The relationship between functional measures of body image and physical activity across the lifespan
Bibliographic record
Abstract
Body image is a multidimensional construct including perceptions and attitudes about the body. While much evidence demonstrates that body image is related to physical activity behaviour, this research has typically investigated appearance aspects of body image, and primarily in adolescent and young adult populations. However, functional concerns about the body may be more relevant to physical activity. Initial research shows sport participation is linked to higher measures of functional body image in adolescent females. However, the relationship between functional measures of body image and physical activity remains relatively unexplored in other populations. The purpose of the present study was to examine the functional dimension of body image (functional investment, value, and satisfaction) in relation to physical activity across the lifespan in a diverse sample of men and women. Two-hundred-and-six women and 144 men between the ages of 18 and 85 years completed measures of body function and a self-report measure of physical activity. Regression analysis showed that gender, functional investment (i.e., the importance placed on body function), and satisfaction with function were significant predictors of moderate-vigorous physical activity, accounting for 16.2% of the variance in physical activity. The functional variables alone accounted for 7.9% of the variance in physical activity. These results suggest that physical activity may be one way to improve body image by helping people focus on what the body can do, rather than just what it looks like.
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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 | 0.005 |
| 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 | 0.000 | 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".