People who stick to the program: Understanding self-efficacy in middle-aged and older adult men and women
Bibliographic record
Abstract
Physical activity rates in Canada are poor across adulthood, with rates declining as people get older. With the Canadian population aging, understanding factors related to exercise adherence in older populations is critical. This study determined if three different types of self-efficacy (task, scheduling, and barriers) could predict adherence to an exercise program in middle-aged and older men and women. Adherence data was examined from a subset of women (n = 125; Mage = 66.74 years, SD = 6.29) and men (n = 51; Mage = 69.69 years, SD = 6.46) who participated in a 12-week structured exercise program. Participants were community dwelling, independent walkers with no neural impairments. Hierarchal regressions were conducted, one for each gender. For women, controlling for body mass index (BMI), age and baseline physical activity, the self-efficacy variables accounted for significant variance in adherence, F(6, 118) = 4.19, p < .001, R2adj. = .134. Significant predictors of adherence were physical activity (I² = .228, p = .01), barrier self-efficacy (I² = .239, p = .02) and scheduling self-efficacy (I² = .288, p = .00). For men, controlling for BMI, age and baseline physical activity, the self-efficacy variables accounted for significant variance in adherence, F(6, 44) = 4.30, p = .00, R2adj. = .283. Significant predictors of adherence were age (I² = .290, p = .03) and task self-efficacy (I² = .425, p = .01). Future research should focus on designing physical activity programs that emphasize increasing types of self-efficacy specific to men and women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".