Role of trust in sustaining provision and uptake of maternal and child healthcare: Evidence from a national programme in Nigeria

Social Science and Medicine, Volume 293, Year 2022

Ukuhunyushwa

Despite increasing attention to implementation research in global health, evidence from low- and middle-income countries (LMICs) using realist evaluations, in understanding how complex health programmes work remains limited. This paper contributes to bridging this knowledge gap by reporting how, why and in what circumstances, the implementation and subsequent termination of a maternal and child health programme affected the trust of service users and healthcare providers in Nigeria. Key documents were reviewed, and initial programme theories of how context triggers mechanisms to produce intended and unintended outcomes were developed. These were tested, consolidated and refined through iterative cycles of data collection and analysis. Testing and validation of the trust theory utilized eight in-depth interviews with health workers, four focus group discussions with service users and a household survey of 713 pregnant women and analysed retroductively. The conceptual framework adopted Hurley’s perspective on ‘decision to trust’ and Straten et al.‘s framework on public trust and social capital theory. Incentives offered by the programme triggered confidence and satisfaction among service users, contributing to their trust in healthcare providers, increased service uptake, motivated healthcare providers to have a positive attitude to work, and facilitated their trust in the health system. Termination of the programme led to most service users’ dissatisfaction, and distrust reflected in the reduction in utilization of MCH services, increased staff workloads leading to their decreased performance although residual trust remained. Understanding the role of trust in a programme’s short and long-term outcomes can help policymakers and other key actors in the planning and implementation of sustainable and effective health programmes. We call for more theory-driven approaches such as realist evaluation to advance understanding of the implementation of health programmes in LMICs. This paper report results from a component of a broader mixed-methods theory-driven study (Mirzoev et al., 2016), that adopted a RE approach to examine the relationships between contexts, mechanisms and outcomes of community health workers (CHW) programme in Anambra State, Nigeria. It complements our previous reports of focused theoretical lessons (Ebenso et al., 2019; Mirzoev et al., 2020) and empirical results on advocacy for maternal and child health in Nigeria (Okeke et al., 2021; Uzochukwu et al., 2020), security in the provision and utilization of maternal healthcare (Etiaba et al., 2020) and health worker motivation (Ebenso et al., 2020). RE is a theory-driven approach that guides the implementation of complex interventions through iterative theory development, testing and refinement (Pawson and Tilley, 1997; Robert et al., 2012; Wilson and McCormack, 2006; Wong et al., 2017). Programme theories developed within realist studies explore which contexts trigger which mechanisms that produce intended or unintended outcomes in different contexts. This enables a clear understanding of the ‘whys’ and the ‘hows’ of programme outcomes within a particular context that is well suited to evaluating programmes implemented at diverse levels of the health system investigations in low-resource settings (Marchal et al., 2012). In RE, data extraction proceeds from baseline enquiries and development of programme theory to testing/refinement and consolidation of the programme theory, using empirical data (Dalkin et al., 2015). The study was conducted in three phases, corresponding to the building of initial programme theories (IPTs), testing/validation and consolidation/refinement (Manzano, 2016; Pawson and Manzano-Santaella, 2012; Pawson and Tilley, 1997) (see Table 1 in supplementary file). In phase 1, we reviewed key SURE-P/MCH programme documents and relevant MCH Federal and state policies, between June and September 2015, to understand the programme architecture and design (Ebenso et al., 2019). Initial qualitative interviews were held (May–November 2016) with purposefully identified 96 stakeholders comprising in-depth interviews (IDIs) with 10 policymakers, 11 programme officers, 16 health workers/PHC staff, and 15 facility managers at federal and state levels. Focus Group discussions (FGDs) were held with 8 Village Health Workers (VHWs), 12 WDCs, 12 service users (pregnant women) and 12 family members of service users. Different numbers of interviewees reflect the three phases of our research and different engagements with the Trust theory. The selection of all these different respondents was done to explore their views and experiences of the SURE-P/MCH programme. These data facilitated the development of 8 programme theories for the main study (Mirzoev et al., 2016). In phase 2, which entailed data testing and validation of trust theories, qualitative and quantitative methods were utilized. Data were collected in 12 PHCs and three general hospitals purposively selected to reflect the implementation of the SURE-P/MCH programme in Anambra state, Nigeria. These facilities were clustered into three, each cluster comprised one general hospital and four PHCs. The focus on the clusters reflects the setup of the SURE-P/MCH programme. Two of the clusters benefitted from the SURE-P/MCH intervention, while the third cluster was used as a control. This was relevant to enable us to determine if there were any differences in MCH service utilization in the clusters that benefited from the intervention compared to the control cluster. For the qualitative methods, 8 IDIs with health workers and 4 FGDs with service users were conducted (August–September 2018). The IDIs and FGDs were guided by a semi-structured question guide designed around the different versions of initial programme theories and included questions for testing and validating the different components of the programme theories for the main study. The FGD interviews were conducted in the Igbo language, while the IDIs were conducted in both Igbo and English languages depending on respondents’ preference. All IDIs and FGDs were conducted face-to-face and were audio-recorded with respondents’ consent, transcribed and translated into English as necessary. Female researchers (NE, (Sociologist), UE, (Health Economist), UO and EE (Medical doctors) trained in realist interviewing undertook the data collection while NE, UE, UO, TE (male Health economist), EE and AM (female Sociologist) were involved in data analysis. Qualitative data collection was complemented