Effectiveness of an anti-stigma training on improving attitudes and decreasing discrimination towards people with mental disorders among care assistant workers in Guangzhou, China

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Background: Care assistant workers as a new pattern of care providers in China play an important role in bridging the mental health treatment gap. Stigma and discrimination against people with mental disorders among care assistant workers is a barrier which adversely influences mental health service delivery. However, programs aimed at reducing stigma among care assistant workers are rare in China. Methods: A total of 293 care assistant workers from four districts of Guangzhou, China were randomly divided into an intervention group (n = 139) and a control group (n = 154). The intervention group received anti-stigma training and the control group received traditional mental health training. Both trainings lasted for 3 h. Participants were measured before and after training using Perceived Devaluation and Discrimination Scale (PDD), Mental illness: Clinicians' Attitudes (MICA) and Mental Health Knowledge Schedule (MAKS). Data were analyzed by descriptive statistics, t-test, Chi square test or Fisher's exact test. Multilinear regression models were performed to calculate adjusted regression coefficient of the intervention on PPD, MAKS, and MICA. Results: There were significant lower scores on PDD and MICA in the intervention group after training when compared with the control group (both P < 0.001). No significant difference was found on MAKS total score between the two groups after training (P = 0.118). Both groups had better correct identification of schizophrenia, depression and bipolar disorder before and after training. Conclusions: These findings suggest that anti-stigma training may be effective in reducing the perception of devaluation-discrimination against people with mental illness and decreasing the level of negative stigma-related mental health attitudes among care assistant workers. © 2019 The Author(s).

International Journal of Mental Health Systems
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