Self-efficacy difference among patients with cancer with different socioeconomic status: Application of latent class analysis and standardization and decomposition analysis |
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| Institution: | 1. School of Nursing, Second Military Medical University, No. 800, Xiangyin Road, Shanghai 200433, People''s Republic of China;2. Nursing Department, School of Medicine, Tongji University, No. 727, Zhongshan North Road, Shanghai 200070, People''s Republic of China;3. School of Medicine, George Washington University, Washington, DC, USA;4. Children''s Research Institute, Children''s National Medical Center, 111 Michigan Avenue, Washington, DC, USA;5. Orthopedics Department, Shanghai Jiaotong University Affiliated Sixth People''s Hospital, No. 600, Yishan Road, Shanghai 200003, People''s Republic of China;6. Department of Nursing, The Central Hospital of Jinhua City, Mingyue Street No. 351, Jinhua, Zhejiang Province 321001, People''s Republic of China;7. Yingbo Community Health Service Center of Pudong New District, Shanghai 200125, People''s Republic of China;8. Department of Pediatric, George Washington University, Washington, DC, USA;9. Clinical and Community Research Center, Children''s National Medical Center, Washington, DC, USA;1. Division of Surgical Oncology, Department of Surgery, University of Minnesota, Minneapolis, MN;2. Department of Surgery, City of Hope National Medical Center, Duarte, CA;3. Department of Information Sciences, City of Hope National Medical Center, Duarte, CA;4. Department of Supportive Medicine, City of Hope National Medical Center, Duarte, CA;1. Department of Physics, McGill University, Montréal, QC H3A 2T8, Canada;2. Asia Pacific Center for Theoretical Physics, Pohang 790-784, Korea;3. Department of Physics, Postech, Pohang 790-784, Korea;1. Department of Ophthalmology, Mayo Clinic, Rochester, Minnesota;2. Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota;1. Department of Nutrition, University of North Carolina at Chapel Hill, NC 27516, USA;2. Carolina Population Center, 137 East Franklin St. Campus Box 8120, Chapel Hill, NC 27516, USA;3. Department of Biostatistics, University of North Carolina at Chapel Hill, NC 27516, USA;4. Department of Public Health and Preventive Medicine, Oregon Health & Science University, Portland, OR, USA;5. Department of Epidemiology, University of North Carolina at Chapel Hill, NC 27516, USA;6. UNC Center for Health Promotion and Disease Prevention, University of North Carolina at Chapel Hill, NC 27516, USA;7. Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA;8. Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA |
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| Abstract: | IntroductionAlthough the relationship between partial socioeconomic status (SES) and self-efficacy has been studied in previous studies, few research have examined self-efficacy difference among patients with cancer with different SES.MethodsA cross-sectional survey involving 764 patients with cancer was completed. Latent class analysis (LCA) was applied to identify distinct groups of patients with cancer using four SES indicators (education, income, employment status and health insurance status). Standardization and decomposition analysis (SDA) was then used to examine differences in patients’ self-efficacy among SES groups and the components of the differences attributed to confounding factors, such as gender, age, anxiety, depression and social support.ResultsParticipants were classified into four distinctive SES groups via using LCA method, and the observed self-efficacy level significantly varied by SES groups; as theorized, higher self-efficacy was associated with higher SES. The self-efficacy differences by SES groups were decomposed into “real” group differences and factor component effects that are attributed to group differences in confounding factor compositions.ConclusionSelf-efficacy significantly varies by SES. Social support significantly confounded the observed differences in self-efficacy between different SES groups among Chinese patients with cancer. |
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| Keywords: | Patients with cancer China Self-efficacy Socioeconomic status Latent class analysis (LCA) Standardization and decomposition analysis (SDA) DECOMP |
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