Reliability and Validity of the International Physical Activity Questionnaire for Assessing Walking
Why this work is in the frame
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Bibliographic record
Abstract
Physical inactivity and its accompanying adverse sequelae (e.g., obesity and diabetes) are global health concerns. The single most commonly reported physical activity in public health surveys is walking (Centers for Disease Control and Prevention, 2000; Rafferty, Reeves, McGee, & Pivarnik, 2002). As evidence accumulates that walking is important for preventing weight gain (Levine et al., 2008) and reducing the risk of diabetes (Jeon, Lokken, Hu, & van Dam, 2007), there is increased need to capture this behavior in a valid and reliable manner. Although the disadvantages of a self-report methodology are well known (Sallis, & Saelens, 2000), it still represents the most feasible approach for conducting population-level surveillance across developed and developing countries. The International Physical Activity Questionnaire (IPAQ) was created and evaluated as a standardized instrument for this purpose. Although two versions of the IPAQwere designed and evaluated (short: nine items; and long: 31 items), the short form was recommended for population monitoring (Craig et al., 2003). However, it has not been recommended for intervention or research studies that require precise physical activity quantification to examine changes in physical activity at the individual level. IPAQ was also not intended to replace instruments that are more responsive to individual changes in activity level, such as objective measures. In addition to walking behaviors, IPAQ also assesses time spent in moderate- and vigorous-intensity activity as well as sitting behaviors, although the latter is not the focus of this analysis. Aggregated IPAQ data have been previously validated compared to accelerometers, and overall reliability was confirmed across 12 countries (Craig et al., 2003). Previous research showed criterion validity Spearman correlations with a median of 0.30 and test-retest reliability Spearman correlations clustered around 0.8 (Craig et al., 2003). The purpose of this study, however, was to reanalyze these data with respect to validity (again compared to an accelerometer) and test-retest reliability specifically for population monitoring of walking.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it