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      The ethical and legal landscape of brain data governance

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      PLOS ONE
      Public Library of Science

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          Abstract

          Neuroscience research is producing big brain data which informs both advancements in neuroscience research and drives the development of advanced datasets to provide advanced medical solutions. These brain data are produced under different jurisdictions in different formats and are governed under different regulations. The governance of data has become essential and critical resulting in the development of various governance structures to ensure that the quality, availability, findability, accessibility, usability, and utility of data is maintained. Furthermore, data governance is influenced by various ethical and legal principles. However, it is still not clear what ethical and legal principles should be used as a standard or baseline when managing brain data due to varying practices and evolving concepts. Therefore, this study asks what ethical and legal principles shape the current brain data governance landscape? A systematic scoping review and thematic analysis of articles focused on biomedical, neuro and brain data governance was carried out to identify the ethical and legal principles which shape the current brain data governance landscape. The results revealed that there is currently a large variation of how the principles are presented and discussions around the terms are very multidimensional. Some of the principles are still at their infancy and are barely visible. A range of principles emerged during the thematic analysis providing a potential list of principles which can provide a more comprehensive framework for brain data governance and a conceptual expansion of neuroethics.

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          The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

          The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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            PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation

            Scoping reviews, a type of knowledge synthesis, follow a systematic approach to map evidence on a topic and identify main concepts, theories, sources, and knowledge gaps. Although more scoping reviews are being done, their methodological and reporting quality need improvement. This document presents the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) checklist and explanation. The checklist was developed by a 24-member expert panel and 2 research leads following published guidance from the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network. The final checklist contains 20 essential reporting items and 2 optional items. The authors provide a rationale and an example of good reporting for each item. The intent of the PRISMA-ScR is to help readers (including researchers, publishers, commissioners, policymakers, health care providers, guideline developers, and patients or consumers) develop a greater understanding of relevant terminology, core concepts, and key items to report for scoping reviews.
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              A typology of reviews: an analysis of 14 review types and associated methodologies.

              The expansion of evidence-based practice across sectors has lead to an increasing variety of review types. However, the diversity of terminology used means that the full potential of these review types may be lost amongst a confusion of indistinct and misapplied terms. The objective of this study is to provide descriptive insight into the most common types of reviews, with illustrative examples from health and health information domains. Following scoping searches, an examination was made of the vocabulary associated with the literature of review and synthesis (literary warrant). A simple analytical framework -- Search, AppraisaL, Synthesis and Analysis (SALSA) -- was used to examine the main review types. Fourteen review types and associated methodologies were analysed against the SALSA framework, illustrating the inputs and processes of each review type. A description of the key characteristics is given, together with perceived strengths and weaknesses. A limited number of review types are currently utilized within the health information domain. Few review types possess prescribed and explicit methodologies and many fall short of being mutually exclusive. Notwithstanding such limitations, this typology provides a valuable reference point for those commissioning, conducting, supporting or interpreting reviews, both within health information and the wider health care domain.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                29 December 2022
                2022
                : 17
                : 12
                : e0273473
                Affiliations
                [001] Centre for Computing and Social Responsibility, De Montfort University, Leicester, United Kingdom
                University of Oregon, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-4853-6547
                https://orcid.org/0000-0002-4058-4456
                Article
                PONE-D-22-00318
                10.1371/journal.pone.0273473
                9799320
                36580464
                264e7662-9840-4d49-81d3-8ab233e7270a
                © 2022 Ochang et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 16 January 2022
                : 9 August 2022
                Page count
                Figures: 2, Tables: 1, Pages: 29
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100010661, Horizon 2020 Framework Programme;
                Award ID: No. 945539 (HBP SGA3)
                Award Recipient :
                This work was supported by the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreements No. 945539 (HBP SGA3). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
                Categories
                Research Article
                Science Policy
                Research Integrity
                Research Ethics
                Biology and Life Sciences
                Neuroscience
                Computer and Information Sciences
                Data Management
                Biology and Life Sciences
                Bioethics
                Science Policy
                Bioethics
                Biology and Life Sciences
                Computational Biology
                Computational Neuroscience
                Coding Mechanisms
                Biology and Life Sciences
                Neuroscience
                Computational Neuroscience
                Coding Mechanisms
                Biology and Life Sciences
                Bioethics
                Scientific Beneficence
                Science Policy
                Bioethics
                Scientific Beneficence
                Social Sciences
                Law and Legal Sciences
                Research and Analysis Methods
                Database and Informatics Methods
                Database Searching
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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