(see Poster Gallery) Predictors of Structural Stigma in State Mental Health Legislation during the Trump Administration

Background/Purpose: Mental health (MH) advocates have consistently pressed for increased legislation and funding, yet the majority of those with mental illness (MI) still do not receive treatment, as systemic gaps persist. Structural forms of MI stigma are a critical barrier, as legislators who stigmatize MI may block valuable bills or introduce stigmatizing legislation. However, the extent of structural stigma in mental health-related policy is mostly unknown, including which legislative factors may predict its presence in structures (e.g., legislatures). Thus, the aims of this study were to (1) examine structural stigma in the language and potential effect of state mental health-related bills as well as (2) report any legislative factors that predict forms of structural stigma in the bills.

Methods: Quantitative content analysis was conducted on a stratified random sample of mental health-related bills using several key steps. First, the study’s dataset was formed by searching state-level legislation using inclusion criteria related to bill topic, time period of bill introduction, and level of government. Second, multistage, stratified random sampling was carried out based on (1) the political party majority of the state legislatures, (2) the current status of the bills, and (3) the country’s distribution of each state’s popular vote during the 2016 presidential election, respectively (N = 200). Third, a codebook was developed consisting of legislative variables from the literature, and the manifest (e.g., legislator gender and political party) and latent content (e.g., both structural stigma variables) of the bills were coded into excel. Finally, data were downloaded into SPSS and analyzed using chi-square and binary logistic regression models.

Results: Findings indicated that (1) ~19% of bills were structurally stigmatic in their potential effect and/or language; (2) structural stigma- potential effect was significantly associated with (a) political party: sponsor χ² (1, N = 167) = 4.25, p = .039, (b) chamber χ² (1, N = 200) = 5.80, p = .016, and (c) gender χ² (1, N = 164) = 4.05, p = .044; (3) structurally stigmatic language was significantly associated with political party: sponsor χ² (1, N = 167) = 4.25, p = .039; and (4) political party: sponsor was a significant predictor of structural stigma in bill language (OR = 0.424, p = .043).

Conclusion/Implications: Forms of structural stigma were present in both the language and potential effect of MH bills. Further, stigmatic legislation was more likely to be sponsored by Republicans, members of the House of Representatives, and males. Finally, Republican party membership predicted structural stigma in bill language. Based on findings from the current study and using HIV/AIDS as a blueprint for successful advocacy, activists should target Republicans and males in power with strong anti-stigma campaigns that consist of (1) personal success stories of individuals with MI, especially those who are currently well-known in society, and (2) research that discredits stereotypes and illustrates the presence of structural stigma. The above should assist in the destigmatization of MI, which in turn, should aid in the reduction of structural stigma present in MH legislation.