Implementation Of mHealth Interventions Research Articles

Enhancing the Implementation and Integration of mHealth Interventions in Resource-Limited Settings: A Scoping Review.

Although mobile health (mHealth) interventions have shown promise in improving health outcomes, most of them rarely translate to scale. Prevailing mHealth studies are largely small-sized, short-term and donor-funded pilot studies with limited evidence on their effectiveness. To facilitate scale-up, several frameworks have been proposed to enhance the generic implementation of health interventions. However, there is a lack of a specific focus on the implementation and integration of mHealth interventions in routine care in low-resource settings. Our scoping review aimed to synthesize and develop a framework that could guide the implementation and integration of mHealth interventions. We searched the PubMed, Google Scholar, and ScienceDirect databases for published theories, models, and frameworks related to the implementation and integration of clinical interventions from 1st January 2000 to 31st December 2023. The data processing was guided by a scoping review methodology proposed by Arksey and O'Malley. Studies were included if they were i) peer-reviewed and published between 2000 and 2023, ii) explicitly described a framework for clinical intervention implementation and integration, or iii) available in full text and published in English. We integrated different domains and constructs from the reviewed frameworks to develop a new framework for implementing and integrating mHealth interventions. We identified eight eligible papers with eight frameworks composed of 102 implementation domains. None of the identified frameworks were specific to the integration of mHealth interventions in low-resource settings. Two constructs (skill impartation and intervention awareness) related to the training domain, four constructs (technical and logistical support, identifying committed staff, supervision, and redesigning) from the restructuring domain, two constructs (monetary incentives and nonmonetary incentives) from the incentivize domain, two constructs (organizational mandates and government mandates) from the mandate domain and two constructs (collaboration and routine workflows) from the integrate domain. Therefore, a new framework that outlines five main domains-train, restructure, incentivize, mandate, and integrate (TRIMI)-in relation to the integration and implementation of mHealth interventions in low-resource settings emerged. The TRIMI framework presents a realistic and realizable solution for the implementation and integration deficits of mHealth interventions in low-resource settings.

Does mHealth suitable for the Indian population? analysing criticisms and possibilities

India is the second-largest country globally in terms of population, with two-thirds of the population living in rural areas. India has made a significant pace in improving the overall health scenario even with several existing hurdles like vast geographical area, lack of quality transport facilities, high population density and nutrition, illiteracy, and poverty in the past decade. India has an exponential increase in mobile phones that have covered a substantially higher number of rural households. Even though technological innovations, especially mHealth platforms, are growing in developing countries like India, it faces many criticisms. This paper aims to analyse whether mHealth is a potential tool for the Indian population or not. mHealth interventions can be used in different domains to improve the performance of health workers, such as data collection and reporting, decision support and training, emergency referrals, alerts and reminders and supervision and interaction with other members of the healthcare system. It also helps the health system manage the problem of healthcare personnel absenteeism and can be used as an alternative to telemedicine. However, mHealth apps may not be broad enough to provide a healthy environment that enables individuals and populations to adopt a healthy life. Our study highlights the importance of integrating beneficiary-specific factors in developing mHealth interventions. The pathways linking access to, and use of, mobile services with healthcare utilisation need an in-depth study to ensure effective planning, designing and implementation of mHealth interventions.

Towards a Framework on the Use of Infomediaries in Maternal mHealth in Rural Malawi

