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Causal beliefs of the public and social acceptance of persons with mental illness: a comparative analysis of schizophrenia, depression and alcohol dependence

Published online by Cambridge University Press:  11 April 2013

G. Schomerus*
Affiliation:
Department of Psychiatry, Greifswald University, Germany HELIOS Hanseklinikum Stralsund, Germany
H. Matschinger
Affiliation:
Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Germany
M. C. Angermeyer
Affiliation:
Department of Public Health, University of Cagliari, Italy Center for Public Mental Health, Gösing am Wagram, Austria
*
* Address for correspondence: G. Schomerus, M.D., Department of Psychiatry, University of Greifswald, Rostocker Chaussee 70, 17437 Stralsund, Germany. (Email:georg.schomerus@uni-greifswald.de)
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Abstract

Background

There is an ongoing debate whether biological illness explanations improve tolerance towards persons with mental illness or not. Several theoretical models have been proposed to predict the relationship between causal beliefs and social acceptance. This study uses path models to compare different theoretical predictions regarding attitudes towards persons with schizophrenia, depression and alcohol dependence.

Method

In a representative population survey in Germany (n = 3642), we elicited agreement with belief in biogenetic causes, current stress and childhood adversities as causes of either disorder as described in an unlabelled case vignette. We further elicited potentially mediating attitudes related to different theories about the consequences of biogenetic causal beliefs (attribution theory: onset responsibility, offset responsibility; genetic essentialism: differentness, dangerousness; genetic optimism: treatability) and social acceptance. For each vignette condition, we calculated a multiple mediator path model containing all variables.

Results

Biogenetic beliefs were associated with lower social acceptance in schizophrenia and depression, and with higher acceptance in alcohol dependence. In schizophrenia and depression, perceived differentness and dangerousness mediated the largest indirect effects, the consequences of biogenetic causal explanations thus being in accordance with the predictions of genetic essentialism. Psychosocial causal beliefs had differential effects: belief in current stress as a cause was associated with higher acceptance in schizophrenia, while belief in childhood adversities resulted in lower acceptance of a person with depression.

Conclusions

Biological causal explanations seem beneficial in alcohol dependence, but harmful in schizophrenia and depression. The negative correlates of believing in childhood adversities as a cause of depression merit further exploration.

Information

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2013 
Figure 0

Table 1. Hypothesized mediated effects of biogenetic causal explanations on social acceptance, according to different theoretical frameworks

Figure 1

Table 2. Sociodemographic characteristics of the population sample

Figure 2

Fig. 1. Different causal explanations and social acceptance of a person with schizophrenia. Path analysis is shown, with standardized path coefficients. Only significant coefficients are reported (p < 0.05). Numbers on arrows are direct effects. Numbers in boxes are indirect effects. n.s., Non-significant. The data are from a representative population survey in Germany (n = 1183).

Figure 3

Fig. 2. Different causal explanations and social acceptance of a person with depression. Path analysis is shown, with standardized path coefficients. Only significant coefficients are reported (p < 0.05). Numbers on arrows are direct effects. Numbers in boxes are indirect effects. n.s., Non-significant. The data are from a representative population survey in Germany (n = 1173).

Figure 4

Fig. 3. Different causal explanations and social acceptance of a person with alcohol dependence. Path analysis is shown, with standardized path coefficients. Only significant coefficients are reported (p < 0.05). Numbers on arrows are direct effects. Numbers in boxes are indirect effects. n.s., Non-significant. The data are from a representative population survey in Germany (n = 1126).

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