Predicting Adolescent Intervention Non-responsiveness for Precision HIV Prevention Using Machine Learning

Interventions to teach protective behaviors may be differentially effective within an adolescent population. Identifying the characteristics of youth who are less likely to respond to an intervention can guide program modifications to improve its effectiveness. Using comprehensive longitudinal data...

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Detalles Bibliográficos
Autores principales: Wang, Bo, Liu, Feifan, Deveaux, Lynette, Ash, Arlene, Gerber, Ben, Allison, Jeroan, Herbert, Carly, Poitier, Maxwell, MacDonell, Karen, Li, Xiaoming, Stanton, Bonita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10129965/
https://www.ncbi.nlm.nih.gov/pubmed/36255592
http://dx.doi.org/10.1007/s10461-022-03874-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10129965/
https://www.ncbi.nlm.nih.gov/pubmed/36255592
http://dx.doi.org/10.1007/s10461-022-03874-4

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