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Screening for adolescent alcohol and drug use in pediatric health-care settings: predictors and implications for practice and policy

OBJECTIVE: This paper used data from a study of pediatric primary care provider (PCP) screening practices to examine barriers to and facilitators of adolescent alcohol and other drug (AOD) screening in pediatric primary care. METHODS: A web-based survey (N = 437) was used to examine the influence of...

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Detalles Bibliográficos
Autores principales: Sterling, Stacy, Kline-Simon, Andrea H, Wibbelsman, Charles, Wong, Anna, Weisner, Constance
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3684548/
https://www.ncbi.nlm.nih.gov/pubmed/23186254
http://dx.doi.org/10.1186/1940-0640-7-13
Descripción
Sumario:OBJECTIVE: This paper used data from a study of pediatric primary care provider (PCP) screening practices to examine barriers to and facilitators of adolescent alcohol and other drug (AOD) screening in pediatric primary care. METHODS: A web-based survey (N = 437) was used to examine the influence of PCP factors (attitudes and knowledge, training, self-efficacy, comfort with alcohol and drug issues); patient characteristics (age, gender, ethnicity, comorbidities and risk factors); and organizational factors (screening barriers, staffing resources, confidentiality issues) on AOD screening practices. Self-reported and electronic medical record (EMR)-recorded screening rates were also assessed. RESULTS: More PCPs felt unprepared to diagnose alcohol abuse (42%) and other drug abuse (56%) than depression (29%) (p < 0.001). Overall, PCPs were more likely to screen boys than girls, and male PCPs were even more likely than female PCPs to screen boys (23% versus 6%, p < 0.0001). Having more time and having other staff screen and review results were identified as potential screening facilitators. Self-reported screening rates were significantly higher than actual (EMR-recorded) rates for all substances. Feeling prepared to diagnose AOD problems predicted higher self-reported screening rates (OR = 1.02, p <0.001), and identifying time constraints as a barrier to screening predicted lower self-reported screening rates (OR = 0.91, p < 0.001). Higher average panel age was a significant predictor of increased EMR-recorded screening rates (OR = 1.11, p < 0.001). CONCLUSIONS: Organizational factors, lack of training, and discomfort with AOD screening may impact adolescent substance-abuse screening and intervention, but organizational approaches (e.g., EMR tools and workflow) may matter more than PCP or patient factors in determining screening.