers and full-text review by pairs of reviewers working independently. Consultation with an expert in mental health care quality and a hand search of the references of identified articles finalized the search. A review of the grey literature, including the reports and websites of Canadian or international organizations, was also conducted. Results From 2837 initial references, the review of systematic reviews led to the inclusion of 6 systematic reviews. For the grey literature, relevant indicators were found on the websites of 13 organizations, including 7 international and 6 Canadian ones, from 25 organizations consulted. A total of 106 indicators were retrieved, including 91 for person-centred care approaches and 15 for recovery-oriented approaches. Among the indicators for person-centred care, two levels emerged: the organizational level, focusing mainly on continuity issues, and the practice level, focusing on processes related to the care providers or the individual. For recovery-oriented approaches to care, four categories emerged: community connections, discrimination and stigma, social roles, and social support. Conclusion Evaluating person-centered, recovery-oriented care for people with mental disorders based on robust quality indicators poses a major challenge and our review revealed several limitations related to the current set of indicators that exist to measure these approaches. Further efforts must be made to improve the measurement of quality of mental health care in terms of person-centred and recovery-oriented care, so that the governmental and clinical strategies currently in place, such as the Programme Québécois pour les Troubles Mentaux (PQPTM), can achieve their goals.
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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 | 0.111 | 0.323 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.014 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".