Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Formative Research

Date Submitted: May 12, 2023
Date Accepted: Nov 27, 2023

The final, peer-reviewed published version of this preprint can be found here:

Developing Mood-Based Computer-Tailored Health Communication for Smoking Cessation: Feasibility Randomized Controlled Trial

Lee DN, Sadasivam RS, Stevens EM

Developing Mood-Based Computer-Tailored Health Communication for Smoking Cessation: Feasibility Randomized Controlled Trial

JMIR Form Res 2023;7:e48958

DOI: 10.2196/48958

PMID: 38133916

PMCID: 10770788

Developing Mood-Based Computer-Tailored Health Communication for Smoking Cessation: Pilot Study

  • Donghee Nicole Lee; 
  • Rajani S Sadasivam; 
  • Elise M Stevens

ABSTRACT

Background:

Most smokers want to quit smoking despite the low success rates. Thus, innovative strategies are needed to help smokers quit and stay quit. Incorporating computer-tailored health communication (CTHC) systems into a smoking cessation digital intervention can increase its effectiveness. CTHC systems can deliver smoking cessation messages tailored to individual’s mood to increase the efficacy of smoking cessation digital interventions.

Objective:

We examined the association of mood and smoking cessation message effectiveness among adults who currently smoke cigarettes.

Methods:

In January 2022, we recruited an online convenience sample of adults who smoke cigarettes (N=617, Mage=41.13). Participants were randomized to one of three mood conditions: positive, negative, or neutral, and viewed a picture selected from the International Affective Picture System (IAPS) to induce an emotional state within the assigned condition. Participants then viewed 30 previously tested smoking cessation messages with topics covering five themes: 1) financial costs/rewards, 2) health, 3) quality-of-life, 4) challenges of quitting, and 5) motivation/reasons to quit. Following each message, participants completed questions on three constructs: message receptivity, perceived relevance, and their motivation to quit. We used one-way ANOVA to estimate the association of mood condition on these constructs, controlling for demographics, cigarettes per day, and motivation to quit measured during pre-test. We also estimated the association between mood and outcomes for each of the five smoking message theme categories.

Results:

Participants in the positive mood condition reported significantly greater motivation to quit compared to those in the negative mood condition (P=.005). Furthermore, participants in the positive mood condition reported higher motivation to quit after viewing smoking cessation messages in the financial (P=.031), health (P=.013), quality-of-life (P=.036), and challenges of quitting (P=.034) theme categories. Furthermore, participants in the positive mood condition reported significantly greater motivation to quit after seeing messages in the financial (P=.010), health (P=.003), quality-of-life theme, (P=.010), and challenges of quitting (P=.013) theme categories than those in the negative mood condition.

Conclusions:

Considering individuals’ mood at the time of message exposure can influence the effects of smoking cessation messages on adults who smoke cigarettes. Future smoking cessation interventions should consider avenues to increase positive mood among adult smokers to increase their motivation to quit smoking and increase message effectiveness. Clinical Trial: N/A


 Citation

Please cite as:

Lee DN, Sadasivam RS, Stevens EM

Developing Mood-Based Computer-Tailored Health Communication for Smoking Cessation: Feasibility Randomized Controlled Trial

JMIR Form Res 2023;7:e48958

DOI: 10.2196/48958

PMID: 38133916

PMCID: 10770788

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.