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Cengiz N, Kabanda SM, Moodley K. Cross-border data sharing through the lens of research ethics committee members in sub-Saharan Africa. PLoS One 2024; 19:e0303828. [PMID: 38781141 PMCID: PMC11115285 DOI: 10.1371/journal.pone.0303828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 05/01/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Several factors thwart successful data sharing-ambiguous or fragmented regulatory landscapes, conflicting institutional/researcher interests and varying levels of data science-related expertise are among these. Traditional ethics oversight mechanisms and practices may not be well placed to guarantee adequate research oversight given the unique challenges presented by digital technologies and artificial intelligence (AI). Data-intensive research has raised new, contextual ethics and legal challenges that are particularly relevant in an African research setting. Yet, no empirical research has been conducted to explore these challenges. MATERIALS AND METHODS We explored REC members' views and experiences on data sharing by conducting 20 semi-structured interviews online between June 2022 and February 2023. Using purposive sampling and snowballing, we recruited representatives across sub-Saharan Africa (SSA). We transcribed verbatim and thematically analysed the data with Atlas.ti V22. RESULTS Three dominant themes were identified: (i) experiences in reviewing data sharing protocols, (ii) perceptions of data transfer tools and (iii) ethical, legal and social challenges of data sharing. Several sub-themes emerged as: (i.a) frequency of and approaches used in reviewing data sharing protocols, (i.b) practical/technical challenges, (i.c) training, (ii.a) ideal structure of data transfer tools, (ii.b) key elements of data transfer tools, (ii.c) implementation level, (ii.d) key stakeholders in developing and reviewing a data transfer agreement (DTA), (iii.a) confidentiality and anonymity, (iii.b) consent, (iii.c) regulatory frameworks, and (iii.d) stigmatisation and discrimination. CONCLUSIONS Our results indicated variability in REC members' perceptions, suboptimal awareness of the existence of data protection laws and a unanimously expressed need for REC member training. To promote efficient data sharing within and across SSA, guidelines that incorporate ethical, legal and social elements need to be developed in consultation with relevant stakeholders and field experts, along with the training accreditation of REC members in the review of data-intensive protocols.
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Affiliation(s)
- Nezerith Cengiz
- Department of Medicine, Division for Medical Ethics and Law, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Siti M. Kabanda
- Department of Medicine, Division for Medical Ethics and Law, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Keymanthri Moodley
- Department of Medicine, Division for Medical Ethics and Law, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
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Harris J, Germain J, McCoy E, Schofield R. Ethical guidance for conducting health research with online communities: A scoping review of existing guidance. PLoS One 2024; 19:e0302924. [PMID: 38758778 PMCID: PMC11101025 DOI: 10.1371/journal.pone.0302924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 04/15/2024] [Indexed: 05/19/2024] Open
Abstract
Online research methods have grown in popularity due in part to the globalised and far-reaching nature of the internet but also linked to the Covid-19 pandemic whereby restrictions to travel and face to face contact necessitated a shift in methods of research recruitment and data collection. Ethical guidance exists to support researchers in conducting online research, however this is lacking within health fields. This scoping review aims to synthesise formal ethical guidance for applying online methods within health research as well as provide examples of where guidance has been used. A systematic search of literature was conducted, restricted to English language records between 2013 and 2022. Eligibility focused on whether the records were providing ethical guidance or recommendations, were situated or relevant to health disciplines, and involved the use or discussion of online research methods. Following exclusion of ineligible records and duplicate removal, three organisational ethical guidance and 24 research papers were charted and thematically analysed. Four key themes were identified within the guidance documents, 1) consent, 2) confidentiality and privacy, 3) protecting participants from harm and 4) protecting researchers from harm with the research papers describing additional context and understanding around these issues. The review identified that there are currently no specific guidelines aimed at health researchers, with the most cited guidance coming from broader methodological perspectives and disciplines or auxiliary fields. All guidance discussed each of the four key themes within the wider context of sensitive topics and vulnerable populations, areas and issues which are often prominent within health research thus highlighting the need for unifying guidance specific for health researchers. Further research should aim to understand better how online health studies apply ethical principles, to support in informing gaps across both research and guidance.
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Affiliation(s)
- Jane Harris
- Public Health Institute, Liverpool John Moores University, Liverpool, United Kingdom
| | - Jennifer Germain
- Public Health Institute, Liverpool John Moores University, Liverpool, United Kingdom
| | - Ellie McCoy
- Public Health Institute, Liverpool John Moores University, Liverpool, United Kingdom
| | - Rosemary Schofield
- Public Health Institute, Liverpool John Moores University, Liverpool, United Kingdom
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3
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Lakkimsetti M, Devella SG, Patel KB, Dhandibhotla S, Kaur J, Mathew M, Kataria J, Nallani M, Farwa UE, Patel T, Egbujo UC, Meenashi Sundaram D, Kenawy S, Roy M, Khan SF. Optimizing the Clinical Direction of Artificial Intelligence With Health Policy: A Narrative Review of the Literature. Cureus 2024; 16:e58400. [PMID: 38756258 PMCID: PMC11098056 DOI: 10.7759/cureus.58400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/16/2024] [Indexed: 05/18/2024] Open
Abstract
Artificial intelligence (AI) has the ability to completely transform the healthcare industry by enhancing diagnosis, treatment, and resource allocation. To ensure patient safety and equitable access to healthcare, it also presents ethical and practical issues that need to be carefully addressed. Its integration into healthcare is a crucial topic. To realize its full potential, however, the ethical issues around data privacy, prejudice, and transparency, as well as the practical difficulties posed by workforce adaptability and statutory frameworks, must be addressed. While there is growing knowledge about the advantages of AI in healthcare, there is a significant lack of knowledge about the moral and practical issues that come with its application, particularly in the setting of emergency and critical care. The majority of current research tends to concentrate on the benefits of AI, but thorough studies that investigate the potential disadvantages and ethical issues are scarce. The purpose of our article is to identify and examine the ethical and practical difficulties that arise when implementing AI in emergency medicine and critical care, to provide solutions to these issues, and to give suggestions to healthcare professionals and policymakers. In order to responsibly and successfully integrate AI in these important healthcare domains, policymakers and healthcare professionals must collaborate to create strong regulatory frameworks, safeguard data privacy, remove prejudice, and give healthcare workers the necessary training.
