Table 3 eHealth and HIV treatment adherence
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. |