Latent profiles of volume management behaviors and their relationship with symptom distress in patients with chronic heart failure
Year: 2026
Type: article
Study design: Observational Study
Abstract: Objective To explore the latent categories of volume management behaviors in patients with chronic heart failure (CHF) and analyze their relationship with symptom distress. Methods This cross-sectional study utilized a convenience sampling method to select 552 CHF patients from the cardiology departments of Nantong Sixth People's Hospital and Nantong Fourth People's Hospital. Volume management behaviors were assessed using the Volume Management Behavior Scale, and symptom distress was evaluated using the Symptom Distress Questionnaire (SDQ), which measures the severity of eight core symptoms. Latent Profile Analysis (LPA) was employed to identify behavioral categories. Multivariate Analysis of Variance (MANOVA) and multiple linear regression were used to analyze differences in symptom distress across behavioral categories and to examine the independent predictive effect of behavioral classification on symptom distress. Results The volume management behaviors of CHF patients were classified into three latent categories: active management type (43.1%), selective adherence type (27.7%), and passive dependence type (29.2%). Symptom distress scores showed a significant increasing trend across the three categories (active type: 10.5 ± 3.8; selective type: 13.2 ± 4.1; passive type: 16.3 ± 5.2, P < 0.001). After controlling for confounding factors such as age, gender, and NYHA classification, behavioral categories independently explained 41% of the total variance in symptom distress (adjusted R 2 = 0.41, F = 32.17, P < 0.001), with the passive dependence type demonstrating the strongest predictive effect ( β = 5.82, 95% CI: 4.21–7.43). Conclusion CHF patients exhibit three distinct clinical patterns of volume management behaviors, with the passive dependence type associated with the highest symptom burden. Behavioral category is a significant predictor of symptom distress. These findings provide an empirical basis for developing precise intervention strategies tailored to different behavioral phenotypes.
Authors: Weiwei Liu, Yuzhong Gu, Qingqing Yang, Yi Lu
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7118914080