Is Mental Illness like Any Other Medical Illness? Causal Attributions, Supportive Communication and the Social Withdrawal Inclination of People with Chronic Mental Illnesses in China

ABSTRACT

The saying “mental illness is like any other illness” has increasingly become pervasive in promoting mental health literacy among the public in China. This discourse is based on the fact that mental illness is attributed to primarily biogenetic causes. This study comprises an investigation of the impact of causal attributions of mental illness on the social withdrawal inclination of people with chronic mental illnesses (PCMIs) in China. Drawing on attribution theory and a sample of PCMIs, the current authors further question the effectiveness of biogenetic discourse to combat social stigma and to integrate PCMIs into society. In addition, in response to the proliferation of discussion on the digital inclusion of those with mental disabilities, this study constructs a structural model in which the varied effects of supportive communication are used as bridging factors, including face-to-face, telephonic and social media communication. The results indicate a stronger social withdrawal inclination when the PCMIs attributed their illnesses to biogenetic causes. In addition, biogenetic attribution was also found to potentially hinder the PCMIs from using the telephone and social media to seek supportive communication, while psychosocial attribution was found to have potential to combat PCMIs’ social withdrawal inclination. In this vein, this study calls for further investigation on the conditional factors upon which digital inclusion might work for PCMIs in China.

Acknowledgment

We wish to thank the colleagues of Guangzhou LIKANG Social Service Center for their assistance with data collection, as well as Professor LI Xigen for his suggestions in improving the paper. This work was supported by the Ministry of Education of the People’s Republic of China under Young Scholar Grant in Humanities and Social Sciences “The online communication and intervention mechanism of stigmatized discourses on mental illnesses in the context of social media” [Project ID: 19YJC860023].

Notes

1. We employ this distinction because during data collection, the PCMIs could not properly distinguish the differences between emotional and communication appraisal support or between informational and instrumental support. Thus, for the sake of analytical parsimony, we combined the items to operationalize the concept of social support.

2. Civil non-enterprise is a unique category denoting the non-governmental and nonprofit organizations in Guangzhou, which are the social services sponsored by government.

3. The sample size is relatively small in this study. However, the registered members in Likang are a bit more than 400, among whom only 100 more are active participants of the activities in the organization. So, considering the particularity of our study population, our samples are acceptably representative of PCMIs, at least within this organization. Other than a mental hospital, there should be no better place to address the concern of our study.

4. The sum exceeds 102 because some participants were diagnosed with more than one illness.

5. By testing the primary structural model in AMOS, the modification indices were used to optimize the model. By modification, we assumed covariance between error terms of ITEM1 and ITEM2 and between ITEM1 and ITEM3 as well as covariance between error terms of informational and emotional support.

Additional information

Funding

This work was supported by the Ministry of Education of the People’s Republic of China under Young Scholar Grant in Humanities and Social Sciences “The online communication and intervention mechanism of stigmatized discourses on mental illnesses in the context of social media” [Project ID: 19YJC860023].