An Ecological Momentary Intervention for Smoking Cessation: The Associations of Just-in-time, Tailored Messages with Lapse Risk Factors

Overview

Journal Addict Behav

Specialties Psychiatry
Social Sciences

Date 2017 Nov 10

PMID 29121530

Citations 44

Authors

Emily T Hebert

Elise M Stevens

Summer G Frank

Darla E Kendzor

David W Wetter

Michael J Zvolensky

Julia D Buckner

Michael S Businelle

Affiliations

Soon will be listed here.

Abstract

Background: Smartphone apps can provide real-time, tailored interventions for smoking cessation. The current study examines the effectiveness of a smartphone-based smoking cessation application that assessed risk for imminent smoking lapse multiple times per day and provided messages tailored to current smoking lapse risk and specific lapse triggers.

Methods: Participants (N=59) recruited from a safety-net hospital smoking cessation clinic completed phone-based ecological momentary assessments (EMAs) 5 times/day for 3 consecutive weeks (1week pre-quit, 2weeks post-quit). Risk for smoking lapse was estimated in real-time using a novel weighted lapse risk estimator. With each EMA, participants received messages tailored to current level of risk for imminent smoking lapse and self-reported presence of smoking urge, stress, cigarette availability, and motivation to quit. Generalized linear mixed model analyses determined whether messages tailored to specific lapse risk factors were associated with greater reductions in these triggers than messages not tailored to specific triggers.

Results: Overall, messages tailored to smoking urge, cigarette availability, or stress corresponded with greater reductions in those triggers than messages that were not tailored to specific triggers (p's=0.02 to <0.001). Although messages tailored to stress were associated with greater reductions in stress than messages not tailored to stress, the association was non-significant (p=0.892) when only moments of high stress were included in the analysis.

Conclusions: Mobile technology can be used to conduct real-time smoking lapse risk assessment and provide tailored treatment content. Findings provide initial evidence that tailored content may impact users' urge to smoke, stress, and cigarette availability.

Citing Articles

A feature-based qualitative assessment of smoking cessation mobile applications.

Tesfaye L, Wakeman M, Baskin G, Gruse G, Gregory T, Leahy E PLOS Digit Health. 2024; 3(11):e0000658.

PMID: 39571041 PMC: 11581403. DOI: 10.1371/journal.pdig.0000658.

Personalized interventions for behaviour change: A scoping review of just-in-time adaptive interventions.

Hsu T, Whelan P, Gandrup J, Armitage C, Cordingley L, McBeth J Br J Health Psychol. 2024; 30(1):e12766.

PMID: 39542743 PMC: 11583291. DOI: 10.1111/bjhp.12766.

Smartphone-Based Smoking Cessation Intervention (OKquit) for Oklahoma Tobacco Helpline Users: Protocol for a Randomized Controlled Trial.

Businelle M, Becerra J, Witten C, Chen S, Kezbers K, Beebe L JMIR Res Protoc. 2024; 13:e56827.

PMID: 39088254 PMC: 11327626. DOI: 10.2196/56827.

Towards AI-Driven Healthcare: Systematic Optimization, Linguistic Analysis, and Clinicians' Evaluation of Large Language Models for Smoking Cessation Interventions.

Calle P, Shao R, Liu Y, Hebert E, Kendzor D, Neil J Proc SIGCHI Conf Hum Factor Comput Syst. 2024; 2024.

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Towards Predicting Smoking Events for Just-in-time Interventions.

Yu H, Kotlyar M, Thuras P, Dufresne S, Pakhomov S AMIA Jt Summits Transl Sci Proc. 2024; 2024:468-477.

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