Aim/Purpose: The aim of the study is to explore factors that affect how healthcare clients in rural areas use infomediaries in maternal mHealth interventions. The study focuses on maternal healthcare clients who do not own mobile phones but use the mHealth intervention. Background: Maternal mHealth interventions in poor-resource settings are bedevilled by inequalities in mobile phone ownership. Clients who do not own mobile phones risk being excluded from benefiting from the interventions. Some maternal mHealth providers facilitate the access of mobile phones for those who do not own them using “infomediaries”. Infomediaries, in this case, refer to individuals who have custody of mobile phones that other potential beneficiaries may use. However, the use of infomediaries to offer access to the “have nots” may be influenced by a number of factors. Methodology: The study uses a case of a maternal mHealth intervention project in Malawi, as well as a qualitative research method and interpretive paradigm. Data was collected using secondary data from the implementing agency, semi-structured interviews, and focus group discussions. Empirical data was collected from maternal healthcare clients who do not own mobile phones and infomediaries. Data were analysed inductively using thematic analysis. Contribution: The study proposed a theoretical framework for studying infomediaries in ICT4D. The study may inform mHealth designers, implementers, and policymakers on how infomediaries could be implemented in a rural setting. Consequently, understanding the factors that affect the use of infomediaries may inform mHealth intervention implementers on how they could overcome the challenges by implementing mHealth interventions that reduce the challenges on the mHealth infomediaries side, and the maternal healthcare clients’ side. Findings: Characteristics of the maternal healthcare client, characteristics of the mHealth infomediary, perceived value of mHealth intervention, and socio-environmental factors affect maternal healthcare clients’ use of mHealth infomediaries. Recommendations for Practitioners: Implementers of interventions ought to manage the use of infomediaries to avoid volunteer fatigue and infomediaries who may not be compatible with the potential users of the intervention. Implementers could leverage traditional systems of identifying and using infomediaries instead of reinventing the wheel. Recommendation for Researchers: This research adopted a single case study to develop the theoretical framework for mHealth infomediary use. We recommend future studies are conducted in order to test and develop this framework further, not only in ICT4D, but also in other areas of application. Impact on Society: People still lack access. The lack of ownership of technology may still exclude them from participating in an information society. The use of infomediaries may help to provide access to technologies to those who do not have them thereby bridging the digital divide gap. Future Research: We propose herein that traditional systems may offer a good starting point for designing a system that would work for communities. We, therefore, recommend that future research may explore these possibilities.

Geographical variation in mobile phone ownership and SMS literacy among women (age 15–49) in India: A cross-sectional analysis based on National Family Health Survey-4

In India, studies on mobile phone ownership and digital literacy have focused on the gender dimension, perspectives of women and men towards mobile phone use, and socio-economic determinants of ownership. There are no studies with a large sample size that present the variation in mobile phone ownership and ability to read short message services (SMS) message among women across different geographic levels. We use multilevel models to estimate the contribution of geographic levels in explaining the variation in mobile phone ownership and SMS literacy. The data from the fourth round of National Family Health Survey (NFHS) which collected information on health and nutrition indicators was used for our analysis. 122,351 women were interviewed about mobile phone ownership and SMS literacy. Information on mobile phone ownership and ability to read text messages were used to create the dependent variables. The independent variables included women's education, age, religion, social class, wealth quintile and place of residence. Two and four level variants of a multilevel model, with individuals (level-1) nested within primary sampling unit (level 2), districts (level 3) and States (level 4), were used to estimate the probability of mobile phone ownership and ability to read text message. The results from multilevel model and variance partition analysis indicate that contribution of State and primary sampling unit towards explaining variation in mobile phone ownership and ability to read text message is greater than the districts. The variance estimates are sensitive to the number of levels included in the multilevel model, so relying on estimates obtained for a particular level could lead to a bias. Our findings suggest that understanding the magnitude of inequalities at different geographic levels should be warranted more attention before tackling the socio-economic factors. State estimates should be supplemented with information available for lower geographic levels. It is important to identify the geographical clusters with high and low coverage of mobile ownership and ability to read text messages before implementing mhealth interventions.

An Interactive Text Messaging Intervention to Improve Adherence to Option B+ Prevention of Mother-to-Child HIV Transmission in Kenya: Cost Analysis.

