Factors influencing self-quantification for patients with hypertension: A cross-sectional Study

Medicine (Baltimore). 2023 Dec 1;102(48):e36185. doi: 10.1097/MD.0000000000036185.

Abstract

This study aimed to investigate the level of self-quantification among patients with hypertension and identify the factors influencing this behavior. This study aimed to investigate self-quantification levels and identify influencing factors among 400 patients diagnosed with hypertension. Employing a convenience sampling method, the research was conducted across diverse healthcare settings, including a tertiary hospital, 2 community hospitals, 2 pension institutions, and 5 residential areas. Participants underwent assessment using a self-quantification scale. The collected data underwent thorough analysis using various statistical methods, including descriptive analysis for an overview, 2 independent samples t test for mean comparisons, one-way analysis of variance for variations among groups, and multiple linear regression analysis to identify influential factors. This robust methodology was applied to gain comprehensive insights into the self-quantification behaviors of patients with hypertension. The total self-quantification score for patients with hypertension was found to be (96.64 ± 14.16). The average value for all dimensions was (3.22 ± 0.47). Notably, medical insurance type, education level, age, and complications were identified as significant factors influencing self-quantification among patients with hypertension. The study concludes that patients without medical insurance, with lower education levels, older age, and no complications tended to have lower levels of self-quantification. These findings underscore the necessity for targeted interventions to improve self-quantification in these specific patient groups. By addressing the identified influencing factors, healthcare providers can implement measures to enhance self-quantification among patients with hypertension.

MeSH terms

  • Cross-Sectional Studies
  • Humans
  • Hypertension*
  • Multivariate Analysis
  • Regression Analysis
  • Tertiary Care Centers