• Title of article

    Self-efficacy difference among patients with cancer with different socioeconomic status: Application of latent class analysis and standardization and decomposition analysis

  • Author/Authors

    Yuan، نويسنده , , Changrong and Wei، نويسنده , , Chunlan and Wang، نويسنده , , Jichuan and Qian، نويسنده , , Huijuan and Ye، نويسنده , , Xianghong and Liu، نويسنده , , Yingyan and Hinds، نويسنده , , Pamela S.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    9
  • From page
    298
  • To page
    306
  • Abstract
    AbstractIntroduction gh 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. s s-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. s ipants 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. sion fficacy significantly varies by SES. Social support significantly confounded the observed differences in self-efficacy between different SES groups among Chinese patients with cancer.
  • Keywords
    Self-efficacy , DECOMP , patients with cancer , Socioeconomic status , Standardization and decomposition analysis (SDA) , Latent class analysis (LCA) , CHINA
  • Journal title
    Cancer Epidemiology
  • Serial Year
    2014
  • Journal title
    Cancer Epidemiology
  • Record number

    1766816