by data from a quantitative household survey. The survey was based on a community listing of all households in the project cluster areas that had a birth in the last 6 years; covering a period before, during and after the SURE-P/MCH programme. A stratified random sample of 713 women was selected for quantitative interviews across the three project areas. A questionnaire was administered, which collected information on maternal health-seeking behaviour to the care given and socioeconomic information on the household between May and June 2018. In phase 3, we refined and modelled the complex relations between the actors, contexts, intervention processes and mechanisms, and its outcomes (December 2018). Using the Context-Mechanism-Outcome (C-M-O) configuration, we examined the emerging data on trust to make inferences about the relationships between contexts, mechanisms and outcomes (Fig. 1). We examined the quantitative data critically to explore the effect of the intervention on various sub-groups of women and to identify sub-period variation in outcome relative to the period before, during and after the withdrawal of the programme. Patterns across data sets were identified by accumulation (the same factor was present within a set and across sets) and causal relationships were established with further support of the theoretical literature and our qualitative data set. This enabled us to refine and consolidate our programme theory on trust which states as follow: In the context of improved staff attitude, upgraded health facilities and functioning WDCs achieved during the implementation of the SURE-P/MCH programme, pregnant women who receive sustained financial and non-financial incentives to use MCH services (Context), are likely to develop and maintain a sense of improved trust (including confidence and satisfaction) with health facilities and staff (Mechanism), ultimately leading to the improved likelihood of repeated and regular utilization of MCH services from these health facilities (Outcome). Fig. 1: CMO template visualizing the causal linkages among contexts (Cs), Mechanisms (Ms) and Outcomes (Os) (See Fig. 1 in supplementary file). To explain how trust works, we drew upon Hurley’s (2006) perspective on the ‘decision to trust’ and Straten et al. (2002) framework of factors that influence public trust in healthcare systems. We also utilized social capital theory (Agampodi et al., 2015; Bourdieu, 1986; De Silva et al., 2007). in our interpretation of the sustainability of trust during the SURE-P/MCH Programme and the existence of residual trust by service users after the withdrawal of the programme. Elements of Hurley’s (2006) perspective relevant to explaining trust in LMIC context include security; the number of similarities between the trustee and truster; if the trustee shows benevolent concerns, trustee’s capability to do their work. Straten et al. (2002) provide a useful framework in the explanation of factors influencing public trust at micro, meso and macro levels. They specify that at the micro-level, people are more concerned about the behaviour of the healthcare providers, whether they will listen to them and handle their problems appropriately. At the meso level, peoples’ concern is whether the health providers are cooperating among themselves; at the macro level, people are worried about impacts of interventions accompanying the development process in the society on their access to, as well as the quality of healthcare. This framework is relevant in the analysis of trust in LMICs. Peters and Youssef (2016) indicate that at the micro-level, the interaction between the doctor and patient can become more effective based on trust and consequently will enhance the patient’s satisfaction and compliance with treatment while at the macro level, the importance of trust is expressed in the impact it makes in society by influencing efforts being made to meet societal expectations. Studies on trust in Nigeria (Amuta-Onukagha et al., 2017, Fagbamigbe and Idemudia, 2015; Ugboaja et al., 2018), reinforce the relevance of articulating factors at the micro, meso, and macro levels in the analysis of trust in health systems. Social capital is conceptualized regarding entitlements to resources including information, financial benefits, favours and services individuals get through membership to a community and participation in networks. It also implies an expectation of reciprocity among members of the networks (Bourdieu, 1986; De Silva et al., 2007). Hence social capital is perceived as ‘tangible’ and ‘intangible’ resources that members of a group have access to on account of their membership to the group (De Silva et al., 2007). Three types of ties namely ‘bonding’, ‘bridging’, and ‘linking’ social capital are identified. Bonding social capital refers to relationships of trust and cooperation, with strong ties among people who have shared identity such as ethnicity, social class, age and place of residence. The bonding ties serve as means through which individuals seek help and support from members of the network (Erickson, 2011). Bridging social capital derives from respect and mutual relationships in networks that are not homogeneous (Erickson, 2011; Putnam, 2000), while linking social capital, on the other hand, refers to “vertical” ties existing among people who belong to different levels of power in the society (Erickson, 2011). Three dimensions of social capital are structural, cognitive and relational social capital. Structural capital refers to the existence of social networks through which people have access to resources, people, roles, rules and procedures (Bourdieu, 1986). Cognitive social capital refers to people’s perceptions and interpretations of the shared relationships in the networks. The relational social capital is concerned with the nature of personal relationships existing among people through interactions in the social system as well as feelings of trust in the network (Claridge, 2018, Harpham and Grant, 2002). Although the social capital theory has its origin in developed countries, it has been successfully used in the analysis of health behaviour and outcomes in some LMICs including Nigeria (Agampodi et al., 2017; Lau et al., 2020, Ozawa and Walker, 2011; Semali et al., 2015; Ware et al., 2009). The social capital theory demonstrates that health outcomes are dependent on income inequality levels with a greater impact on communities where inequality is higher and safety nets lower (Rodgers et al., 2019; Vincens et al., 2018) in most LMICs. Therefore, social capital plays a vital role in increasing the levels of trust in the analysis of health behaviour and outcomes in some LMICs and is relevant to our study in Nigeria.

