Sanne M Thysen1,2,3, Charlotte Tawiah4, Joy E Lawn5, Vladimir Sergeevich Gordeev5,6, Hannah Blencowe5, Grace Manu4, Joseph Akuze5,7,8, M Moinuddin Haider9, Nurul Alam9, Temesgen Azemeraw Yitayew10, Angela Baschieri5, Gashaw A Biks10,11, Francis Dzabeng4, Ane B Fisker12,13,14, Md Ali Imam9, Justiniano S D Martins12, Davis Natukwatsa15. 1. Bandim Health Project, Bissau, Guinea-Bissau. s.thysen@bandim.org. 2. Research Centre for Vitamins and Vaccines, Statens Serum Institut, Copenhagen, Denmark. s.thysen@bandim.org. 3. Bandim Health Project, OPEN, Institute of Clinical Research, University of Southern Denmark, Odense, Denmark. s.thysen@bandim.org. 4. Kintampo Health Research Centre, Kintampo, Ghana. 5. Maternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical Medicine, London, UK. 6. Institute of Population Health Sciences, Queen Mary University of London, London, UK. 7. Dept. of Health Policy, Planning and Management, Makerere University School of Public Health, Kampala, Uganda. 8. Centre of Excellence for Maternal Newborn and Child Health Research, Makerere University, Kampala, Uganda. 9. Health Systems and Population Studies Division, icddr,b, Dhaka, Bangladesh. 10. Dabat Research Centre Health and Demographic Surveillance System, Dabat, Ethiopia. 11. Dept. of Health Services Management and Health Economics, Institute of Public Health College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia. 12. Bandim Health Project, Bissau, Guinea-Bissau. 13. Research Centre for Vitamins and Vaccines, Statens Serum Institut, Copenhagen, Denmark. 14. Bandim Health Project, OPEN, Institute of Clinical Research, University of Southern Denmark, Odense, Denmark. 15. IgangaMayuge Health and Demographic Surveillance System, Makerere University Centre for Health and Population Research, Makerere, Uganda.
Abstract
BACKGROUND: Electronic data collection is increasingly used for household surveys, but factors influencing design and implementation have not been widely studied. The Every Newborn-INDEPTH (EN-INDEPTH) study was a multi-site survey using electronic data collection in five INDEPTH health and demographic surveillance system sites. METHODS: We described experiences and learning involved in the design and implementation of the EN-INDEPTH survey, and undertook six focus group discussions with field and research team to explore their experiences. Thematic analyses were conducted in NVivo12 using an iterative process guided by a priori themes. RESULTS: Five steps of the process of selecting, adapting and implementing electronic data collection in the EN-INDEPTH study are described. Firstly, we reviewed possible electronic data collection platforms, and selected the World Bank's Survey Solutions® as the most suited for the EN-INDEPTH study. Secondly, the survey questionnaire was coded and translated into local languages, and further context-specific adaptations were made. Thirdly, data collectors were selected and trained using standardised manual. Training varied between 4.5 and 10 days. Fourthly, instruments were piloted in the field and the questionnaires finalised. During data collection, data collectors appreciated the built-in skip patterns and error messages. Internet connection unreliability was a challenge, especially for data synchronisation. For the fifth and final step, data management and analyses, it was considered that data quality was higher and less time was spent on data cleaning. The possibility to use paradata to analyse survey timing and corrections was valued. Synchronisation and data transfer should be given special consideration. CONCLUSION: We synthesised experiences using electronic data collection in a multi-site household survey, including perceived advantages and challenges. Our recommendations for others considering electronic data collection include ensuring adaptations of tools to local context, piloting/refining the questionnaire in one site first, buying power banks to mitigate against power interruption and paying attention to issues such as GPS tracking and synchronisation, particularly in settings with poor internet connectivity.
BACKGROUND: Electronic data collection is increasingly used for household surveys, but factors influencing design and implementation have not been widely studied. The Every Newborn-INDEPTH (EN-INDEPTH) study was a multi-site survey using electronic data collection in five INDEPTH health and demographic surveillance system sites. METHODS: We described experiences and learning involved in the design and implementation of the EN-INDEPTH survey, and undertook six focus group discussions with field and research team to explore their experiences. Thematic analyses were conducted in NVivo12 using an iterative process guided by a priori themes. RESULTS: Five steps of the process of selecting, adapting and implementing electronic data collection in the EN-INDEPTH study are described. Firstly, we reviewed possible electronic data collection platforms, and selected the World Bank's Survey Solutions® as the most suited for the EN-INDEPTH study. Secondly, the survey questionnaire was coded and translated into local languages, and further context-specific adaptations were made. Thirdly, data collectors were selected and trained using standardised manual. Training varied between 4.5 and 10 days. Fourthly, instruments were piloted in the field and the questionnaires finalised. During data collection, data collectors appreciated the built-in skip patterns and error messages. Internet connection unreliability was a challenge, especially for data synchronisation. For the fifth and final step, data management and analyses, it was considered that data quality was higher and less time was spent on data cleaning. The possibility to use paradata to analyse survey timing and corrections was valued. Synchronisation and data transfer should be given special consideration. CONCLUSION: We synthesised experiences using electronic data collection in a multi-site household survey, including perceived advantages and challenges. Our recommendations for others considering electronic data collection include ensuring adaptations of tools to local context, piloting/refining the questionnaire in one site first, buying power banks to mitigate against power interruption and paying attention to issues such as GPS tracking and synchronisation, particularly in settings with poor internet connectivity.
Entities:
Keywords:
DHS; Data collection application; Electronic data collection; Field experiences; Household surveys