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      Informal mhealth at scale in Africa: Opportunities and challenges

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          Highlights

          • Community health-workers across Africa use mobile phones ‘informally’ in their work.

          • Informal mhealth is an emergent phenomenon, used to bridge gaps in formal provision.

          • Informal mhealth is happening at scale, far outstripping its formal equivalent.

          • Informal mhealth is inherently responsive to local needs and contingencies.

          • But it carries hidden costs (financial and other) which are inequitably distributed.

          Abstract

          The extraordinary global growth of digital connectivity has generated optimism that mobile technologies can help overcome infrastructural barriers to development, with ‘mobile health’ (mhealth) being a key component of this. However, while ‘formal’ (top-down) mhealth programmes continue to face challenges of scalability and sustainability, we know relatively little about how health-workers are using their own mobile phones informally in their work. Using data from Ghana, Ethiopia and Malawi, we document the reach, nature and perceived impacts of community health-workers’ (CHWs’) ‘informal mhealth’ practices, and ask how equitably these are distributed. We implemented a mixed-methods study, combining surveys of CHWs across the three countries, using multi-stage proportional-to-size sampling (N = 2197 total), with qualitative research (interviews and focus groups with CHWs, clients and higher-level stake-holders). Survey data were weighted to produce nationally- or regionally-representative samples for multivariate analysis; comparative thematic analysis was used for qualitative data. Our findings confirm the limited reach of ‘formal’ compared with ‘informal’ mhealth: while only 15% of CHWs surveyed were using formal mhealth applications, over 97% reported regularly using a personal mobile phone for work-related purposes in a range of innovative ways. CHWs and clients expressed unequivocally enthusiastic views about the perceived impacts of this ‘informal health’ usage. However, they also identified very real practical challenges, financial burdens and other threats to personal wellbeing; these appear to be borne disproportionately by the lowest-paid cadre of health-workers, especially those serving rural areas. Unlike previous small-scale, qualitative studies, our work has shown that informal mhealth is already happening at scale, far outstripping its formal equivalent. Policy-makers need to engage seriously with this emergent health system, and to work closely with those on the ground to address sources of inequity, without undermining existing good practice.

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          Most cited references75

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          Using thematic analysis in psychology

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            The Impact of mHealth Interventions: Systematic Review of Systematic Reviews

            Background Mobile phone usage has been rapidly increasing worldwide. mHealth could efficiently deliver high-quality health care, but the evidence supporting its current effectiveness is still mixed. Objective We performed a systematic review of systematic reviews to assess the impact or effectiveness of mobile health (mHealth) interventions in different health conditions and in the processes of health care service delivery. Methods We used a common search strategy of five major scientific databases, restricting the search by publication date, language, and parameters in methodology and content. Methodological quality was evaluated using the Measurement Tool to Assess Systematic Reviews (AMSTAR) checklist. Results The searches resulted in a total of 10,689 articles. Of these, 23 systematic reviews (371 studies; more than 79,665 patients) were included. Seventeen reviews included studies performed in low- and middle-income countries. The studies used diverse mHealth interventions, most frequently text messaging (short message service, SMS) applied to different purposes (reminder, alert, education, motivation, prevention). Ten reviews were rated as low quality (AMSTAR score 0-4), seven were rated as moderate quality (AMSTAR score 5-8), and six were categorized as high quality (AMSTAR score 9-11). A beneficial impact of mHealth was observed in chronic disease management, showing improvement in symptoms and peak flow variability in asthma patients, reducing hospitalizations and improving forced expiratory volume in 1 second; improving chronic pulmonary diseases symptoms; improving heart failure symptoms, reducing deaths and hospitalization; improving glycemic control in diabetes patients; improving blood pressure in hypertensive patients; and reducing weight in overweight and obese patients. Studies also showed a positive impact of SMS reminders in improving attendance rates, with a similar impact to phone call reminders at reduced cost, and improved adherence to tuberculosis and human immunodeficiency virus therapy in some scenarios, with evidence of decrease of viral load. Conclusions Although mHealth is growing in popularity, the evidence for efficacy is still limited. In general, the methodological quality of the studies included in the systematic reviews is low. For some fields, its impact is not evident, the results are mixed, or no long-term studies exist. Exceptions include the moderate quality evidence of improvement in asthma patients, attendance rates, and increased smoking abstinence rates. Most studies were performed in high-income countries, implying that mHealth is still at an early stage of development in low-income countries.
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              "Everything Is Perfect, and We Have No Problems": Detecting and Limiting Social Desirability Bias in Qualitative Research.

              Many qualitative research studies acknowledge the possibility of social desirability bias (a tendency to present reality to align with what is perceived to be socially acceptable) as a limitation that creates complexities in interpreting findings. Drawing on experiences conducting interviews and focus groups in rural Ethiopia, this article provides an empirical account of how one research team developed and employed strategies to detect and limit social desirability bias. Data collectors identified common cues for social desirability tendencies, relating to the nature of the responses given and word choice patterns. Strategies to avoid or limit bias included techniques for introducing the study, establishing rapport, and asking questions. Pre-fieldwork training with data collectors, regular debriefing sessions, and research team meetings provided opportunities to discuss social desirability tendencies and refine approaches to account for them throughout the research. Although social desirability bias in qualitative research may be intractable, it can be minimized.

                Author and article information

                Contributors
                Journal
                World Dev
                World Dev
                World Development
                Pergamon Press
                0305-750X
                0305-750X
                1 April 2021
                April 2021
                : 140
                : 105257
                Affiliations
                [a ]Department of Anthropology, Durham University, Durham DH1 3LE, UK
                [b ]University of Malawi, Malawi
                [c ]University of Gondar, Ethiopia
                [d ]University of Cape Coast, Ghana
                [e ]University of Hull, UK
                [f ]University of Newcastle, UK
                [g ]University of Hasselt, Belgium
                [h ]Research Triangle Institute, United States
                [i ]Durham University, UK
                Author notes
                [* ]Corresponding author. K.R.Hampshire@ 123456durham.ac.uk
                Article
                S0305-750X(20)30384-3 105257
                10.1016/j.worlddev.2020.105257
                7903241
                33814676
                ada6a30e-dfeb-4226-a906-18248197239b
                © 2021 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 19 October 2020
                Categories
                Article

                Economic development
                mobile health,informal mhealth,community health workers,ghana,malawi,ethiopia
                Economic development
                mobile health, informal mhealth, community health workers, ghana, malawi, ethiopia

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