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How do we measure the costs, benefits, and harms of sharing data from biomedical studies? A protocol for a scoping
Lauren Maxwell1, Priya Shreedhar1, Ankur Krishnan1
1Heidelberger Institut für Global Health, Universitätsklinikum Heidelberg, Heidelberg, Baden-Württemberg, 69120, Germany.
Introduction:
The benefits of sharing participant-level data, including clinical or epidemiological data, genomic data, high-dimensional imaging data, or human-derived samples, from biomedical studies have been widely touted and may be taken for granted. As investments in data sharing and reuse efforts continue to grow, understanding the cost and positive and negative effects of data sharing for research participants, the general public, individual researchers, research and development, clinical practice, and public health is of growing importance. In this scoping review, we will identify and summarize existing evidence on the positive and negative impacts and costs of data sharing and how they are measured.
Methods And Analysis:
Eligible studies will report on qualitative or quantitative approaches for measuring the cost of data sharing or its impact on participant privacy, individual or public health, researcher's careers, clinical or public health practice, or research or development. The systematic search strategy uses MeSH and text terms and is tailored for Ovid Medline, Cumulative Index to Nursing and Allied Health Literature, and Web of Science. We will apply the Arskey and O'Malley scoping review methodology. We selected a scoping rather than a systematic review approach to address multiple related questions and provide guidance related to an emerging field. Two reviewers will conduct the title-abstract and full-text screening and data charting independently. Discrepancies will be resolved through consensus and results will be summarized in a narrative form.
Conclusion:
Research participants, investigators, regulatory groups, ethics review committees, data protection officers, and funders cannot make informed decisions or policies about data reuse without appropriate means of measuring the effects, positive or negative, and cost of data sharing.
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