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Affiliation(s)
| | - Swati G Devella
- Medicine, Kempegowda Institute of Medical Sciences, Bangalore, IND
| | - Keval B Patel
- Surgery, Narendra Modi Medical College, Ahmedabad, IND
| | | | | | - Midhun Mathew
- Internal Medicine, Trinitas Regional Medical Center, Elizabeth, USA
| | | | - Manisha Nallani
- Medicine, Kamineni Academy of Medical Sciences and Research Center, Hyderabad, IND
| | - Umm E Farwa
- Emergency Medicine, Jinnah Sindh Medical University, Karachi, PAK
| | - Tirath Patel
- Medicine, American University of Antigua, Saint John's, ATG
| | | | - Dakshin Meenashi Sundaram
- Internal Medicine, Employees' State Insurance Corporation (ESIC) Medical College & Post Graduate Institute of Medical Science and Research (PGIMSR), Chennai, IND
| | | | - Mehak Roy
- Internal Medicine, School of Medicine Science and Research, Delhi, IND
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4
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Williams LM, Carpenter WT, Carretta C, Papanastasiou E, Vaidyanathan U. Precision psychiatry and Research Domain Criteria: Implications for clinical trials and future practice. CNS Spectr 2024; 29:26-39. [PMID: 37675453 DOI: 10.1017/s1092852923002420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Psychiatric disorders are associated with significant social and economic burdens, many of which are related to issues with current diagnosis and treatments. The coronavirus (COVID-19) pandemic is estimated to have increased the prevalence and burden of major depressive and anxiety disorders, indicating an urgent need to strengthen mental health systems globally. To date, current approaches adopted in drug discovery and development for psychiatric disorders have been relatively unsuccessful. Precision psychiatry aims to tailor healthcare more closely to the needs of individual patients and, when informed by neuroscience, can offer the opportunity to improve the accuracy of disease classification, treatment decisions, and prevention efforts. In this review, we highlight the growing global interest in precision psychiatry and the potential for the National Institute of Health-devised Research Domain Criteria (RDoC) to facilitate the implementation of transdiagnostic and improved treatment approaches. The need for current psychiatric nosology to evolve with recent scientific advancements and increase awareness in emerging investigators/clinicians of the value of this approach is essential. Finally, we examine current challenges and future opportunities of adopting the RDoC-associated translational and transdiagnostic approaches in clinical studies, acknowledging that the strength of RDoC is that they form a dynamic framework of guiding principles that is intended to evolve continuously with scientific developments into the future. A collaborative approach that recruits expertise from multiple disciplines, while also considering the patient perspective, is needed to pave the way for precision psychiatry that can improve the prognosis and quality of life of psychiatric patients.
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Affiliation(s)
- Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - William T Carpenter
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Evangelos Papanastasiou
- Boehringer Ingelheim Pharma GmbH & Co, Ingelheim am Rhein, Rhineland-Palatinate, Germany
- HMNC Holding GmbH, Wilhelm-Wagenfeld-Strasse 20, 80807Munich, Bavaria, Germany
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5
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Zee TW, Abdul Aziz MFB, Wei PC. Ethical challenges of conducting and reviewing human genomics research in Malaysia: An exploratory study. Dev World Bioeth 2023:10.1111/dewb.12435. [PMID: 37997006 PMCID: PMC11111594 DOI: 10.1111/dewb.12435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/17/2023] [Accepted: 10/24/2023] [Indexed: 11/25/2023]
Abstract
Even though there is a significant amount of scholarly work examining the ethical issues surrounding human genomics research, little is known about its footing in Malaysia. This study aims to explore the experience of local researchers and research ethics committee (REC) members in developing it in Malaysia. In-depth interviews were conducted from April to May 2021, and the data were thematically analysed. In advancing this technology, both genomics researchers and REC members have concerns over how this research is being developed in the country especially the absence of a clear ethical and regulatory framework at the national level as a guidance. However, this study argues that it is not a salient issue as there are international guidelines in existence and both researchers and RECs will benefit from a training on the guidelines to ensure genomics research can be developed in an ethical manner.
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Scheibner J, Kroesche N, Wakefield L, Cockburn T, McPhail SM, Richards B. Does Legislation Impede Data Sharing in Australia Across Institutions and Jurisdictions? A Scoping Review. J Med Syst 2023; 47:116. [PMID: 37962613 DOI: 10.1007/s10916-023-02009-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 10/30/2023] [Indexed: 11/15/2023]
Abstract
In Australia, regulations governing data, including formal legislation and policies promulgated by private and public agencies, are often seen as a barrier to data sharing. This sharing can include between institutions, as well as across jurisdictional borders in a federated jurisdiction such as Australia. In some cases, these regulations place a barrier to sharing data across borders or between institutions without a prerequisite requirement. In other cases, these regulations may be perceived as a justification not to share data. The objective of this review was to analyse published literature from Australia to see what regulations were used to justify not sharing data, along with any other factors that might discourage data sharing. We searched PubMed, Scopus and Web of Science for empirical and policy articles discussing data sharing in Australia. We then filtered these results via abstract and conducted a full text assessment to include 33 articles for analysis. Although there are a few areas of notable regulatory divergence with respect to legislation governing health data, most regulations in Australia are relatively consistent. Further, the absence of uniform ethics approval between sites in different states was frequently cited as a barrier to data sharing.
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Affiliation(s)
- James Scheibner
- College of Business, Government and Law, Flinders University, Adelaide, Australia.
