‘We always find things to learn from.’ Lessons from the implementation of the global maternal sepsis study on research capacity: a qualitative study

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Study Justification:
The study titled “We always find things to learn from.” Lessons from the implementation of the global maternal sepsis study on research capacity: a qualitative study aimed to explore the impact of the global maternal sepsis study (GLOSS) on developing and strengthening sexual and reproductive health research capacity in low- and middle-income countries. The study aimed to identify the unintended outcomes of participating in research and highlight the needs for research capacity strengthening.
Highlights:
1. The study found that participating in the GLOSS project unintentionally led to the development and strengthening of research capacity among local researchers in the participating countries.
2. Six themes emerged from the data analysis, including the recognized need for research capacity, unintended effects of participating in research, perceived ownership and linkage with the research study, being just data collectors, belonging to an institution that supports and fosters research, and presenting study results back to study implementers.
3. The study highlighted the importance of involvement in protocol development, training and technical support, data analysis, and project management for research capacity strengthening.
4. Institutional support for researchers to conduct research was identified as a crucial factor for sustainable research capacity building.
Recommendations:
1. Deliberate planning for research capacity strengthening should be incorporated into large multi-country research projects like GLOSS.
2. Study coordinators and funders should address the needs of both individuals and institutions to ensure sustainable research capacity building.
3. Involvement in protocol development, training and technical support, data analysis, and project management should be prioritized in research capacity strengthening efforts.
4. Institutional support for researchers, including resources and infrastructure, should be provided to facilitate research activities.
Key Role Players:
1. Study coordinators: Responsible for planning and implementing research capacity strengthening activities.
2. Funders: Provide financial support for research capacity strengthening initiatives.
3. Principal Investigators (PIs): Lead the research teams and coordinate study implementation.
4. Local researchers: Actively participate in research activities and contribute to capacity strengthening efforts.
5. Institutions supporting research: Provide resources, infrastructure, and support for researchers.
Cost Items for Planning Recommendations:
1. Training programs: Budget for organizing training sessions on protocol development, data analysis, and project management.
2. Technical support: Allocate funds for providing technical assistance to researchers during the research process.
3. Institutional support: Include resources and infrastructure costs to support research activities within institutions.
4. Travel and logistics: Plan for travel expenses and logistics associated with conducting site visits and interviews.
5. Communication and dissemination: Budget for sharing study results with study implementers and stakeholders.
Please note that the above cost items are examples and may vary depending on the specific context and requirements of the research capacity strengthening initiatives.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is based on a qualitative study employing grounded theory, which is a rigorous research method. The study included a focus group discussion and semi-structured interviews with participants from 16 countries. The themes that emerged from the data analysis provide valuable insights into the unintended outcomes of the global maternal sepsis study on research capacity strengthening. The study also highlights the need for deliberate planning to build sustainable research capacity. To improve the evidence, it would be helpful to provide more specific details about the sample size and characteristics of the participants, as well as the methodology used for data analysis. Additionally, including some direct quotes or examples from the data analysis would further support the findings.

BACKGROUND: Research capacity strengthening could be an indirect outcome of implementing a research project. The objective of this study was to explore the ability of the global maternal sepsis study (GLOSS), implemented in 52 countries, to develop and strengthen sexual and reproductive health research capacity of local participants in low- and middle- income participating countries. METHODS: We carried out a qualitative study employing grounded theory in sixteen countries in Africa and Latin America. We used inductive and deductive methods through a focus group discussion and semi-structured interviews for the emergence of themes. Participants of the focus group discussion (n = 8) were GLOSS principal investigators (PIs) in Latin America. Interviewees (n = 63) were selected by the country GLOSS PIs in both Africa and Latin America, and included a diverse sample of participants involved in different aspects of study implementation. Eighty-two percent of the participants were health workers. We developed a conceptual framework that took into consideration data obtained from the focus group and refined it based on data from the interviews. RESULTS: Six themes emerged from the data analysis: recognized need for research capacity, unintended effects of participating in research, perceived ownership and linkage with the research study, being just data collectors, belonging to an institution that supports and fosters research, and presenting study results back to study implementers. Research capacity strengthening needs were consistently highlighted including involvement in protocol development, training and technical support, data analysis, and project management. The need for institutional support for researchers to conduct research was also emphasised. CONCLUSION: This study suggests that research capacity strengthening of local researchers was an unintentional outcome of the large multi-country study on maternal sepsis. However, for sustainable research capacity to be built, study coordinators and funders need to deliberately plan for it, addressing needs at both the individual and institutional level.

