The physical activity parenting practices (PAPP) item Bank: a psychometrically validated tool for improving the measurement of physical activity parenting practices of parents of 5–12-year-old children
Bibliographic record
Abstract
BACKGROUND: Many tools have been developed to measure physical activity parenting practices (PAPP). Currently, there is little standardization on how PAPP constructs are operationalized for 5-12 year-old children. Given this lack of consistency our team have started the process of standardizing the measurement of PAPP by developing an item bank which was conceptually informed by 24 experts from 6 countries. PURPOSE: The purpose of this paper is to present the psychometric properties of the PAPP item bank using the expert-informed PAPP conceptual framework. METHODS: A sample (N = 626) of Canadian parents completed the PAPP item bank (100 items measuring 12 constructs). Confirmatory Factor Analyses (CFA), confirmatory bi-factor item analyses, and Item Response Modeling (IRM) were used to assess the structural validity of scores derived from the PAPP item bank. Differential Item Functioning (DIF) and Differential Response Functioning (DRF) were used to determine whether the PAPP items are invariant by parent sex, ethnicity of parent, and household income. Finally, Computerized Adaptive Testing (CAT) simulations were used to determine the efficiency of the item bank - this involved ascertaining whether each construct can be assessed with fewer items. RESULTS: The PAPP expert-informed conceptual framework was mainly supported by the CFA analyses. Notable changes included: a) collapsing smaller constructs into one general construct (modeling, co-participation, and monitoring constructs were collapsed into a construct assessing nondirective support); or b) splitting a construct into two smaller constructs (restrict for safety reason construct was split into indoor physical activity restriction and allowance for unsupervised outside physical activity). While the CFA analyses supported the structural validity of 11 constructs, the bi-factor item analyses and IRM analyses supported collapsing correlated constructs into more general constructs. These analyses further reduced the number of constructs measured by the PAPP item bank to nine constructs (65 items - reliability ranging from .79 to .94). As seven of the PAPP constructs had reliability greater than .80, CAT simulations further reduced the number of items to 31 items. CONCLUSION: Overall, the PAPP item bank has excellent psychometric properties and provides an efficient way to assess PAPP.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".