Gender Differences in Belief-Based Markers for Physical Activity among Adolescents
Bibliographic record
Abstract
Patterns during adolescence indicate a decrease in physical activity compounded by lower levels of activity exhibited among females compared to males. Thus an understanding of gender differences in physical activity motivation and participation is needed to develop effective interventions. PURPOSE: To determine gender differences in physical activity beliefs on intention and behavior using the Theory of Planned Behaviour (TPB). METHODS: One hundred and fifty-seven students (male=97, female=60; mean grade=9.97, SD=0.94) from grades 9–12 completed self-reported measures of intention, behavioral-, normative-, and control- beliefs and a one-month follow-up of physical activity behaviour (Godin Leisure-Time Exercise Questionnaire). RESULTS: Compared to girls, boys had larger (Fisher Z, p < .05) intention-belief correlations with physical ability /skill, benefits to social interaction, physical fitness, mental health, resources, weather as a barrier, and norms from one's father (q = .16 to .37). In contrast, girls had larger intention-belief correlations than boys for pain as an anticipated outcome, and norms from siblings and friends (q = .22 to .29). For belief-behavior relationships, boys had larger (p < .05) correlations for school work as a barrier, and other plans as barriers (q = .17 to .23), compared to girls who reported larger correlations for skill/ability, opportunity as a barrier, and norms from friends (q = .24 to .36). CONCLUSION: Gender differences were found at the physical activity belief level for both exercise intention and behavior relations. Future research should consider developing interventions that target both the needs of boys and girls to effectively increase their physical activity adoption and adherence. A focus on belief-behavior differences by gender would suggest that interventions for boys should focus on time barriers and planning, while interventions for girls should pay special attention to physical activity skill development, more opportunities, and including friends in these activities.
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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 | 0.000 | 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) | 0.002 | 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".