A multilevel intervention in pediatric primary care for youth tobacco control: Outcomes of implementing an Ask, Advise, and Connect model.

children implementation pediatrics tobacco use prevention

Journal

Translational behavioral medicine
ISSN: 1613-9860
Titre abrégé: Transl Behav Med
Pays: England
ID NLM: 101554668

Informations de publication

Date de publication:
08 Feb 2024
Historique:
medline: 8 2 2024
pubmed: 8 2 2024
entrez: 8 2 2024
Statut: aheadofprint

Résumé

Multilevel interventions in healthcare settings (e.g. Ask, Advise, and Connect; AAC) can reduce tobacco product use among adult patients: their effectiveness in pediatric practice is largely unknown. We implemented an AAC model in pediatric primary care to deter children's tobacco use, and evaluated its effectiveness in a single-arm trial. At wellness visits, young patients (ages 12-17) completed a tablet-based assessment (Ask) of lifetime and current tobacco use. These data were made available within the electronic health record to pediatric primary care providers for preventive counseling (Advise). Providers then referred patients to an e-health evidence-based tobacco control intervention (Connect). Tobacco control outcomes were examined in the clinic population (N = 2219) and in a sample of patients (N = 388, 62% female, 39% non-White, M age = 15) over time, along with intervention engagement. Population use of tobacco products decreased following introduction of AAC (more than 2-fold). At the patient level, most children (80.9%) engaged with the intervention: those who were Black or African American, who never used tobacco products/were not susceptible to use, and who used fewer non-cigarette tobacco products were more likely to engage, but only after multiple prompts versus a single prompt. Engagement was positively associated with lowering children's susceptibility to using tobacco at follow-up. A pediatric AAC model holds promise in deterring youth tobacco use, including among historically marginalized populations who may require additional support. By implementing a multilevel Ask, Advise, and Connect intervention, pediatric tobacco use declined in a clinical population, with high intervention engagement and improved outcomes.

Autres résumés

Type: plain-language-summary (eng)
By implementing a multilevel Ask, Advise, and Connect intervention, pediatric tobacco use declined in a clinical population, with high intervention engagement and improved outcomes.

Identifiants

pubmed: 38330454
pii: 7603952
doi: 10.1093/tbm/ibae002
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Public Health Service
ID : CA162839

Informations de copyright

© Society of Behavioral Medicine 2024. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Auteurs

Darren Mays (D)

Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.

Joseph M Macisco (JM)

Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.

Kirsten B Hawkins (KB)

MedStar Georgetown University Hospital, Georgetown University Medical Center, Washington, DC, USA.

Marcelo M Sleiman (MM)

Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA.

Mary Rose Yockel (MR)

Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA.

Shoulong Xie (S)

Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA.

Lilianna Phan (L)

Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA.

George Luta (G)

Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA.

Tania Lobo (T)

Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA.

Anisha Abraham (A)

Children's National Health System, Washington, DC, USA.

Alexander V Prokhorov (AV)

MD Anderson Cancer Center, Houston, TX, USA.

Kenneth P Tercyak (KP)

Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA.

Classifications MeSH