BackgroundMobile health (mHealth) approaches offer potentially affordable ways to support the care of HIV-infected patients in overstretched health care systems. However, only few studies have analyzed the costs associated with mHealth solutions for HIV care.ObjectiveThe aim of this study was to estimate the total incremental costs and incremental cost per beneficiary of an interactive SMS text messaging support intervention within a clinical trial.MethodsThe Mobile WAChX trial (NCT02400671) evaluates an interactive semiautomated SMS text messaging intervention to improve adherence to antiretroviral therapy and retention in care among peripartum women infected with HIV in Kenya to reduce the mother-to-child transmission of HIV. Women were randomized to receive one-way versus two-way SMS text messages. Messages were sent weekly, and these messages included motivational and educational content and visit reminders; two-way messaging enabled prompt consultation with the nurse as needed. Microcosting methods were used to collect resource-use data related to implementing the Mobile WAChX SMS text messaging intervention. At 2 sites (Nairobi and Western Kenya), we conducted semistructured interviews with health personnel to identify startup and recurrent activities by obtaining information on the personnel, supplies, and equipment. Data on expenditures and prices from project expense reports, administrative records, and published government salary data were included to estimate the total incremental costs. Using a public provider perspective, we estimated incremental unit costs per beneficiary and per contact during 2017.ResultsThe weighted average annual incremental costs for the two-way SMS text messaging group were US $3725 per facility, US $62 per beneficiary, and US $0.85 per contact to reach 115 beneficiaries. For the one-way SMS text messaging group, the weighted average annual incremental costs were US $2542 per facility, US $41 per beneficiary, and US $0.66 per contact to reach 117 beneficiaries. The largest cost shares were for the personnel: 48.2% (US $1794/US $3725) in two-way and 32.4% (US $825/US $2542) in one-way SMS text messaging groups. Costs associated with software development and communication accounted for 29.9% (US $1872/US $6267) of the costs in both intervention arms (US $1042 vs US $830, respectively).ConclusionsCost information for budgeting and financial planning is relevant for implementing mHealth interventions in national health plans. Given the proportion of costs related to systems development, it is likely that costs per beneficiary will decline with the scale-up of the interventions.

Perceived barriers and facilitators in using text and voice messaging for improving HIV and sexual and reproductive health of female entertainment workers in Cambodia: a qualitative study.

Female entertainment workers (FEWs) in Cambodia are one of the hard-to-reach populations at risk of human immunodeficiency virus (HIV) and poor sexual and reproductive health (SRH). Due to the stigmatizing nature of their work, it is difficult to reach them with prevention and treatment services. The Mobile Link project is a mobile health (mHealth) intervention that aims to deliver health messages to FEWs and link them up to health services. This study aims to explore the perspectives of stakeholders on the Mobile Link and identify barriers and facilitators to the project implementation, in order to determine areas for improvement of future mHealth interventions. This study was conducted between November to December 2018 in the capital city and other three provinces where the Mobile Link was implemented. We employed a qualitative research design using an interpretative approach. A purposive sampling method was used to recruit participants across four project sites. All participants were stakeholders involved directly or indirectly with the Mobile Link. Nine different groups of stakeholders at the national, non-governmental organizations, community, and individual levels were recruited. Seventeen semi-structured in-depth interviews (IDIs) and five focus group discussions (FGDs) were conducted and transcribed. Data were managed using NVivo 12 and analysed using thematic analysis with an inductive approach. We derived four major themes: (I) perceived benefits, (II) attitudes, (III) access, and (IV) enabling environment. Different levels of stakeholders reported on the perceived benefits of the Mobile Link, including ease of use, knowledge gained, link to services, and cost-effectiveness. Perceived benefits and enabling environment were identified as facilitators to implementation of the project. Barriers included technological issues, operational challenges, poor rapport with entertainment establishment owners, and low motivation to participate in the Mobile Link among FEWs. The Mobile Link has many advantages and is well-accepted by stakeholders from the national and community levels. We discussed the implications of the perceived facilitators and barriers identified on the project and mHealth interventions. Implications discussed should be taken into consideration by organizations implementing mHealth interventions for HIV key populations in Cambodia as well as in other resource-limited settings.

Evaluating Network Readiness for mHealth Interventions Using the Beacon Mobile Phone App: Application Development and Validation Study.

BackgroundMobile health (mHealth) interventions have the potential to transform the global health care landscape. The processing power of mobile devices continues to increase, and growth of mobile phone use has been observed worldwide. Uncertainty remains among key stakeholders and decision makers as to whether global health interventions can successfully tap into this trend. However, when correctly implemented, mHealth can reduce geographic, financial, and social barriers to quality health care.ObjectiveThe aim of this study was to design and test Beacon, a mobile phone–based tool for evaluating mHealth readiness in global health interventions. Here, we present the results of an application validation study designed to understand the mobile network landscape in and around Macha, Zambia, in 2019.MethodsBeacon was developed as an automated mobile phone app that continually collects spatiotemporal data and measures indicators of network performance. Beacon was used in and around Macha, Zambia, in 2019. Results were collected, even in the absence of network connectivity, and asynchronously uploaded to a database for further analysis.ResultsBeacon was used to evaluate three mobile phone networks around Macha. Carriers A and B completed 6820/7034 (97.0%) and 6701/7034 (95.3%) downloads and 1349/1608 (83.9%) and 1431/1608 (89.0%) uploads, respectively, while Carrier C completed only 62/1373 (4.5%) file downloads and 0/1373 (0.0%) file uploads. File downloads generally occurred within 4 to 12 seconds, and their maximum download speeds occurred between 2 AM and 5 AM. A decrease in network performance, demonstrated by increases in upload and download durations, was observed beginning at 5 PM and continued throughout the evening.ConclusionsBeacon was able to compare the performance of different cellular networks, show times of day when cellular networks experience heavy loads and slow down, and identify geographic “dead zones” with limited or no cellular service. Beacon is a ready-to-use tool that could be used by organizations that are considering implementing mHealth interventions in low- and middle-income countries but are questioning the feasibility of the interventions, including infrastructure and cost. It could also be used by organizations that are looking to optimize the delivery of an existing mHealth intervention with improved logistics management.

