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Bridging research integrity and global health epidemiology (BRIDGE) statement: guidelines for good epidemiological practice

<p>Research integrity and research fairness have gained considerable momentum in the past decade and have direct implications for global health epidemiology. Research integrity and research fairness principles should be equally nurtured to produce high quality impactful research &ndash; but bridging the two can lead to practical and ethical dilemmas. In order to provide practical guidance to researchers and epidemiologist, we set out to develop good epidemiological practice guidelines specifically for global health epidemiology, &nbsp;&nbsp;targeted at stakeholders involved in the commissioning, conduct, appraisal and publication of global health research.</p> <p>We developed preliminary guidelines based on targeted online searches on existing best practices for epidemiological studies and sought to align these with key elements of global health research and research fairness. We validated these guidelines through a Delphi consultation study, to reach a consensus among a wide representation of stakeholders.&nbsp;</p> <p>A total of 45 experts provided input on the first round of GEP e-Delphi consultation, and 40 in the second. Respondents covered a range of organisations (including for example academia, ministries, NGOs, research funders, technical agencies) involved in epidemiological studies from countries around the world.&nbsp;A selection of eight experts were invited for a face-to-face meeting. The final guidelines consists of a set of six standards and 42 accompanying criteria including study preparation, study protocol and ethical review, data collection, data management, analysis, reporting and dissemination.</p> <p>This database only includes anonymised responses of participants who agreed to their data being shared in this depository , i.e.19 out of the 45 (Round 1) and 40 (Round 2) participants.&nbsp;</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
0
Engagement
4

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