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Despite the significant benefits of maternal immunisation, uptake remains low in many parts of the world. In this qualitative study, we aimed to assess the factors that influence pregnant women’s decision to engage with maternal immunisation in rural KwaZulu-Natal, South Africa. We conducted in-depth interviews with a total of 28 purposively sampled pregnant women and key informants using semi-structured topic guides. Data analysis was conducted using a modified Health Belief Model framework that included constructs of barriers to action, modifying factors of cue to action and perceived social norms. The findings show that traditional customs and institutional barriers such as low-quality health service delivery, long queues, and distance to the health facilities, immunisation vaccine stockouts and low levels of maternal knowledge influence the choice and decision to engage with maternal immunisation. Understanding health-related behaviours and addressing barriers to care is important in facilitating vaccination uptake. This study contributes to the understanding of maternal immunisation uptake in low-resource settings.
This study was conducted in rural uMkhanyakude district of northern KwaZulu-Natal. This district is one of the poorest in South Africa, with 98% of the population living in rural homesteads; 22% have access to safe water; only 10% of households are within a short distance, approximately 4.72 km, of a health clinic [12,13]. The district is situated within the Mpukunyoni Tribal Authority and the community is guided by tribal laws, customs and traditional structures. The sub-study results on which this paper draws are part of a larger study, assessing community acceptance and health facility preparedness for the implementation of maternal immunisation programs in urban and rural South Africa funded through IMPRINT—Immunising Pregnant Women and Infants Network. The overall IMPRINT study aimed to understand the knowledge, attitudes and acceptability of maternal immunisation amongst pregnant and non-pregnant women, healthcare providers and community members in rural and urban South Africa [14]. The study design was exploratory, and we used qualitative data collection methods that included in-depth interviews and focus group discussions. Individual interviews were conducted with 28 participants. Six of the participants were interviewed via the telephone later in June 2020 because of the COVID-19 non-pharmacological measures in place at that time. One focus group discussion was conducted with five pregnant women of different age groups. Table 1 gives a description of the study participants. The sample comprised women who were unemployed, school dropouts and students. Topic guides were translated into the local language, isiZulu, and back translated into English. After gaining informed consent, the interviews were conducted in IsiZulu from December 2019 to June 2020. All data collection activities were digitally recorded, transcribed verbatim and then translated to English. We provide the topic guides we used in Supplementary Materials (S1–S5). Study participant description. Interviews were conducted by trained field workers in private settings where the participants felt comfortable. Interviews lasted approximately forty-five minutes to an hour. Interview summaries were written by the fieldworkers immediately after each interview to provide an overview of the interview and the main points raised and to complement the transcription, which took longer to produce. Debriefings between the lead researchers and the fieldworkers were conducted after each interview. Data quality checks were conducted by the facilitators to ensure the completeness and accuracy of transcripts. Participants were given identification numbers; these are used in the presentation of our results to allow readers to distinguish between quotes from different people. Thematic content analysis was conducted manually by two authors (RSC) and (NN), who are experienced social scientists. Data were managed using a framework analysis approach. The theoretical framing of the Health Belief Model (HBM) was used as a guide to identify and group emerging themes related to the acceptability of maternal immunisation. Themes related to HBM constructs were identified through coding and data were copied and pasted into excel sheets according to thematic areas. Indexing (coding) and charting (copying and pasting data according to thematic areas) were carried out simultaneously. The Health Belief Model (HBM) is one of the most widely used theoretical frameworks for understanding health behaviour [15,16]. This model is used to assess intra-personal factors, including risk-related beliefs that may influence individuals’ health decision making [17]. The HBM conceptual framework comprises six constructs that predict health behaviours, namely, perceived susceptibility, perceived severity, benefits to action, barriers to action, cue to action and self-efficacy [18,19]. The HBM focuses on health behaviour and perceptions towards an illness and prevention. For the purposes of this analysis, we used a modified HBM as illustrated in Figure 1. The HBM analytical framework was used as a foundation for our data analysis. The HBM states that people will take action to prevent illness if they regard themselves as susceptible to a disease (perceived susceptibility) and if they believe it would have potentially serious consequences (perceived severity) [19]. In preparing our coding framework, with the HBM as a basis, we observed additional factors that motivated people to disengage in preventive health behaviours beyond those originally specified by the HBM. Social norms have been significant predictors of health behaviours in our study setting and can predict health behaviours towards interventions [20], while susceptibility and the perceived severity of disease were seldom mentioned, because of limited awareness among participants on the diseases that maternal vaccination might prevent. The Health Belief Model, adapted from Rosenstock et al. (1974). Social norms often relate to perceived social pressure to engage or not engage in specific behaviours [21]. Attitudes and cultural beliefs shape individuals’ health behaviour and are strong motivators of behavioural change [22]. Taking these factors into account, we modified the HBM framework to include constructs of barriers to action, perceived social norms and cues to action.