Implementing mHealth Interventions in a Resource-Constrained Setting: Case Study From Uganda.

BackgroundMobile health (mHealth) interventions are becoming more common in low-income countries. Existing research often overlooks implementation challenges associated with the design and technology requirements of mHealth interventions.ObjectiveWe aimed to characterize the challenges that we encountered in the implementation of a complex mHealth intervention in Uganda.MethodsWe customized a commercial mobile survey app to facilitate a two-arm household-randomized, controlled trial of home-based tuberculosis (TB) contact investigation. We incorporated digital fingerprinting for patient identification in both study arms and automated SMS messages in the intervention arm only. A local research team systematically documented challenges to implementation in biweekly site visit reports, project management reports, and minutes from biweekly conference calls. We then classified these challenges using the Consolidated Framework for Implementation Research (CFIR).ResultsWe identified challenges in three principal CFIR domains: (1) intervention characteristics, (2) inner setting, and (3) characteristics of implementers. The adaptability of the app to the local setting was limited by software and hardware requirements. The complexity and logistics of implementing the intervention further hindered its adaptability. Study staff reported that community health workers (CHWs) were enthusiastic regarding the use of technology to enhance TB contact investigation during training and the initial phase of implementation. After experiencing technological failures, their trust in the technology declined along with their use of it. Finally, complex data structures impeded the development and execution of a data management plan that would allow for articulation of goals and provide timely feedback to study staff, CHWs, and participants.ConclusionsmHealth technologies have the potential to make delivery of public health interventions more direct and efficient, but we found that a lack of adaptability, excessive complexity, loss of trust among end users, and a lack of effective feedback systems can undermine implementation, especially in low-resource settings where digital services have not yet proliferated. Implementers should anticipate and strive to avoid these barriers by investing in and adapting to local human and material resources, prioritizing feedback from end users, and optimizing data management and quality assurance procedures.Trial RegistrationPan-African Clinical Trials Registration PACTR201509000877140; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=877

4056 Dementia family caregivers’ mobile app use and intention to adopt mHealth apps

OBJECTIVES/GOALS: To describe preliminary results of Alzheimer’s and dementia caregivers’ (CGs) mobile app use and intention to adopt mHealth apps for their own chronic condition self-management. To discuss implications for designing and implementing mHealth interventions for CGs. METHODS/STUDY POPULATION: This study aims to recruit 110 racially and ethnically diverse family caregivers (CGs) who have a chronic condition, provide care for persons with Alzheimer’s disease or related dementias, and have access to a mobile device. This is a cross-sectional correlational study collecting data with computer-assisted telephone interviews stored through REDCap. The study survey was created using existing surveys about mobile app use; relevant, well-validated research instruments; and questions from the U.S. Census and other national surveys. CGs are being actively recruited from the Baltimore-Washington metropolitan area using various recruitment strategies that have been effective in prior studies. RESULTS/ANTICIPATED RESULTS: The majority of CGs used websites (86%), mobile devices (68%) or apps (53%) to manage their own health. CGs using health-related apps were tracking their exercise (60%), diet (60%), medical records (50%), and physical health measures (50%). More than 4 out of 5 (82%) predicted they would use mobile apps to self-manage their chronic condition, though only 68% actually planned to use them. 86% of CGs were using mobile apps for non-health related purposes, with the most popular app being weather (90%), followed by social media (74%), music/entertainment (68%), and banking/business apps (63%). CGs used weather and social media apps most often (2 or more times/day) and spent 9 hours/week on apps. DISCUSSION/SIGNIFICANCE OF IMPACT: Websites and mobile apps appear to be feasible modes to deliver health interventions to CGs. Researchers should consider including features of apps most frequently used by CGs, such as the weather, ways to connect with others, and music/entertainment, when delivering mHealth interventions to CGs.

