A Mixed-Methods Study of Policymakers' Adoption of AI to Support Use of Research Evidence: Implications for Artificial Intelligence in Prevention Policy.
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| Title: | A Mixed-Methods Study of Policymakers' Adoption of AI to Support Use of Research Evidence: Implications for Artificial Intelligence in Prevention Policy. |
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| Authors: | Crowley DM; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA. dmc397@psu.edu., Wright J; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA., Winters A; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA., Jones D; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA., Pugel J; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA., O'Neill P; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA., Shaw B; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA., Hamel S; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA., Long E; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA., Donovan M; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA., Scott T; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, University Park, PA, USA. |
| Source: | Prevention science : the official journal of the Society for Prevention Research [Prev Sci] 2026 May 02. Date of Electronic Publication: 2026 May 02. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 100894724 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-6695 (Electronic) Linking ISSN: 13894986 NLM ISO Abbreviation: Prev Sci Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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