Analysis of the Levels of Physical Activity in the Quality of Life of Elderly Patients With Hypertension
Bibliographic record
Abstract
BACKGROUND: Changes in lifestyle are essential to promote the control of hypertension and quality of life in older adults. Objective: To verify the influence of the level of physical activity (LPA) on quality of life in hypertensive older adults. METHOD: The sample included a total of 291 hypertensive older adults, 102 men and 189 women, with a mean age of 69.7 ± 7.7 and 69.2 ± 7.2 respectively. The General Linear Model was applied to measure the interactions (LPA and sex) between active and inactive groups. RESULTS: There was a difference between active men and active women with inactive older adults of both sexes for mental status (p<.0001), as well as a difference between active men and active women with inactive older adults of both sexes for somatic manifestations (p<.0001). No differences were observed between active men and active women for any other variables. CONCLUSION: Our results suggest that a higher level of physical activity can lead to a better quality of life.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".