Validation for the Children Health Promotion Scale: Development and Psychometric Testing
Bibliographic record
Abstract
BACKGROUND: Several investigators have developed health promoting lifestyle instruments for adult population. However, few instruments in Taiwan have focused on health-promoting lifestyle measurements from the perspective of children.METHODS: The Children Health Promotion scale (CHP) was developed to focus on health promotion among children. The content validity was supported on the observations of a 6-member panel of experts. Here, based on the responses of 681 Taiwanese children, we examined the construct validity and reliability of the CHP as well as its psychometric properties through factor analysis and reliability measures.RESULTS: The results of Kaiser-Meyer-Olkin (KMO) and Bartlett’s sphericity tests indicated that our sample fulfilled the factor analysis criteria. Moreover, the factor analysis yielded a 6-factor instrument, explaining 52.5% of variance in all 32 items; the 6 factors were myopia prevention, stress management, health maintenance behaviors, nutritional behaviors, physical activities, and basic health-promoting behaviors. The Cronbach’s alpha reliability coefficient for the total scale was 0.92 and alpha coefficients for the subscales ranged from 0.71 to 0.85.CONCLUSION: The results of this study indicate that the CHP has satisfactory construct validity and reliability for Taiwanese children. School health providers can therefore use the CHP for children’s health promotion efforts.
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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 | 0.025 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".