“ <i>I Am Not Alone”</i> : A Photovoice Exploration of Diabetes Self-Management for Older Persons in Rural Ontario, Canada
Bibliographic record
Abstract
ObjectiveTo explore diabetes self-management for older adults in rural Ontario.MethodsFourteen adults, 65 and older, with diabetes, participated in this study using a participatory, art-based approach involving photovoice and semi-structured interviews. Data underwent hermeneutic phenomenology analysis.FindingsFour themes emerged, elucidating the lived experiences of participants managing diabetes in a rural context.DiscussionThis study underscores the challenges and strategies of diabetes self-management in rural older adults. A holistic approach, encompassing physical, emotional, and mental well-being, is pivotal, augmented by proactive lifestyle choices. Effective coordination in medication management and enhanced communication among health care providers emerged as essential. The unique role of pets illuminates their profound impact on participants' activity levels and emotional fortitude, suggesting they can be vital assets in diabetes care. Collectively, these findings guide health professionals and policymakers in crafting nuanced, context-sensitive interventions to optimize diabetes management for older adults in rural contexts.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".