Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study
Abstract Background Paradata are (timestamped) records tracking the process of (electronic) data collection. We analysed paradata from a large household survey of questions capturing pregnancy outcomes to assess performance (timing and correction processes). We examined how paradata can be used to i...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-02-01
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| Series: | Population Health Metrics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12963-020-00241-0 |
| _version_ | 1819178369467547648 |
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| author | Vladimir Sergeevich Gordeev Joseph Akuze Angela Baschieri Sanne M. Thysen Francis Dzabeng M. Moinuddin Haider Melanie Smuk Michael Wild Michael M. Lokshin Temesgen Azemeraw Yitayew Solomon Mokonnen Abebe Davis Natukwatsa Collins Gyezaho Seeba Amenga-Etego Joy E. Lawn Hannah Blencowe the Every Newborn-INDEPTH Study Collaborative Group |
| author_facet | Vladimir Sergeevich Gordeev Joseph Akuze Angela Baschieri Sanne M. Thysen Francis Dzabeng M. Moinuddin Haider Melanie Smuk Michael Wild Michael M. Lokshin Temesgen Azemeraw Yitayew Solomon Mokonnen Abebe Davis Natukwatsa Collins Gyezaho Seeba Amenga-Etego Joy E. Lawn Hannah Blencowe the Every Newborn-INDEPTH Study Collaborative Group |
| author_sort | Vladimir Sergeevich Gordeev |
| collection | DOAJ |
| description | Abstract Background Paradata are (timestamped) records tracking the process of (electronic) data collection. We analysed paradata from a large household survey of questions capturing pregnancy outcomes to assess performance (timing and correction processes). We examined how paradata can be used to inform and improve questionnaire design and survey implementation in nationally representative household surveys, the major source for maternal and newborn health data worldwide. Methods The EN-INDEPTH cross-sectional population-based survey of women of reproductive age in five Health and Demographic Surveillance System sites (in Bangladesh, Guinea-Bissau, Ethiopia, Ghana, and Uganda) randomly compared two modules to capture pregnancy outcomes: full pregnancy history (FPH) and the standard DHS-7 full birth history (FBH+). We used paradata related to answers recorded on tablets using the Survey Solutions platform. We evaluated the difference in paradata entries between the two reproductive modules and assessed which question characteristics (type, nature, structure) affect answer correction rates, using regression analyses. We also proposed and tested a new classification of answer correction types. Results We analysed 3.6 million timestamped entries from 65,768 interviews. 83.7% of all interviews had at least one corrected answer to a question. Of 3.3 million analysed questions, 7.5% had at least one correction. Among corrected questions, the median number of corrections was one, regardless of question characteristics. We classified answer corrections into eight types (no correction, impulsive, flat (simple), zigzag, flat zigzag, missing after correction, missing after flat (zigzag) correction, missing/incomplete). 84.6% of all corrections were judged not to be problematic with a flat (simple) mistake correction. Question characteristics were important predictors of probability to make answer corrections, even after adjusting for respondent’s characteristics and location, with interviewer clustering accounted as a fixed effect. Answer correction patterns and types were similar between FPH and FBH+, as well as the overall response duration. Avoiding corrections has the potential to reduce interview duration and reproductive module completion by 0.4 min. Conclusions The use of questionnaire paradata has the potential to improve measurement and the resultant quality of electronic data. Identifying sections or specific questions with multiple corrections sheds light on typically hidden challenges in the survey’s content, process, and administration, allowing for earlier real-time intervention (e.g.,, questionnaire content revision or additional staff training). Given the size and complexity of paradata, additional time, data management, and programming skills are required to realise its potential. |
| first_indexed | 2024-12-22T21:41:27Z |
| format | Article |
| id | doaj.art-f5f8fa2329d04ca7825a4224c1081d1f |
| institution | Directory Open Access Journal |
| issn | 1478-7954 |
| language | English |
| last_indexed | 2024-12-22T21:41:27Z |
| publishDate | 2021-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Population Health Metrics |
