{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T23:57:40Z","timestamp":1783468660835,"version":"3.55.0"},"reference-count":63,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T00:00:00Z","timestamp":1750896000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Good adherence to pre-exposure prophylaxis (PrEP) is critical for effective HIV prevention. Despite the growing awareness of PrEP, many individuals remain at a preliminary understanding stage and struggle to achieve sustained adherence. mHealth (mobile Health) technology is emerging as one of the promising tools in the HIV prevention cascade. While research on mHealth applications for HIV prevention is rapidly advancing, their effectiveness in promoting robust PrEP adherence and optimizing cascade outcomes remains inconclusive, with fragmented evidence limiting scalable implementation.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>To evaluate the efficacy of mHealth tools in optimizing the HIV prevention cascade (from risk identification to PrEP adherence) among key populations (including men who have sex with men, bisexual individuals, sex workers, transgender populations and some other groups who at elevated risk of HIV acquisition).<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We searched in PubMed, Cochrane Library, Web of Science, Embase, Ovid and CINAHL (EBSCO) from the inception to February 3, 2025. Our inclusion criteria focused on randomized controlled trials (RCTs). Literature screening and data extraction were performed independently by two authors. Methodological quality was assessed using Cochrane\u2019s Risk of Bias in Randomized Controlled Trials tool. The primary outcome was adherence to PrEP and secondary outcomes included PrEP use, HIV testing and number of condomless sex events. Analyses were performed using standardized mean difference (SMD) and 95% confidence interval (CI) for continuous variables and using odds ratios (OR) and 95% CI for categorical variables. Data analysis and forest plotting were carried out using R Statistical Software version 4.4.0.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>16 RCT studies met the inclusion criteria. The results of the meta-analysis showed that mHealth interventions significantly promoted PrEP adherence (OR\u202f=\u202f1.60, 95% CI [1.09, 2.35], \u03c1 = 0.016) and HIV testing (OR\u202f=\u202f1.63, 95% CI [1.39, 1.90], \u03c1 &amp;lt; 0.01). It had also shown some effectiveness in promoting the use of PrEP. However, there were no significant effects on reducing the number of condomless sex events during the entire follow-up period.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>mHealth effectively enhances specific stages of the prevention cascade. However, further optimization of technology design and intervention is needed to address complex difficulties.<\/jats:p><\/jats:sec><jats:sec><jats:title>Systematic review registration<\/jats:title><jats:p><jats:uri>https:\/\/www.crd.york.ac.uk\/PROSPERO\/display_record.php?RecordID=533772<\/jats:uri>, identifier PROSPERO CRD42024533772.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2025.1600773","type":"journal-article","created":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T05:27:59Z","timestamp":1750915679000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Impact of mHealth on enhancing pre-exposure prophylaxis adherence and strengthening the HIV prevention cascade among key populations: a systematic review and meta-analysis"],"prefix":"10.3389","volume":"13","author":[{"given":"Fan","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaoying","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Xiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,6,26]]},"reference":[{"key":"ref1","year":"2023"},{"key":"ref2","year":"2024"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"e25509","DOI":"10.1002\/jia2.25509","article-title":"Operationalizing the HIV prevention cascade for PWID using the integrated bio-behavioural survey data from Ukraine","volume":"23","author":"Dumchev","year":"2020","journal-title":"J Int AIDS Soc"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"e318","DOI":"10.1016\/S2352-3018(16)30063-7","article-title":"The 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