Can Mobile Health Improve Depression Treatment Access and Adherence Among Rural Indian Women? A Qualitative Study.

Major Depressive Disorder (MDD) is associated with low rates of treatment and medication non-adherence, more so in low- and middle-income countries (LMICs). Mobile mental health (mHealth) interventions offer promise as a tool to address these problems. However, the feasibility and acceptability of mHealth interventions among rural women in LMICs is unknown. We examined barriers to accessing mental health treatment, reasons for non-adherence, and attitudes towards mHealth solutions among women with MDD in rural south India. Six focus groups were conducted among women with MDD (n = 69) who had been in treatment at a rural community health center. The discussion was transcribed and analyzed using a modified grounded-theory approach. Women perceived limited autonomy within their family structure, and experienced financial and systemic barriers as contributing to poor treatment access and non-adherence. Illiteracy, limited personal access to mobile phones, and preference for in-person clinical consultation were identified as barriers to use of mHealth. This is the first qualitative study, to our knowledge, that examines attitude towards mHealth among women with MDD in a rural setting in India. The study identified contextual barriers that will be important to address before implementing mHealth interventions.

Efficacy of Acceptance and Commitment Therapy in Daily Life (ACT-DL) in early psychosis: study protocol for a multi-centre randomized controlled trial

BackgroundPsychotic experiences, social functioning and general psychopathology are important targets for early intervention in individuals with Ultra-High-Risk state (UHR) and a first-episode psychosis (FEP). Acceptance and Commitment Therapy (ACT) is a promising, next-generation Cognitive Behavioural Therapy (CBT) that aims to modify these targets, but evidence on sustainable change and its underlying mechanisms in individuals’ daily lives remains limited. The aim of the INTERACT study is to investigate the efficacy of a novel ecological momentary intervention, Acceptance and Commitment Therapy in Daily Life (ACT-DL) in a multi-centre randomised controlled trial of individuals with UHR or FEP.Methods/designIn a multi-centre randomised controlled trial, individuals aged 16–65 years with UHR or FEP will be randomly allocated to ACT-DL in addition to treatment as usual (TAU) as the experimental condition or a control condition of TAU only, which will include – for the entire study period – access to routine mental health care and, where applicable, CBT for psychosis (CBTp). Outcomes will be assessed at baseline (i.e. before randomisation), post-intervention (i.e. after the 8-week intervention period), and 6-month and 12-month follow-ups (i.e. 6 and 12 months after completing the intervention period) by blinded assessors. The primary outcome will be distress associated with psychotic experiences, while secondary outcomes will include (momentary) psychotic experiences, social functioning and psychopathology. Process measures to assess putative mechanisms of change will include psychological flexibility, stress sensitivity and reward experiences. In addition, acceptability, treatment adherence and treatment fidelity of ACT-DL will be assessed.DiscussionThe current study is the first to test the efficacy of ACT-DL in individuals with UHR and FEP. If this trial demonstrates the efficacy of ACT-DL, it has the potential to significantly advance the treatment of people with UHR and FEP and, more generally, provides initial support for implementing mHealth interventions in mental health services.Trial registrationNetherlands Trial Register, ID: NTR4252. Registered on 26 September 2013.

Targeting strategies of mHealth interventions for maternal health in low and middle-income countries: a systematic review protocol

IntroductionRecently, there has been a steady increase in mobile health (mHealth) interventions aimed at improving maternal health of women in low-income and middle-income countries. While there is evidence indicating that...

Listen before you leap: Sri Lankan health professionals' perspectives on m-health.