I-AI Digest

Study Justification:

This study aims to address the limited evidence from low- and middle-income countries (LMICs) on how complex health programs work, specifically focusing on the role of trust in sustaining the provision and uptake of maternal and child healthcare in Nigeria. By understanding the impact of a maternal and child health program on the trust of service users and healthcare providers, policymakers and key actors can better plan and implement sustainable and effective health programs.

Highlights:

– The study utilized a realist evaluation approach to develop, test, and refine program theories on trust in the context of a maternal and child health program in Nigeria.
– Incentives offered by the program increased service users’ confidence and satisfaction, leading to their trust in healthcare providers and increased service uptake.
– The termination of the program resulted in service users’ dissatisfaction and distrust, leading to reduced utilization of maternal and child health services.
– The study highlights the importance of trust in achieving positive outcomes in health programs and calls for more theory-driven approaches, such as realist evaluation, to advance understanding in LMICs.

Recommendations:

– Policymakers and key actors should prioritize the inclusion of trust-building mechanisms in the planning and implementation of health programs.
– Efforts should be made to sustain financial and non-financial incentives for service users to promote trust and regular utilization of maternal and child health services.
– Attention should be given to improving staff attitudes, upgrading health facilities, and fostering cooperation among healthcare providers to enhance trust in the health system.
– The findings emphasize the need for continued support and resources to maintain trust even after the termination of a program.

Key Role Players:

– Policymakers: Responsible for incorporating trust-building mechanisms into health program planning and implementation.
– Healthcare Providers: Play a crucial role in building and maintaining trust through their behavior and interactions with service users.
– Service Users: Their trust in healthcare providers and the health system influences their utilization of maternal and child health services.
– Program Officers: Involved in the design and implementation of health programs, including the provision of incentives and support for service users.

