Background State legislators make policy decisions that influence children’s exposure to adverse childhood experiences (ACEs), such as child maltreatment, and their effects on behavioral health. Effective dissemination of scientific research can increase the likelihood that legislators’ decisions are aligned with evidence to prevent ACEs and their consequences, and effective dissemination requires legislators to engage with dissemination materials. Informed by the elaboration likelihood model of persuasive communication and Brownson’s Model of Dissemination Research, we tested the hypothesis that inclusion of economic evidence and local data would increase legislator engagement with dissemination materials about evidence-supported policies related to ACEs and behavioral health. Methods A three-arm randomized dissemination trial was conducted. A university researcher e-mailed dissemination materials which contained evidence about ACEs and behavioral health problems to state legislators (two e-mails sent 2 weeks apart, 12,662 e-mails delivered to 6509 legislators). The e-mail subject lines, text, and policy brief content were manipulated across the study arms. The intervention condition received state-tailored data about rates of ACEs and state-tailored economic evidence about the costs of ACEs for public systems, the enhanced control condition received state-tailored data and not economic evidence, and the control condition received national data and not economic evidence. Outcomes were rates of e-mail views, policy brief link clicks, requests for researcher consultation, and mentions of child maltreatment terms in legislators’ social media posts. Results For the first e-mail, the e-mail view rate was 42.6% higher in the intervention than in the enhanced control condition (22.8% vs. 14.8%) and 20.8% higher than in the control condition (22.8% vs. 18.5%) (both p < .0001). Similar results were observed for the second e-mail. These differences remained significant after adjustment for demographic differences across study conditions in individual-level models, but not multilevel models. There was a significant interaction between the experimental condition and political party (p < .0001) in which the intervention increased e-mail view rates among Democrats but not Republicans. The intervention had no effect on policy brief link clicks or requests for consultation and a mixed effect on social media posts. Conclusions Inclusion of state-tailored economic evidence in dissemination materials can increase engagement with research evidence among Democrat, but not Republican, legislators. Dissemination strategies tailored for legislators’ political party affiliation may be needed.

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Objectives. To quantify variation in the restrictiveness of local public housing authority policies related to the admission and eviction of people with criminal justice histories. Methods. We conducted content analysis of housing authority policy documents for US cities with a population of 100 000 or more (n = 152). Factor analysis identified policy provisions to create a restrictiveness score (range = 0–8). We explored associations between restrictiveness scores and city-level measures of racial/ethnic diversity, racial/ethnic neighborhood segregation, ideology, and public housing scarcity. Results. Eight policy provisions, 6 relating to consideration of mitigating circumstances, explained 71.0% of the variance in housing authority policy provisions related to criminal justice histories. We observed small but significant positive associations between restrictiveness scores and racial/ethnic diversity (r = 0.22) and neighborhood segregation (r = 0.18). There was no correlation between restrictiveness scores of housing authorities within the same state (intraclass correlation = 0.0002). Conclusions. Housing authority policies vary substantially regarding the circumstances under which people with criminal justice histories can obtain and retain public housing. Exposure to constellations of policy provisions that might institutionalize health inequities and increase health risk among people with criminal justice histories can be quantified through a systematic process.

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