| | - Nicole Kroesche
- Australian Centre for Health Law Research (ACHLR), School of Law, Faculty of Business and Law, Queensland University of Technology, Brisbane, Australia
| | - Luke Wakefield
- Australian Centre for Health Law Research (ACHLR), School of Law, Faculty of Business and Law, Queensland University of Technology, Brisbane, Australia
| | - Tina Cockburn
- Australian Centre for Health Law Research (ACHLR), School of Law, Faculty of Business and Law, Queensland University of Technology, Brisbane, Australia
| | - Steven M McPhail
- Australian Centre for Health Services Innovation (AusHSI) and Centre for Healthcare Transformation, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
- Digital Health and Informatics Directorate, Metro South Health, Brisbane, Australia
| | - Bernadette Richards
- Associate Professor of Ethics and Professionalism, Medical School, Academy for Medical Education, University of Queensland, Brisbane, Australia
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Lissak IA, Edlow BL, Rosenthal E, Young MJ. Ethical Considerations in Neuroprognostication Following Acute Brain Injury. Semin Neurol 2023; 43:758-767. [PMID: 37802121 DOI: 10.1055/s-0043-1775597] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/08/2023]
Abstract
Neuroprognostication following acute brain injury (ABI) is a complex process that involves integrating vast amounts of information to predict a patient's likely trajectory of neurologic recovery. In this setting, critically evaluating salient ethical questions is imperative, and the implications often inform high-stakes conversations about the continuation, limitation, or withdrawal of life-sustaining therapy. While neuroprognostication is central to these clinical "life-or-death" decisions, the ethical underpinnings of neuroprognostication itself have been underexplored for patients with ABI. In this article, we discuss the ethical challenges of individualized neuroprognostication including parsing and communicating its inherent uncertainty to surrogate decision-makers. We also explore the population-based ethical considerations that arise in the context of heterogenous prognostication practices. Finally, we examine the emergence of artificial intelligence-aided neuroprognostication, proposing an ethical framework relevant to both modern and longstanding prognostic tools.
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Affiliation(s)
- India A Lissak
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Eric Rosenthal
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Michael J Young
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
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8
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Dipietro L, Gonzalez-Mego P, Ramos-Estebanez C, Zukowski LH, Mikkilineni R, Rushmore RJ, Wagner T. The evolution of Big Data in neuroscience and neurology. JOURNAL OF BIG DATA 2023; 10:116. [PMID: 37441339 PMCID: PMC10333390 DOI: 10.1186/s40537-023-00751-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 05/08/2023] [Indexed: 07/15/2023]
Abstract
Neurological diseases are on the rise worldwide, leading to increased healthcare costs and diminished quality of life in patients. In recent years, Big Data has started to transform the fields of Neuroscience and Neurology. Scientists and clinicians are collaborating in global alliances, combining diverse datasets on a massive scale, and solving complex computational problems that demand the utilization of increasingly powerful computational resources. This Big Data revolution is opening new avenues for developing innovative treatments for neurological diseases. Our paper surveys Big Data's impact on neurological patient care, as exemplified through work done in a comprehensive selection of areas, including Connectomics, Alzheimer's Disease, Stroke, Depression, Parkinson's Disease, Pain, and Addiction (e.g., Opioid Use Disorder). We present an overview of research and the methodologies utilizing Big Data in each area, as well as their current limitations and technical challenges. Despite the potential benefits, the full potential of Big Data in these fields currently remains unrealized. We close with recommendations for future research aimed at optimizing the use of Big Data in Neuroscience and Neurology for improved patient outcomes. Supplementary Information The online version contains supplementary material available at 10.1186/s40537-023-00751-2.
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Affiliation(s)
| | - Paola Gonzalez-Mego
- Spaulding Rehabilitation/Neuromodulation Lab, Harvard Medical School, Cambridge, MA USA
| | | | | | | | | | - Timothy Wagner
- Highland Instruments, Cambridge, MA USA
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA USA
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9
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McKay F, Williams BJ, Prestwich G, Bansal D, Treanor D, Hallowell N. Artificial intelligence and medical research databases: ethical review by data access committees. BMC Med Ethics 2023; 24:49. [PMID: 37422629 PMCID: PMC10329342 DOI: 10.1186/s12910-023-00927-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 06/22/2023] [Indexed: 07/10/2023] Open
Abstract
BACKGROUND It has been argued that ethics review committees-e.g., Research Ethics Committees, Institutional Review Boards, etc.- have weaknesses in reviewing big data and artificial intelligence research. For instance, they may, due to the novelty of the area, lack the relevant expertise for judging collective risks and benefits of such research, or they may exempt it from review in instances involving de-identified data. MAIN BODY Focusing on the example of medical research databases we highlight here ethical issues around de-identified data sharing which motivate the need for review where oversight by ethics committees is weak. Though some argue for ethics committee reform to overcome these weaknesses, it is unclear whether or when that will happen. Hence, we argue that ethical review can be done by data access committees, since they have de facto purview of big data and artificial intelligence projects, relevant technical expertise and governance knowledge, and already take on some functions of ethical review. That said, like ethics committees, they may have functional weaknesses in their review capabilities. To strengthen that function, data access committees must think clearly about the kinds of ethical expertise, both professional and lay, that they draw upon to support their work. CONCLUSION Data access committees can undertake ethical review of medical research databases provided they enhance that review function through professional and lay ethical expertise.
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Affiliation(s)
- Francis McKay
- Population Health Sciences Institute, University of Newcastle, NE2 4AX Newcastle Upon Tyne, UK
| | - Bethany J. Williams
- National Pathology Imaging Co-operative, Leeds Teaching Hospitals NHS Trust, Leeds, LS9 7TF UK
| | - Graham Prestwich
- Yorkshire and Humber Academic Health Science Network, Unit 1, Calder Close, Calder Park, Wakefield, WF4 3BA UK
| | - Daljeet Bansal
- National Pathology Imaging Co-operative, Leeds Teaching Hospitals NHS Trust, Leeds, LS9 7TF UK
| | - Darren Treanor
- National Pathology Imaging Co-operative, Leeds Teaching Hospitals NHS Trust, Leeds, LS9 7TF UK
- Department of Pathology, University of Leeds, Leeds, UK
- Department of Clinical Pathology, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Nina Hallowell
- The Ethox Centre and the Wellcome Centre for Ethics and Humanities, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF UK
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Muurling M, Pasmooij AMG, Koychev I, Roik D, Froelich L, Schwertner E, Religa D, Abdelnour C, Boada M, Almici M, Galluzzi S, Cardoso S, de Mendonça A, Owens AP, Kuruppu S, Gjestsen MT, Lazarou I, Gkioka M, Tsolaki M, Diaz A, Gove D, Visser PJ, Aarsland D, Lucivero F, de Boer C. Ethical challenges of using remote monitoring technologies for clinical research: A case study of the role of local research ethics committees in the RADAR-AD study. PLoS One 2023; 18:e0285807. [PMID: 37418385 PMCID: PMC10328231 DOI: 10.1371/journal.pone.0285807] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 05/02/2023] [Indexed: 07/09/2023] Open
Abstract
INTRODUCTION Clinical research with remote monitoring technologies (RMTs) has multiple advantages over standard paper-pencil tests, but also raises several ethical concerns. While several studies have addressed the issue of governance of big data in clinical research from the legal or ethical perspectives, the viewpoint of local research ethics committee (REC) members is underrepresented in the current literature. The aim of this study is therefore to find which specific ethical challenges are raised by RECs in the context of a large European study on remote monitoring in all syndromic stages of Alzheimer's disease, and what gaps remain. METHODS Documents describing the REC review process at 10 sites in 9 European countries from the project Remote Assessment of Disease and Relapse-Alzheimer's Disease (RADAR-AD) were collected and translated. Main themes emerging in the documents were identified using a qualitative analysis approach. RESULTS Four main themes emerged after analysis: data management, participant's wellbeing, methodological issues, and the issue of defining the regulatory category of RMTs. Review processes differed across sites: process duration varied from 71 to 423 days, some RECs did not raise any issues, whereas others raised up to 35 concerns, and the approval of a data protection officer was needed in half of the sites. DISCUSSION The differences in the ethics review process of the same study protocol across different local settings suggest that a multi-site study would benefit from a harmonization in research ethics governance processes. More specifically, some best practices could be included in ethical reviews across institutional and national contexts, such as the opinion of an institutional data protection officer, patient advisory board reviews of the protocol and plans for how ethical reflection is embedded within the study.
