Perceived Need for Mental Health Care and Associated Factors and Outcomes in Older Adults Consulting in Primary Care
Bibliographic record
Abstract
OBJECTIVE: To assess the individual and health system factors and health-related outcomes associated with perceived need for mental health care in older adults consulting in primary care. METHOD: This longitudinal cohort study was conducted among 771 cognitively intact older adults aged ≥65 years recruited in primary care practices in Quebec between 2011 and 2013 and followed 4 years later. Predisposing, enabling and need factors were based on Andersen's framework on help-seeking behaviors. Health-related outcomes included course of common mental disorders (CMDs), change in quality of life and societal costs. Perceived need for care (PNC) was categorized as no need, met and unmet need. Multinomial regression analyses were conducted to assess the association between study variables and PNC in the overall and the subsample of participants with a CMD at baseline. RESULTS: As compared with individuals reporting no need, those with an unmet need were more likely to have cognitive decline and lower continuity of care; while those with a met need were more likely to report decreased health-related quality of life. As compared with individuals with an unmet need, those reporting a met need were more likely to report ≥ 3 physical diseases and an incident and persistent CMD, and less likely to show cognitive decline. In participants with a CMD, individuals reporting a met as compared with no need were more likely to be categorized as receiving minimally adequate care and a persistent CMD. Need for care was not associated with societal costs related to health service use. CONCLUSIONS: Overall, physicians should focus on individuals with cognitive impairment and lower continuity of care which was associated with unmet mental health need. Improved follow-up in these populations may improve health care needs and outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".