Background: Comprehensive state behavioral health parity legislation (C-SBHPL) is an evidence-based policy that increases access to behavioral health services. C-SBHPL can also enhance and promote compliance with federal behavioral health parity laws. However, adoption of C-SBHPL is low and only 19 states have implemented the law. State legislators have the exclusive authority to adopt C-SBHPL, but little is known about how C-SBHPL evidence might be most effectively disseminated to this audience. The effectiveness of efforts to disseminate C-SBHPL evidence to legislators can be enhanced by identifying legislator characteristics and contextual factors that are associated with C-SBHPL support. This information can then be used to tailor evidence summaries for legislators on the basis of these characteristics. The study objective was to describe associations between legislator fixed characteristics, mutable characteristics, state-level contextual factors and C-SBHPL support.

Methods: A multi-modal (post-mail, e-mail, telephone) survey of a state-stratified random sample of state legislators was conducted in 2017 (N=475). Non-response weights were applied. The dependent variable was strong support for C-SBHPL. Independent variables were fixed legislator characteristics (e.g., ideology), mutable legislator characteristics (e.g., beliefs about policy impact, stigma towards people with mental illness), and state-level contextual factors (e.g., opioid overdose death rate). Multivariable, multilevel logistic regression was conducted.

Results: Thirty-nine percent of legislators strongly supported C-SBHPL. After adjustment for covariates, the strongest predictors of C-SBHPL support were beliefs that C-SBHPL increases access to behavioral health treatments (aOR=6.29; 95% CI= 2.70, 14.67) and does not increase insurance premium costs (aOR= 3.11; 95% CI= 1.48, 6.55). Mental illness stigma was inversely associated with support (aOR= 0.86; 95% CI= 0.78, 0.95). Liberal, compared to conservative, ideology was the only fixed legislator characteristic significantly associated with C-SBHPL support after adjustment (aOR= 2.38; 95% CI= 1.06, 5.37). State-level contextual factors were not significantly associated with C-SBHPL support after adjustment.

Conclusions: Mutable legislator characteristics are stronger predictors of C-SBHPL support than most fixed legislator characteristics and all state-level contextual factors. The dissemination of evidence about C-SBHPL, and potentially other evidence-based behavioral health policies, should target mutable characteristics as they could be antecedent to changes in policy support and ultimately policy adoption.