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Affiliation(s)
- Marijn Muurling
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | | | - Ivan Koychev
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Dora Roik
- Department of Geriatric Psychiatry, Central Institute for Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Lutz Froelich
- Department of Geriatric Psychiatry, Central Institute for Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Emilia Schwertner
- Division of Clinical Geriatrics, Department of Neurobiology, Department of Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Faculty of Psychology, SWPS University of Social Sciences and Humanities, Krakow, Poland
| | - Dorota Religa
- Division of Clinical Geriatrics, Department of Neurobiology, Department of Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Carla Abdelnour
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States of America
| | - Mercè Boada
- Ace Alzheimer Center Barcelona–Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Monica Almici
- Laboratory Alzheimer’s Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Samantha Galluzzi
- Laboratory Alzheimer’s Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Sandra Cardoso
- Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal
| | | | - Andrew P. Owens
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Sajini Kuruppu
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | | | - Ioulietta Lazarou
- Information Technologies Institute, Center for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Greece
| | - Mara Gkioka
- Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI–AUTh), Balkan Center, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Magda Tsolaki
- Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI–AUTh), Balkan Center, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Ana Diaz
- Alzheimer Europe, Luxembourg, Luxembourg
| | | | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Division of Clinical Geriatrics, Department of Neurobiology, Department of Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Dag Aarsland
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Federica Lucivero
- Ethox and Welcome Centre for Ethics and Humanities, University of Oxford, Oxford, United Kingdom
| | - Casper de Boer
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
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Kirana PS, Gudeloglu A, Sansone A, Sokolakis I. Web based research in sexual medicine: a position statement of the European Society for Sexual Medicine. Sex Med 2023; 11:qfad032. [PMID: 37426312 PMCID: PMC10324026 DOI: 10.1093/sexmed/qfad032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/21/2023] [Accepted: 05/26/2023] [Indexed: 07/11/2023] Open
Abstract
Background Although the use of the Web has brought major advances in every step of the research process, this also comes with several methodological challenges. Aim The article presents the European Society for Sexual Medicine's position statements on key methodological concerns relative to Web-based research in sexual medicine. Methods The authors conducted a systematic scoping review of articles using Web-based research methods in sexual medicine. For the creation of the statements, the authors processed the data from the methodology of the studies and formulated the final statements reaching 100% agreement in the group. Outcomes European Society for Sexual Medicine statements were provided on the following domains: definition of the population of interest, selection of the population of interest, data collection quality, response rate, self-reported questionnaire, consent, and legal obligations. Results Researchers should justify the relevance of the Internet population to the population of interest; should clearly describe how they identified study participants; should select and employ specific measures to avoid hoax; should explicitly describe the process of calculation of response and completion rates as well as the relative implications; should validate traditional sexual health questionnaires for online and, if possible, multilingual use; should not ignore consent in Web-based research; and need to be knowledgeable of the technical measures and legal obligations to protect anonymity. Implications Researchers are advised to include trained computer scientists in their group, have a good understanding of their legal obligations as to collecting, storing and disseminating personal data, and design their studies by taking into account the challenges of Web-based research. Strengths and limitations The heterogeneity of the included studies and methodological low quality of most of them was a limitation, which also shows the importance of this study and the need for guidelines regarding Web-based research. Conclusion Large uncontrolled samples could be a threat to the quality of the studies and increase bias if researchers are not mindful of the methodological challenges they would need to account for.
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Affiliation(s)
- Paraskevi-Sofia Kirana
- Corresponding author: Institute for the Study of Urological Diseases, Thessaloniki, Greece.
| | - Ahmet Gudeloglu
- Department of Urology, Hacettepe University Hospital, Ankara, Turkey
| | - Andrea Sansone
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Ioannis Sokolakis
- 2nd Department of Urology, Aristotle University of Thessaloniki, Thessaloniki 54640, Greece
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Douglas J, Winkler D, McLeod A, Oliver S, Gardner K, Supple J, Pearce C. Primary healthcare needs and service utilisation of people with disability: a data linkage protocol. BMJ Open 2023; 13:e068059. [PMID: 37076156 PMCID: PMC10124289 DOI: 10.1136/bmjopen-2022-068059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/21/2023] Open
Abstract
INTRODUCTION General practitioners (GPs) play a crucial role in the early management and treatment of the comorbidities and complications experienced by people with disability. However, GPs experience multiple constraints, including limited time and disability-related expertise. Knowledge gaps around the health needs of people with disability as well as the frequency and extent of their engagement with GPs mean evidence to inform practice is limited. Using a linked dataset, this project aims to enhance the knowledge of the GP workforce by describing the health needs of people with disability. METHODS AND ANALYSIS This project is a retrospective cohort study using general practice health records from the eastern Melbourne region in Victoria, Australia. The research uses Eastern Melbourne Primary Health Network (EMPHN)-owned de-identified primary care data from Outcome Health's POpulation Level Analysis and Reporting Tool (POLAR). The EMPHN POLAR GP health records have been linked with National Disability Insurance Scheme (NDIS) data. Data analysis will involve comparisons across disability groups and the rest of the population to explore utilisation (eg, frequency of visits), clinical and preventative care (eg, cancer screening, blood pressure readings) and health needs (eg, health conditions, medications). Initial analyses will focus on NDIS participants as a whole and NDIS participants whose condition is either an acquired brain injury, stroke, spinal cord injury, multiple sclerosis or cerebral palsy, as classified by the NDIS. ETHICS AND DISSEMINATION Ethics approval was obtained from the Eastern Health Human Research Ethics Committee (E20/001/58261), and approval for the general collection, storage and transfer of data was from the Royal Australian College of General Practitioners National Research Ethics and Evaluation Committee (protocol ID: 17-088). Dissemination mechanisms will include the engagement of stakeholders through reference groups and steering committees, as well as the production of research translation resources in parallel with peer-reviewed publications and conference presentations.
