Evidence map›Paper›PMID 31621641›Full record

SynthesisJMIR mHealth and uHealth2019

Electronic Health Interventions to Improve Adherence to Antiretroviral Therapy in People Living With HIV: Systematic Review and Meta-Analysis.

Ziqi Wang, Yaxin Zhu, Liyuan Cui, Bo Qu

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 9 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 9 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Trial
  11. Trial
  12. Trial
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ziqi WangSchool of Public Health, China Medical University, Shenyang, China.ORCID 0000-0001-7324-5808
Yaxin ZhuSchool of Public Health, China Medical University, Shenyang, China.ORCID 0000-0001-8779-4218
Liyuan CuiSchool of Medical Informatics, China Medical University, Shenyang, China.ORCID 0000-0002-1831-0379
Bo QuSchool of Public Health, China Medical University, Shenyang, China.ORCID 0000-0003-2526-9690

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElectronic health (eHealth) is increasingly used for self-management and service delivery of HIV-related diseases. With the publication of studies increasingly focusing on antiretroviral therapy (ART) adherence, this makes it possible to quantitatively and systematically assess the effectiveness and feasibility of eHealth interventions.

objectiveThe purpose of this review was to explore the effectiveness of eHealth interventions on improving ART adherence in people living with HIV. The effects of different intervention characteristics, participant characteristics, and study characteristics were also assessed.

methodsWe systematically searched MEDLINE (via PubMed), EMBASE, the Cochrane Central Register of Controlled Trials, and 3 conference abstract databases using search terms related to HIV, ART, adherence, and eHealth interventions. We independently screened the studies, extracted the data, and assessed the study quality and then compared the information in pairs. Articles published in English that used randomized controlled trials to assess eHealth interventions to improve ART adherence of people living with HIV were identified. We extracted the data including study characteristics, participant characteristics, intervention characteristics, and outcome measures. The Cochrane risk-of-bias tool was used to assess the risk of bias and study overall quality. Odds ratios, Cohen d, and their 95% CIs were estimated using random-effects models. We also performed multiple subgroup analyses and sensitivity analyses to define any sources of heterogeneity.

resultsAmong 3941 articles identified, a total of 19 studies (including 21 trials) met the inclusion criteria. We found 8 trials from high-income countries and 13 trials from low- and middle-income countries. Furthermore, at baseline, the health status of participants in 14 trials was healthy. Of the trials included, 7 of 21 used personality content, 12 of 21 used a 2-way communication strategy, and 7 of 21 used medical content. In the pooled analysis of 3937 participants (mean age: 35 years; 47.16%, 1857/3937 females), eHealth interventions significantly improved the ART adherence of people living with HIV (pooled Cohen d=0.25; 95% CI 0.05 to 0.46; P=.01). The interventions were also correlated with improved biochemical outcomes reported by 11 trials (pooled Cohen d=0.25; 95% CI 0.11 to 0.38; P<.001). The effect was sensitive to sample size (Q=5.56; P=.02) and study duration (Q=8.89; P=.003), but it could not be explained by other moderators. The primary meta-analysis result was stable in the 3 sensitivity analyses.

conclusionsSome of the eHealth interventions may be used as an effective method to increase the ART adherence of people living with HIV. Considering that most of the trials included a small sample size and were conducted for a short duration, these results should be interpreted with caution. Future studies need to determine the features of eHealth interventions to better improve ART adherence along with long-term effectiveness of interventions, effectiveness of real-time adherence monitoring, enhancement of study design, and influences on biochemical outcomes.

Indexed as

AdultAnti-Retroviral AgentsChinaElectronic Health RecordsFemaleHIV InfectionsHumansMaleMedication AdherenceAnti-Retroviral AgentseHealthhighly active antiretroviral therapyHIVmedication adherence

Identifiers

PMID31621641
PMCPMC6913542

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.