Currently submitted to: JMIR mHealth and uHealth
Date Submitted: Jun 11, 2026
Open Peer Review Period: Jun 12, 2026 - Aug 7, 2026
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).
Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Digital and AI-Based mHealth Interventions, Including Chatbots, for HIV and STI Prevention Among Men Who Have Sex With Men and LGBTIQ+ Populations: A Critical Narrative Review With Systematic Search
ABSTRACT
Background:
Men who have sex with men (MSM) and LGBTIQ+ populations bear a disproportionate burden of HIV and other sexually transmitted infections (STIs) due to structural stigma and barriers to culturally competent care. Mobile and other digital health technologies, and more recently artificial intelligence (AI)–based tools such as chatbots and risk prediction models, may help improve prevention, testing, and pre-exposure prophylaxis (PrEP) use in these groups.
Objective:
This review aimed to (1) synthesize evidence from the past decade on the effectiveness and acceptability of mHealth and other digital sexual health interventions targeting MSM and LGBTIQ+ individuals—focusing on HIV, other STIs, and PrEP—and (2) identify the distinctive features and current evidence base of interventions incorporating AI or advanced automation, particularly conversational agents.
Methods:
We conducted a critical narrative review with a systematic search following PRISMA recommendations to identify mHealth and other digital sexual health interventions targeting MSM and LGBTIQ+ individuals. Databases searched included PubMed/MEDLINE, Embase, PsycINFO, CINAHL, Web of Science, and the Cochrane Library for studies published between January 1, 2016, and December 31, 2025, complemented by exploratory searches in technology repositories. Eligible studies included MSM and/or LGBTIQ+ participants; evaluated digital sexual health, HIV/STI, or PrEP interventions; and reported quantitative outcomes on behavior, service use, or cognitive/psychosocial variables. Randomized and nonrandomized trials, quasi-experimental, pre–post, pilot, and feasibility studies were included. Two reviewers independently screened records and extracted data. Owing to substantial heterogeneity in designs and outcomes, a narrative synthesis was conducted instead of a meta-analysis. The review protocol was not registered in any public registry.
Results:
Of 12,995 records identified, 15 intervention studies met the inclusion criteria, complemented by 9 recent systematic or scoping reviews on digital and AI-based sexual health interventions. Conventional digital interventions using websites, mobile apps, SMS, social media, and interactive online programs showed modest but relatively consistent improvements in sexual health knowledge, attitudes, HIV/STI testing frequency, and some risk-reduction behaviors among MSM and LGBTIQ+ populations, whereas evidence for PrEP initiation and adherence was sparse and mixed. Interventions explicitly incorporating AI—mainly chatbots for HIV testing support, PrEP decision-making, and sexual health counseling, as well as risk prediction tools often embedded in mobile or web-based platforms—were generally evaluated in pilot or feasibility studies with small samples and short follow-up. These AI-based tools demonstrated high acceptability, perceived confidentiality, and usability, and in some cases facilitated correct HIV self-testing and linkage to services, but robust evidence on sustained behavior change, PrEP uptake and adherence, or clinical outcomes remains very limited. Reporting of equity, data protection, and algorithmic transparency was scarce, and few interventions were specifically co-designed with MSM and LGBTIQ+ communities.
Conclusions:
Digital and especially mHealth interventions are an established and promising component of HIV and STI prevention for MSM and LGBTIQ+ populations, especially for improving access to information and HIV/STI testing. Evidence on the added value of AI-based tools and conversational agents is still preliminary, largely limited to feasibility and acceptability outcomes, and rarely focused on PrEP. Future research should prioritize rigorously designed, co-designed AI-enhanced mHealth interventions that integrate behavior change theory, ethical safeguards, and equity analyses, and that systematically assess their impact on PrEP initiation and adherence, sexual behaviors, and HIV/STI incidence within community sexual health and HIV prevention services
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© 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.