# Latent profile analysis and influencing factors of proactive health behaviors in hypertensive patients from the perspective of the health belief model

## TL;DR

This study identifies four distinct types of proactive health behaviors in hypertension patients and explores factors influencing each type.

## Contribution

The study introduces a novel application of latent profile analysis to categorize proactive health behaviors in hypertension patients.

## Key findings

- Four distinct proactive health behavior profiles were identified among hypertension patients.
- Factors like age, education, and self-efficacy influence different behavior profiles.
- The health belief model was used to guide the analysis of influencing factors.

## Abstract

To identify latent profiles of proactive health behaviors in patients with hypertension, examine the category-specific influencing factors.

Proactive health behavior, as an emerging concept, refers to a self-motivated approach to systematically managing health-related factors in order to actively maintain and promote one’s health status. However, existing studies have largely focused on describing the overall level of such behaviors among patients with hypertension, with insufficient exploration of behavioral heterogeneity within this population. Moreover, there has been a lack of systematic integration of established behavioral theories to explain the multifactorial mechanisms underlying different behavioral patterns, which limits the development of precise nursing interventions.

A cross-sectional study was performed, involving 352 patients with hypertension from 8 communities in Anhui Province from September to December 2025. The survey tools included self-designed demographic and clinical instrument, the Proactive Health Behavior Scale for Hypertensive Patients, the Self-Efficacy Scale for Hypertensive Patients, the Health Literacy Management Scale (HeLMS). Latent profile analysis (LPA) was used to identify subtypes of proactive health behavior among hypertension patients. Multinomial logistic regression analysis was applied to determine the factors associated with the identified subtypes.

A total of 352 questionnaires were distributed, yielding 321 valid responses (a response rate of 91.2%). The total score of proactive health behavior was 89.57 ± 22.99 points. The LPA revealed four profiles of proactive health behavior: the positive proactive health behavior profile (Class 1, n = 50, 15.8%), the self-regulating proactive health behavior profile (Class 2, n = 114, 35.4%), the medically compliant-proactive health behavior profile (Class 3, n = 96, 30.2%), and the passive proactive health behavior profile (Class 4, n = 61, 18.6%). The entropy value was high (0.856), indicating a correct classification. Multivariate regression analyses showed that age, educational level, marital status, employment status, disease duration, hospitalization due to hypertension, self-management level, self-efficacy level and health literacy as factors influencing proactive health behavior profiles.

The proactive health behavior among hypertension patients was at a moderate level, revealing four distinct behavioral categories with significant differences. Guided by the Health Belief Model, profile-specific influencing factors were analyzed, which informed the development of tailored intervention strategies.