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Understanding and Measuring Adaptation Level Among Community-Dwelling Patients with Metabolic Syndrome: A Cross-Sectional Survey

Authors Wang X, Shao J, Ye Z

Received 3 February 2020

Accepted for publication 13 May 2020

Published 4 June 2020 Volume 2020:14 Pages 939—947

DOI https://doi.org/10.2147/PPA.S248126

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Naifeng Liu


Xiyi Wang,1 Jing Shao,2 Zhihong Ye1,2

1Department of Nursing, Zhejiang University School of Medicine Sir Run Run Shaw Hospital, Hangzhou, People’s Republic of China; 2Faculty of Nursing, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China

Correspondence: Zhihong Ye
Department of Nursing, Zhejiang University School of Medicine Sir Run Run Shaw Hospital, Hangzhou, Zhejiang 310020, People’s Republic of China
Tel +86-0571-86006608
Fax +86 0571-86044817
Email yezh@zju.edu.cn

Purpose: This study aimed to translate the Roy adaptation model concept of adaptation level into measurable concepts when considering the health-related quality of life, social support, and self-efficacy of community-dwelling Chinese adults with metabolic syndrome.
Patients and Methods: This was a descriptive cross-sectional study. Data were collected from 144 adults with metabolic syndrome in the suburban area of Hangzhou, China. Correlation analysis was performed to examine the relationships between environmental stimuli (sociodemographic characteristics), adaptation level (health-related quality of life and social support), and prerequisite of behavior (self-efficacy). Regression analysis was applied to test the effect of stimuli on adaptation level and their associations with behavior.
Results: Adaptation level was potentially influenced by environmental stimuli and evaluated by the quality of life. Age and education level were related to physiological and psychological function. Besides, family income was related to physiological function. Thus, adaptation level may predict individuals’ behavior towards illness management, with a percentage classification accuracy of 76.40%. The vitality and social functioning of the quality of life were identified as significant correlates of self-efficacy.
Conclusion: Our findings demonstrate that individuals’ internal and external resources should be considered when developing nursing interventions to improve patients’ adaptation level. Future research should explore whether facilitating self-efficacy among community-dwelling adults with metabolic syndrome may positively influence an individual’s adaptation process in health management.

Keywords: chronic illness, physiological adaptation, psychosocial adaptation, quality of life, social support, self-efficacy

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