Self-Management Strategy Clustering, Quality of Life, and Health Status in Cancer Patients Considering Cancer Stages.

CANCER patient psychology; SELF-management (Psychology); MULTIVARIATE analysis; HEALTH status indicators; TUMOR classification; SURVEYS; QUALITY of life; QUESTIONNAIRES; FACTOR analysis; DESCRIPTIVE statistics; RESEARCH funding; SOCIODEMOGRAPHIC factors; CLUSTER analysis (Statistics); DATA analysis software; LONGITUDINAL method

Background : In the cancer-care continuum, self-management can help cancer patients regardless of their treatment plan or cancer stage. However, research examining self-management strategy clusters considering cancer stages is lacking. Thus, we examined self-management strategy clusters considering cancer stages and the effects of self-management strategy clusters on quality of life (QoL) and overall health status. Method: A total of 256 patients who completed both baseline and second surveys for a 6-month period ultimately participated in this prospective cohort study. To identify the interrelationship between self-management strategies measured by the Smart management strategies for health assessment tool (SAT), we conducted cluster analysis using a principal component analysis in varimax rotation and the k-mean clustering method. We also performed multivariate-adjusted analyses in QoL and overall health status comparisons by dividing the cancer stage into early (I, II) and advanced (III, IV). Results: All patients experienced two domains of self-management strategies concurrently. However, self-management strategy clusters differed by cancer stage, and the effect of self-management strategy clusters on quality of life and overall health status also differed. Self-management strategy clusters effectively improved the quality of life and overall health status of the entire cohort of patients, even in patients with advanced-stage cancer. Conclusion: This study revealed that the pattern of using self-management strategies might differ by cancer stage. The strategy cluster positively affected QoL and overall health status in cancer patients. Identifying the self-management clusters of cancer patients with different cancer stages may have clinical implications for supporting their health management. [ABSTRACT FROM AUTHOR]

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