| spelling | doaj.art-f5f8fa2329d04ca7825a4224c1081d1f2022-12-21T18:11:37ZengBMCPopulation Health Metrics1478-79542021-02-0119S111410.1186/s12963-020-00241-0Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH studyVladimir Sergeevich Gordeev0Joseph Akuze1Angela Baschieri2Sanne M. Thysen3Francis Dzabeng4M. Moinuddin Haider5Melanie Smuk6Michael Wild7Michael M. Lokshin8Temesgen Azemeraw Yitayew9Solomon Mokonnen Abebe10Davis Natukwatsa11Collins Gyezaho12Seeba Amenga-Etego13Joy E. Lawn14Hannah Blencowe15the Every Newborn-INDEPTH Study Collaborative GroupInstitute of Population Health Sciences, Queen Mary University of LondonMaternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical MedicineMaternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical MedicineBandim Health ProjectKintampo Health Research CentreHealth Systems and Population Studies Division, icddr,bDepartment of Medical Statistics, London School of Hygiene & Tropical MedicineThe World BankThe World BankDabat Research Centre Health and Demographic Surveillance SystemDabat Research Centre Health and Demographic Surveillance SystemIgangaMayuge Health and Demographic Surveillance System, Makerere University Centre for Health and Population ResearchIgangaMayuge Health and Demographic Surveillance System, Makerere University Centre for Health and Population ResearchKintampo Health Research CentreMaternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical MedicineMaternal, Adolescent, Reproductive & Child Health (MARCH) Centre, London School of Hygiene & Tropical MedicineAbstract Background Paradata are (timestamped) records tracking the process of (electronic) data collection. We analysed paradata from a large household survey of questions capturing pregnancy outcomes to assess performance (timing and correction processes). We examined how paradata can be used to inform and improve questionnaire design and survey implementation in nationally representative household surveys, the major source for maternal and newborn health data worldwide. Methods The EN-INDEPTH cross-sectional population-based survey of women of reproductive age in five Health and Demographic Surveillance System sites (in Bangladesh, Guinea-Bissau, Ethiopia, Ghana, and Uganda) randomly compared two modules to capture pregnancy outcomes: full pregnancy history (FPH) and the standard DHS-7 full birth history (FBH+). We used paradata related to answers recorded on tablets using the Survey Solutions platform. We evaluated the difference in paradata entries between the two reproductive modules and assessed which question characteristics (type, nature, structure) affect answer correction rates, using regression analyses. We also proposed and tested a new classification of answer correction types. Results We analysed 3.6 million timestamped entries from 65,768 interviews. 83.7% of all interviews had at least one corrected answer to a question. Of 3.3 million analysed questions, 7.5% had at least one correction. Among corrected questions, the median number of corrections was one, regardless of question characteristics. We classified answer corrections into eight types (no correction, impulsive, flat (simple), zigzag, flat zigzag, missing after correction, missing after flat (zigzag) correction, missing/incomplete). 84.6% of all corrections were judged not to be problematic with a flat (simple) mistake correction. Question characteristics were important predictors of probability to make answer corrections, even after adjusting for respondent’s characteristics and location, with interviewer clustering accounted as a fixed effect. Answer correction patterns and types were similar between FPH and FBH+, as well as the overall response duration. Avoiding corrections has the potential to reduce interview duration and reproductive module completion by 0.4 min. Conclusions The use of questionnaire paradata has the potential to improve measurement and the resultant quality of electronic data. Identifying sections or specific questions with multiple corrections sheds light on typically hidden challenges in the survey’s content, process, and administration, allowing for earlier real-time intervention (e.g.,, questionnaire content revision or additional staff training). Given the size and complexity of paradata, additional time, data management, and programming skills are required to realise its potential.https://doi.org/10.1186/s12963-020-00241-0SurveyParadataNeonatalNewbornAnswer correction typeSurvey design |
| spellingShingle | Vladimir Sergeevich Gordeev Joseph Akuze Angela Baschieri Sanne M. Thysen Francis Dzabeng M. Moinuddin Haider Melanie Smuk Michael Wild Michael M. Lokshin Temesgen Azemeraw Yitayew Solomon Mokonnen Abebe Davis Natukwatsa Collins Gyezaho Seeba Amenga-Etego Joy E. Lawn Hannah Blencowe the Every Newborn-INDEPTH Study Collaborative Group Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study Population Health Metrics Survey Paradata Neonatal Newborn Answer correction type Survey design |
| title | Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study |
| title_full | Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study |
| title_fullStr | Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study |
| title_full_unstemmed | Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study |
| title_short | Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study |
| title_sort | paradata analyses to inform population based survey capture of pregnancy outcomes en indepth study |
| topic | Survey Paradata Neonatal Newborn Answer correction type Survey design |
| url | https://doi.org/10.1186/s12963-020-00241-0 |
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