PHYSICAL ACTIVITY MEDIATES LATIN DANCE PARTICIPATION AND FITNESS OUTCOMES IN OLDER LATINOS
Bibliographic record
Abstract
Abstract Background The benefits of engaging in physical activity (PA) for older adults (OA) are well documented; however, participation rates remain low, especially among OA Latinos. Latin dance expresses and promotes culture among Latinos, and can be an effective approach to promote PA. However, the physical function and cardiorespiratory fitness (CRF) benefits of OA engaging in Latin dance have not been investigated. The purpose of this study was to test if PA from an 8-month dance trial yielded and explained improvements in physical function and CRF. Methods The study analyzed physical function and CRF outcomes from the BAILA trial. Participants (n= 333) were Latinos (age 55+) who were randomized to a dance or control condition for an 8-month study. PA was assessed using the Community Healthy Activities Model Program for Seniors (CHAMPS), physical function was assessed with the short physical performance battery protocol (SPPB) and estimated CRF was assessed using the Jurca non–exercise test model. Results. ANCOVA models found significant change in SPPB total scores(F1, 331= 4.01, p=0.046) and estimated CRF (F1, 331= 7.66, p= 0.006) over eight months in favor of the dance group. Follow-up mediation models found MVPA to mediate between group and SBBP scores, (β= 0.05, 95% CI [0.0128, 0.1147]). MVPA also mediated between group and CRF, (β= 0.06, 95% CI [0.0164, 0.1197]). Conclusion. The study supports organized Latin dance programs to be effective for improving physical and cardiorespiratory benefits among older adults. The findings also encourage future investigations to promote PA in culturally relevant forms.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".