preprint · medRxiv
Between 2016 and 2022, Muhimbili University of Health and Allied Sciences in Tanzania conducted six structured workshops to train health researchers in using Research Electronic Data Capture, known as REDCap. Post-training evaluations gathered feedback from 110 participants, comprising academic staff, postgraduate and undergraduate students, and other professionals, mainly from Tanzania alongside attendees from Ghana and Nigeria. Participants reported high overall satisfaction, recording average scores exceeding 4.4 on a five-point scale. Over 85 percent of respondents agreed or strongly agreed that the software boosted research effectiveness, enhanced productivity, and improved task completion. The delivery of structured training helped address adoption hurdles, showing that this capacity-building model can reliably support research data management across institutions in sub-Saharan Africa.
High-quality medical and clinical research depends on secure, accurate, and efficient data handling. Demonstrating that local researchers and students readily adopt digital data capture tools when given structured training shows a clear route to upgrading institutional research capabilities. This helps academic institutions across the region run robust clinical studies that meet international standards.
The work reflects an applied and tested capacity-building initiative for deploying digital data collection systems within academic and healthcare environments. Potential users include medical universities, clinical research organisations, and hospital networks seeking reliable data infrastructure. Although focused on operational deployment rather than commercial product creation, the training framework offers an established, ready-to-use template for scaling research software adoption across other regional institutions.
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Objective: To document the deployment and training of Research Electronic Data Capture (REDCap) at Muhimbili University of Health and Allied Sciences (MUHAS) in Tanzania and to evaluate user satisfaction and perceived impact on research practices in Tanzania. Materials and Methods: Six structured REDCap training workshops were conducted between 2016 and 2022. The post-training evaluation surveys were completed by 110 participants. Descriptive statistics were generated for demographics and cadres, while Likert-scale responses assessed satisfaction and perceived utility. Diverging stacked bar charts were used to visualize attitudes toward adopting REDCap. Results: Most trainees were male (62.7%), aged 26-32 years (52.7%), and affiliated with MUHAS (66.4%), with additional representation from Ghana and Nigeria. The participants included academic or research staff (41.8%), postgraduate students (28.2%), undergraduate students (11.8%), and other professionals (18.2%). Post-training evaluations indicated consistently high satisfaction, with mean scores above 4.4 on a 5-point scale. Trainees strongly endorsed REDCap's ability to enhance research effectiveness (mean 4.53, SD 0.65), increase productivity (mean 4.52, SD 0.69), and improve task completion (mean 4.50, SD 0.68). More than 85% of the respondents agreed or strongly agreed with the positive statements, underscoring the broad acceptance of REDCap as a reliable tool for research data management. Discussion: The findings underscore the importance of structured training in mitigating barriers to adoption and enhancing data quality, efficiency, and institutional visibility. Conclusion: Structured REDCap training in Tanzania was associated with high user satisfaction and perceived improvements in research productivity and data quality, offering a scalable model for strengthening data management capacity in sub-Saharan Africa.
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DOI: 10.1101/2025.10.25.25338769
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