Given the increasingly widespread use of mobile phones in the developing world, the application of this technology for healthcare (also referred to as m-health) has tremendous potential. However, there is a need for more research on factors that influence the sustainable and scalable adoption of m-health in developing countries. To fill this gap, in this study, drawing on the theory of diffusion of innovation, we conducted in-depth interviews with 29 health professionals in Sri Lanka to understand their views on the benefits and barriers to adopting m-health. Participants had mixed views on the adoption of this technology. Reasons for m-health adoption included efficiency and usefulness in emergency situations. Barriers to adoption included risks for miscommunication/misinterpretation and lack of systems/policies for implementing m-health technology. With regard to the innovation-decision process, most participants appear to be in the stages of "persuasion" and "decision"; with regard to degree of innovativeness, interviewees comprise a mix of "early adopters" and "laggards." Assuming mobile health apps afford improvements in health outcomes for developing countries, contextual factors in each national setting should inform design and implementation of m-health interventions.

Challenges in implementing mHealth interventions: a technical perspective.

Over the years, the healthcare community has witnessed many improvements in methods and technologies used in healthcare delivery, including mHealth as an emerging area of healthcare applications to improve access to health services. However, challenges involved in implementing mHealth to optimal advantage do exist. In this article, we identify some of the most important challenges and propose feasible solutions.

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.

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. 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. 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. 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.

Factors associated with patterns of mobile technology use among persons who inject drugs

ABSTRACTBackground: New and innovative methods of delivering interventions are needed to further reduce risky behaviors and increase overall health among persons who inject drugs (PWID). Mobile health (mHealth) interventions have potential for reaching PWID; however, little is known about mobile technology use (MTU) in this population. In this study, the authors identify patterns of MTU and identified factors associated with MTU among a cohort of PWID. Methods: Data were collected through a longitudinal cohort study examining drug use, risk behaviors, and health status among PWID in San Diego, California. Latent class analysis (LCA) was used to define patterns of MTU (i.e., making voice calls, text messaging, and mobile Internet access). Multinomial logistic regression was then used to identify demographic characteristics, risk behaviors, and health indicators associated with mobile technology use class. Results: In LCA, a 4-class solution fit the data best. Class 1 was defined by low MTU (22%, n = 100); class 2, by PWID who accessed the Internet using a mobile device but did not use voice or text messaging (20%, n = 95); class 3, by primarily voice, text, and connected Internet use (17%, n = 91); and class 4, by high MTU (41%, n = 175). Compared with low MTU, high MTU class members were more likely to be younger, have higher socioeconomic status, sell drugs, and inject methamphetamine daily. Conclusion: The majority of PWID in San Diego use mobile technology for voice, text, and/or Internet access, indicating that rapid uptake of mHealth interventions may be possible in this population. However, low ownership and use of mobile technology among older and/or homeless individuals will need to be considered when implementing mHealth interventions among PWID.

Perceptions and acceptability of mHealth interventions for improving patient care at a community-based HIV/AIDS clinic in Uganda: A mixed methods study

Mobile technologies for health (mHealth) represents a growing array of tools being applied in diverse health care settings. mHealth interventions for improving HIV/AIDS care is a promising strategy, but its evidence base is limited. We conducted a formative research evaluation to inform the development of novel mHealth HIV/AIDS care interventions to be used by community health workers (CHWs) in Kampala, Uganda. A mixed methods formative research approach was utilized. Qualitative methods included 20 in-depth interviews (IDIs) and six focus groups with CHWs, clinic staff, and patients. Thematic analysis was performed and selected quotations used to illustrate themes. Quantitative methods consisted of a survey administered to CHWs and clinic staff, using categorical and Likert scale questions regarding current mobile phone and internet access and perceptions on the potential use of smartphones by CHWs. Qualitative results included themes on significant current care challenges, multiple perceived mHealth benefits, and general intervention acceptability. Key mHealth features desired included tools to verify CHWs’ task completions, clinical decision support tools, and simple access to voice calling. Inhibiting factors identified included concerns about CHWs’ job security and unrealistic expectations of mHealth capabilities. Quantitative results from 27 staff participants found that 26 (96%) did not have internet access at home, yet only 2 (7.4%) did not own a mobile phone. Likert scale survey responses (1–5, 1 = Strongly Disagree, 5 = Strongly Agree) indicated general agreement that smartphones would improve efficiency (Mean = 4.35) and patient care (4.31) but might be harmful to patient confidentiality (3.88) and training was needed (4.63). Qualitative and quantitative results were generally consistent, and, overall, there was enthusiasm for mHealth technology. However, a number of potential inhibiting factors were also discovered. Findings from this study may help guide future design and implementation of mHealth interventions in this setting, optimizing their chances for success.