Predictors of adherence to nicotine replacement therapy: Machine learning evidence that perceived need predicts medication use.

ABSTRACT: BACKGROUND:Nonadherence to smoking cessation medication is a frequent problem. Identifying pre-quit predictors of nonadherence may help explain nonadherence and suggest tailored interventions to address it. AIMS:Identify and characterize subgroups of smokers based on adherence to nicotine replacement therapy (NRT). METHOD:Secondary classification tree analyses of data from a 2-arm randomized controlled trial of Recommended Usual Care (R-UC, n = 315) versus Abstinence-Optimized Treatment (A-OT, n = 308) were conducted. R-UC comprised 8 weeks of nicotine patch plus brief counseling whereas A-OT comprised 3 weeks of pre-quit mini-lozenges, 26 weeks of nicotine patch plus mini-lozenges, 11 counseling contacts, and 7-11 automated reminders to use medication. Analyses identified subgroups of smo

SUBMITTER: Kim N 

PROVIDER: S-EPMC6931262 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature