Cell Phone-Based and Adherence Device Technologies for HIV Care and Treatment in Resource-Limited Settings: Recent Advances

Campbell, Jeffrey I.; Haberer, Jessica

doi:10.1007/s11904-015-0282-8

Cited by 24 publications

(29 citation statements)

References 52 publications

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“…A rapid increase in access to mobile phones in resource-limited settings (RLS) has been accompanied by the proliferation of research and clinical programs leveraging mobile technologies to address structural barriers to healthcare delivery 2 . Many of these programs have focused on people living with HIV (PLWH) 3 . Despite this growing body of work, most mobile health (mHealth) programs in RLS do not move beyond the pilot testing phase 4 .…”

Section: Introductionmentioning

confidence: 99%

“…Although these models have been employed to understand mHealth acceptability and guide technology development among PLWH 23,24 , they do not focus on the unique social, cultural and behavioral factors specific to low-literacy populations in RLS, such as resistance to new technologies 25 and limited familiarity with electronic devices 26 . Furthermore, despite an abundance of literature evaluating efficacy of mHealth for HIV care in research settings 27 , existing technology acceptance models were not designed to account for the social factors related to HIV and other stigmatized disease states that are often the target of novel mHealth interventions in RLS 3,27,28 . Consequently, there is an important need to better define the behavioral frameworks that describe contributions to technology acceptance, in order to optimize design and implementation of efficacious mHealth interventions in RLS.…”

Section: Introductionmentioning

confidence: 99%

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The Technology Acceptance Model for Resource-Limited Settings (TAM-RLS): A Novel Framework for Mobile Health Interventions Targeted to Low-Literacy End-Users in Resource-Limited Settings

et al. 2017

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Background Although mobile health (mHealth) technologies have shown promise in improving clinical care in resource-limited settings (RLS), they are infrequently brought to scale. One limitation to the success of many mHealth interventions is inattention to end-user acceptability, which is an important predictor of technology adoption. Methods We conducted in-depth interviews with 43 people living with HIV in rural Uganda who had participated in a clinical trial of a short messaging system (SMS)-based intervention designed to prompt return to clinic after an abnormal laboratory test. Interviews focused on established features of technology acceptance models, including perceived ease of use and perceived usefulness, and included open-ended questions to gain insight into unexplored issues related to the intervention’s acceptability. We used conventional (inductive) and direct content analysis to derive categories describing use behaviors and acceptability. Results Interviews guided development of a proposed conceptual framework, the technology acceptance model for resource-limited settings (TAM-RLS). This framework incorporates both classic technology acceptance model categories as well as novel factors affecting use in this setting. Participants described how SMS message language, phone characteristics, and experience with similar technologies contributed to the system’s ease of use. Perceived usefulness was shaped by the perception that the system led to augmented HIV care services and improved access to social support from family and colleagues. Emergent themes specifically related to mHealth acceptance among PLWH in Uganda included 1) the importance of confidentiality, disclosure, and stigma, and 2) the barriers and facilitators downstream from the intervention that impacted achievement of the system’s target outcome. Conclusion The TAM-RLS is a proposed model of mHealth technology acceptance based upon end-user experiences in rural Uganda. Although the proposed model requires validation, the TAM-RLS may serve as a useful tool to guide design and implementation of mHealth interventions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Technology Acceptance Model for Resource-Limited Settings (TAM-RLS): A Novel Framework for Mobile Health Interventions Targeted to Low-Literacy End-Users in Resource-Limited Settings

et al. 2017

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“…Objective measures of adherence that do not rely on self-report are attractive in not being subject to reporting bias and as such they have potential for routine use as a means of informing and targeting interventions to improve adherence. Objective adherence measurement approaches include recording of on-time drug pick-up and electronic monitors of adherence [3–7]. This latter might consist of a device that enables clinic staff to read out the adherence history of the patient since the last clinic visit [3,4], or perhaps even monitoring of adherence in real time using mobile phone technology [3, 8, 9].…”

Section: Introductionmentioning

confidence: 99%

“…Objective adherence measurement approaches include recording of on-time drug pick-up and electronic monitors of adherence [3–7]. This latter might consist of a device that enables clinic staff to read out the adherence history of the patient since the last clinic visit [3,4], or perhaps even monitoring of adherence in real time using mobile phone technology [3, 8, 9]. Real time monitoring means there is the potential to react rapidly to missed doses to prevent default from care and reduce the risk of resistance development.…”

Section: Introductionmentioning

confidence: 99%

Cost Effectiveness of Potential ART Adherence Monitoring Interventions in Sub-Saharan Africa

