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Publication and related biases in health services research: a systematic review of empirical evidence
BACKGROUND: Publication and related biases (including publication bias, time-lag bias, outcome reporting bias and p-hacking) have been well documented in clinical research, but relatively little is known about their presence and extent in health services research (HSR). This paper aims to systematic...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268600/ https://www.ncbi.nlm.nih.gov/pubmed/32487022 http://dx.doi.org/10.1186/s12874-020-01010-1 |
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author | Ayorinde, Abimbola A. Williams, Iestyn Mannion, Russell Song, Fujian Skrybant, Magdalena Lilford, Richard J. Chen, Yen-Fu |
author_facet | Ayorinde, Abimbola A. Williams, Iestyn Mannion, Russell Song, Fujian Skrybant, Magdalena Lilford, Richard J. Chen, Yen-Fu |
author_sort | Ayorinde, Abimbola A. |
collection | PubMed |
description | BACKGROUND: Publication and related biases (including publication bias, time-lag bias, outcome reporting bias and p-hacking) have been well documented in clinical research, but relatively little is known about their presence and extent in health services research (HSR). This paper aims to systematically review evidence concerning publication and related bias in quantitative HSR. METHODS: Databases including MEDLINE, EMBASE, HMIC, CINAHL, Web of Science, Health Systems Evidence, Cochrane EPOC Review Group and several websites were searched to July 2018. Information was obtained from: (1) Methodological studies that set out to investigate publication and related biases in HSR; (2) Systematic reviews of HSR topics which examined such biases as part of the review process. Relevant information was extracted from included studies by one reviewer and checked by another. Studies were appraised according to commonly accepted scientific principles due to lack of suitable checklists. Data were synthesised narratively. RESULTS: After screening 6155 citations, four methodological studies investigating publication bias in HSR and 184 systematic reviews of HSR topics (including three comparing published with unpublished evidence) were examined. Evidence suggestive of publication bias was reported in some of the methodological studies, but evidence presented was very weak, limited in both quality and scope. Reliable data on outcome reporting bias and p-hacking were scant. HSR systematic reviews in which published literature was compared with unpublished evidence found significant differences in the estimated intervention effects or association in some but not all cases. CONCLUSIONS: Methodological research on publication and related biases in HSR is sparse. Evidence from available literature suggests that such biases may exist in HSR but their scale and impact are difficult to estimate for various reasons discussed in this paper. SYSTEMATIC REVIEW REGISTRATION: PROSPERO 2016 CRD42016052333. |
format | Online Article Text |
id | pubmed-7268600 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72686002020-06-07 Publication and related biases in health services research: a systematic review of empirical evidence Ayorinde, Abimbola A. Williams, Iestyn Mannion, Russell Song, Fujian Skrybant, Magdalena Lilford, Richard J. Chen, Yen-Fu BMC Med Res Methodol Research Article BACKGROUND: Publication and related biases (including publication bias, time-lag bias, outcome reporting bias and p-hacking) have been well documented in clinical research, but relatively little is known about their presence and extent in health services research (HSR). This paper aims to systematically review evidence concerning publication and related bias in quantitative HSR. METHODS: Databases including MEDLINE, EMBASE, HMIC, CINAHL, Web of Science, Health Systems Evidence, Cochrane EPOC Review Group and several websites were searched to July 2018. Information was obtained from: (1) Methodological studies that set out to investigate publication and related biases in HSR; (2) Systematic reviews of HSR topics which examined such biases as part of the review process. Relevant information was extracted from included studies by one reviewer and checked by another. Studies were appraised according to commonly accepted scientific principles due to lack of suitable checklists. Data were synthesised narratively. RESULTS: After screening 6155 citations, four methodological studies investigating publication bias in HSR and 184 systematic reviews of HSR topics (including three comparing published with unpublished evidence) were examined. Evidence suggestive of publication bias was reported in some of the methodological studies, but evidence presented was very weak, limited in both quality and scope. Reliable data on outcome reporting bias and p-hacking were scant. HSR systematic reviews in which published literature was compared with unpublished evidence found significant differences in the estimated intervention effects or association in some but not all cases. CONCLUSIONS: Methodological research on publication and related biases in HSR is sparse. Evidence from available literature suggests that such biases may exist in HSR but their scale and impact are difficult to estimate for various reasons discussed in this paper. SYSTEMATIC REVIEW REGISTRATION: PROSPERO 2016 CRD42016052333. BioMed Central 2020-06-01 /pmc/articles/PMC7268600/ /pubmed/32487022 http://dx.doi.org/10.1186/s12874-020-01010-1 Text en © The Author(s) 2020 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 Article Ayorinde, Abimbola A. Williams, Iestyn Mannion, Russell Song, Fujian Skrybant, Magdalena Lilford, Richard J. Chen, Yen-Fu Publication and related biases in health services research: a systematic review of empirical evidence |
title | Publication and related biases in health services research: a systematic review of empirical evidence |
title_full | Publication and related biases in health services research: a systematic review of empirical evidence |
title_fullStr | Publication and related biases in health services research: a systematic review of empirical evidence |
title_full_unstemmed | Publication and related biases in health services research: a systematic review of empirical evidence |
title_short | Publication and related biases in health services research: a systematic review of empirical evidence |
title_sort | publication and related biases in health services research: a systematic review of empirical evidence |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268600/ https://www.ncbi.nlm.nih.gov/pubmed/32487022 http://dx.doi.org/10.1186/s12874-020-01010-1 |
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