Predictors of family-focused practices among mental health workers in Quebec
Bibliographic record
Abstract
Context: Engaging family members in the ongoing care of individuals with mental illness is a practice known to bolster the client's recovery journey and enhance the overall wellbeing of both children and families involved. Despite its potential benefits, there remains a dearth of understanding surrounding the implementation of family-focused practices (FFP) by mental health professionals serving adults, as well as the factors that could either promote or hinder such practices. This knowledge gap is particularly pronounced within North American settings. Goal: The goal of this study was to identify potential hindering and enabling factors of FFP used in adult mental health services. Methods: A sample of 512 professionals working with adult mental health clients, from all regions of Quebec, Canada, with a variety of disciplinary backgrounds and working in different work settings, completed the Family Focused Mental Health Practice Questionnaire (FFMHPQ). Multinominal logistic regression analysis was performed to assess the impact of several factors - organizational, professional, and personal - on the degree of family-based practices of mental health workers. Results and discussion: Findings of this study show that the strongest predictors for the adoption of higher FFP levels among adult mental health professionals in Quebec, are being employed on a full-time basis, perceiving a higher level of skills, knowledge, and confidence toward FFP, and having a supportive workplace environment. Results underscore the need to address both organizational and worker-related aspects to effectively promote better FFP in mental health services.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".