Development and validation of the Global Adolescent and Child Physical Activity Questionnaire (GAC-PAQ) in 14 countries: study protocol
Bibliographic record
Abstract
INTRODUCTION: Global surveillance of physical activity (PA) of children and adolescents with questionnaires is limited by the use of instruments developed in high-income countries (HICs) lacking sociocultural adaptation, especially in low- and middle-income countries (LMICs); under-representation of some PA domains; and omission of active play, an important source of PA. Addressing these limitations would help improve international comparisons, and facilitate the cross-fertilisation of ideas to promote PA. We aim to develop and assess the reliability and validity of the app-based Global Adolescent and Child Physical Activity Questionnaire (GAC-PAQ) among 8-17 years old in 14 LMICs and HICs representing all continents; and generate the 'first available data' on active play in most participating countries. METHODS AND ANALYSIS: Our study involves eight stages: (1) systematic review of psychometric properties of existing PA questionnaires for children and adolescents; (2) development of the GAC-PAQ (first version); (3) content validity assessment with global experts; (4) cognitive interviews with children/adolescents and parents in all 14 countries; (5) development of a revised GAC-PAQ; (6) development and adaptation of the questionnaire app (application); (7) pilot-test of the app-based GAC-PAQ; and, (8) main study with a stratified, sex-balanced and urban/rural-balanced sample of 500 children/adolescents and one of their parents/guardians per country. Participants will complete the GAC-PAQ twice to assess 1-week test-retest reliability and wear an ActiGraph wGT3X-BT accelerometer for 9 days to test concurrent validity. To assess convergent validity, subsamples (50 adolescents/country) will simultaneously complete the PA module from existing international surveys. ETHICS AND DISSEMINATION: Approvals from research ethics boards and relevant organisations will be obtained in all participating countries. We anticipate that the GAC-PAQ will facilitate global surveillance of PA in children/adolescents. Our project includes a robust knowledge translation strategy sensitive to social determinants of health to inform inclusive surveillance and PA interventions globally.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".