Construct validity of the brief physical activity assessment tool for clinical use in COPD
Bibliographic record
Abstract
INTRODUCTION: Low physical activity (PA) levels are associated with poor health-related outcomes in Chronic Obstructive Pulmonary Disease (COPD). Thus, PA should be routinely assessed in clinical practice. OBJECTIVES: This study assessed the construct validity of the Brief Physical Activity Assessment Tool (BPAAT) for clinical use in COPD and explored differences in age, sex and COPD grades. METHODS: = 59.3 ± 25.5%predicted) completed the BPAAT and received an accelerometer. The BPAAT includes two questions assessing the weekly frequency and duration of vigorous- and moderate-intensity PA/walking, classifying individuals as insufficiently or sufficiently active. The BPAAT was correlated with accelerometry (moderate PA, MPA = 1952-5724 counts-per-min [CPM]); vigorous PA, VPA = 5725-∞CPM; moderate-to-vigorous PA, MVPA = 1952-∞CPM; daily steps), through: Spearman's correlations (ρ) for continuous data; %agreement, Kappa, sensitivity and specificity, positive and negative predictive values (PPV, NPV) for categorical data. RESULTS: The BPAAT identified 73.6% patients as "insufficiently active" and 26.4% as "sufficiently active". The BPAAT was weakly to moderately correlated with accelerometry (0.394 ≤ ρ ≤ 0.435, P < 0.05), except for VPA (P = 0.440). This was also observed in age (<65/≥65yrs), COPD grades (GOLD 1-2/3-4) and in male patients (0.363 ≤ ρ ≤ 0.518, P < 0.05 except for VPA). No significant correlations were found in female patients (P > 0.05). Agreement was fair to moderate (0.36 ≤ κ ≤ 0.43; 73.6% ≤ %agreement ≤ 74.5%; 0.50 ≤ sensitivity ≤ 0.52; 0.84 ≤ specificity ≤ 0.91, 0.55 ≤ PPV ≤ 0.79, 0.72 ≤ NPV ≤ 0.82). CONCLUSION: The BPAAT may be useful to screen patients' PA, independently of age and COPD grade, and identify male patients who are insufficiently active. Care should be taken when using this tool to assess vigorous PA or female patients.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.001 | 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".