Latent profile analysis of benefit finding in maintenance hemodialysis patients and its association with treatment adherence

Vollständiger Abstract

Worum geht es in dieser Arbeit?

Abstract Maintenance hemodialysis (MHD) patients experience prominent negative emotions, and dialysis outcomes/prognosis rely heavily on treatment adherence. Few studies have explored the relationship between latent Benefit Finding (BF) categories and adherence. This study aims to identify BF’s latent characteristics in MHD patients and analyze their link to adherence for targeted interventions. From Oct. 2024 to Mar. 2025, 250 MHD patients were convenience-sampled from 2 tertiary hospitals in Guangzhou. Measurement tools included a General Information Questionnaire, a Benefit Finding Scale, and a Treatment Adherence Scale for MHD Patients with End-Stage Renal Disease. Latent profile analysis, multivariate logistic regression, and one-way ANOVA were used. MHD patients had a mean BF score of (55.36 ± 14.65), with three BF categories: Low benefit-perceived lacking (20.4%), Medium benefit-balanced adaptive (59.6%), and High benefit-personal growth dominant (20%). Literacy, occupational status, and renal transplantation experience influenced patients’ BF categories ( P < 0.05). BF correlated positively with adherence ( r = 0.327, P < 0.001), and adherence scores differed statistically by BF categories ( P < 0.05).MHD patients’ BF has three latent profiles. Clinical staff should design targeted interventions based on BF characteristics to improve adherence.