This was a qualitative study based on concepts from grounded theory which used a focus group discussion and semi-structured interviews to gather in-depth insights from participants [11]. We have used the Consolidated Criteria for Reporting Qualitative research (COREQ) for qualitative studies for this report [12] (Additional file 2). Sixteen countries were purposively selected from those participating in GLOSS across three of the study regions: Anglophone Africa, Francophone Africa, and Latin America. The selection of countries within those regions was based on the following criteria: was a GLOSS participating country [9], was a priority country for research capacity strengthening for the UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP) [13], had previous experience in multi-country research with HRP, feasibility and ease of travel, interest and availability to participate, and representability for each region in terms of geographic and language diversities. Participants in this study were members of local research teams that took part in GLOSS. For the focus group discussion (FGD), we selected a convenience sample of participants who were GLOSS principal investigators (PI) for Latin America. The FGD participants were taking part in a study results workshop in Brazil in 2018. For the interviews we first selected three countries per study region: Anglophone Africa (Kenya, Malawi, and Zimbabwe), Francophone Africa (Benin, Mali, and Senegal) and Latin America (Guatemala, Honduras, and Nicaragua). Then, participants were selected by each country PI and included a diverse sample of interviewees involved in different aspects of study implementation, ranging from data collectors to study coordinators, and from different health facilities, oftentimes located in different country localities. We sought for gender diversity and aimed to interview at least five people per country until we achieved data saturation. A thematic guide for the FGD was developed based on existing frameworks for evaluation of RCS [3, 14–16]. The following a priori themes based on the existing literature were identified as specific areas for exploration during the FGDs: opportunities and challenges with regards to embedded RCS, experience with research, and institutional support. The FGD was moderated by a senior researcher who had not been part of GLOSS and observed by a member of the GLOSS research team. The FGD was conducted in Spanish and had eight participants. It lasted 2 h, and was audio recorded and transcribed verbatim into Spanish. Additional notes taken by the moderator and observer were used in the interpretation of findings. See Additional file 3 for a copy of the FGD guide. Preliminary findings from the focus group discussion were used to develop the semi-structured interview guide. All interviewers participated in an online workshop to standardize data collection. Three researchers conducted 63 semi-structured interviews in total, each lasting on average 42 min (range 21–65 min) and completed during site visits to interviewees’ respective work settings. Twenty interviews were in English (8 in Kenya, 6 in Malawi, and 6 in Zimbabwe), 26 in French (9 in Benin, 11 in Mali, and 6 in Senegal), and 17 in Spanish (5 in Guatemala, 5 in Honduras, and 7 in Nicaragua). Sixty-one interviews were conducted face-to-face and two over the phone. The latter were not recorded because of technical difficulties but hand-written notes were used for the analysis. Interviews in Latin America were conducted in December 2018, in Francophone Africa between March and June 2019, and in Anglophone Africa between April and September 2019. Interviews covered broad questions on participants’ role with GLOSS and prior experience with research, and about opportunities and challenges faced with study implementation and its ability to strengthen research and clinical capacity. Certain socio-demographic data were collected for all focus group participants and interviewees (sex, occupation, place of work) for categorization purposes only. See Additional file 4 for a copy of the interview guide. VB knew all PIs in Latin America participating in the FGD; VB also knew two PIs and two project managers interviewed by her from her role in GLOSS. RC knew all the PIs in Francophone Africa from previous WHO projects (N = 3). None of the other interviewees (N = 56) were known to any of the interviewers. All interviewers and FGD moderator had experience with qualitative research and in leading these activities. Interviews were conducted individually and confidentially in a private space within participants’ work settings and in the native or the official language spoken in each of the countries (English, French or Spanish) and by each of the interviewers. Interviews were recorded using a digital voice recorder to facilitate analysis after obtaining participants’ permission, and transcribed verbatim. Excerpts of the transcripts in French and Spanish were translated into English to enable joint team analysis. All transcripts were anonymised to remove identifying information for participants before uploading to a central secure portal for the team to access. We used inductive and deductive methods using thematic data analysis starting with a priori themes identified from existing literature and refined in a first instance with findings from the FGD and further, at a second stage, with additional emergent themes that arose from the interviews. Examples of emergent themes were: “we were just data collectors” and unintended effects of research. These then informed the final coding used for the analysis of all FGD and interview data. Atlas.ti (version 8.4.18.0 for Windows) was used for the analysis. To ensure rigour, initial coding and analyses were done by each researcher who led the activity in the respective countries and in the original language after verifying the accuracy of transcripts. Transcripts were coded to identify quotes corresponding to the initial themes in our analysis framework. This coding was then cross-checked by another team member fluent in the language: focus group discussions (ALG and VB), interviews in Spanish (ALG, MB, and VB), interviews in French (MB and RC), and interviews in English (AB and AK), during a validation workshop. A final check was done by four researchers (AB, AK, RC, and VB) to ensure the consistency of the quotes included in this manuscript. We did not involve participants directly in this study. However, PIs in each study country helped in organizing site visits, getting needed approvals, and in selecting and contacting participants. Initial findings from this study were shared with all country PIs so that they could extend to the study participants to ensure that everyone agreed with our findings before manuscript submission.

