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      The Effectiveness of Electronic Health Interventions for Promoting HIV-Preventive Behaviors Among Men Who Have Sex With Men: Meta-Analysis Based on an Integrative Framework of Design and Implementation Features

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          Abstract

          Background

          The disproportionately high prevalence of HIV among men who have sex with men (MSM) is a global concern. Despite the increasing utilization of electronic health (eHealth) technology in the delivery of HIV prevention interventions, few studies have systematically explored its effectiveness and association with various intervention characteristics.

          Objective

          This study aimed to conduct a meta-analysis of the effectiveness of eHealth technology–based interventions for promoting HIV-preventive behaviors among MSM and to determine effectiveness predictors within a framework integrating design and implementation features.

          Methods

          A systematic literature search using terms related to eHealth technology, HIV, the MSM population, and an experimental study design was performed using 5 databases (ie, MEDLINE, PsycINFO, EMBASE, Web of Science, and ProQuest Dissertations & Theses) and other sources (eg, bibliographies of relevant reviews and JMIR Publications). First, primary meta-analyses were conducted to estimate the effectiveness of eHealth interventions ( d +) in changing 3 HIV-preventive behaviors among MSM: unprotected anal intercourse (UAI), HIV testing, and multiple sex partnership (MSP). Moderation analyses were then conducted to examine a priori effectiveness predictors including behavioral treatment components (eg, theory use, tailoring strategy use, navigation style, and treatment duration), eHealth technology components (eg, operation mode and modality type), and intervention adherence.

          Results

          A total of 46 studies were included. The overall effect sizes at end point were small but significant for all outcomes (UAI: d +=−.21, P<.001; HIV testing: d +=.38, P<.001; MSP: d +=−.26, P=.02). The intervention effects on UAI were significantly larger when compared with preintervention groups than with concurrent groups. Greater UAI reductions were associated with the increased use of tailoring strategies, provision of feedback, and tunneling navigation in interventions with a concurrent group, whereas reductions were associated with the use of self-paced navigation in interventions with a preintervention group. Greater uptake of HIV testing was associated with longer treatment duration; computer-mediated communication; and the use of messaging, social media, or a combined technology modality. Higher intervention adherence consistently predicted larger effects on UAI and HIV testing.

          Conclusions

          This study provided empirical evidence for the effectiveness of eHealth interventions in promoting HIV-preventive behaviors among MSM. Features of treatment content and eHealth technology might best predict the intervention effects on UAI and HIV testing, respectively. Most importantly, intervention adherence tended to play an important role in achieving better effectiveness. The findings could help inform the development of efficacious interventions for HIV prevention in the future.

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          Most cited references62

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          Persuasive System Design Does Matter: A Systematic Review of Adherence to Web-Based Interventions

          Background Although web-based interventions for promoting health and health-related behavior can be effective, poor adherence is a common issue that needs to be addressed. Technology as a means to communicate the content in web-based interventions has been neglected in research. Indeed, technology is often seen as a black-box, a mere tool that has no effect or value and serves only as a vehicle to deliver intervention content. In this paper we examine technology from a holistic perspective. We see it as a vital and inseparable aspect of web-based interventions to help explain and understand adherence. Objective This study aims to review the literature on web-based health interventions to investigate whether intervention characteristics and persuasive design affect adherence to a web-based intervention. Methods We conducted a systematic review of studies into web-based health interventions. Per intervention, intervention characteristics, persuasive technology elements and adherence were coded. We performed a multiple regression analysis to investigate whether these variables could predict adherence. Results We included 101 articles on 83 interventions. The typical web-based intervention is meant to be used once a week, is modular in set-up, is updated once a week, lasts for 10 weeks, includes interaction with the system and a counselor and peers on the web, includes some persuasive technology elements, and about 50% of the participants adhere to the intervention. Regarding persuasive technology, we see that primary task support elements are most commonly employed (mean 2.9 out of a possible 7.0). Dialogue support and social support are less commonly employed (mean 1.5 and 1.2 out of a possible 7.0, respectively). When comparing the interventions of the different health care areas, we find significant differences in intended usage (p = .004), setup (p < .001), updates (p < .001), frequency of interaction with a counselor (p < .001), the system (p = .003) and peers (p = .017), duration (F = 6.068, p = .004), adherence (F = 4.833, p = .010) and the number of primary task support elements (F = 5.631, p = .005). Our final regression model explained 55% of the variance in adherence. In this model, a RCT study as opposed to an observational study, increased interaction with a counselor, more frequent intended usage, more frequent updates and more extensive employment of dialogue support significantly predicted better adherence. Conclusions Using intervention characteristics and persuasive technology elements, a substantial amount of variance in adherence can be explained. Although there are differences between health care areas on intervention characteristics, health care area per se does not predict adherence. Rather, the differences in technology and interaction predict adherence. The results of this study can be used to make an informed decision about how to design a web-based intervention to which patients are more likely to adhere.
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            Efficacy of text messaging-based interventions for health promotion: a meta-analysis.

