The PAPA Questionnaire: Assessment of Long-Term Engagement in Activities, with Separate Quantification of Their Physical, Cognitive, and Social Components
Bibliographic record
Abstract
Purpose: Engagement in activities promotes healthy living. Evaluating it is a challenging issue. Assessing engagement in activities while differentiating the physical, cognitive, and social component of each activity and taking into account the intensity level involved in each of the three components would be very relevant. Since none of the currently available cognitive reserve and questionnaires on the activities practiced takes into consideration both points, the purpose of this new questionnaire, called Pertinent Activities Practice in Adults (PAPA) questionnaire, is to fill these gaps. Patients and Methods: The questionnaire was developed through a literature review and interviews with older adults (n=177 ≥55 years). The intensity level of each item (none, light, moderate, or high) was determined by the compendium of physical activities for the physical component and consensus for the cognitive and social components, then validated by 56 professional experts (6 groups: physiotherapists, neuropsychologists, occupational therapists, geriatricians, etc.). Results: The PAPA questionnaire includes 75 items that give rise to 4 scores (sedentary lifestyle and physical, cognitive, and social activity scores) weighted by the frequency, duration, and intensity level for each component. The weighted percentage of agreement of the expert groups for the intensity levels was never significantly lower than the minimum target threshold (80% of the hypothetical median) except in a single domain (cognitive) for an expert group non-specialized in cognition. Cronbach's alpha was ≥0.85. Conclusion: This questionnaire, which assesses long-term engagement in activities, with separate quantification of the physical, cognitive, and social components of a wide range of activities, should help guide actions to promote healthy aging and reduce dementia risk.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".