Engagement in a summer physical activity-based positive youth development program predicts improvement in life skills among youth from low-income families
Bibliographic record
Abstract
Physical activity-based positive youth development (PYD) programs integrate social, personal, and life skill lessons into recreation to facilitate growth and reduce health risk behaviors (Snyder, 2014). Evidence regarding the mechanisms of these changes is emerging. One potential mechanism is engagement, the degree to which youth find meaningful emotional and behavioral connections to the program. We examined whether engagement in a 20-day daytime summer physical activity-based PYD program for youth from low-income families predicted improved character (social conscience and personal values), caring, and reasoning skills (decision making, and critical thinking) over the course of the program. N = 298 youth (42% girls, 58% boys) aged 7–15 (M = 10.37 SD = 1.84) were surveyed on day 2 and 17 of the program. Youth self-reported social conscience, personal values, caring, decision-making, and critical thinking at both time points, and behavioral and emotional engagement at the conclusion of the program. Multiple regression was used to test whether engagement predicted change in each life skill variable. Greater behavioral engagement predicted increased social conscience (ß = .21, p = .02, R2 = .07) and decision-making (ß = .20, p = .02, R2 = .09) skills. Greater emotional engagement predicted improved personal values (ß = .22, p = .01, R2 = .10). Neither engagement measure predicted changes in caring or critical thinking (p > .05) skills. While the effects of engagement on life skills are small in magnitude, they show that even brief programs can support youth development if they are engaging to youth.Acknowledgments: The authors would like to acknowledge support from the United States Department of Agriculture/National Institute of Food and Agriculture/Children, Youth, and Families at Risk Sustainable Community Projects
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".