Evidence map›Paper›PMID 41406415›Full record

ArticleJMIR human factors2025

Perceptions of User-Generated Content as a Source of Health Messages in Smoking Cessation Mobile Interventions: Focus Group Study.

Michael Wakeman, Lydia Tesfaye, Tim Gregory, Erin Leahy, Gunnar Baskin, Greg Gruse, Brandon Kendrick, Sherine El-Toukhy

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Michael WakemanDivision of Intramural Research, National Institute on Minority Health and Health Disparities, 11545 Rockville Pike, Rockville, MD, 20852, United States, 1 3015944743.ORCID 0009-0001-3970-6057
Lydia TesfayeDivision of Intramural Research, National Institute on Minority Health and Health Disparities, 11545 Rockville Pike, Rockville, MD, 20852, United States, 1 3015944743.ORCID 0009-0006-7484-9631
Tim GregoryICF NEXT (United States), Reston, VA, United States.ORCID 0009-0000-3421-7847
Erin LeahyICF NEXT (United States), Reston, VA, United States.ORCID 0009-0009-9806-6131
Gunnar BaskinICF NEXT (United States), Reston, VA, United States.ORCID 0009-0008-9093-3563
Greg GruseICF NEXT (United States), Reston, VA, United States.ORCID 0009-0002-1600-4164
Brandon KendrickICF NEXT (United States), Reston, VA, United States.ORCID 0009-0007-5893-7372
Sherine El-ToukhyDivision of Intramural Research, National Institute on Minority Health and Health Disparities, 11545 Rockville Pike, Rockville, MD, 20852, United States, 1 3015944743.ORCID 0000-0002-0329-5823

Funding

Digital Health and Health Disparities Research LabZIAMD000011 · NIMHD · NATIONAL INSTITUTE ON MINORITY HEALTH AND HEALTH DISPARITIES · PI EL-TOUKHY, SHERINE · 2018 to 2025
$3.1M
Intramural NIH HHS ZIA MD000011
6 · The paper itself

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.

Indexed as

Mobile ApplicationsSmoking CessationSocial MediaAdolescentAdultFemaleFocus GroupsHumansMaleYoung Adultfocus group discussionslow socioeconomic statussmoking cessation appssocial mediaTwitteruser-generated contentXyoung adults

Identifiers

PMID41406415
PMCPMC12711135

What OpenQuestion holds

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Registered trials

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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.