Cost Items for Planning Recommendations:

– Financial incentives for service users: Budget allocation for sustained provision of incentives to promote trust and regular utilization of maternal and child health services.
– Non-financial incentives for service users: Resources needed to provide non-monetary rewards or benefits to service users to enhance trust.
– Staff training and capacity building: Investment in training programs to improve staff attitudes and enhance their capability to provide quality healthcare services.
– Health facility upgrades: Funding for infrastructure improvements and equipment upgrades to create a conducive environment for service users and healthcare providers.
– Monitoring and evaluation: Resources required for ongoing monitoring and evaluation of trust-building efforts and program outcomes.
Please note that the cost items provided are general categories and not actual cost estimates. The specific budget items would depend on the context and scale of the health program.

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a mixed-methods theory-driven study that utilized qualitative interviews, focus group discussions, and a quantitative household survey. The study followed a realist evaluation approach to understand the role of trust in sustaining provision and uptake of maternal and child healthcare in Nigeria. The evidence is supported by a comprehensive data collection and analysis process. However, the abstract does not provide specific details about the sample size, sampling methods, or statistical analysis used in the study. To improve the strength of the evidence, the abstract could include more information about the methodology, such as the inclusion criteria for participants, the data analysis techniques used, and any limitations of the study. Additionally, providing specific findings or results from the study would further enhance the evidence.

