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Background: Travel time and healthcare financing are critical determinants of the provision of quality maternal health care in low resource settings. Despite the availability of pregnancy-related mHealth and smart travel applications, there is a lack of evidence on their usage to travel to health facilities for routine antenatal care and emergencies. There is a shortage of information about the feasibility of using a custom-made mobile technology that integrates smart travel and mHealth. This paper explores the feasibility of implementing a custom-made geographically enabled mobile technology-based tool (RoadMApp) to counter the adverse effects of long travel times for maternal care in Kwekwe District, Zimbabwe. Methods: We frame the paper using the first two steps (listen and plan) of the Spiral Technology Action Research (STAR model). The paper uses an exploratory case study design and Participatory Learning Approaches (PLA) with stakeholders (community members) and in-depth interviews with key informants (health care service providers, pregnant women, transport operators). One hundred ninety-three participants took part in the study. We conducted focus group discussions with pregnant women, women of childbearing age, men (household heads), and elderly women. The discussion questions centered on travel time, availability of transport, cellular network coverage, and perceptions of the RoadMApp application. Data were analysed thematically using Nvivo Pro 12. Results: Most parts of rural Kwekwe are far from health facilities and have an inefficient road and telecommunications network. Hence, it is hard to predict if RoadMApp will integrate into the lives of the community – especially those in rural areas. Since these issues are pillars of the design of the RoadMApp mHealth, the implementation will probably be a challenge. Conclusion: Communities are keen to embrace the RoadMApp application. However, the feasibility of implementing RoadMApp in Kwekwe District will be a challenge because of maternal health care barriers such as poor road network, poor phone network, and the high cost of transport. There is a need to investigate the social determinants of access to maternity services to inform RoadMApp implementation.
The case study research design suits the investigation of the complexity of community concerns. We chose Participatory Learning for Action (PLA) methods to engage the community in line with the STAR model. PLA combines action and participatory action research with several techniques borrowed from qualitative social research (participatory, visual techniques such as maps, transect walks, and problem trees) [22]. The discussion questions centred on travel time, availability of transport, cellular network coverage, and participants’ perceptions of the RoadMApp application (see Additional file 1, showing the research instrument). We used registers and maps at the provincial level for the selection of study sites. We purposively sampled two hospitals (rural and urban), four rural health centres, two peri-urban clinics, and two urban clinics to get information-rich cases in the communities (see Fig. 2). Showing the map of the data collection sites [18] We based the selection criteria on health facilities providing obstetric care services, distance to the health facilities, and availability of mothers’ waiting shelters. We treated a radius of 40 km as the catchment area of each rural clinic. We then looked for representative cases (i.e., Kwekwe residents with experience and knowledge of travelling to institutional birth facilities) at each health centre. This purposive sampling strategy accounts for participants’ clinical variation (parity), demographic groups, geographical spread (i.e., rural, peri-urban, and urban). This is consistent with the goals of qualitative research to achieve credibility and transferability as opposed to validity and generalization used in quantitative studies [23]. We asked health workers to help identify people whose experiences could significantly contribute to the study (snowballing). An interview guide was used to solicit information from the participants. The participants included pregnant women, women of childbearing age (WOCBA), community members, older women (50 years and above), and men (i.e., their roles as household decision-makers) and health care providers. Participants provided written or verbal (particularly for the less literate) informed consent. Data from the audio voice recorders were transcribed verbatim and later translated into English. Two translators verified the transcripts for authenticity. We imported the anonymized transcripts into Nvivo Pro 12™ to generate codes to aid in the analysis process. ZNJ and IMD performed first-cycle coding using elemental methods (i.e., descriptive and in vivo coding) [24]. They shared the coded data with the rest of the team to identify emerging themes. After the first-cycle, a thematic analysis summarized the data to identify and interpret the key features of the data, guided by the initial research questions [25]. Three authors cross-checked the themes with the transcripts and field notes to ensure consistency. We disseminated the preliminary findings to local authorities and the participants to verify if we had accurately represented their views.
