ReviewmHealth2023
Virtual avatars as a new tool for human immunodeficiency virus prevention among men who have sex with men: a narrative review.
Review in mHealth, 2023. 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
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
2 citing papers in PubMed, 8 citations in OpenAlex.
- Comprehensive Communication for a Syndemic Approach to HIV Care: A Framework for Enhancing Health Communication Messages for People Living with HIV.International journal of environmental research and public health · 2025Review
- Digital Interventions to Enhance PrEP Uptake and Adherence Through Stigma Reduction.Current HIV/AIDS reports · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Objective: Human immunodeficiency virus (HIV) continues to affect sexual and gender minorities, predominantly men who have sex with men (MSM). Stigma, medical mistrust, and apprehension towards discussing sexual health with one's medical provider are significant barriers in seeking or accessing preventive services. Those obstacles could be surpassed through novel digital and electronic health interventions, specifically with virtual avatar technology. Avatars are digital self-representative agents that are controlled with an interactive electronic device. Avatars allow for virtual self-immersion within infinitely customizable environments to practice skill building, fostering relationships and more, through an optional incognito approach. The objective of this narrative review is to examine recent uses of and developments in avatar technology, highlight the personalization attribute of this technology, and evaluate its strengths and limitations as a tool for HIV prevention among MSM. Methods: We reviewed recent scientific literature generated by PubMed that use virtual avatar technology in HIV prevention and treatment among populations put at risk. Articles that met the inclusion criteria were then categorized on how the avatar technology was used. Key Content and Findings: We identified eleven studies that met inclusion criteria. Avatar technology was found to create a comfortable environment for participants to address and discuss their sexual behaviors with less hesitation. Avatars can build rapport with populations put at high risk, creating an opportunity for reevaluation of their sexual behavior while assisting them in being able seek information, preventive services, or treatment for HIV or other sexually transmitted infections (STIs). Conclusions: Given the increased use of digital technology in health and prevention, avatars might be useful in sexual health education and HIV prevention among populations put at risk. The benefits and potential in utilizing this technology for HIV prevention are highlighted.
Indexed as
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.