Strategies for Aging in Place
Bibliographic record
Abstract
For healthy and independent older adults, aging in place can be seen as identical to any other adult living at home. Little is known about how frail seniors, particularly those who speak a minority language, manage the challenges of aging in place. The present qualitative descriptive study explores the strategies that Canadian French-speaking seniors have put in place to counter their loss of independence and promote their ability to stay in their home. Semistructured individual interviews were conducted with 39 older adults and transcribed, followed by content analysis to identify common themes related to study objectives. Six themes emerged in response to strategies described for aging in place. Findings reveal the limited extent to which language issues were perceived as a barrier by participants. In conclusion, the results of this study provide us with fruitful insights to guide community nursing practice, future research, and public policy.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".