Dance for health: The importance of community engagement and project sustainability
Bibliographic record
Abstract
Dance for Health is an intergenerational approach to increasing activity, reducing the risk of obesity, and improving health awareness in an urban community. The purpose of this research was to explore the impact of community engagement in Dance for Health on graduate nurse practitioner (NP) students and inner city high school (HS) students, and to describe the factors that impact project sustainability. Qualitative surveys were administered to all students to explore their experience with community engagement. Attendance was taken and quantitative surveys were administered to community participants to evaluate the factors impacting sustainability of the intervention. We deduced the following themes from the student surveys: 1) Intergenerational togetherness, 2) Positive environment, 3) Increased awareness, 4) HS student leaders, 5) Health careers exposure for HS students, 6) Community exposure for NP students, 7) Rewarding collaboration. Eighty-eight percent of community participants continued to attend the events two months after the University involvement ceased. Community participants most commonly responded that they attended the events because it was good exercise, fun, safe, and made them “feel good”. Students who were involved stated that engagement in a community-driven, culturally relevant intervention enriched their education and leadership skills. To increase this kind of activity and improve community health overtime, universities must promote sustainability of their interventions by partnering with communities to understand their goals and priorities, and providing a culturally relevant, positive environment for physical activity and education.
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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 | 0.020 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.002 |
| 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".