Exploring the effects of a 12-week exercise intervention on body image in older adults
Bibliographic record
Abstract
By 2030, 1 in 4 Canadians will be a senior. This aging population experiences several physical and psychological changes that can negatively impact health and lead to strain on the health care system. Physical activity has been associated with many physical and psychological benefits, such as decreased risk of chronic disease, improved cognitive functioning, ability to perform activities of daily living, higher quality of life, and decreased depression. One benefit that remains understudied in older adults is body image. Exercise can potentially alleviate the negative effects of aging on body image, however, older adults' participation rates in physical activity remain low. The purpose of this study was to examine the effects of a 12-week general physical activity program on body image in men and women 55 years and older. Participants (81 men and 217 women) were randomly assigned to an exercise group (60 minutes of supervised cardiovascular, strength, balance, and flexibility training three times per week) or a wait-list control. Measures of evaluation and investment in appearance, health, and illness as well as anxiety about the body were completed at baseline and 12 weeks later. Repeated measures analyses, controlling for gender, were conducted. The results showed no significant group (exercise, control) x time (pre, post) interaction, indicating no improvements on any of the outcomes following exercise (all ps > .05). Overall, the sample was healthy and active prior to participation; future research should investigate changes in a less active sample.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".