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.

Background: Care assistant workers (CAWs) are a part of a new pattern of mental health care providers in China and play a significant role in bridging the human resource shortage. CAWs in China mainly include community cadres, community mental health staff and community policemen. The mental health related knowledge and attitudes of CAWs could influence their mental health care delivery. This study aimed to assess the mental health related knowledge and attitudes of CAWs in Guangzhou, China. Methods: In November 2017, a study was conducted among 381 CAWs from four districts of Guangzhou, China. Participants were assessed using the Perceived Devaluation and Discrimination Scale (PDD), the Mental Health Knowledge Schedule (MAKS), and the Mental illness: Clinicians’ Attitudes (MICA). Data were analyzed by descriptive statistics, ANOVA, Bonferroni corrections and multivariable linear regression. Results: The mean scores (standard deviation) of PDD, MAKS and MICA were 36.45 (6.54), 22.72 (2.56), 51.67 (7.88), respectively. Univariate analyses showed that the older CAWs, community policemen and those who were less willing to deliver care had significant higher MICA scores when compared with other staff (P < 0.001). However, participants who disagreed additional item 1（views towards inpatients) and additional item 2 (affiliate stigma) had a significant lower MICA scores when compared with those who agreed (P < 0.001). Multivariable linear regression showed that after controlling some variables, care willingness and PDD total score were significantly positively associated with the MICA total score (all P < 0.05), while attitudes on additional items were significantly negatively associated with the MICA total score (all P < 0.01).Conclusion: These findings suggest negative attitudes towards people with mental disorders among CAWs are common, especially among older staff. Community policemen suggest that they applied stereotypes of ‘violent mentally ill’ people to all people they deal with who have mental disorders. The results also indicate human rights are being paid attention to now, but need to be improved in the future. Strategies to improve attitudes and to reduce stigma and discrimination should be conducted with particular staff groups.