Adolescent, Parent, and Provider Perceptions of a Predictive Algorithm to Identify Adolescent Suicide Risk in Primary Care.

Autor: Davis M; Department of Child and Adolescent Psychiatry and Behavioral Sciences (M Davis, GC Dysart, KTG Schwartz, and JF Young), Children's Hospital of Philadelphia, Philadelphia, Pa; PolicyLab (M Davis, GC Dysart, SK Doupnik, KTG Schwartz, and JF Young), Children's Hospital of Philadelphia, Philadelphia, Pa; Clinical Futures (M Davis and SK Doupnik), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Psychiatry (M Davis and JF Young), University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa; Penn Implementation Science Center at the Leonard Davis Institute of Health Economics (PISCE@LDI) (M Davis and SK Doupnik), University of Pennsylvania, Philadelphia, Pa. Electronic address: davismf@chop.edu., Dysart GC; Department of Child and Adolescent Psychiatry and Behavioral Sciences (M Davis, GC Dysart, KTG Schwartz, and JF Young), Children's Hospital of Philadelphia, Philadelphia, Pa; PolicyLab (M Davis, GC Dysart, SK Doupnik, KTG Schwartz, and JF Young), Children's Hospital of Philadelphia, Philadelphia, Pa., Doupnik SK; PolicyLab (M Davis, GC Dysart, SK Doupnik, KTG Schwartz, and JF Young), Children's Hospital of Philadelphia, Philadelphia, Pa; Clinical Futures (M Davis and SK Doupnik), Children's Hospital of Philadelphia, Philadelphia, Pa; Penn Implementation Science Center at the Leonard Davis Institute of Health Economics (PISCE@LDI) (M Davis and SK Doupnik), University of Pennsylvania, Philadelphia, Pa; Division of General Pediatrics (SK Doupnik), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Pediatrics (SK Doupnik), University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa., Hamm ME; Department of Medicine (ME Hamm), University of Pittsburgh, Pittsburgh, Pa., Schwartz KTG; Department of Child and Adolescent Psychiatry and Behavioral Sciences (M Davis, GC Dysart, KTG Schwartz, and JF Young), Children's Hospital of Philadelphia, Philadelphia, Pa; PolicyLab (M Davis, GC Dysart, SK Doupnik, KTG Schwartz, and JF Young), Children's Hospital of Philadelphia, Philadelphia, Pa., George-Milford B; University of Pittsburgh Medical Center Western Psychiatric Hospital (B George-Milford and DA Brent), Pittsburgh, Pa., Ryan ND; Department of Psychiatry (ND Ryan, NM Melhem, SD Stepp, and DA Brent), University of Pittsburgh School of Medicine, Pittsburgh, Pa; Clinical and Translational Science Institute (ND Ryan), University of Pittsburgh, Pittsburgh, Pa., Melhem NM; Department of Psychiatry (ND Ryan, NM Melhem, SD Stepp, and DA Brent), University of Pittsburgh School of Medicine, Pittsburgh, Pa., Stepp SD; Department of Psychiatry (ND Ryan, NM Melhem, SD Stepp, and DA Brent), University of Pittsburgh School of Medicine, Pittsburgh, Pa., Brent DA; University of Pittsburgh Medical Center Western Psychiatric Hospital (B George-Milford and DA Brent), Pittsburgh, Pa; Department of Psychiatry (ND Ryan, NM Melhem, SD Stepp, and DA Brent), University of Pittsburgh School of Medicine, Pittsburgh, Pa., Young JF; Department of Child and Adolescent Psychiatry and Behavioral Sciences (M Davis, GC Dysart, KTG Schwartz, and JF Young), Children's Hospital of Philadelphia, Philadelphia, Pa; PolicyLab (M Davis, GC Dysart, SK Doupnik, KTG Schwartz, and JF Young), Children's Hospital of Philadelphia, Philadelphia, Pa; Department of Psychiatry (M Davis and JF Young), University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa.
Jazyk: angličtina
Zdroj: Academic pediatrics [Acad Pediatr] 2024 May-Jun; Vol. 24 (4), pp. 645-653. Date of Electronic Publication: 2024 Jan 06.
DOI: 10.1016/j.acap.2023.12.015
Abstrakt: Objective: To understand adolescent, parent, and provider perceptions of a machine learning algorithm for detecting adolescent suicide risk prior to its implementation primary care.
Methods: We conducted semi-structured, qualitative interviews with adolescents (n = 9), parents (n = 12), and providers (n = 10; mixture of behavioral health and primary care providers) across two major health systems. Interviews were audio recorded and transcribed with analyses supported by use of NVivo. A codebook was developed combining codes derived inductively from interview transcripts and deductively from implementation science frameworks for content analysis.
Results: Reactions to the algorithm were mixed. While many participants expressed privacy concerns, they believed the algorithm could be clinically useful for identifying adolescents at risk for suicide and facilitating follow-up. Parents' past experiences with their adolescents' suicidal thoughts and behaviors contributed to their openness to the algorithm. Results also aligned with several key Consolidated Framework for Implementation Research domains. For example, providers mentioned barriers inherent to the primary care setting such as time and resource constraints likely to impact algorithm implementation. Participants also cited a climate of mistrust of science and health care as potential barriers.
Conclusions: Findings shed light on factors that warrant consideration to promote successful implementation of suicide predictive algorithms in pediatric primary care. By attending to perspectives of potential end users prior to the development and testing of the algorithm, we can ensure that the risk prediction methods will be well-suited to the providers who would be interacting with them and the families who could benefit.
Competing Interests: Declaration of Competing Interest The authors declare there are no conflicts of interest relevant to the current manuscript. This work is funded by the National Institute of Mental Health. Authors receive additional funding from the National Institute of Mental Health and other federal granting agencies. Dr. Young receives royalties from Oxford University Press. Dr. Brent receives royalties from Guilford Press, eRT, and UpToDate and consulting fees from HealthWise. Dr. Brent also receives funding from the American Foundation for Suicide Prevention, the Beckwith Institute, and the Once Upon A Time Foundation. Dr. Melhem received an honorarium from Oakstone Publishing for providing a lecture for one of their courses.
(Copyright © 2024 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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