Health Literacy, Pedometer, and Self-Reported Walking Among Older Adults
Bibliographic record
Abstract
OBJECTIVES: We examined the association of health literacy with physical activity and physical activity guideline adherence in older adults. METHODS: We used cross-sectional data from a 2012 population-based study in Alberta, Canada, assessing health literacy, and deriving moderate-to-vigorous physical activity (MVPA) and metabolic equivalent of task (MET) minutes per week from the Godin Leisure-Time Exercise Questionnaire, and steps per day via a pedometer. RESULTS: Mean age of participants (n = 1296) was 66.4 (SD = 8.2) years, 57% were female, and 94% were White. Nine percent had inadequate health literacy, and 46% met guidelines for self-reported physical activity and 18% for steps per day. Participants with inadequate health literacy had nonsignificant adjusted decrements of 58 MVPA minutes and 218 MET minutes per week and were less likely to meet physical activity guidelines (MVPA: odds ratio = 0.63; 95% confidence interval [CI] = 0.41, 0.97; P = .037; MET: odds ratio = 0.65; 95% CI = 0.42, 1.01; P = .057) compared with their health-literate counterparts. Such differences were nonsignificant for steps per day. CONCLUSIONS: Inadequate health literacy was associated with less likelihood of meeting MVPA guidelines based on self-reported physical activity, but not based on an objective measure of steps per day.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".