            This meta-analysis investigated the efficacy of text messaging-based health promotion interventions. Nineteen randomized controlled trials conducted in 13 countries met inclusion criteria and were coded on a variety of participant, intervention, and methodological moderators. Meta-analytic procedures were used to compute and aggregate effect sizes. The overall weighted mean effect size representing the impact of these interventions on health outcomes was d = .329 (95% CI = .274, .385; p < .001). This effect size was statistically heterogeneous (Q18 = 55.60, p < .001, I(2) = 67.62), and several variables significantly moderated the effects of interventions. Smoking cessation and physical activity interventions were more successful than interventions targeting other health outcomes. Message tailoring and personalization were significantly associated with greater intervention efficacy. No significant differences were found between text-only interventions and interventions that included texting plus other components. Interventions that used an individualized or decreasing frequency of messages over the course of the intervention were more successful than interventions that used a fixed message frequency. We discuss implications of these results for health promotion interventions that use text messaging. Copyright © 2013 Elsevier Ltd. All rights reserved.
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              The increase in global HIV epidemics in MSM.

              Epidemics of HIV in MSM continue to expand in most low, middle, and upper income countries in 2013 and rates of new infection have been consistently high among young MSM. Current prevention and treatment strategies are insufficient for this next wave of HIV spread. We conducted a series of comprehensive reviews of HIV prevalence and incidence, risks for HIV, prevention and care, stigma and discrimination, and policy and advocacy options. The high per act transmission probability of receptive anal intercourse, sex role versatility among MSM, network level effects, and social and structural determinants play central roles in disproportionate disease burdens. HIV can be transmitted through large MSM networks at great speed. Molecular epidemiologic data show marked clustering of HIV in MSM networks, and high proportions of infections due to transmission from recent infections. Prevention strategies that lower biological risks, including those using antiretrovirals, offer promise for epidemic control, but are limited by structural factors including, discrimination, criminalization, and barriers to healthcare. Subepidemics, including among racial and ethnic minority MSM in the United States and UK, are particularly severe and will require culturally tailored efforts. For the promise of new and combined bio-behavioral interventions to be realized, clinically competent healthcare is necessary and community leadership, engagement, and empowerment are likely to be key. Addressing the expanding epidemics of HIV in MSM will require continued research, increased resources, political will, policy change, structural reform, community engagement, and strategic planning and programming, but it can and must be done.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                May 2020
                25 May 2020
                : 22
                : 5
                : e15977
                Affiliations
                [1 ] Jockey Club School of Public Health and Primary Care The Chinese University of Hong Kong Hong Kong China (Hong Kong)
                [2 ] TH Chan School of Public Health Harvard University Boston, MA United States
                [3 ] Center for Evidence Synthesis in Health School of Public Health Brown University Providence, RI United States
                [4 ] School of Public Health Shanghai University of Traditional Chinese Medicine Shanghai China
                Author notes
                Corresponding Author: Phoenix Kit-Han Mo phoenix.mo@ 123456cuhk.edu.hk
                Author information
                https://orcid.org/0000-0002-8636-4918
                https://orcid.org/0000-0002-4795-5803
                https://orcid.org/0000-0002-1358-5701
                https://orcid.org/0000-0002-6163-2760
                https://orcid.org/0000-0002-5155-958X
                https://orcid.org/0000-0003-2344-7107
                https://orcid.org/0000-0001-9822-5424
                Article
                v22i5e15977
                10.2196/15977
                7281149
                32449685
                8c041d89-005a-4338-9771-0c6f5be55a33
                ©Meiqi Xin, Kasisomayajula Viswanath, Angela Yuen-Chun Li, Wangnan CAO, Yuhong HU, Joseph Tak-Fai Lau, Phoenix Kit-Han Mo. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.05.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 26 August 2019
                : 28 September 2019
                : 19 December 2019
                : 1 February 2020
                Categories
                Review
                Review

                Medicine
                hiv,aids,sexual and gender minorities,telemedicine,meta-analysis,systematic review
                Medicine
                hiv, aids, sexual and gender minorities, telemedicine, meta-analysis, systematic review

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