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Prioritising measures and interventions to strengthen research reproducibility: a Delphi consultation study
Dora Pejdo1, Ivan Buljan2, Ana Marušić3
1Department of Research in Biomedicine and Health and Center for Evidence-Based Medicine, School of Medicine, University of Split, Split, Croatia. dora.pejdo@mefst.hr.
Experts reached consensus on key practices to improve research reproducibility. Prioritized measures include data/code availability and methodological transparency, while interventions focus on training and data sharing policies.
Area of Science:
- Scientific integrity and research methodology.
- Enhancing the reliability of scientific evidence.
Background:
- Research reproducibility is crucial for scientific integrity and trust in evidence.
- Lack of consensus on prioritizing reproducibility measures and interventions hinders progress.
- This study aimed to establish expert consensus on key practices to strengthen research reproducibility.
Purpose of the Study:
- To identify and prioritize essential reproducibility measures and interventions.
- To achieve expert consensus on actionable steps for improving research reproducibility.
- To inform future strategies for enhancing the reliability of scientific findings.
Main Methods:
- A Delphi consensus study involving experts from five stakeholder groups.
- Two online survey rounds followed by a virtual consensus panel.
- Consensus defined as at least 70% agreement on high-priority scores (8-10 on a 10-point Likert scale).
Main Results:
- Consensus reached on eight reproducibility measures and six reproducibility interventions.
- Prioritized measures: methodological and reporting quality, data/code availability, computational reproducibility, transparency, trial registration.
- Prioritized interventions: data management and statistical training, data quality checks, data sharing policies, protocol registration.
Conclusions:
- The identified measures and interventions offer a framework for enhancing research reproducibility across disciplines.
- Findings can guide the development of training programs and institutional policies.
- Informs future empirical evaluations of these practices in diverse research contexts.
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