Based on the provided description, it seems that the study focused on exploring the ability of the global maternal sepsis study (GLOSS) to develop and strengthen sexual and reproductive health research capacity in low- and middle-income countries. The study identified several themes related to research capacity strengthening, including involvement in protocol development, training and technical support, data analysis, project management, and the need for institutional support for researchers to conduct research.

Based on these findings, here are some potential innovations that could be considered to improve access to maternal health:

1. Research Capacity Building Programs: Develop and implement programs that provide training and support for local researchers in low- and middle-income countries. These programs could focus on areas such as study design, data collection and analysis, and research management.

2. Collaborative Partnerships: Foster partnerships between local researchers and international organizations to facilitate knowledge exchange, resource sharing, and mentorship opportunities. This can help strengthen research capacity and promote sustainable collaborations.

3. Technology and Data Management: Utilize innovative technologies and data management systems to streamline data collection, analysis, and reporting processes. This can improve efficiency and accuracy in research implementation and enable real-time monitoring of maternal health indicators.

4. Community Engagement and Participation: Involve local communities in the research process to ensure their needs and perspectives are considered. This can be done through community advisory boards, participatory research approaches, and community-based interventions that address maternal health issues.

5. Funding and Resource Allocation: Increase funding and resources dedicated to maternal health research in low- and middle-income countries. This can support the development and implementation of research projects, as well as the establishment of research infrastructure and capacity-building initiatives.

6. Policy and Advocacy: Advocate for policies and strategies that prioritize maternal health research and address the underlying social, economic, and cultural determinants of maternal health. This can help create an enabling environment for research and ensure that research findings are translated into evidence-based policies and interventions.

It is important to note that these recommendations are based on the information provided and may need to be tailored to specific contexts and challenges faced in improving access to maternal health.
AI Innovations Description
The recommendation that can be developed into an innovation to improve access to maternal health based on the study is to deliberately plan and prioritize research capacity strengthening in large multi-country studies on maternal health. This includes addressing the needs of local researchers at both the individual and institutional level. Some specific areas for improvement include involvement in protocol development, training and technical support, data analysis, project management, and institutional support for conducting research. By intentionally focusing on research capacity strengthening, study coordinators and funders can ensure that sustainable research capacity is built, leading to improved access to maternal health services.
AI Innovations Methodology
Based on the provided description, it seems that you are looking for innovations to improve access to maternal health and a methodology to simulate the impact of these recommendations. Unfortunately, the provided text does not explicitly mention any specific innovations or a methodology for simulation. However, I can provide you with some general recommendations for improving access to maternal health and a methodology that can be used to simulate the impact of these recommendations.

Recommendations to Improve Access to Maternal Health:
1. Telemedicine: Implementing telemedicine services can help overcome geographical barriers and provide remote access to healthcare professionals for prenatal care, consultations, and postnatal follow-ups.
2. Mobile Health (mHealth) Applications: Developing mobile applications that provide information, reminders, and support for pregnant women can improve access to maternal health services, especially in remote areas.
3. Community Health Workers: Training and deploying community health workers who can provide basic maternal health services, education, and referrals in underserved areas can improve access to care.
4. Transport and Emergency Services: Establishing reliable transportation systems and emergency services can ensure timely access to healthcare facilities for pregnant women, especially in rural areas.
5. Health Education and Awareness: Conducting community-based health education programs to raise awareness about maternal health, family planning, and the importance of antenatal and postnatal care can improve access to services.

Methodology to Simulate the Impact of Recommendations:
1. Define the Objectives: Clearly define the objectives of the simulation study, such as assessing the impact of specific recommendations on access to maternal health services.
2. Identify Key Variables: Identify the key variables that will be used to measure the impact, such as the number of women accessing prenatal care, the distance traveled to healthcare facilities, or the reduction in maternal mortality rates.
3. Collect Baseline Data: Gather relevant data on the current state of maternal health access, including the number of healthcare facilities, their locations, and the utilization rates.
4. Develop a Simulation Model: Create a simulation model that incorporates the identified variables and their relationships. This model can be based on mathematical equations, statistical models, or computer simulations.
5. Validate the Model: Validate the simulation model by comparing its outputs with real-world data or expert opinions to ensure its accuracy and reliability.
6. Implement Scenarios: Define different scenarios based on the recommended innovations and their potential impact on access to maternal health. For example, simulate the impact of telemedicine implementation or the deployment of community health workers.
7. Analyze Results: Analyze the simulation results to assess the impact of each scenario on the defined objectives. Compare the outcomes of different scenarios to identify the most effective recommendations.
8. Refine and Iterate: Based on the analysis, refine the simulation model and repeat the simulation process to further explore the impact of different variables or recommendations.
9. Communicate Findings: Present the findings of the simulation study to relevant stakeholders, policymakers, and healthcare providers to inform decision-making and guide the implementation of innovations to improve access to maternal health.

Please note that the provided methodology is a general framework and may need to be adapted based on the specific context and available data for the simulation study.

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