Abstract

This paper report results from a component of a broader mixed-methods theory-driven study (Mirzoev et al., 2016), that adopted a RE approach to examine the relationships between contexts, mechanisms and outcomes of community health workers (CHW) programme in Anambra State, Nigeria. It complements our previous reports of focused theoretical lessons (Ebenso et al., 2019; Mirzoev et al., 2020) and empirical results on advocacy for maternal and child health in Nigeria (Okeke et al., 2021; Uzochukwu et al., 2020), security in the provision and utilization of maternal healthcare (Etiaba et al., 2020) and health worker motivation (Ebenso et al., 2020). RE is a theory-driven approach that guides the implementation of complex interventions through iterative theory development, testing and refinement (Pawson and Tilley, 1997; Robert et al., 2012; Wilson and McCormack, 2006; Wong et al., 2017). Programme theories developed within realist studies explore which contexts trigger which mechanisms that produce intended or unintended outcomes in different contexts. This enables a clear understanding of the ‘whys’ and the ‘hows’ of programme outcomes within a particular context that is well suited to evaluating programmes implemented at diverse levels of the health system investigations in low-resource settings (Marchal et al., 2012). In RE, data extraction proceeds from baseline enquiries and development of programme theory to testing/refinement and consolidation of the programme theory, using empirical data (Dalkin et al., 2015). The study was conducted in three phases, corresponding to the building of initial programme theories (IPTs), testing/validation and consolidation/refinement (Manzano, 2016; Pawson and Manzano-Santaella, 2012; Pawson and Tilley, 1997) (see Table 1 in supplementary file). In phase 1, we reviewed key SURE-P/MCH programme documents and relevant MCH Federal and state policies, between June and September 2015, to understand the programme architecture and design (Ebenso et al., 2019). Initial qualitative interviews were held (May–November 2016) with purposefully identified 96 stakeholders comprising in-depth interviews (IDIs) with 10 policymakers, 11 programme officers, 16 health workers/PHC staff, and 15 facility managers at federal and state levels. Focus Group discussions (FGDs) were held with 8 Village Health Workers (VHWs), 12 WDCs, 12 service users (pregnant women) and 12 family members of service users. Different numbers of interviewees reflect the three phases of our research and different engagements with the Trust theory. The selection of all these different respondents was done to explore their views and experiences of the SURE-P/MCH programme. These data facilitated the development of 8 programme theories for the main study (Mirzoev et al., 2016). In phase 2, which entailed data testing and validation of trust theories, qualitative and quantitative methods were utilized. Data were collected in 12 PHCs and three general hospitals purposively selected to reflect the implementation of the SURE-P/MCH programme in Anambra state, Nigeria. These facilities were clustered into three, each cluster comprised one general hospital and four PHCs. The focus on the clusters reflects the setup of the SURE-P/MCH programme. Two of the clusters benefitted from the SURE-P/MCH intervention, while the third cluster was used as a control. This was relevant to enable us to determine if there were any differences in MCH service utilization in the clusters that benefited from the intervention compared to the control cluster. For the qualitative methods, 8 IDIs with health workers and 4 FGDs with service users were conducted (August–September 2018). The IDIs and FGDs were guided by a semi-structured question guide designed around the different versions of initial programme theories and included questions for testing and validating the different components of the programme theories for the main study. The FGD interviews were conducted in the Igbo language, while the IDIs were conducted in both Igbo and English languages depending on respondents’ preference. All IDIs and FGDs were conducted face-to-face and were audio-recorded with respondents’ consent, transcribed and translated into English as necessary. Female researchers (NE, (Sociologist), UE, (Health Economist), UO and EE (Medical doctors) trained in realist interviewing undertook the data collection while NE, UE, UO, TE (male Health economist), EE and AM (female Sociologist) were involved in data analysis. Qualitative data collection was complemented by data from a quantitative household survey. The survey was based on a community listing of all households in the project cluster areas that had a birth in the last 6 years; covering a period before, during and after the SURE-P/MCH programme. A stratified random sample of 713 women was selected for quantitative interviews across the three project areas. A questionnaire was administered, which collected information on maternal health-seeking behaviour to the care given and socioeconomic information on the household between May and June 2018. In phase 3, we refined and modelled the complex relations between the actors, contexts, intervention processes and mechanisms, and its outcomes (December 2018). Using the Context-Mechanism-Outcome (C-M-O) configuration, we examined the emerging data on trust to make inferences about the relationships between contexts, mechanisms and outcomes (Fig. 1). We examined the quantitative data critically to explore the effect of the intervention on various sub-groups of women and to identify sub-period variation in outcome relative to the period before, during and after the withdrawal of the programme. Patterns across data sets were identified by accumulation (the same factor was present within a set and across sets) and causal relationships were established with further support of the theoretical literature and our qualitative data set. This enabled us to refine and consolidate our programme theory on trust which states as follow: In the context of improved staff attitude, upgraded health facilities and functioning WDCs achieved during the implementation of the SURE-P/MCH programme, pregnant women who receive sustained financial and non-financial incentives to use MCH services (Context), are likely to develop and maintain a sense of improved trust (including confidence and satisfaction) with health facilities and staff (Mechanism), ultimately leading to the improved likelihood of repeated and regular utilization of MCH services from these health facilities (Outcome). Fig. 1: CMO template visualizing the causal linkages among contexts (Cs), Mechanisms (Ms) and Outcomes (Os) (See Fig. 1 in supplementary file). To explain how trust works, we drew upon Hurley’s (2006) perspective on the ‘decision to trust’ and Straten et al. (2002) framework of factors that influence public trust in healthcare systems. We also utilized social capital theory (Agampodi et al., 2015; Bourdieu, 1986; De Silva et al., 2007). in our interpretation of the sustainability of trust during the SURE-P/MCH Programme and the existence of residual trust by service users after the withdrawal of the programme. Elements of Hurley’s (2006) perspective relevant to explaining trust in LMIC context include security; the number of similarities between the trustee and truster; if the trustee shows benevolent concerns, trustee’s capability to do their work. Straten et al. (2002) provide a useful framework in the explanation of factors influencing public trust at micro, meso and macro levels. They specify that at the micro-level, people are more concerned about the behaviour of the healthcare providers, whether they will listen to them and handle their problems appropriately. At the meso level, peoples’ concern is whether the health providers are cooperating among themselves; at the macro level, people are worried about impacts of interventions accompanying the development process in the society on their access to, as well as the quality of healthcare. This framework is relevant in the analysis of trust in LMICs. Peters and Youssef (2016) indicate that at the micro-level, the interaction between the doctor and patient can become more effective based on trust and consequently will enhance the patient’s satisfaction and compliance with treatment while at the macro level, the importance of trust is expressed in the impact it makes in society by influencing efforts being made to meet societal expectations. Studies on trust in Nigeria (Amuta-Onukagha et al., 2017, Fagbamigbe and Idemudia, 2015; Ugboaja et al., 2018), reinforce the relevance of articulating factors at the micro, meso, and macro levels in the analysis of trust in health systems. Social capital is conceptualized regarding entitlements to resources including information, financial benefits, favours and services individuals get through membership to a community and participation in networks. It also implies an expectation of reciprocity among members of the networks (Bourdieu, 1986; De Silva et al., 2007). Hence social capital is perceived as ‘tangible’ and ‘intangible’ resources that members of a group have access to on account of their membership to the group (De Silva et al., 2007). Three types of ties namely ‘bonding’, ‘bridging’, and ‘linking’ social capital are identified. Bonding social capital refers to relationships of trust and cooperation, with strong ties among people who have shared identity such as ethnicity, social class, age and place of residence. The bonding ties serve as means through which individuals seek help and support from members of the network (Erickson, 2011). Bridging social capital derives from respect and mutual relationships in networks that are not homogeneous (Erickson, 2011; Putnam, 2000), while linking social capital, on the other hand, refers to “vertical” ties existing among people who belong to different levels of power in the society (Erickson, 2011). Three dimensions of social capital are structural, cognitive and relational social capital. Structural capital refers to the existence of social networks through which people have access to resources, people, roles, rules and procedures (Bourdieu, 1986). Cognitive social capital refers to people’s perceptions and interpretations of the shared relationships in the networks. The relational social capital is concerned with the nature of personal relationships existing among people through interactions in the social system as well as feelings of trust in the network (Claridge, 2018, Harpham and Grant, 2002). Although the social capital theory has its origin in developed countries, it has been successfully used in the analysis of health behaviour and outcomes in some LMICs including Nigeria (Agampodi et al., 2017; Lau et al., 2020, Ozawa and Walker, 2011; Semali et al., 2015; Ware et al., 2009). The social capital theory demonstrates that health outcomes are dependent on income inequality levels with a greater impact on communities where inequality is higher and safety nets lower (Rodgers et al., 2019; Vincens et al., 2018) in most LMICs. Therefore, social capital plays a vital role in increasing the levels of trust in the analysis of health behaviour and outcomes in some LMICs and is relevant to our study in Nigeria.

