Self-reported adherence to physical activity recommendations compared to the IPAQ interview in patients with hypertension
Bibliographic record
Abstract
Background: Physical activity (PA) is recommended as adjuvant therapy to control blood pressure (BP). The effectiveness of simple recommendations is not clear. We aimed to assess the agreement between self-report of adherence to PA in clinical routine and International Physical Activity Questionnaire (IPAQ) interview and its association with BP control. Methods: A cross-sectional study was conducted with hypertensive outpatients. Adherence to recommendation to PA was assessed by the physician and IPAQ interview. A cutoff of 150 minutes/week was used to classify active or nonactive patients. High sitting time was considered >4 hours/day. A total of 127 individuals (SBP 144.9±24.4 mmHg/DBP 82.0±12.8 mmHg) were included. Results: A total of 69 subjects (54.3%) reported to be active to their physician, whereas 81 (63.8%) were classified as active by IPAQ (6.3% active in leisure time PA). Kappa test was 0.22 (95% CI, 0.06–0.37). The rate of BP control was 45.7%. There was no association with the reported PA assessed by both methods nor with sitting time. Our results demonstrated poor agreement between self-report adherence and IPAQ interview, and neither evaluation was associated with BP control. Conclusion: Our findings underpin evidences that a simple PA recommendation has low association with BP control in clinical settings.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".