Extent of Open Science Practices in the Reporting of Real World Evidence Research

Introduction: Open sharing of research methods and software code is fundamental to open science principles and reproducible research practices and has long been the norm in some scientific disciplines. Increasingly, scientific publishers are introducing policies to encourage or mandate sharing of research protocols and analytical code. Code sharing is especially important when research data cannot be shared, as is often the case in research using population data. However, the prevalence of protocol and code sharing in population data science research has been underexplored. Objectives: To assess open science practice usage by authors in real world evidence (RWE) research published in the International Journal of Population Data Science (IJPDS). Method: We reviewed RWE research articles publishing estimates of associations in the IJPDS from January 2019 to October 2024. We determined the proportion of published articles reporting (i) a link to a study protocol, (ii) a link to a pre-registered study protocol, (iii) a statement about the availability of the data, (iv) a link to the analytical code, and (iv) reference to a reporting checklist or guideline. Results: None of the 41 eligible articles met all five open science domains. One article included a link to the study protocol and none cited a pre-registered protocol. Fourteen (34%) articles included a statement about data availability. No articles included a link to the analytical code, although one included it in supplementary material and two indicated availability on request. Five (12%) articles referred to using a reporting checklist. There was no clear evidence of increasing adoption of open science practices over time. Conclusions: Researcher alignment with international best practice for open science was poor among RWE articles published in IJPDS. Potential solutions to encourage an open science culture include increasing awareness through training and education, building Communities of Practice, providing incentives and implementing open science publication policies.

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Publication Details

Journal
International Journal for Population Data Science
Published
2026-04-16
DOI
https://doi.org/10.23889/ijpds.v10i2.2960
Primary Topic
Research Data Management Practices
Type
article
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article

Extent of Open Science Practices in the Reporting of Real World Evidence Research

Tom Honeyman, Claire Melissa Vajdic, Lillian Liu, Nahee Kim et al.
International Journal for Population Data Science
Research Data Management Practices
article

Extent of Open Science Practices in the Reporting of Real World Evidence Research

Tom Honeyman, Claire Melissa Vajdic, Lillian Liu, Nahee Kim, Louisa Jorm
article en

Abstract

Introduction: Open sharing of research methods and software code is fundamental to open science principles and reproducible research practices and has long been the norm in some scientific disciplines. Increasingly, scientific publishers are introducing policies to encourage or mandate sharing of research protocols and analytical code. Code sharing is especially important when research data cannot be shared, as is often the case in research using population data. However, the prevalence of protocol and code sharing in population data science research has been underexplored. Objectives: To assess open science practice usage by authors in real world evidence (RWE) research published in the International Journal of Population Data Science (IJPDS). Method: We reviewed RWE research articles publishing estimates of associations in the IJPDS from January 2019 to October 2024. We determined the proportion of published articles reporting (i) a link to a study protocol, (ii) a link to a pre-registered study protocol, (iii) a statement about the availability of the data, (iv) a link to the analytical code, and (iv) reference to a reporting checklist or guideline. Results: None of the 41 eligible articles met all five open science domains. One article included a link to the study protocol and none cited a pre-registered protocol. Fourteen (34%) articles included a statement about data availability. No articles included a link to the analytical code, although one included it in supplementary material and two indicated availability on request. Five (12%) articles referred to using a reporting checklist. There was no clear evidence of increasing adoption of open science practices over time. Conclusions: Researcher alignment with international best practice for open science was poor among RWE articles published in IJPDS. Potential solutions to encourage an open science culture include increasing awareness through training and education, building Communities of Practice, providing incentives and implementing open science publication policies.

International Journal for Population Data ScienceVol. 10(2)
University of Technology Sydney (AU), UNSW Sydney (AU), New South Wales Institute of Psychiatry (AU)
Openalex Percentile: Top 10%
Research Data Management Practices
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