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Affiliation(s)
- Jacinta Douglas
- Research and Innovation, Summer Foundation, Melbourne, Victoria, Australia
- Living with Disability Research Centre, La Trobe University, Melbourne, Victoria, Australia
| | - Di Winkler
- Research and Innovation, Summer Foundation, Melbourne, Victoria, Australia
- Living with Disability Research Centre, La Trobe University, Melbourne, Victoria, Australia
| | - Adam McLeod
- Department of Primary Care Research, Outcome Health, Melbourne, Victoria, Australia
| | - Stacey Oliver
- Research and Innovation, Summer Foundation, Melbourne, Victoria, Australia
- Living with Disability Research Centre, La Trobe University, Melbourne, Victoria, Australia
| | - Karina Gardner
- Department of Primary Care Research, Outcome Health, Melbourne, Victoria, Australia
| | - Jamie Supple
- Department of Primary Care Research, Outcome Health, Melbourne, Victoria, Australia
| | - Christopher Pearce
- Department of Primary Care Research, Outcome Health, Melbourne, Victoria, Australia
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Salerno J, Coughlin SS, Goodman KW, Hlaing WM. Current ethical and social issues in epidemiology. Ann Epidemiol 2023; 80:37-42. [PMID: 36758845 DOI: 10.1016/j.annepidem.2023.02.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 02/01/2023] [Accepted: 02/01/2023] [Indexed: 02/10/2023]
Abstract
PURPOSE The American College of Epidemiology held its 2021 Annual Meeting virtually, September 8-10, with a conference theme of 'From Womb to Tomb: Insights from Health Emergencies'. The American College of Epidemiology Ethics Committee hosted a symposium session in recognition of the ethical and social challenges brought to light by the coronavirus disease 2019 pandemic and on the occasion of the publication of the third edition of the classic text, Ethics and Epidemiology. The American College of Epidemiology Ethics Committee invited the book editor and contributing authors to present at the symposium session titled 'Current Ethical and Social Issues in Epidemiology.' The purpose of this paper is to further highlight the ethical challenges and presentations. METHODS Three speakers with expertise in ethics, health law, health policy, global health, health information technology, and translational research in epidemiology and public health were selected to present on the social and ethical issues in the current landscape. Dr. S Coughlin presented on the 'Ethical and Social Issues in Epidemiology', Dr. L Beskow presented on 'Ethical Challenges in Genetic Epidemiology', and Dr. K Goodman presented on the 'Ethics of Health Informatics'. RESULTS New digital sources of data and technologies are driving the ethical challenges and opportunities in epidemiology and public health as it relates to the three emerging topic areas identified: (1) digital epidemiology, (2) genetic epidemiology, and (3) health informatics. New complexities such as the reliance on social media to control infectious disease outbreaks and the introduction of computing advancements are requiring re-evaluation of traditional bioethical frameworks for epidemiology research and public health practice. We identified several cross-cutting ethical and social issues related to informed consent, benefits, risks and harms, and privacy and confidentiality and summarized these alongside more nuanced ethical considerations such as algorithmic bias, group harms related to data (mis)representation, risks of misinformation, return of genomic research results, maintaining data security, and data sharing. We offered an integrated synthesis of the stages of epidemiology research planning and conduct with the ethical issues that are most relevant in these emerging topic areas. CONCLUSIONS New realities exist for epidemiology and public health as professional groups who are faced with addressing population health, and especially given the recent pandemic and the widespread use of digital tools and technologies. Many ethical issues can be understood in the context of existing ethical frameworks; however, they have yet to be clearly identified or connected with the new technical and methodological applications of digital tools and technologies currently in use for epidemiology research and public health practice. To address current ethical challenges, we offered a synthesis of traditional ethical principles in public health science alongside more nuanced ethical considerations for emerging technologies and aligned these with lifecycle stages of epidemiology research. By critically reflecting on the impact of new digital sources of data and technologies on epidemiology research and public health practice, specifically in the control of infectious outbreaks, we offered insights on cultivating these new areas of professional growth while striving to improve population health.
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Affiliation(s)
- Jennifer Salerno
- Department of Family Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada; Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.
| | - Steven S Coughlin
- Department of Population Health Sciences, Medical College of Georgia, Augusta University, Augusta, GA; Institute of Public and Preventive Health, Augusta University, Augusta, GA
| | - Kenneth W Goodman
- Institute for Bioethics and Health Policy, University of Miami Miller School of Medicine, Miami, FL
| | - WayWay M Hlaing
- Division of Epidemiology and Population Sciences, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL
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Atenas J, Havemann L, Timmermann C. Reframing data ethics in research methods education: a pathway to critical data literacy. INTERNATIONAL JOURNAL OF EDUCATIONAL TECHNOLOGY IN HIGHER EDUCATION 2023; 20:11. [PMID: 36846483 PMCID: PMC9939253 DOI: 10.1186/s41239-023-00380-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 01/16/2023] [Indexed: 06/18/2023]
Abstract
This paper presents an ethical framework designed to support the development of critical data literacy for research methods courses and data training programmes in higher education. The framework we present draws upon our reviews of literature, course syllabi and existing frameworks on data ethics. For this research we reviewed 250 research methods syllabi from across the disciplines, as well as 80 syllabi from data science programmes to understand how or if data ethics was taught. We also reviewed 12 data ethics frameworks drawn from different sectors. Finally, we reviewed an extensive and diverse body of literature about data practices, research ethics, data ethics and critical data literacy, in order to develop a transversal model that can be adopted across higher education. To promote and support ethical approaches to the collection and use of data, ethics training must go beyond securing informed consent to enable a critical understanding of the techno-centric environment and the intersecting hierarchies of power embedded in technology and data. By fostering ethics as a method, educators can enable research that protects vulnerable groups and empower communities.
