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移动健康对提高关键人群暴露前预防依从性及强化艾滋病预防流程的影响:一项系统评价与荟萃分析

Impact of mHealth on enhancing pre-exposure prophylaxis adherence and strengthening the HIV prevention cascade among key populations: a systematic review and meta-analysis.

作者信息

Li Fan, Xie Chaoying, Xiang Fang

机构信息

School of Nursing, University of South China, Hengyang, China.

The First Hospital of Changsha, Changsha, China.

出版信息

Front Public Health. 2025 Jun 26;13:1600773. doi: 10.3389/fpubh.2025.1600773. eCollection 2025.

DOI:10.3389/fpubh.2025.1600773
PMID:40642253
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12240955/
Abstract

BACKGROUND

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.

OBJECTIVE

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).

METHODS

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's 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.

RESULTS

16 RCT studies met the inclusion criteria. The results of the meta-analysis showed that mHealth interventions significantly promoted PrEP adherence (OR = 1.60, 95% CI [1.09, 2.35], ρ = 0.016) and HIV testing (OR = 1.63, 95% CI [1.39, 1.90], ρ < 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.

CONCLUSION

mHealth effectively enhances specific stages of the prevention cascade. However, further optimization of technology design and intervention is needed to address complex difficulties.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=533772, identifier PROSPERO CRD42024533772.

摘要

背景

良好坚持暴露前预防(PrEP)对于有效预防艾滋病毒至关重要。尽管对PrEP的认识不断提高,但许多人仍处于初步了解阶段,难以实现持续坚持。移动健康(mHealth)技术正在成为艾滋病毒预防体系中有前景的工具之一。虽然关于用于艾滋病毒预防的移动健康应用的研究正在迅速推进,但其在促进强有力的PrEP坚持和优化预防体系结果方面的有效性仍无定论,证据零散限制了可扩展实施。

目的

评估移动健康工具在优化关键人群(包括男男性行为者、双性恋者、性工作者、跨性别群体以及其他一些感染艾滋病毒风险较高的群体)的艾滋病毒预防体系(从风险识别到PrEP坚持)方面的疗效。

方法

我们在PubMed、Cochrane图书馆、科学网、Embase、Ovid和CINAHL(EBSCO)中进行检索,检索时间从建库至2025年2月3日。我们的纳入标准侧重于随机对照试验(RCT)。文献筛选和数据提取由两位作者独立进行。使用Cochrane随机对照试验偏倚风险工具评估方法学质量。主要结局是PrEP坚持情况,次要结局包括PrEP使用情况、艾滋病毒检测和无保护性行为事件数量。对于连续变量,使用标准化均数差(SMD)和95%置信区间(CI)进行分析,对于分类变量,使用比值比(OR)和95%CI进行分析。使用R统计软件4.4.0版进行数据分析和森林图绘制。

结果

16项RCT研究符合纳入标准。荟萃分析结果显示,移动健康干预显著促进了PrEP坚持(OR = 1.60,95%CI [1.09, 2.35],ρ = 0.016)和艾滋病毒检测(OR = 1.63,95%CI [1.39, 1.90],ρ < 0.01)。在促进PrEP使用方面也显示出一定效果。然而,在整个随访期间,对减少无保护性行为事件数量没有显著影响。

结论

移动健康有效地增强了预防体系的特定阶段。然而,需要进一步优化技术设计和干预措施来解决复杂难题。

系统评价注册

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=533772,标识符PROSPERO CRD42024533772。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/4b810510df4f/fpubh-13-1600773-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/01df44081c84/fpubh-13-1600773-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/1b3265473c2f/fpubh-13-1600773-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/dbf12cba1270/fpubh-13-1600773-g005.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/01df44081c84/fpubh-13-1600773-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/1b3265473c2f/fpubh-13-1600773-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/27845329a91c/fpubh-13-1600773-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/f7ab67ffea52/fpubh-13-1600773-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/dbf12cba1270/fpubh-13-1600773-g005.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/0fe71bcd3877/fpubh-13-1600773-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f30/12240955/4b810510df4f/fpubh-13-1600773-g009.jpg

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