Health literacy programs for older adults: a systematic literature review
Bibliographic record
Abstract
Older adults make up the fastest growing age group in North America. This has demanded increased attention in supporting the health and well-being of this population and, in particular, the role of health information in promoting the health and well-being of older adults. Increased availability and accessibility of information as well as a greater emphasis on self-management and care have raised concern about an individual's health literacy skills. The purpose of this study is to conduct a systematic literature review using explicit systematic literature review methodology. This includes a detailed online search process of recent publications on programs that focus on health literacy in the older adult population using the Rychetnik et al. guiding questions and the Population Intervention Comparison Outcome framework. The search yielded nine articles describing functional (n = 4) and interactive (n = 5) health literacy programs. Overall, the selected articles demonstrated positive outcomes in supporting the health literacy skills of older adults. However, there are limitations in study designs and evaluation measures and outcomes of the programs remain unknown in demonstrating long-term impact in supporting health literacy skills. Further high quality studies with clear and strong research methodology are needed to develop and evaluate evidence-based interactive health literacy programs targeted specifically to older adults.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".