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The World Health Organization recommends that all adults with HIV adhere to antiretroviral therapy (ART). Good adherence to ART is beneficial to patients and the public. Furthermore, mHealth has shown promise in improving HIV medication adherence globally.
The aim of this meta-analysis is to analyze the effectiveness of mHealth on adherence to antiretroviral therapy in patients living with HIV.
Randomized controlled trials (RCTs) of the association between mHealth and adherence to ART published until December 2021 were searched in electronic databases. Odds ratios (ORs), weighted mean differences, and 95% CIs were calculated. This meta-analysis was performed using the Mantel-Haenszel method or the inverse variance test. We evaluated heterogeneity with the
A total of 2163 participants in 8 studies were included in this meta-analysis. All included studies were RCTs. The random effects model was used for a meta-analysis of the effects of various intervention measures compared to routine nursing; the outcome was not statistically significant (OR 1.54, 95% CI 0.99-2.38;
Interactive or bidirectional SMS can enhance intervention effects. However, whether mHealth can improve adherence to ART in patients with HIV needs further study. Owing to a lack of the required significant staff time, training, and ongoing supervision, there is still much more to do to apply mHealth to the clinical use of ART for patients living with HIV.
PROSPERO CRD42022358774; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=358774
HIV is a public health issue that every country needs to address. There were an estimated 37.7 million people living with HIV at the end of 2020 [
This paper contains no primary data obtained directly from research participants. Data obtained from previously published resources have been acknowledged with references. Ethical approval was not required.
The review protocol was prospectively registered with PROSPERO (International Prospective Register of Systematic Reviews; CRD42022358774).
This meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines [
The screening process was divided into 2 phases: a preliminary selection by title and abstract and a second phase that screened the full text of the remaining articles. Articles were included based on the following criteria: (1) they reported the results of a randomized controlled trial (RCT); (2) they included HIV-positive persons receiving antiretroviral treatment regardless of age, sex, or nationality; (3) the intervention measures included, but were not limited to, short message service (SMS) texts and voice calls; (4) an mHealth intervention was used in the experimental group with no limits on intervention frequency, time, content, or period and the control group received routine nursing at the same time to help patients improve their treatment compliance; and (5) the primary outcome was adherence to ART. This was measured directly (eg, by pill count) or indirectly (eg, by self-reporting). If the article reported the use of a variety of measurement methods, priority was given to measurement results obtained with the self-report method. The secondary outcome was CD4 cell count.
The exclusion criteria included the following: (1) the study was a duplicate, (2) the study was a systematic review or meta-analysis, (3) the study was missing outcome measures, (4) the experimental group used a variety of interventions, and (5) the control group did not receive routine nursing.
A predesigned Excel sheet was used to extract and organize the data into categories by 2 independent researchers. These data included (1) authors, (2) location, (3) publication date, (4) intervention details (ie, intervention mode and duration), (5) outcome measures, including ART adherence and CD4 cell counts, and (6) risk of bias.
Two of the authors assessed the risk of bias using RevMan (version 5.4; Cochrane Collaboration); the results are summarized in
Risk of bias of the studies included in the meta-analysis. Green indicates a low risk of bias, yellow indicates an unclear risk of bias, and red indicates a high risk of bias.
The meta-analysis was conducted using RevMan. Measures of effect are presented as odds ratios (ORs) with the 95% CI. For continuous data, we calculated the sample-size weighted mean difference (WMD). This meta-analysis was performed using the Mantel-Haenszel method or the inverse variance test. We evaluated heterogeneity with the
The search strategy identified 2783 articles from the electronic databases. In total, 423 articles were excluded because of duplication. We screened the titles and abstracts of the remaining articles and included 26 for full-text review based on the inclusion and exclusion criteria. Of these 26 studies, 8 met the inclusion criteria, and 18 studies were excluded: 15 because they were missing outcome measures, 1 because a variety of interventions were used in the experimental group, and 2 because they did not use routine nursing in the control group. Therefore, 8 studies were selected for the current meta-analysis [
Flow chart of study selection for the meta-analysis.
