ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2026
Dual trajectories of capacity management behavior and quality of life in hemodialysis patients: a longitudinal study.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeTo examine the individual and dual trajectories of capacity management behavior and quality of life among hemodialysis patients, and to explore factors that may influence these trajectories.
methodsA longitudinal study was conducted involving 310 hemodialysis patients and their caregivers. Of these, 282 dyads completed follow-up assessments at three and six months. Group-based dual-trajectory modeling and logistic regression were used to analyze the trajectories of capacity management behavior and quality of life, as well as their interrelationships and predictive factors.
resultsFour trajectories of capacity management behavior, six trajectories of physical quality of life, and two trajectories of mental quality of life were identified among hemodialysis patients. Patients who demonstrated more consistent and stable capacity management behaviors were more likely to maintain a higher quality of life. Early and effective capacity management behaviors appeared to be more beneficial for sustaining quality of life than later improvements. Similarly, patients with a higher quality of life tended to exhibit better and more consistent performance in these behaviors. Predictors across latent trajectory groups included education level, insomnia, and caregiver contributions to self-care.
conclusionsThere was a bidirectional association between dynamic changes in capacity management behaviors and quality of life among hemodialysis patients. It is necessary to develop tailored intervention strategies at an early stage based on their trajectory patterns and predictive factors.
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