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. 2021 Feb-Mar;76(2):364-378.
doi: 10.1037/amp0000756.

Implications of adverse childhood experiences screening on behavioral health services: A scoping review and systems modeling analysis

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Implications of adverse childhood experiences screening on behavioral health services: A scoping review and systems modeling analysis

Miya L Barnett et al. Am Psychol. 2021 Feb-Mar.

Abstract

Widespread implementation of adverse childhood experiences (ACEs) screening is occurring in the United States in response to policies and practice recommendations. However, limited research has established how these screening efforts impact the health care system and ultimately health outcomes. This article examines the current knowledge base on screening in medical settings. A scoping review of articles reporting on ACEs screening and prevalence in the United States was conducted. Of the 1,643 unique studies across two decades, 12 articles meeting criteria included nine on routine screening in medical settings and three on population-based surveys. A Monte Carlo simulation model was designed to synthesize evidence, identify key areas of uncertainty, and explore service system implications. Results indicated significant heterogeneity in the proportion of respondents who reported ACEs, with 6% to 64% of patients reporting 1+ ACEs and .01% to 40.7% reporting 4+ ACEs. Gaps in the literature were identified regarding cut-scores for referrals and referral completion rates. Three scenarios, modeled based on these data and past research on behavioral health screenings in pediatric primary care, demonstrated how ACEs screening may differentially impact behavioral health care systems. Priorities for future research were highlighted to refine estimates of the likely impact of ACEs screening on health care delivery. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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Figures

Figure 1.
Figure 1.
PRISMA Flow Diagram of Literature Search and Selection Process
Figure 2.
Figure 2.
Proportion of population reporting different numbers of ACEs in population surveys and screening-based studies in primary care settings.
Figure 3.
Figure 3.
Simulation Model Structure
Figure 4.
Figure 4.
Results of Model Scenarios

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