Predictors of adherence to nicotine replacement therapy: Machine learning evidence that perceived need predicts medication use. (1st December 2019)
- Record Type:
- Journal Article
- Title:
- Predictors of adherence to nicotine replacement therapy: Machine learning evidence that perceived need predicts medication use. (1st December 2019)
- Main Title:
- Predictors of adherence to nicotine replacement therapy: Machine learning evidence that perceived need predicts medication use
- Authors:
- Kim, Nayoung
McCarthy, Danielle E.
Loh, Wei-Yin
Cook, Jessica W.
Piper, Megan E.
Schlam, Tanya R.
Baker, Timothy B. - Abstract:
- Highlights: Classification trees identified smokers high vs. low in adherence to medication. Nicotine dependence, quitting motivation, and smoking triggers predicted adherence. Negative beliefs about nicotine medication predicted nonadherence. 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 smokers highly adherent to nicotine patch use in both treatment conditions, and identified subgroups of A-OT participants highly adherent to mini-lozenges. Results: Varied facets of nicotine dependence predicted adherence across treatment conditions 4 weeks post-quit and between 4- and 16-weeks post-quit in A-OT, with greater baseline dependence and greater smoking trigger exposure and reactivity predicting greater medication use. GreaterHighlights: Classification trees identified smokers high vs. low in adherence to medication. Nicotine dependence, quitting motivation, and smoking triggers predicted adherence. Negative beliefs about nicotine medication predicted nonadherence. 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 smokers highly adherent to nicotine patch use in both treatment conditions, and identified subgroups of A-OT participants highly adherent to mini-lozenges. Results: Varied facets of nicotine dependence predicted adherence across treatment conditions 4 weeks post-quit and between 4- and 16-weeks post-quit in A-OT, with greater baseline dependence and greater smoking trigger exposure and reactivity predicting greater medication use. Greater quitting motivation and confidence, and believing that stop smoking medication was safe and easy to use were associated with greater adherence. Conclusion: Adherence was especially high in those who were more dependent and more exposed to smoking triggers. Quitting motivation and confidence predicted greater adherence, while negative beliefs about medication safety and acceptability predicted worse adherence. Results suggest that adherent use of medication may reflect a rational appraisal of the likelihood that one will need medication and will benefit from it. … (more)
- Is Part Of:
- Drug and alcohol dependence. Volume 205(2019)
- Journal:
- Drug and alcohol dependence
- Issue:
- Volume 205(2019)
- Issue Display:
- Volume 205, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 205
- Issue:
- 2019
- Issue Sort Value:
- 2019-0205-2019-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-12-01
- Subjects:
- Classification tree -- Adherence -- Nicotine replacement therapy -- Nicotine dependence -- Smoking cessation
Drug abuse -- Periodicals
Alcoholism -- Periodicals
616.86 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03768716 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.drugalcdep.2019.107668 ↗
- Languages:
- English
- ISSNs:
- 0376-8716
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3627.890000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17178.xml