Affective Benefits are as Important as the Awareness of Improved Health as Motivators to be Physically Active
Bibliographic record
Abstract
Most people are aware of the health benefits associated with physical activity (PA). Nonetheless, most Americans and Canadians do not meet the recommended PA guidelines of 150 minutes of moderate to vigorous PA plus 2 or more strengthening activities per week. The purpose of this study was to explore and compare the top motivators of PA for adults in Southern Ontario and South Carolina. In addition to better health, it was hypothesized that affective motivators such as “feeling good and happier afterwards” would be indicated as preferred motivator towards exercise. Focus group facilitated discussions were conducted with 234 people from Southwestern Ontario and 175 people from South Carolina representing various focus groups. Guiding questions included their beliefs, attitudes, opinions, and attitudes on motivators to PA and exercise including their main motivators to want to participate in physical activity. Surveys were distributed in Southern Ontario and South Carolina to individuals 18 years of age and older from the same community groups where the focus group data were initially collected. Both Canadian and American adults residing in Southern Ontario and South Carolina indicated the same top 3 barriers: i) better health, ii) feeling good and happier afterwards, and iii) losing or maintaining my weight. Interestingly, not even making the top five were exercising with a friend or group and personally impacted by negative consequences of health. The results indicate that while people realize better health is a positive outcome when engaged in day to day PA, it is the affective benefits of PA that are equally or even more important. The successful promotion of PA, in order to reach as many people as possible, should focus not only on the physical health benefits, but affective outcomes such as feeling good, enjoying the PA experience, developing confidence and a higher level of self-esteem.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".