Heterogeneity in stereotypes of depression and schizophrenia: A meta-analysis of warmth and competence evaluations

Stereotypes about mental illness (MI) are not necessarily context-free or stably localized within the stereotype content model (SCM). Studies using different comparison sets are expected to produce different relationships between the two SCM dimensions, meaning that placements derived from visual maps, cluster solutions or quadrant descriptions should not be interpreted as fixed properties of social categories. Drawing on a PRISMA-guided meta-analysis, we synthesize SCM ratings of depression and schizophrenia and demonstrate substantial heterogeneity across studies, both in pooled mean estimates for each diagnosis-by-dimension combination and in contrasts between diagnostic categories. Analyses used random-intercept and random-slope meta-analytic models, with heterogeneity assessed through I², τ and Cochran's Q. Across 17 studies, results showed considerable heterogeneity in evaluations of both diagnoses on both SCM dimensions. Although comparative analyses also showed high heterogeneity, findings consistently indicated that schizophrenia is rated as less warm than depression, whereas both diagnoses receive similar competence evaluations. These findings support the theoretical and methodological claim that SCM research should avoid treating depression and schizophrenia stereotypes as stable diagnosis-specific placements. We discuss how a diagnostic approach can be developed within a contextual framework using standardized procedures for data collection and analysis.