Izinto zokwakha

Emisha

Based on the provided description, the following innovations could be considered to improve access to maternal health:

1. Mobile Health (mHealth) Applications: Develop and implement mobile applications that provide pregnant women with information on prenatal care, nutrition, and healthcare services. These apps can also offer appointment reminders and allow women to communicate with healthcare providers.

2. Telemedicine: Establish telemedicine services to enable pregnant women in remote or underserved areas to consult with healthcare professionals remotely. This can help overcome geographical barriers and improve access to prenatal care.

3. Community Health Worker (CHW) Programs: Expand and strengthen CHW programs to provide education, counseling, and support to pregnant women in their communities. CHWs can play a crucial role in promoting maternal health and facilitating access to healthcare services.

4. Financial Incentives: Implement financial incentive programs to encourage pregnant women to seek and utilize maternal healthcare services. This can include cash transfers, vouchers, or subsidies for transportation, medications, or healthcare fees.

5. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve leveraging private healthcare facilities and resources to expand service availability and reduce the burden on public healthcare systems.

6. Health Education Campaigns: Launch targeted health education campaigns to raise awareness about the importance of maternal health and the available healthcare services. These campaigns can address cultural and social barriers, dispel myths, and promote positive health-seeking behaviors.

7. Infrastructure Development: Invest in improving healthcare infrastructure, including the construction and renovation of maternal health clinics and facilities. This can help ensure that pregnant women have access to well-equipped and accessible healthcare facilities.

8. Transportation Support: Provide transportation support for pregnant women living in remote or underserved areas to overcome transportation barriers and enable them to reach healthcare facilities for prenatal care and delivery.

