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• W4210880596 abstract "Colorectal cancer screening (CRCS) rates remain suboptimal among Korean Americans despite recommendations from health organizations. Little is known about the mechanism underlying their CRCS adoption within complex systems. This study aimed to examine the multi-level predictors of CRCS adoption among Korean Americans using a decision tree model.A cross-sectional survey was performed to assess CRCS adoption and multiple levels of influence - individual (i.e. CRCS self-efficacy, CRCS attitudes, risk of colorectal cancer, psychological distress, health status), interpersonal (i.e. social support, social networks, CRCS recommendations), and organizational/community (i.e. health insurance, primary doctor, primary clinic) factors. A total of 433 Korean Americans aged 50-75 in a metropolitan area in the Southeastern U.S. completed a self-report questionnaire. To determine the important variables that predict CRCS adoption, the study generated a decision tree predictive model using R statistical software.The results indicated that CRCS self-efficacy and CRCS attitudes at the individual level and CRCS recommendations and social support at the interpersonal level differentiate adopting or not adopting CRCS. Furthermore, CRCS recommendations (n = 138, 56%, prob = 0.64) and CRCS self-efficacy (n = 51, 21%, prob = 0.88) were the most powerful predictors of CRCS adoption.The findings highlight the critical roles of CRCS recommendations from healthcare providers and family/friends and patients' confidence in performing screening-related tasks in influencing CRCS adoption among Korean Americans. Practice efforts should target individual and interpersonal characteristics when developing interventions for promoting CRCS among Korean Americans, especially who are not adherent to screening guidelines." @default.
• W4210880596 created "2022-02-09" @default.
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• W4210880596 date "2022-02-09" @default.
• W4210880596 modified "2023-10-18" @default.
• W4210880596 title "Predicting adoption of colorectal cancer screening among Korean Americans using a decision tree model" @default.
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• W4210880596 doi "https://doi.org/10.1080/13557858.2022.2035693" @default.
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