The characteristics of the studies are summarized in
Characteristics of the included studies. All studies used routine nursing in the control group.
First author, year | Location | Participants, n (age, years) | Recruitment period (duration) | Intervention | Outcome measures |
Ruan, 2017 [ |
Hengyang, China | 100 (≥18) | Mar 2013-Mar 2014 (6 months) | SMSa | ARTb adherence measured by VASc, Community Programs for Clinical Research on AIDS Antiretroviral Medication Self-Report, and CD4 cell count |
Guo, 2018 [ |
South China | 53 (≥18) | Oct 2016-Mar 2017 (3 months) | SMS and WeChat | CD4 cell count |
Shet, 2014 [ |
South India | 631 (18-60) | Jul 2010-Aug 2011 (6 months) | Customized motivational voice call | ART adherence measured by pill count |
Sherman, 2020 [ |
South Florida, US | 94 (>18) | Sept 2011-Apr 2014 (3-6 months) | Automated 1-way medication reminders delivered via SMS | ART adherence measured by VAS and CD4 cell count |
Lester, 2010 [ |
Kenya | 538 (>18) | May 2007-Oct 2008 (12 months) | SMS | ART adherence measured by self-report |
Sabin, 2015 [ |
Guangxi, China | 119 (≥18) | Dec 2012-Apr 2013 (6 months) | SMS | ART adherence measured by a medication device |
Pop-Eleches, 2011 [ |
Kenya | 428 (>18) | Jun 2007-Aug 2008 (3-12 months) | SMS | ART adherence measured by a medication event monitoring system and CD4 cell count |
Mbuagbaw, 2013 [ |
Cameroon | 200 (≥21) | Nov 2010-Dec 2010 (3-6 months) | Weekly standardized motivational text message | VAS and self-reported adherence |
aSMS: short message service.
bART: antiretroviral therapy.
cVAS: visual analog scale.
Adherence to ART was measured as a primary outcome in 7 studies. The method and frequency of measuring adherence varied across the studies. The details are listed in
Forest plot of odds ratios with 95% CIs for the effect of various intervention measures and routine nursing on adherence to antiretroviral therapy. MH: Mantel-Haenszel method.
Six studies were included in a meta-analysis of the effect of SMS on adherence to ART; this showed that SMS could improve adherence (OR 1.76, 95% CI 1.07-2.89;
Forest plot of odds ratios with 95% CIs for the effect of short message service interventions on adherence to antiretroviral therapy. MH: Mantel-Haenszel.
Four studies reported CD4 cell count as a secondary outcome of medication adherence. Combining the differences in CD4 cell count before and after the interventions revealed no statistical heterogeneity among the studies (
Forest plot of pooled odds ratios with 95% CIs for the effect of mHealth interventions on CD4 cell count. IV: inverse variance.
A total of 2163 participants in 8 studies were included in this meta-analysis. The main result of the meta-analysis was that the pooled OR was 1.54. However, the outcome was not statistically significant, and there was considerable heterogeneity among the studies (
A subgroup analysis showed that SMS interventions improved adherence to ART. Further analysis suggested that interactive or bidirectional SMS interventions could enhance intervention effects. This result matches that of a 2014 study [
CD4 cell count and viral load are good indicators of treatment success [
The WHO recommends mHealth strategies for improving ART adherence [
There are several limitations of the current review. The interventions used in the included studies differed in form and frequency. At the same time, these studies used diverse methods for measuring their primary outcomes. This may have produced bias. The robustness and relevance of results increase with the number of distinct outcome measures that show the same result [
Interactive or bidirectional SMS interventions can enhance intervention effects. However, whether mHealth can improve adherence to ART in patients with HIV is a question that needs further study. Owing to a lack of staff time, training, and ongoing supervision, there is still much work to be done to use mHealth in the clinic for ART adherence among patients living with HIV.
Keywords.
antiretroviral therapy
mobile health
odds ratio
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
randomized controlled trial
short message service
visual analog scale
weighted mean difference
This work has been partly supported by the Program for Youth Backbone Teacher Training in University of Henan Province (2019GGJS021), and Science and Technology Project in Henan province in 2018 (182102310201).
None declared.