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Affiliation(s)
- Javiera Atenas
- Centre for Excellence in Learning and Teaching, University of Suffolk, Ipswich, UK
| | - Leo Havemann
- Arena Centre for Research-Based Education, University College London, London, UK
- Institute of Educational Technology, The Open University, Milton Keynes, UK
| | - Cristian Timmermann
- Ethics of Medicine, Medical Faculty, University of Augsburg, Augsburg, Germany
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15
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Slack-Smith L, Arena G. Why and how we can use data linkage in oral health research: a narrative review. Community Dent Oral Epidemiol 2023; 51:75-78. [PMID: 36749677 DOI: 10.1111/cdoe.12815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 08/30/2022] [Accepted: 11/09/2022] [Indexed: 02/08/2023]
Abstract
OBJECTIVES Poor oral health, impacting health and wellbeing across the life-course, is a costly and wicked problem. Data (or record) linkage is the linking of different sets of data (often administrative data gathered for non-research purposes) that are matched to an individual and may include records such as medical data, housing information and sociodemographic information. It often uses population-level data or 'big data'. Data linkage provides the opportunity to analyse complex associations from different sources for total populations. The aim of the paper is to explore data linkage, how it is important for oral health research and what promise it holds for the future. METHODS This is a narrative review of an approach (data linkage) in oral health research. RESULTS Data linkage may be a powerful method for bringing together various population datasets. It has been used to explore a wide variety of topics with many varied datasets. It has substantial current and potential application in oral health research. CONCLUSIONS Use of population data linkage is increasing in oral health research where the approach has been very useful in exploring the complexity of oral health. It offers promise for exploring many new areas in the field.
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Affiliation(s)
- Linda Slack-Smith
- School of Population and Global Health M431, The University of Western Australia, Perth, Western Australia, Australia
| | - Gina Arena
- School of Population and Global Health M431, The University of Western Australia, Perth, Western Australia, Australia
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16
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Favaretto M, De Clercq E, Caplan A, Elger BS. United in Big Data? Exploring scholars' opinions on academic-industry partnership and the use of corporate data in digital behavioral research. PLoS One 2023; 18:e0280542. [PMID: 36662904 PMCID: PMC9858826 DOI: 10.1371/journal.pone.0280542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 01/03/2023] [Indexed: 01/21/2023] Open
Abstract
The growing amount of data produced through digital technologies holds great promise for advancing behavioral research. Scholars worldwide now have the chance to access an incredible amount of personal information, thanks to the digital trace users continuously leave behind them. Private corporations play a crucial role in this scenario as the leading collectors of data on users, thus creating new incentives for partnerships between academic institutions and private companies. Due to the concerns that academic-company partnerships might raise and the ethical issues connected with Big Data research, our study explores the challenges and opportunities associated with the academic use of corporate data. We conducted 39 semi-structured interviews with academic scholars (professors, senior researchers, and postdocs) involved in Big Data research in Switzerland and the United States. We also investigated their opinions on using corporate data for scholarly research. Researchers generally showed an interest in using corporate data; however, they coincidentally shared ethical reservations towards this practice, such as threats to research integrity and concerns about a lack of transparency of companies' practices. Furthermore, participants mentioned issues of scholarly access to corporate data that might both disadvantage the academic research community and create issues of scientific validity. Academic-company partnerships could be a positive development for the advancement of scholarly behavioral research. However, strategies should be implemented to appropriately guide collaborations and appropriate use of corporate data, like implementing updated protocols and tools to govern conflicts of interest and the institution of transparent regulatory bodies to ensure adequate oversight of academic-corporate research collaborations.
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Affiliation(s)
| | - Eva De Clercq
- Institute for Biomedical Ethics, University of Basel, Basel, Switzerland
| | - Arthur Caplan
- Division of Medical Ethics, NYU Grossman School of Medicine, New York, NY, United States of America
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17
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Affiliation(s)
- Marcello Ienca
- Intelligent Systems Group, College of Humanities, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,School of Medicine, Institute of History and Ethics in Medicine, Technical University of Munich, Munich, Germany
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18
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Braunack-Mayer A, Carolan L, Street J, Ha T, Fabrianesi B, Carter S. Ethical issues in big data: A qualitative study comparing responses in the health and higher education sectors. PLoS One 2023; 18:e0282285. [PMID: 37097990 PMCID: PMC10129011 DOI: 10.1371/journal.pone.0282285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 02/13/2023] [Indexed: 04/26/2023] Open
Abstract
INTRODUCTION The health and higher education sectors are increasingly using large administrative datasets for secondary purposes. Both sectors experience ethical challenges in the use of big data. This study identifies and explores how these two sectors are responding to these ethical challenges. OBJECTIVES AND APPROACH Through in-depth qualitative interviews, we asked 18 key Australian stakeholders using or sharing big data in the health and higher education sectors to identify the ethical, social and legal issues associated with big data use and their views on how to build ethical policies in this area. RESULTS There was strong agreement between participants in the two sectors in a number of areas. All participants believed in the benefits of data usage and recognised the importance of privacy, transparency and consent, and the duties for data custodians which followed from these principles. However, there were also significant differences. The participants in the two sectors took different views on what data are for, what benefits data should provide, who should benefit and how, and the imagined unit of analysis for working with data. Broadly, participants from the higher education sector approached these questions with individual students in mind, while health sector informants approached these questions with collectives, groups, or publics in mind. In deciding what to do, the health participants drew principally on a shared toolkit of legislative, regulatory and ethical instruments, and higher education participants on a culture of duties towards individuals. CONCLUSION / IMPLICATIONS The health and higher education sectors are responding to ethical challenges in the use of big data in different, but potentially complementary, ways.
