Utility of the Montreal Assessment of Need Questionnaire for Community Mental Health Planning
Bibliographic record
Abstract
Needs assessment facilitates mental health services planning, provision, and evaluation. This study aimed to (a) validate a new instrument, the Montreal Assessment of Needs Questionnaire (MANQ), and (b) use this to assess variations and predictors of need (number and seriousness) in 297 individuals with severe mental disorders for 18 months, during implementation of the Quebec Mental Health Action Plan. MANQ internal and external validations were adequate. Variables significantly associated with need number and seriousness variations were used to build multiple linear regression models. Autonomous housing, not receiving welfare, not having consulted a health educator, higher level of help from services, Alcohol Use Disorders Identification Test total score, and social support were associated with decreasing need number and seriousness over time. Having a higher education was also associated with decreasing need number. In a reform context, the MANQ's unique ability to detect rapid improvement in patient needs has usefulness for Quebec mental health planning.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".