Attitudes towards people with mental disorders: results of a psychometric evaluation and confirmatory factor analysis of the stigma towards people with mental disorders (SToP-MD) scale.
Stigmatizing attitudes toward individuals with mental disorders represent a major barrier to treatment, recovery, and social inclusion. The present research introduces and psychometrically evaluates the German-language Stigma Toward People with Mental Disorders scale (SToP-MD) across three independent studies with distinct samples.In study 1 (N = 266), an initial item pool was developed and refined based on theoretical frameworks and exploratory factor analysis. In study 2 (N = 448), confirmatory factor analysis supported a two-factor structure comprising prejudiced stigmatization (SToP-MD-PS) and assumption of problems (SToP-MD-AP). The model demonstrated adequate fit according to conventional indices (CFI = 0.97, TLI = 0.96, SRMR = 0.07), although robust indices indicated only moderate fit (robust CFI = 0.91, robust RMSEA = 0.13). Internal consistency was good for the PS subscale (ω = 0.83) but limited for the AP subscale (ω = 0.51). In study 3 (N = 266), the scale's sensitivity to short-term change was examined following exposure to differently framed media content.As hypothesized, the SToP-MD subscales were positively associated with depression stigma (DSS) and social distance (SDI), and negatively correlated with openness and agreeableness (NEO-FFI), supporting convergent validity. Discriminant validity was partially confirmed by low or non-significant correlations with attitudes toward physically disabled individuals (ATDP), suicide-related cognitions (CCSS), and socially desirable responding (BIDR).Across all three studies, the SToP-MD demonstrated preliminary yet consistent evidence of structural and construct validity, as well as change sensitivity. It captures both overt prejudices and implicit burden assumptions, offering a nuanced assessment of public stigma toward mental disorders. The scale can serve as a valuable tool in stigma research, public health monitoring, and evaluation of interventions. Future research should extend validation to more diverse samples and test predictive and longitudinal utility.
Authors
Woud Woud, Blackwell Blackwell, Teismann Teismann, Keita Keita, Margraf Margraf, Cwik Cwik
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