Phillips¹,

Cambiano²,

Nakagawa³

et al. 2016

PLoS ONE

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BackgroundInterventions based around objective measurement of adherence to antiretroviral drugs for HIV have potential to improve adherence and to enable differentiation of care such that clinical visits are reduced in those with high adherence. It would be useful to understand the approximate upper limit of cost that could be considered for such interventions of a given effectiveness in order to be cost effective. Such information can guide whether to implement an intervention in the light of a trial showing a certain effectiveness and cost.MethodsAn individual-based model, calibrated to Zimbabwe, which incorporates effects of adherence and resistance to antiretroviral therapy, was used to model the potential impact of adherence monitoring-based interventions on viral suppression, death rates, disability adjusted life years and costs. Potential component effects of the intervention were: enhanced average adherence when on ART, reduced risk of ART discontinuation, and reduced risk of resistance acquisition. We considered a situation in which viral load monitoring is not available and one in which it is. In the former case, it was assumed that care would be differentiated based on the adherence level, with fewer clinic visits in those demonstrated to have high adherence. In the latter case, care was assumed to be primarily differentiated according to viral load level. The maximum intervention cost required to be cost effective was calculated based on a cost effectiveness threshold of $500 per DALY averted.FindingsIn the absence of viral load monitoring, an adherence monitoring-based intervention which results in a durable 6% increase in the proportion of ART experienced people with viral load < 1000 cps/mL was cost effective if it cost up to $50 per person-year on ART, mainly driven by the cost savings of differentiation of care. In the presence of viral load monitoring availability, an intervention with a similar effect on viral load suppression was cost-effective when costing $23-$32 per year, depending on whether the adherence intervention is used to reduce the level of need for viral load measurement.ConclusionThe cost thresholds identified suggest that there is clear scope for adherence monitoring-based interventions to provide net population health gain, with potential cost-effective use in situations where viral load monitoring is or is not available. Our results guide the implementation of future adherence monitoring interventions found in randomized trials to have health benefit.

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“…If so, is such pressure ethically unacceptable when it improves medical adherence and health? Electronic adherence monitors (EAMs) take many forms, including pill bottles that transmit the timing of bottle openings 1 , pills that indicate ingestion 2 , and drug metabolite detectors 3 . As a host of new EAMs have become available, questions about potential autonomy effects of these devices impact the ethics of their use and may guide further device development, as well as the studies that use them.…”

Section: Introductionmentioning

confidence: 99%

Ugandan Study Participants Experience Electronic Monitoring of Antiretroviral Therapy Adherence as Welcomed Pressure to Adhere

et al. 2018

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Many new technologies monitor patients' and study participants' medical adherence. Some have cautioned that these devices transgress personal autonomy and ethics. But do they? This qualitative study explored how Ugandan study participants perceive the effect of electronic monitoring of their adherence to antiretroviral therapy (ART) on their freedoms to be non-adherent and pursue other activities that monitoring may inadvertently expose. Between August 2014 and June 2015, we interviewed 60 Ugandans living with HIV and enrolled in the Uganda AIDS Rural Treatment Outcomes (UARTO) study, a longitudinal, observational study involving electronic adherence monitors (EAMs) to assess ART adherence. We also interviewed 6 UARTO research assistants. Both direct and indirect content analysis were used to interpret interview transcripts. We found that monitoring created a sense of pressure to adhere to ART, which some participants described as "forcing" them to adhere. However, even participants who felt that monitoring forced them to take medications perceived using the EAM as conducive to their fundamental goal of high ART adherence. Overall, even if monitoring may have limited participants' effective freedom to be non-adherent, participants welcomed any such effect. No participant rejected the EAM on the grounds that it would limit that effective freedom. Reports that monitoring altered behaviors unrelated to pill-taking were rare. Researchers should continue to be vigilant about the ways in which behavioral health monitoring affects autonomy, but should also recognize that even autonomy-limiting monitoring strategies may enable participants to achieve their own goals.

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Cell Phone-Based and Adherence Device Technologies for HIV Care and Treatment in Resource-Limited Settings: Recent Advances

Cited by 24 publications

References 52 publications

The Technology Acceptance Model for Resource-Limited Settings (TAM-RLS): A Novel Framework for Mobile Health Interventions Targeted to Low-Literacy End-Users in Resource-Limited Settings

The Technology Acceptance Model for Resource-Limited Settings (TAM-RLS): A Novel Framework for Mobile Health Interventions Targeted to Low-Literacy End-Users in Resource-Limited Settings

Cost Effectiveness of Potential ART Adherence Monitoring Interventions in Sub-Saharan Africa

Ugandan Study Participants Experience Electronic Monitoring of Antiretroviral Therapy Adherence as Welcomed Pressure to Adhere

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