Late-life mental health, substance use and addiction service needs in Manitoba
Bibliographic record
Abstract
Adults ages 65+ may experience mental health or substance use / addiction (‘SUA’) challenges that can endanger their quality of life, health, and longevity. Yet mental health and/or SUA services are often unavailable or inaccessible for adults 65+, which can perpetuate unmet needs. Services become more accessible when they reflect the needs and priorities of intended users; however, few studies have engaged individuals who use and deliver late-life mental health and/or SUA services to better understand their needs and priorities. The primary objective of this mixed-methods research was to describe the mental health and SUA service needs and priorities of adults 65+ and those who deliver services to adults 65+. A secondary objective was to explore adults’ 65+ SUA literacy (i.e., knowledge of how to recognize and manage SUA problems and find and access SUA services and information). Six adults 65+ who had tried to access services participated in two virtual focus groups, and six service leaders and providers participated in a separate two-part focus group series, to discuss service and research needs, and define and set service priorities. Using reflexive thematic analysis, four main themes described adults’ 65+ experiences of services: 1. “What you need just isn’t there”; 2. “Where do I go?”: Knowing about and finding services; 3. “Roadblocks” along pathways to services; 4. COVID-19 “forced” new ways of connecting with people and services. Four additional themes reflected service leader and provider perspectives. Priority-setting was achieved with each group using a modified nominal group technique. Emergent priorities were then built into an online survey for validation with a convenience sample of community-living adults 65+ (n = 138). Respondents selected protection and advocacy services for older adults as a top priority, followed by more involvement of caregivers in treatments and care teams. The survey was also used to examine differences between respondents’ SUA and mental health literacy (analyzed using a paired samples t-test), and sociodemographic and psychosocial predictors of SUA literacy (analyzed using hierarchical linear regression). Low to moderate SUA literacy (M = 3.1, SD = 0.97) among the adult 65+ sample was significantly lower than their mental health literacy, t(137) = -3.30, p = .001, and both older age and limited SUA lived experience were significant predictors of lower SUA literacy. Findings inform future selection, funding, and delivery of services that are targeted to the needs of aging populations and recommend clarifying pathways into them.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".