Comparing the Validity of 2 Physical Activity Questionnaire Formats in African-American and Hispanic Women
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to compare the validity of 2 physical activity questionnaire formats--one that lists activities (Checklist questionnaire) and one that assesses overall activities (Global questionnaire) by domain. METHODS: Two questionnaire formats were validated among 260 African-American and Hispanic women (age 40-70) using 3 validation standards: 1) accelerometers to validate activities of ambulation; 2) diaries to validate physical activity domains (occupation, household, exercise, yard, family, volunteer/church work, and transportation); and 3) doubly-labeled water to validate physical activity energy expenditure (DLW-PAEE). RESULTS: The proportion of total variance explained by the Checklist questionnaire was 38.4% with diaries, 9.0% with accelerometers, and 6.4% with DLW-PAEE. The Global questionnaire explained 17.6% of the total variance with diaries and about 5% with both accelerometers and with DLWPAEE. Overall, associations with the 3 validation standards were slightly better with the Checklist questionnaire. However, agreement with DLW-PAEE was poor with both formats and the Checklist format resulted in greater overestimation. Validity results also indicated the Checklist format was better suited to recall household, family, and transportation activities. CONCLUSIONS: Overall, the Checklist format had slightly better measurement properties than the Global format. Both questionnaire formats are better suited to rank individuals.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".