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Background: Uganda’s maternal mortality rate remains unacceptably high. Mobile phones can potentially provide affordable means of accessing maternal health services even among the otherwise hard-to-reach populations. Evidence about the acceptability and feasibility of mobile phone-based interventions targeting illiterate women, however, is limited. Objective: To assess the acceptability and feasibility of a mobile phone-based multimedia application (MatHealth app) to support maternal health amongst illiterate pregnant women in rural southwestern Uganda. Methods: 80 pregnant women initiating antenatal care from Mbarara regional referral hospital were enrolled in a pilot randomized controlled trial and followed until six weeks after delivery. The 40 women in the intervention group received a MatHealth app composed of educational videos/audios, clinic appointment reminders, and the calling function. Qualitative interviews on acceptability of this technology were carried out with 30 of the intervention participants. An inductive, content analytic approach was used to analyze qualitative data. Quantitative feasibility data were recorded and summarized descriptively. Results: Participants reported that the intervention is acceptable as it enabled them adopt good maternal health practices, enhanced social support from spouses, provided clinic appointment reminders, and facilitated communication with healthcare providers. Challenges included: phone sharing (74%), accidental deletion of the application 15 (43%), lack of electricity 15 (43%), and inability to set up a reminder function 20 (57%). Conclusion: The MatHealth app is an acceptable and feasible intervention among illiterate women, in a resource limited setting. Future efforts should focus on optimized application design, spouse orientation, and incorporating economic support to overcome the challenges we encountered.
The study utilized a mixed methods study design. Participants (pregnant mothers) were recruited from mbarara regional referral hospital (MRRH), which is the largest hospital in rural southwestern Uganda. According to the hospital records, the MRRH employs 11 obstetricians and 22 midwives and performs over 10,000 deliveries annually with a maternal mortality rate of 270/100,000 live birth, caesarean section rate of 30% and a perinatal mortality rate of 56/1000.21 Sociodemographic and basic health data are captured from pregnant women during their first visit, and stored in paper-based antenatal registers. Each woman is given an antenatal card that contains her biodata as well as the date of the next appointment. Women are expected to attend at least eight antenatal appointments, and they are supposed to bring their antenatal cards on every visit. The clinic verbally provides group-based maternal health talks to pregnant women scheduled according to the trimesters—first trimester talks are offered on Tuesdays, second trimester talks are offered on Wednesdays, while third trimester health talks are offered on Thursdays. Topics covered in these talks include nutrition and birth preparedness. There are currently no follow-up mechanism for pregnant women who miss their antenatal appointments. Between Jan 2019 and Dec 2019, we purposively selected pregnant women receiving antenatal care from MRRH. Inclusion criteria were as follows: a) initiating antenatal care at MRRH at the earliest presentation in the first or second trimester, b) being illiterate (not having studied beyond primary seven or elementary education), c) 18 years and above, d) residents of Mbarara (within 20 km of MRRH), e) ability to use mobile phones, f) willing and able to give informed consent, g) able to speak Runyankole (local language). We excluded women who did not qualify per the inclusion criteria or who were not able or willing to give informed consent. The MatHealth app was developed using Java programming language, while the database that hosts multimedia messages was developed using SQlite. It is an offline (stand-alone) application which does not run on the internet. The development of the MatHealth app followed an iterative and approach that involved engaging potential users (women and healthcare providers) in series of focus group discussions (FGDs) to suggest and review the app designs.20,30 These discussions included letting the prospective users suggest contents of messages, as well as practically logging in and navigating the app. Each FGD informed further refinement of the app until users reported being comfortable satisfied and comfortable with the design. A pictorial password enabled access to the application. The app was installed on low-cost smart phones provided by the project at enrollment. MatHealth app was developed to entirely run on android smart phones due to multimedia videos/audios compatibility. Women were provided with solar chargers to supplement electricity charging. The app has three major functionalities; There is also a login module which uses pictorial password to allow access to the app. This paper reports a qualitative evaluation of a randomized trial (results of which are being analyzed) composed of a total of 80 study participants (pregnant women) who were enrolled and followed until six weeks after delivery. A simple random number generator (https://www.random.org/) was used to determine study arm assignments of the participants. After screening and consenting, participants were randomized 1:1 ({“type”:”clinical-trial”,”attrs”:{“text”:”NCT04089800″,”term_id”:”NCT04089800″}}NCT04089800) as follows: Each participant in the MatHealth app arm was trained at enrollment about the mobile app and received a relatively low cost smartphone (about USD 60 per phone) with the MatHealth app installed on it. Participants were informed that they could retain the phones after the study closure. The research assistant (whose has an MSc in health informatics) and the app developers (researchers) explained and demonstrated how the app works including how to login to access the app, view the multimedia videos, audios, set antenatal appointment reminders, and call in to talk to the obstetrician and gynecologist. Participants were then given the app and asked to explain what it does and to practically demonstrate how it works to the RAs. This is a qualitative inquiry within a pilot randomized trial. From a private space at a research office near the MRRH (recruitment site), the research assistant WT carried out semi-structured face to face interviews with pregnant mothers from the intervention arm (those that used MatHealth app) until reaching thematic saturation (at the 30th participant) when no new information arose from the interviews.” Each interview lasted between 40 and 50 minutes. All questions in the interview guide were translated into the local language (Runyankole) and back-translated to English by a different translator, after which the two versions were compared for accuracy. The interviews were carried out in Runyankole (local language), digitally recorded, transcribed, and translated to English. Interviews mainly elicited information about participants’ understandings and experiences of the key components of the app (videos/audios, appointment reminder function, and the calling function). Following each interview, researchers AM and GM reviewed transcripts for quality, clarity, and detail. WT administered surveys to pregnant women to collect information on socio-demographics, socio economic status, food security, and basic health. Quantitative feasibility data were recorded. We used inductive content analysis22 to derive categories describing and summarizing how participants perceived the intervention. Initially, AM, and WT, and GM reviewed and discussed 20% of transcripts for content relevant to participants’ experiences of the intervention. AM and WT then assembled a codebook from the identified concepts, using an iterative process, which included developing codes to represent content, writing operational definitions, and selecting illustrative quotes. Researchers NP, JK, and ACE reviewed and discussed the codebook. Following completion of the codebook, AM and WT applied codes using NVIVO 11. Differences in coding were harmonized through discussion. WT used STATA 13 to describe study participants’ characteristic, their socio economic status, food security, basic health, and feasibility data.
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