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Table 3 eHealth and HIV treatment adherence

From: Using eHealth to engage and retain priority populations in the HIV treatment and care cascade in the Asia-Pacific region: a systematic review of literature

Study Country Study design Study Population Sample size (N=) Technology mode Purpose of study Study description Study duration Key outcome assessed of interest in this review Results/Authors’ conclusions
Mobile phone calls or SMS reminders to increase adherence
Huang et al. 2013 China RCT PLHIV on ART
N = 172
Mobile phone call Investigate the effect of a phone call intervention to promote adherence to ART and QoL among PLHIV I=Usual care combined with bi-weekly 3-min reminder phone calls made by trained registered nurse or other health workers
C=Usual care
Both groups included HIV treatment-naive and treatment-experienced HIV patients.
12 weeks Self-reported adherencea
QoL
No significant improvements in adherences rates in the intervention group.
Significant improvements in QoL in the intervention groups for treatment-naïve HIV patients (physical health p = 0.003; level of independence p = 0.018; environment p = 0.002; and spirituality/religion/personal beliefs p = 0.021) at 3 months.
Shet et al. 2014 India RCT PLHIV initiating ART
N = 631
Mobile phone call and SMS reminders Assess whether customised mobile phone reminders would improve adherence I=Standard care and weekly customised, interactive, automated voice reminders, and a pictorial message sent weekly to the participants’ mobile phones
C=Standard care
96 weeks Time to virological failure
ART adherence measured by pill count
No significant effect of the mobile phone intervention on either time to virological failure or ART adherence at the end of two years of therapy.
Swendeman et al. 2015 India Cohort PLHIV
N = 44
IVR system using mobile phones To design, pilot and refine IVR intervention to support ART adherence All subjects received two IVR calls daily, timed to dosing schedules with brief messages on strategies for medical, mental health and nutrition and hygiene. 4 weeks Self reported adherence at baseline and 1 month Self reported missed doses decreased from 39 to 18% at one month (p = 0.005).
Tran et al. 2013 Vietnam Cross sectional PLHIV
N = 1016
Mobile phone reminders Assess ART adherence and its determinants among PLHIV Multi-site cross-sectional survey: Inpatients and outpatients adult PLHIV were interviewed using structured questionnaires N/A Self-reported medication adherence questions
Questions about medication adherence self-efficacy, reasons for missing doses and adherence aids
The main devices used for adherence supports were mobile phone alarms (62.2%).
In multivariate analysis, the use of reminder strategies, such as mobile phone alarms was associated with ≥95% optimal adherence (Coefficient 0.89, 95% CI 0.02 to 1.99, p < 0.05).
Uzma et al. 2011 Pakistan RCT PLHIV initiating ART
N = 76
Mobile phone call reminders Assess the efficacy of interventions for improving adherence to ART regimens I = Routine counselling and weekly phone/mobile phone call reminders
C = Routine counselling
8 weeks Self-reported adherence
Pill identification test; defined as ≥95%
CD4 counts
Viral load
Those in the intervention condition had significantly better self-reported adherence (p < .001) and significantly lower viral load (p = .012).
Biofeedback to improve adherence
Sabin et al. 2010 China RCT PLHIV on ART
N = 64
EDM Determine whether EDM feedback improved ART adherence I=Counselling using EDM feedback
C=No EDM feedback
Both groups included participants assessed 6 months after initiation of treatment as either ‘low adherers’ or ‘high adherers’
12 weeks pre-interventi-on
12 weeks interventi-on
Adherence measured by EDM; defined as ≥95%
Markers of disease progression
At month 12 intervention, mean adherence had risen significantly (p = 0.003) among intervention subjects to 96.5% but remained unchanged in controls. The mean CD4 count rose by 90 cells/μl and declined by 9 cells/μl among intervention and control subjects, respectively.
Sabin et al. 2015 China RCT PLHIV
N = 119
EDM including real time wireless medication communicator Determine whether EDM feedback improved ART adherence Subjects with optimal and suboptimal adherence randomised to intervention or control arms.
I=Individualised SMS mobile phone reminders triggered by late dose taking, and data-informed counselling.
C=No reminders, standard adherence counselling
12 weeks pre-interventi-on
24 weeks interventi-on
Adherence measured by EDM; defined as ≥95%
Markers of disease progression
At last intervention month, the proportion of optimal adheres was significantly higher in I group 87.3% vs. 51.8% (RR for optimal adherence in month 9, I vs. C, 1.69; CI: 1.29 to 2.21, p < 0.001).
The mean adherence during intervention period was significantly higher in I group (I vs. C: 96.3% vs.
88.9%, p < 0.001).
Post intervention clinical outcomes not significant.
Perera et al. 2014 New Zealand RCT PLHIV on ART
N = 28
Smartphone app Examine the efficacy of a smartphone application incorporating personalised health-related visual imagery to improve adherence to ART. I = 24-h medication clock and augmented version of the smartphone app which comprised a daily real-time graphical representations of the current estimated plasma concentrations of antiretroviral drugs and simulation of protection against HIV
C = standard version of the smartphone app which comprised a 24-h medication clock displaying daily ART dosing schedule and allowed participants to record when they had taken their medications each day
12 weeks Viral load
Self-reported adherence
Pharmacy dispensing records
Participants in the intervention group showed a significantly higher level of self-reported adherence to ART at 3 months (p = 0.03) and decreased viral load (p = 0.023).
Greater usage of the extra components of the augmented application was associated with greater perceived understanding of HIV infection and increased perceived necessity for ART.
  1. aGood adherence was defined as 95% or greater