Back

Analysis Of Self-Care Factors In Hypertension Patients In Community Settings

Dewi, N. P. A. R.; Pandin, M. G. R.; Nursalam, N.; Agustini, N. L. P. I. B.; Wahyuni, N. W. S.; Putra, K. A. N.

2024-12-09 nursing
10.1101/2024.12.01.24318276 medRxiv
Show abstract

BackgroundControlling blood pressure in hypertensive patients is one of the most important interventions in preventing complications, reducing morbidity, and premature mortality. Patients must practice hypertension self-care to prevent the diseases frequent recurrence from deteriorating their health and to maintain effective behavior. ObjectiveAnalyze the factors that influence the implementation of self-care in hypertensive patients. MethodCross-sectional using the purposive sampling technique involving 120 respondents. The study was conducted in the working area of the Gianyar 1 Health Center, Bali, Indonesia. Data collection utilized the Indonesian version of the High Blood Pressure self-care profile questionnaire. Analysis included univariate, bivariate using chi-square, and multivariate using multinomial logistic regression. ResultsA long history of suffering from hypertension has an effect on behavior; education has an effect on motivation; and education and work have an effect on self-efficacy. ConclusionThe article emphasizes the importance of holistic treatments in managing high blood pressure, with a focus on patient engagement to improve taking care of themselves with focused education and support systems. The outcomes align with the axiological dimension of philosophy by highlighting practical values that enhance patients autonomy and quality of life through education and supportive systems. Further, the research makes an empirical contribution by providing a comprehensive knowledge of self-care characteristics, which can be used to develop culturally appropriate and patient-focused intervention techniques.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.