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

International Journal of Behavioral Medicine - Tập 30 - Trang 769-776 - 2022
Ju Youn Jung1, Young Ho Yun2
1Department of Biomedical Science, Seoul National University College of Medicine and Hospital, Seoul, South Korea
2Department of Family Medicine, Seoul National University College of Medicine and Hospital, Seoul, South Korea

Tóm tắt

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. 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). 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. 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.

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