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Development of a Methodological Quality Criteria List for Observational Studies: The Observational Study Quality Evaluation
Background: Existing study quality and risk of bias lists for observational studies have important disadvantages. For this reason, a comprehensive widely applicable quality assessment tool for observational studies was developed. Methods: Criteria from three quality lists were merged into a new qual...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317224/ https://www.ncbi.nlm.nih.gov/pubmed/34337310 http://dx.doi.org/10.3389/frma.2021.675071 |
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author | Drukker, Marjan Weltens, Irene van Hooijdonk, Carmen F. M. Vandenberk, Emma Bak, Maarten |
author_facet | Drukker, Marjan Weltens, Irene van Hooijdonk, Carmen F. M. Vandenberk, Emma Bak, Maarten |
author_sort | Drukker, Marjan |
collection | PubMed |
description | Background: Existing study quality and risk of bias lists for observational studies have important disadvantages. For this reason, a comprehensive widely applicable quality assessment tool for observational studies was developed. Methods: Criteria from three quality lists were merged into a new quality assessment tool: the observational study quality evaluation (OSQE). OSQE consists of a cohort, case–control, and cross-sectional version. Results: The OSQE cohort, the OSQE case–control, and the OSQE cross-sectional version include all items applicable to that type of study, for example, the representativeness of the study population, the validity of the independent and dependent variables, and the statistical methods used. Before scoring the OSQE, the rater is asked to define how to score items, in detail. A study can obtain a star for each item. Each item also has a veto cell. This cell can be checked when poor quality with respect to that specific item results in a low quality of the study despite stars on other items. Although stars add to a sum score, the comment field is the most important part of the OSQE. Conclusion: The OSQE presented in the current article provides a short, comprehensive, and widely applicable list to assess study quality and therewith risk of bias. |
format | Online Article Text |
id | pubmed-8317224 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83172242021-07-29 Development of a Methodological Quality Criteria List for Observational Studies: The Observational Study Quality Evaluation Drukker, Marjan Weltens, Irene van Hooijdonk, Carmen F. M. Vandenberk, Emma Bak, Maarten Front Res Metr Anal Research Metrics and Analytics Background: Existing study quality and risk of bias lists for observational studies have important disadvantages. For this reason, a comprehensive widely applicable quality assessment tool for observational studies was developed. Methods: Criteria from three quality lists were merged into a new quality assessment tool: the observational study quality evaluation (OSQE). OSQE consists of a cohort, case–control, and cross-sectional version. Results: The OSQE cohort, the OSQE case–control, and the OSQE cross-sectional version include all items applicable to that type of study, for example, the representativeness of the study population, the validity of the independent and dependent variables, and the statistical methods used. Before scoring the OSQE, the rater is asked to define how to score items, in detail. A study can obtain a star for each item. Each item also has a veto cell. This cell can be checked when poor quality with respect to that specific item results in a low quality of the study despite stars on other items. Although stars add to a sum score, the comment field is the most important part of the OSQE. Conclusion: The OSQE presented in the current article provides a short, comprehensive, and widely applicable list to assess study quality and therewith risk of bias. Frontiers Media S.A. 2021-07-14 /pmc/articles/PMC8317224/ /pubmed/34337310 http://dx.doi.org/10.3389/frma.2021.675071 Text en Copyright © 2021 Drukker, Weltens, van Hooijdonk, Vandenberk and Bak. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Research Metrics and Analytics Drukker, Marjan Weltens, Irene van Hooijdonk, Carmen F. M. Vandenberk, Emma Bak, Maarten Development of a Methodological Quality Criteria List for Observational Studies: The Observational Study Quality Evaluation |
title | Development of a Methodological Quality Criteria List for Observational Studies: The Observational Study Quality Evaluation |
title_full | Development of a Methodological Quality Criteria List for Observational Studies: The Observational Study Quality Evaluation |
title_fullStr | Development of a Methodological Quality Criteria List for Observational Studies: The Observational Study Quality Evaluation |
title_full_unstemmed | Development of a Methodological Quality Criteria List for Observational Studies: The Observational Study Quality Evaluation |
title_short | Development of a Methodological Quality Criteria List for Observational Studies: The Observational Study Quality Evaluation |
title_sort | development of a methodological quality criteria list for observational studies: the observational study quality evaluation |
topic | Research Metrics and Analytics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8317224/ https://www.ncbi.nlm.nih.gov/pubmed/34337310 http://dx.doi.org/10.3389/frma.2021.675071 |
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