9. Quality Improvement Initiatives: Implement quality improvement initiatives in healthcare facilities to enhance the overall quality of maternal healthcare services. This can involve training healthcare providers, improving equipment and supplies, and implementing evidence-based practices.

10. Data-driven Decision Making: Utilize data and technology to monitor and evaluate maternal health outcomes, identify gaps in service delivery, and inform evidence-based decision making. This can help optimize resource allocation and improve the effectiveness of maternal health programs.

It is important to note that the specific context and needs of the target population should be considered when implementing these innovations to ensure their relevance and effectiveness.

AI Innovations Description

The recommendation that can be developed into an innovation to improve access to maternal health based on the described research is to focus on building and sustaining trust between service users and healthcare providers. Trust plays a crucial role in the provision and uptake of maternal and child healthcare services.

To implement this recommendation, the following strategies can be considered:

1. Strengthen communication and transparency: Enhance communication channels between healthcare providers and service users to ensure clear and accurate information about maternal health services. Transparency in service delivery processes and outcomes can help build trust.

2. Improve healthcare provider attitudes: Invest in training and capacity building programs for healthcare providers to improve their attitudes towards service users. Positive attitudes can contribute to building trust and increasing service uptake.

3. Provide incentives: Consider offering financial and non-financial incentives to service users to encourage them to utilize maternal health services. Incentives can help build confidence and satisfaction among service users, leading to increased trust in healthcare providers.

4. Enhance healthcare facilities: Invest in upgrading health facilities to improve the quality of maternal health services. Well-equipped and functional facilities can contribute to service users’ trust in the health system.

5. Strengthen community engagement: Engage community members, including women, families, and community leaders, in the planning and implementation of maternal health programs. Community involvement can foster trust and ownership of the services.

6. Ensure continuity of programs: Avoid abrupt termination of maternal health programs to prevent a decline in trust and service utilization. Plan for sustainable and long-term implementation of programs to maintain trust among service users and healthcare providers.

By implementing these strategies, policymakers and other key stakeholders can work towards improving access to maternal health services by building and sustaining trust between service users and healthcare providers.

AI Innovations Methodology

The paper explores the role of trust in sustaining the provision and uptake of maternal and child healthcare in Nigeria. It utilizes a realist evaluation approach to understand how the implementation and termination of a maternal and child health program affected the trust of service users and healthcare providers. The study involved reviewing key program documents, conducting interviews and focus group discussions with stakeholders, and collecting quantitative data through a household survey.

To simulate the impact of recommendations on improving access to maternal health, a methodology could be developed based on the following steps:

1. Identify the recommendations: Based on the findings of the study, identify specific recommendations that can improve access to maternal health. These recommendations could include interventions to enhance trust between service users and healthcare providers, such as providing sustained financial and non-financial incentives, improving staff attitude, upgrading health facilities, and strengthening community engagement.

2. Define the simulation model: Develop a simulation model that represents the maternal health system, including key components such as healthcare facilities, healthcare providers, service users, and contextual factors. The model should capture the relationships and interactions between these components.

3. Incorporate the recommendations: Introduce the identified recommendations into the simulation model. This could involve adjusting parameters related to trust, incentives, staff attitude, and facility upgrades. The changes should reflect the potential impact of the recommendations on improving access to maternal health.

4. Simulate the impact: Run the simulation model to simulate the impact of the recommendations on access to maternal health. This could involve measuring indicators such as the utilization of maternal health services, satisfaction of service users, and performance of healthcare providers. The simulation should consider different scenarios and variations in contextual factors to assess the robustness of the recommendations.

5. Analyze the results: Analyze the simulation results to understand the potential impact of the recommendations on improving access to maternal health. This could involve comparing the outcomes between different scenarios and identifying the key factors influencing the outcomes. The analysis should provide insights into the effectiveness and feasibility of the recommendations.

6. Refine and iterate: Based on the analysis, refine the recommendations and the simulation model if necessary. Iterate the simulation process to further explore the potential impact and optimize the recommendations.

By following this methodology, policymakers and other stakeholders can gain insights into the potential impact of recommendations on improving access to maternal health. This can inform decision-making and the planning and implementation of sustainable and effective health programs.

Umbhali