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The prevalence and predictors of self-stigma of individuals with mental health illness in two Chinese cities

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  • Daniel Kim-Wan Young
  • Petrus Yat-Nam Ng

Abstract

Background: Although self-stigma is found to have adverse effects on the lives of persons with mental illness, little is known on the self-stigma of these individuals in Chinese societies. Objective: This research study explores the prevalence rate and predicting factors of self-stigma of consumers in two Chinese cities, Hong Kong and Guangzhou. Methods: A cross-sectional research design is adopted which involves a random sample of 266 consumers from Hong Kong and a convenient sample of 208 consumers from Guangzhou. These individuals have been assessed in terms of their self-stigma, recovery, self-esteem and quality of life by using standardized assessment scales. Results: In all, 38.3% of the Hong Kong participants and 49.5% of the Guangzhou participants report to have self-stigma. Also, self-stigma is found to be negatively related to self-esteem and quality of life. A logistic regression analysis shows that hope and well-being are predicting factors of self-stigma. Conclusion: Self-stigma is found to be higher in Guangzhou, probably due to the influence of traditional cultural values. Also, as hope and well-being are found to be predicting factors of self-stigma, suitable recovery-orientated interventions that facilitate hope and well-being should be developed so as to reduce self-stigma of consumers in Chinese societies.

Suggested Citation

  • Daniel Kim-Wan Young & Petrus Yat-Nam Ng, 2016. "The prevalence and predictors of self-stigma of individuals with mental health illness in two Chinese cities," International Journal of Social Psychiatry, , vol. 62(2), pages 176-185, March.
    • Handle: RePEc:sae:socpsy:v:62:y:2016:i:2:p:176-185
    DOI: 10.1177/0020764015614596
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    References listed on IDEAS

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    Cited by:

    1. Chen, Xi & Wang, Tianyu & Busch, Susan H., 2019. "Does money relieve depression? Evidence from social pension expansions in China," Social Science & Medicine, Elsevier, vol. 220(C), pages 411-420.

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