ArticleJournal of smoking cessation2020
Text2Quit: An analysis of user experiences with a mobile smoking cessation program.
Article in Journal of smoking cessation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- ChatGPT-Based Chatbot for Help Quitting Smoking via Text Messaging: An Interventional Study.JMIR formative research · 2025Article
- Don't Forget the Humble Text Message: 25 Years of Text Messaging in Health.Journal of medical Internet research · 2024Review
- A pilot randomized controlled trial of automated and counselor-delivered text messages for e-cigarette cessation.Tobacco prevention & cessation · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
introductionStudies have shown that Text2Quit and other mobile cessation programs increase quit rates in adult smokers, but the mechanism of effects and user experiences are not well understood.
aimsThis study reports on participants' experiences with the program and explores aspects of the program that they liked and disliked.
methodsSelf-reported experiences of the program were collected through a follow-up survey conducted one month after enrollment (n=185). Participant responses to open-ended items were dual coded by independent coders.
resultsOverall participants agreed that they liked the program (4.2/5), that the program was helpful (4.1/5) and that they would recommend the program to a friend (4.3/5). Top reasons for liking the program included that it served as a constant reminder of quitting (17.8%), the content (16.7%), the encouragement provided (13.3%), and the on-demand tools (12.2%). Top reasons for disliking the program were message frequency (20.5%), content (7.0%), and the lack of personal interaction (7.0%).
conclusionsThe constancy of messaging was both liked as a reminder and disliked as an annoyance. Future programs might be improved by pre-testing and customizing the content based on user preferences, and by adding in human interactions, while keeping a supportive tone and offering on-demand tools.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.