Measuring Enjoyment of Ballroom Dancing in Filipino Americans Using the Physical Activity Enjoyment Scale
Bibliographic record
Abstract
To advance knowledge about ways to promote physical activity in Filipino Americans, this feasibility study evaluated whether they enjoyed ballroom dancing and at the same time tested the validity of the Physical Activity Enjoyment Scale (PACES) for assessing enjoyment in this population. This study consisted of a single group of healthy Filipino Americans (N = 41) aged between 35 and 65 years residing in southern Nevada. Participants danced 45 min per week for 12 weeks and completed the PACES questionnaire to measure enjoyment at two time points (Week 4 and Week 12). Four participants dropped out during Weeks 2 to 5. Thirty-seven participants completed the 12 consecutive dance sessions. Descriptive statistics, paired- sample t test, Pearson correlation, and a mixed-model ANCOVA were used for data analysis. Principal components analysis assessed the construct validity of the PACES. The mean age of the sample was 50.7 years. On average, the participants’ PACES score significantly improved from Week 4 to Week 12. Age was negatively correlated with perceived enjoyment of dancing. In terms of the validity and reliability of the PACES, high construct validity and internal consistency of the PACES were noted. This study described the effectiveness of ballroom dance as a form of physical activity among first-generation Filipino Americans and confirmed the appropriateness of the PACES for assessing enjoyment in this population. Ballroom dance has the potential to promote physical activity and improve the cardiovascular outcomes of Filipino Americans and other populations who are at risk of heart disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".