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Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study
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 an...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869213/ https://www.ncbi.nlm.nih.gov/pubmed/33557853 http://dx.doi.org/10.1186/s12963-020-00241-0 |
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author | Gordeev, Vladimir Sergeevich Akuze, Joseph Baschieri, Angela Thysen, Sanne M. Dzabeng, Francis Haider, M. Moinuddin Smuk, Melanie Wild, Michael Lokshin, Michael M. Yitayew, Temesgen Azemeraw Abebe, Solomon Mokonnen Natukwatsa, Davis Gyezaho, Collins Amenga-Etego, Seeba Lawn, Joy E. Blencowe, Hannah |
author_facet | Gordeev, Vladimir Sergeevich Akuze, Joseph Baschieri, Angela Thysen, Sanne M. Dzabeng, Francis Haider, M. Moinuddin Smuk, Melanie Wild, Michael Lokshin, Michael M. Yitayew, Temesgen Azemeraw Abebe, Solomon Mokonnen Natukwatsa, Davis Gyezaho, Collins Amenga-Etego, Seeba Lawn, Joy E. Blencowe, Hannah |
author_sort | Gordeev, Vladimir Sergeevich |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7869213 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78692132021-02-08 Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study Gordeev, Vladimir Sergeevich Akuze, Joseph Baschieri, Angela Thysen, Sanne M. Dzabeng, Francis Haider, M. Moinuddin Smuk, Melanie Wild, Michael Lokshin, Michael M. Yitayew, Temesgen Azemeraw Abebe, Solomon Mokonnen Natukwatsa, Davis Gyezaho, Collins Amenga-Etego, Seeba Lawn, Joy E. Blencowe, Hannah Popul Health Metr Research 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. BioMed Central 2021-02-08 /pmc/articles/PMC7869213/ /pubmed/33557853 http://dx.doi.org/10.1186/s12963-020-00241-0 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Gordeev, Vladimir Sergeevich Akuze, Joseph Baschieri, Angela Thysen, Sanne M. Dzabeng, Francis Haider, M. Moinuddin Smuk, Melanie Wild, Michael Lokshin, Michael M. Yitayew, Temesgen Azemeraw Abebe, Solomon Mokonnen Natukwatsa, Davis Gyezaho, Collins Amenga-Etego, Seeba Lawn, Joy E. Blencowe, Hannah Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study |
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 | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7869213/ https://www.ncbi.nlm.nih.gov/pubmed/33557853 http://dx.doi.org/10.1186/s12963-020-00241-0 |
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