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.

[1]  Colin Sharp.  Qualitative Research and Evaluation Methods (3rd ed.) , 2003 .

[2]  J. Fisher,et al.  Clinician-Initiated HIV Risk Reduction Intervention for HIV-Positive Persons: Formative Research, Acceptability, and Fidelity of the Options Project , 2004, Journal of acquired immune deficiency syndromes.

[3]  L. Cheever,et al.  Prevention interventions with persons living with HIV/AIDS: challenges, progress, and research priorities. , 2004, Journal of acquired immune deficiency syndromes.

[4]  W. Kaplan,et al.  Globalization and Health BioMed Central Debate , 2006 .

[5]  John W. Creswell,et al.  Designing and Conducting Mixed Methods Research , 2006 .

[6]  Walter H. Curioso,et al.  Access, use and perceptions regarding Internet, cell phones and PDAs as a means for health promotion for people living with HIV in Peru , 2007, BMC Medical Informatics Decis. Mak..

[7]  T. Quinn,et al.  Two-Year Virologic Outcomes of an Alternative AIDS Care Model: Evaluation of a Peer Health Worker and Nurse-Staffed Community-Based Program in Uganda , 2009, Journal of acquired immune deficiency syndromes.

[8]  W. Jack,et al.  Effects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial , 2010, The Lancet.

[9]  T. Quinn,et al.  Effect of Peer Health Workers on AIDS Care in Rakai, Uganda: A Cluster-Randomized Trial , 2010, PloS one.

[10]  James G Kahn,et al.  'Mobile' health needs and opportunities in developing countries. , 2010, Health affairs.

[11]  Erik Brynjolfsson,et al.  Race against the machine : how the digital revolution is accelerating innovation, driving productivity, and irreversibly transforming employment and the economy , 2011 .

[12]  K. Rivet Amico,et al.  A situated-Information Motivation Behavioral Skills Model of Care Initiation and Maintenance (sIMB-CIM): An IMB Model Based Approach to Understanding and Intervening in Engagement in Care for Chronic Medical Conditions , 2011, Journal of health psychology.

[13]  R. Bollinger,et al.  Building a global health education network for clinical care and research. The benefits and challenges of distance learning tools. Lessons learned from the Hopkins Center for Clinical Global Health Education. , 2011, Infectious disease clinics of North America.

[14]  C. Anandan,et al.  The Impact of eHealth on the Quality and Safety of Health Care: A Systematic Overview , 2011, PLoS medicine.

[15]  Cristian Pop-Eleches,et al.  Mobile phone technologies improve adherence to antiretroviral treatment in a resource-limited setting: a randomized controlled trial of text message reminders , 2011, AIDS.

[16]  Brook K. Baker,et al.  Efficiencies in AIDS Programming: The Rhetoric and the Realities , 2011, Journal of acquired immune deficiency syndromes.

[17]  F. Wabwire-mangen,et al.  Task-shifting to community health workers: evaluation of the performance of a peer-led model in an antiretroviral program in Uganda. , 2012, AIDS patient care and STDs.

[18]  J. Baeten,et al.  Household-Based HIV Counseling and Testing as a Platform for Referral to HIV Care and Medical Male Circumcision in Uganda: A Pilot Evaluation , 2012, PloS one.

[19]  N. Glass,et al.  Research Capacity–Building Program for Clinicians and Staff at a Community‐Based HIV Clinic in Uganda: A Pre/Post Evaluation , 2012, The Journal of the Association of Nurses in AIDS Care : JANAC.