Purpose <p>Behavioral healthcare services are critical, yet are limited across the country. Policymakers could address gaps through the federal policy process, but most relevant legislation fails. Factors that impact bill outcomes are found in the literature, but the research is scarce regarding how these factors may affect behavioral health-specific outcomes in Congress. Thus, this study examined federal behavioral health-related bills as well as identifying factors related to their sponsor(s) in order to identify trends related to bill outcomes.</p> Methods <p>Utilizing a dataset of federal behavioral health-related bills introduced from 2011 to 2023, this study conducted a multilevel logistic regression analysis to determine which legislative factors predicted bill passage.</p> Results <p>This study found that a legislator’s age, gender, political party, political party-status, position, race/ethnicity, and religion were associated with behavioral health-related bill status. Further, senators, Republicans, members of the majority party, and/or White/Caucasians were more likely to sponsor behavioral health-related bills that passed.</p> Conclusion <p>Findings highlight how certain legislative factors in the behavioral health-related policymaking process may impact behavioral health-related bill outcomes. Advocates could use these findings when targeting legislators in their efforts to find bill sponsorship and more effectively influence bill outcomes.</p>

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Factors Influencing Congressional Behavioral Health-Related Bill Outcomes

  • David L. Conley

摘要

Purpose

Behavioral healthcare services are critical, yet are limited across the country. Policymakers could address gaps through the federal policy process, but most relevant legislation fails. Factors that impact bill outcomes are found in the literature, but the research is scarce regarding how these factors may affect behavioral health-specific outcomes in Congress. Thus, this study examined federal behavioral health-related bills as well as identifying factors related to their sponsor(s) in order to identify trends related to bill outcomes.

Methods

Utilizing a dataset of federal behavioral health-related bills introduced from 2011 to 2023, this study conducted a multilevel logistic regression analysis to determine which legislative factors predicted bill passage.

Results

This study found that a legislator’s age, gender, political party, political party-status, position, race/ethnicity, and religion were associated with behavioral health-related bill status. Further, senators, Republicans, members of the majority party, and/or White/Caucasians were more likely to sponsor behavioral health-related bills that passed.

Conclusion

Findings highlight how certain legislative factors in the behavioral health-related policymaking process may impact behavioral health-related bill outcomes. Advocates could use these findings when targeting legislators in their efforts to find bill sponsorship and more effectively influence bill outcomes.