{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Davis M"],"funding":["NIMH NIH HHS"],"pagination":["645-653"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11056301"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["24(4)"],"pubmed_abstract":["<h4>Objective</h4>To understand adolescent, parent, and provider perceptions of a machine learning algorithm for detecting adolescent suicide risk prior to its implementation primary care.<h4>Methods</h4>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.<h4>Results</h4>Reactions to the algorithm were mixed. While many participants expressed privacy concerns, they believed the algorithm"],"journal":["Academic pediatrics"],"pubmed_title":["Adolescent, Parent, and Provider Perceptions of a Predictive Algorithm to Identify Adolescent Suicide Risk in Primary Care."],"pmcid":["PMC11056301"],"funding_grant_id":["P50 MH115838"],"pubmed_authors":["Ryan ND","Doupnik SK","Brent DA","Schwartz KTG","Young JF","Melhem NM","Stepp SD","Hamm ME","George-Milford B","Dysart GC","Davis M"],"additional_accession":[]},"is_claimable":false,"name":"Adolescent, Parent, and Provider Perceptions of a Predictive Algorithm to Identify Adolescent Suicide Risk in Primary Care.","description":"<h4>Objective</h4>To understand adolescent, parent, and provider perceptions of a machine learning algorithm for detecting adolescent suicide risk prior to its implementation primary care.<h4>Methods</h4>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.<h4>Results</h4>Reactions to the algorithm were mixed. While many participants expressed privacy concerns, they believed the algorithm","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 May-Jun","modification":"2025-07-12T03:05:53.721Z","creation":"2025-07-12T03:05:53.721Z"},"accession":"S-EPMC11056301","cross_references":{"pubmed":["38190885"],"doi":["10.1016/j.acap.2023.12.015"]}}