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Affiliation(s)
| | | | | | - Tam Ha
- University of Wollongong, Wollongong, Australia
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Kargl M, Plass M, Müller H. A Literature Review on Ethics for AI in Biomedical Research and Biobanking. Yearb Med Inform 2022; 31:152-160. [PMID: 36463873 PMCID: PMC9719772 DOI: 10.1055/s-0042-1742516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022] Open
Abstract
BACKGROUND Artificial Intelligence (AI) is becoming more and more important especially in datacentric fields, such as biomedical research and biobanking. However, AI does not only offer advantages and promising benefits, but brings about also ethical risks and perils. In recent years, there has been growing interest in AI ethics, as reflected by a huge number of (scientific) literature dealing with the topic of AI ethics. The main objectives of this review are: (1) to provide an overview about important (upcoming) AI ethics regulations and international recommendations as well as available AI ethics tools and frameworks relevant to biomedical research, (2) to identify what AI ethics can learn from findings in ethics of traditional biomedical research - in particular looking at ethics in the domain of biobanking, and (3) to provide an overview about the main research questions in the field of AI ethics in biomedical research. METHODS We adopted a modified thematic review approach focused on understanding AI ethics aspects relevant to biomedical research. For this review, four scientific literature databases at the cross-section of medical, technical, and ethics science literature were queried: PubMed, BMC Medical Ethics, IEEE Xplore, and Google Scholar. In addition, a grey literature search was conducted to identify current trends in legislation and standardization. RESULTS More than 2,500 potentially relevant publications were retrieved through the initial search and 57 documents were included in the final review. The review found many documents describing high-level principles of AI ethics, and some publications describing approaches for making AI ethics more actionable and bridging the principles-to-practice gap. Also, some ongoing regulatory and standardization initiatives related to AI ethics were identified. It was found that ethical aspects of AI implementation in biobanks are often like those in biomedical research, for example with regards to handling big data or tackling informed consent. The review revealed current 'hot' topics in AI ethics related to biomedical research. Furthermore, several published tools and methods aiming to support practical implementation of AI ethics, as well as tools and frameworks specifically addressing complete and transparent reporting of biomedical studies involving AI are described in the review results. CONCLUSIONS The review results provide a practically useful overview of research strands as well as regulations, guidelines, and tools regarding AI ethics in biomedical research. Furthermore, the review results show the need for an ethical-mindful and balanced approach to AI in biomedical research, and specifically reveal the need for AI ethics research focused on understanding and resolving practical problems arising from the use of AI in science and society.
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Affiliation(s)
- Michaela Kargl
- Medical University Graz, Graz, Austria,Correspondence to: Michaela Kargl Medical University GrazAuenbruggerplatz 2 Graz, 8036Austriawww.medunigraz.at
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20
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Stuermer L, Martin R. Characterization of technologies in digital health applied in vision care. JOURNAL OF OPTOMETRY 2022; 15 Suppl 1:S70-S81. [PMID: 36661275 PMCID: PMC9732480 DOI: 10.1016/j.optom.2022.09.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 09/27/2022] [Accepted: 09/29/2022] [Indexed: 06/17/2023]
Abstract
Digital health technology is increasingly becoming part of the evolution of health services, not only for the innovation of equipment but also in support of health processes. Eye health is one of the areas that most explores this field, being a reference in different segments of digital health and the use of applied technological resources. Thus, the purpose of this review was to analyse and characterize the development of research in digital health applied to vision sciences in the last decade. An exploratory-quantitative review of the research based on studies indexed in the SCOPUS database in the last 10 years, which related aspects of digital health technologies with their use within the vision sciences, was conducted. The research results were filtered, including journal articles and excluding those not directly related to vision. The final sample was categorized and classified according to the technology used, the relationship with eye/visual health and its practical applications. A total of 1069 reports were identified (32.09% published since 2021). "Artificial Intelligence" (77.74%) was the most frequent technological tool cited, and posterior segment (68.10%) most eye structure studied, being diabetic retinopathy (27.88%) the main studied disease. The vast majority have potential for clinical use (93.73%), especially those aimed at supporting decision-making. Technologies in digital health in the vision sciences have had a huge growth in recent years, with emphasis on artificial intelligence applied to the posterior segment, but with a low development of studies aimed at using this technology in primary visual care.
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Affiliation(s)
- Leandro Stuermer
- Department of Optometry, University of Contestado, Canoinhas Brazil; Optometry Research Group, IOBA Eye Institute. School of Optometry, University of Valladolid, 47011 Valladolid, Spain
| | - Raul Martin
- Optometry Research Group, IOBA Eye Institute. School of Optometry, University of Valladolid, 47011 Valladolid, Spain; Universidad de Valladolid. Departamento de Física Teórica, Atómica y Óptica. Paseo de Belén, 7 - Campus Miguel Delibes, 47011 Valladolid, Spain.
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21
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Data governance functions to support responsible data stewardship in pediatric radiology research studies using artificial intelligence. Pediatr Radiol 2022; 52:2111-2119. [PMID: 35790559 DOI: 10.1007/s00247-022-05427-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 04/13/2022] [Accepted: 06/06/2022] [Indexed: 03/03/2023]
Abstract
The integration of human and machine intelligence promises to profoundly change the practice of medicine. The rapidly increasing adoption of artificial intelligence (AI) solutions highlights its potential to streamline physician work and optimize clinical decision-making, also in the field of pediatric radiology. Large imaging databases are necessary for training, validating and testing these algorithms. To better promote data accessibility in multi-institutional AI-enabled radiologic research, these databases centralize the large volumes of data required to effect accurate models and outcome predictions. However, such undertakings must consider the sensitivity of patient information and therefore utilize requisite data governance measures to safeguard data privacy and security, to recognize and mitigate the effects of bias and to promote ethical use. In this article we define data stewardship and data governance, review their key considerations and applicability to radiologic research in the pediatric context, and consider the associated best practices along with the ramifications of poorly executed data governance. We summarize several adaptable data governance frameworks and describe strategies for their implementation in the form of distributed and centralized approaches to data management.
