RESUMO
In response to the widespread youth mental health crisis, some kindergarten-through-12th-grade (K-12) schools have begun employing artificial intelligence (AI)-based tools to help identify students at risk for suicide and self-harm. The adoption of AI and other types of educational technology to partially address student mental health needs has been a natural forward step for many schools during the transition to remote education. However, there is limited understanding about how such programs work, how they are implemented by schools, and how they may benefit or harm students and their families. To assist policymakers, school districts, school leaders, and others in making decisions regarding the use of these tools, the authors address these knowledge gaps by providing a preliminary examination of how AI-based suicide risk monitoring programs are implemented in K-12 schools, how stakeholders perceive the effects that the programs are having on students, and the potential benefits and risks of such tools. Using this analysis, the authors also offer recommendations for school and district leaders; state, federal, and local policymakers; and technology developers to consider as they move forward in maximizing the intended benefits and mitigating the possible risks of AI-based suicide risk monitoring programs.
RESUMO
Importance: Medications for opioid use disorder (MOUD) are an effective but underutilized treatment. Opioid use disorder prevalence is high among people receiving treatment in community outpatient mental health treatment facilities (MHTFs), but MHTFs are understudied as an MOUD access point. Objective: To quantify availability of MOUD at community outpatient MHTFs in high-burden states as well as characteristics associated with offering MOUD. Design, Setting, and Participants: This cross-sectional study performed a phone survey between April and July 2023 among a representative sample of community outpatient MHTFs within 20 states most affected by the opioid crisis, including all Certified Community Behavioral Health Centers (CCBHCs). Participants were staff at 450 surveyed community outpatient MHTFs in 20 states in the US. Main Outcomes and Measures: MOUD availability. A multivariable logistic regression was fit to assess associations of facility, county, and state-level characteristics with offering MOUD. Results: Surveys with staff from 450 community outpatient MHTFs (152 CCBHCs and 298 non-CCBHCs) in 20 states were analyzed. Weighted estimates found that 34% (95% CI, 29%-39%) of MHTFs offered MOUD in these states. Facility-level factors associated with increased odds of offering MOUD were: self-reporting being a CCBHC (odds ratio [OR], 2.11 [95% CI, 1.08-4.11]), providing integrated mental and substance use disorder treatment (OR, 5.21 [95% CI, 2.44-11.14), having a specialized treatment program for clients with co-occurring mental and substance use disorders (OR, 2.25 [95% CI, 1.14-4.43), offering housing services (OR, 2.54 [95% CI, 1.43-4.51]), and laboratory testing (OR, 2.15 [95% CI, 1.12-4.12]). Facilities that accepted state-financed health insurance plans other than Medicaid as a form of payment had increased odds of offering MOUD (OR, 1.95 [95% CI, 1.01-3.76]) and facilities that accepted state mental health agency funds had reduced odds (OR, 0.43 [95% CI, 0.19-0.99]). Conclusions and Relevance: In this study of 450 community outpatient MHTFs in 20 high-burden states, approximately one-third offered MOUD. These results suggest that further study is needed to report MOUD uptake, either through increased prescribing at all clinics or through effective referral models.