ArticleJMIR human factors2025
Perceptions of User-Generated Content as a Source of Health Messages in Smoking Cessation Mobile Interventions: Focus Group Study.
Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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Who cites it
2 citing papers in PubMed.
- A tale of two apps: preliminary usability testing of smoking cessation mobile applications among individuals with low socioeconomic status who smoke cigarettes.BMC medical informatics and decision making · 2026Article
- Acceptability of a carbon monoxide monitoring feature of a smoking cessation mobile application: a virtual focus group study.BMJ public health · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Background: Health messages are integral to smoking cessation interventions. Common approaches to health message development include expert-crafted messages and audience-generated messages, which produce messages that can be monotonic, didactic, and limited in number. We introduce an alternative approach to health message development that relies on user-generated content available on open-content platforms as a source of health messages. Objective: We examined the acceptability of user-generated content curated from Twitter (subsequently rebranded X) as a source of health support messages in a newly developed smoking cessation mobile intervention called Quit Journey and the optimal timing and frequency with which health messages can be deployed to support app users in real time. Methods: A total of 12 semistructured focus groups were held with 38 young adults with low socioeconomic status who smoked cigarettes, wanted to quit, and were aged 18 to 29 years. Focus groups were held virtually on GoTo Meeting, audio recorded, and transcribed verbatim. Deductive thematic analysis was used, with themes based on 5 constructs from the second unified theory of acceptance and use of technology (ie, effort expectancy, facilitating conditions, hedonic motivation, performance expectancy, and social influence) and negative, neutral, and positive sentiment. Results: Participants perceived user-generated content positively (56/108, 51.9% of the quotes) and focused on their perceived usefulness (37/108, 34.3% of the quotes). User-generated content was perceived as authentic, nonrepetitive support from people with similar real-life experiences. Negative or sarcastic user-generated content elicited negative reactions from participants. Participants preferred receiving 3 or fewer daily messages, ideally before cravings. Suggestions focused on the need to screen user-generated content before its inclusion in the app library and allow app users to customize message frequency and timing. Conclusions: User-generated content was deemed an acceptable source of health messages. This content can improve the efficacy and effectiveness of smoking cessation interventions by increasing their pool of unique messages that may be better received and more persuasive than expert-curated content. User-generated content can be used to curate health messages for all medical conditions and behaviors with relevant publicly available online content for integration in behavioral interventions given its high volume, brevity, and narrative-like nature. Future research is needed to investigate the effects of user-generated content on health behaviors and identify the theoretical mechanisms for these effects.
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