Validity and Reliability Assessment of a Food and Physical Activity Questionnaire for Adolescents From Low-Income Communities
Bibliographic record
Abstract
OBJECTIVE: Develop and validate an evaluation questionnaire for sixth-12th grade Expanded Food and Nutrition Education Program (EFNEP) participants. DESIGN: Five-step process: domain concept prioritization, question generation, question pretesting, reliability testing, and criterion validity testing. SETTING: Community sites in 4 states and New Jersey EFNEP secondary program data. PARTICIPANTS: Nineteen sixth-12th graders were interviewed; secondary data included 164 ninth-12th graders. VARIABLES MEASURED: Content, face, and criterion validity; internal reliability. ANALYSIS: Iterative template analysis to gauge conceptual understanding; exploratory factor analysis with orthogonal Varimax rotation, interitem correlations, and Cronbach α; Spearman correlations and Bland-Altman plots against the Physical Activity Questionnaire for Adolescents and Youth Risk Behavior Survey questions. RESULTS: Fourteen questions with acceptable face validity were developed. One item (handwashing) had a ceiling effect and was removed. Eleven of the remaining 13 items were loaded onto 4 factors. The remaining 2 items were kept because of conceptual relevance. The questionnaire demonstrated acceptable reliability and validity overall, but subscale Cronbach α values ranged from 0.53-0.75. CONCLUSIONS AND IMPLICATIONS: This 13-item questionnaire was presented to national EFNEP program leaders and was implemented by EFNEP in October 2023. Further research could establish temporal reliability and gold standard criterion validity estimates with a multistate sample of sixth through 12th graders.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".