Factors Affecting Self-Care Among Hypertensive Older Adults Dwelling in the Community: A Cross-Sectional Study
Bibliographic record
Abstract
Abstract Background: Hypertension is a prevalent health problem in older adults, with better outcomes expected through proper self-care. However, little is known about the effects of cognitive function level on self-care in older adults living in the community. Methods: This cross-sectional study, conducted from October 2019 to January 2020, analyzed the effect of cognitive function on self-care in elderly individuals aged > 65 years with hypertension who visited a local general hospital for the treatment of hypertension. The Korean versions of the Mini-Mental State Examination (K-MMSE) and Montreal Cognitive Assessment (MoCA-K) were used to assess cognitive function. The Hypertension Self-Care Behavior Scale (HBP-SC Behavior Scale) was used to analyze the subjects’ self-care, which was divided into diet behavior and health behavior (except diet). The general characteristics and degrees of self-care of the subjects were analyzed using descriptive statistics, and multiple regression analysis was used to analyze the factors affecting self-care. Results: Factors influencing HBP-SC diet behavior scores were religion (β =.27, SE = 0.69, p =.007) and MoCA-K scores (β =.31, SE = 0.08, p = .002). HBP-SC health behavior (except diet) scores were associated with comorbidities (β = −.20, SE = 0.60, p = .032), and the power of the model was 20%. However, there were no variables that significantly affected the total HBP-SC score, which included the diet behavior and health behavior (except diet) scores. Conclusions: Although there was no significant factor influencing the total HBP-SC score, religion, MoCA-K scores, and comorbidities were factors influencing diet behavior and health behavior (except diet). Therefore, tailored education takes into account religion, MoCA-K domains, and comorbidities is necessary to promote self-care in hypertensive older adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".