Exploring Older Adult Mental Health Considerations in the Context of the COVID-19 Pandemic: A Framework Approach
Bibliographic record
Abstract
Older adult mental health is a priority in Canada, especially with the deleterious effects of COVID-19. However, there is a gap in knowledge about the mental health-related considerations and concerns that are important for supporting aging Canadians. \n \nSecondary framework analysis used deductive codes constructed from a critical mental health literature review, and inductive codes generated from n=268 previously gathered free-form survey responses from older adults, caregivers, and health/social care providers in Canada. Key considerations included 1) core principles that influence the experiences and outcomes of older adults; 2) societal and system-level factors affecting older adult mental health; 3) services, supports, and programs that were identified as valuable; and 4) mental health experiences and outcomes mapped to a mental health dual continuum model. \n \nThe expert-by-experience identified considerations are key elements that can be used when developing/adapting resources to ensure they are appropriate, relevant, and effective for aging Canadians’ mental health needs.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".