Background: SMS text messages are affordable, scalable, and effective smoking cessation interventions. However, there is little research on SMS text message interventions specifically designed to support people who smoke to quit by switching to vaping.

Objective: Over 3 phases, with vapers and smokers, we codeveloped and coproduced a mobile phone SMS text message program. The coproduction paradigm allowed us to collaborate with researchers and the community to develop a more relevant, acceptable, and equitable SMS text message program.

Methods: In phase 1, we engaged people who vape via Twitter and received 167 responses to our request to write SMS text messages for people who wish to quit smoking by switching to vaping. We screened, adjusted, refined, and themed the messages, resulting in a set of 95 that were mapped against the Capability, Opportunity, and Motivation-Behavior constructs. In phase 2, we evaluated the 95 messages from phase 1 via a web survey where participants (66/202, 32.7% woman) rated up to 20 messages on 7-point Likert scales on 9 constructs: being understandable, clear, believable, helpful, interesting, inoffensive, positive, and enthusiastic and how happy they would be to receive the messages. In phase 3, we implemented the final set of SMS text messages as part of a larger randomized optimization trial, in which 603 participants (mean age 38.33, SD 12.88 years; n=369, 61.2% woman) received SMS text message support and then rated their usefulness and frequency and provided free-text comments at the 12-week follow-up.

Results: For phase 2, means and SDs were calculated for each message across the 9 constructs. Those with means below the neutral anchor of 4 or with unfavorable comments were discussed with vapers and further refined or removed. This resulted in a final set of 78 that were mapped against early, mid-, or late stages of quitting to create an order for the messages. For phase 3, a total of 38.5% (232/603) of the participants provided ratings at the 12-week follow-up. In total, 69.8% (162/232) reported that the SMS text messages had been useful, and a significant association between quit rates and usefulness ratings was found (χ=9.6; P=.002). A content analysis of free-text comments revealed that the 2 most common positive themes were helpful (13/47, 28%) and encouraging (6/47, 13%) and the 2 most common negative themes were too frequent (9/47, 19%) and annoying (4/47, 9%).

Conclusions: In this paper, we describe the initial coproduction and codevelopment of a set of SMS text messages to help smokers stop smoking by transitioning to vaping. We encourage researchers to use, further develop, and evaluate the set of SMS text messages and adapt it to target populations and relevant contexts.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568393PMC
http://dx.doi.org/10.2196/49668DOI Listing

Publication Analysis

Top Keywords

sms text
40
text messages
28
text message
16
messages
12
messages phase
12
set sms
12
text
11
sms
10
mobile phone
8
support people
8

Similar Publications

We appreciate Reierson's thoughtful commentary on our 2019 paper, which described our experiences, ethical process, judgment calls, and lessons from a 2016-2017 data-sharing pilot between Crisis Text Line and academic researchers. The commentary raises important questions about the ethical conduct of health research in the digital age, particularly regarding informed consent, potential conflicts of interest, and the protection of vulnerable populations. Our article focused specifically on the noncommercial use of Crisis Text Line data for research purposes, so we restrict our reply to points relevant to such usage.

View Article and Find Full Text PDF

Background: Despite efforts to promote optimal breastfeeding practices, the practice of exclusive breastfeeding is low in South Africa. We conducted a trial to determine whether text messaging plus motivational interviewing prolonged exclusive breastfeeding during the first six months of life and improved child health outcomes.

Methods: We conducted a randomized parallel group-controlled trial between July 2022 and May 2024, at a secondary-level healthcare facility.

View Article and Find Full Text PDF

MyEcoReporter: a prototype for artificial intelligence-facilitated pollution reporting.

J Expo Sci Environ Epidemiol

January 2025

Department of Veterinary Physiology & Pharmacology, Texas A&M University, College Station, TX, USA.

Background: Many chemical releases are first noticed by community members, but reporting these concerns often involves considerable hurdles. Artificial Intelligence (AI)-enabled technologies, especially large language models (LLMs), can potentially reduce these barriers.

Objective: We hypothesized that AI-powered chatbots can facilitate reporting of pollution incidents through text messaging.

View Article and Find Full Text PDF

Objectives: Physical activity (PA) is crucial for older adults' wellbeing. Digital health interventions (DHIs) are important, however a synthesis aimed at healthy community-dwelling OA is lacking. This study aims to synthesize DHIs effect on PA levels among community-dwelling 60-year-old adults or older.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!