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22
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Casati S, Ellul B, Mayrhofer MT, Lavitrano M, Caboux E, Kozlakidis Z. Paediatric biobanking for health: The ethical, legal, and societal landscape. Front Public Health 2022; 10:917615. [PMID: 36238242 PMCID: PMC9551217 DOI: 10.3389/fpubh.2022.917615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 09/06/2022] [Indexed: 01/22/2023] Open
Abstract
Biobanks play a central role in pediatric translational research, which deals primarily with genetic data from sample-based research. However, participation of children in biobanking has received only limited attention in the literature, even though research in general and in clinical trials in particular have a long history in involving minors. So, we resolved to explore specific challenging ethical, legal, and societal issues (ELSI) in the current pediatric biobanking landscape to propose a way forward for biobanking with children as partners in research. Methodologically, we first established the accessibility and utilization of pediatric biobanks, mainly in Europe. This was supported by a literature review related to children's participation, taking into account not only academic papers but also relevant guidelines and best-practices. Our findings are discussed under five themes: general vulnerability; ethical issues-balancing risks and benefits, right to an open future, return of results including secondary findings; legal issues-capacity and legal majority; societal issues-public awareness and empowerment; and responsible research with children. Ultimately, we observed an on-going shift from the parents'/guardians' consent being a sine-qua-non condition to the positive minor's agreement: confirming that the minor is the participant, not the parent(s)/guardian(s). This ethical rethinking is paving the way toward age-appropriate, dynamic and participatory models of involving minors in decision-making. However, we identified a requirement for dynamic tools to assess maturity, a lack of co-produced engagement tools and paucity of shared best practices. We highlight the need to provide empowerment and capability settings to support researchers and biobankers, and back this with practical examples. In conclusion, equipping children and adults with appropriate tools, and ensuring children's participation is at the forefront of responsible pediatric biobanking, is an ethical obligation, and a cornerstone for research integrity.
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Affiliation(s)
- Sara Casati
- ELSI Services & Research Unit, BBMRI-ERIC, Graz, Austria
| | - Bridget Ellul
- Centre for Molecular Medicine & Biobanking, University of Malta, Msida, Malta
| | | | | | - Elodie Caboux
- Laboratory Services and Biobank, International Agency for Research on Cancer, IARC, WHO, Lyon, France
| | - Zisis Kozlakidis
- Laboratory Services and Biobank, International Agency for Research on Cancer, IARC, WHO, Lyon, France
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Sahu M, Gupta R, Ambasta RK, Kumar P. Artificial intelligence and machine learning in precision medicine: A paradigm shift in big data analysis. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2022; 190:57-100. [PMID: 36008002 DOI: 10.1016/bs.pmbts.2022.03.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
The integration of artificial intelligence in precision medicine has revolutionized healthcare delivery. Precision medicine identifies the phenotype of particular patients with less-common responses to treatment. Recent studies have demonstrated that translational research exploring the convergence between artificial intelligence and precision medicine will help solve the most difficult challenges facing precision medicine. Here, we discuss different aspects of artificial intelligence in precision medicine that improve healthcare delivery. First, we discuss how artificial intelligence changes the landscape of precision medicine and the evolution of artificial intelligence in precision medicine. Second, we highlight the synergies between artificial intelligence and precision medicine and promises of artificial intelligence and precision medicine in healthcare delivery. Third, we briefly explain the promise of big data analytics and the integration of nanomaterials in precision medicine. Last, we highlight the challenges and opportunities of artificial intelligence in precision medicine.
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Affiliation(s)
- Mehar Sahu
- Molecular Neuroscience and Functional Genomics Laboratory, Delhi Technological University (Formerly Delhi College of Engineering), Shahbad Daulatpur, Delhi, India
| | - Rohan Gupta
- Molecular Neuroscience and Functional Genomics Laboratory, Delhi Technological University (Formerly Delhi College of Engineering), Shahbad Daulatpur, Delhi, India
| | - Rashmi K Ambasta
- Molecular Neuroscience and Functional Genomics Laboratory, Delhi Technological University (Formerly Delhi College of Engineering), Shahbad Daulatpur, Delhi, India
| | - Pravir Kumar
- Molecular Neuroscience and Functional Genomics Laboratory, Delhi Technological University (Formerly Delhi College of Engineering), Shahbad Daulatpur, Delhi, India.
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Bhartiya S. Glaucoma Screening: Is AI the Answer? J Curr Glaucoma Pract 2022; 16:71-73. [PMID: 36128081 PMCID: PMC9452706 DOI: 10.5005/jp-journals-10078-1380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Affiliation(s)
- Shibal Bhartiya
- Department of Ophthalmology, Glaucoma Services, Fortis Memorial Research Institute, Gurugram, Haryana, India
- Shibal Bhartiya, Department of Ophthalmology, Glaucoma Services, Fortis Memorial Research Institute, Gurugram, Haryana, India, e-mail:
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Ju D, Hui D, Hammond DA, Wonkam A, Tishkoff SA. Importance of Including Non-European Populations in Large Human Genetic Studies to Enhance Precision Medicine. Annu Rev Biomed Data Sci 2022; 5:321-339. [PMID: 35576557 PMCID: PMC9904154 DOI: 10.1146/annurev-biodatasci-122220-112550] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
One goal of genomic medicine is to uncover an individual's genetic risk for disease, which generally requires data connecting genotype to phenotype, as done in genome-wide association studies (GWAS). While there may be clinical promise to employing prediction tools such as polygenic risk scores (PRS), it currently stands that individuals of non-European ancestry may not reap the benefits of genomic medicine because of underrepresentation in large-scale genetics studies. Here, we discuss why this inequity poses a problem for genomic medicine and the reasons for the low transferability of PRS across populations. We also survey the ancestry representation of published GWAS and investigate how estimates of ancestry diversity in GWASparticipants might be biased. We highlight the importance of expanding genetic research in Africa, one of the most underrepresented regions in human genomics research, and discuss issues of ethics, resources, and technology for equitable advancement of genomic medicine.
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Affiliation(s)
- Dan Ju
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
| | - Daniel Hui
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
- Graduate Program in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Dorothy A Hammond
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
- Penn Center for Global Genomics & Health Equity, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ambroise Wonkam
- Division of Human Genetics, Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA;
| | - Sarah A Tishkoff
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Bak M, Madai VI, Fritzsche MC, Mayrhofer MT, McLennan S. You Can't Have AI Both Ways: Balancing Health Data Privacy and Access Fairly. Front Genet 2022; 13:929453. [PMID: 35769991 PMCID: PMC9234328 DOI: 10.3389/fgene.2022.929453] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 05/23/2022] [Indexed: 11/13/2022] Open
Abstract
Artificial intelligence (AI) in healthcare promises to make healthcare safer, more accurate, and more cost-effective. Public and private actors have been investing significant amounts of resources into the field. However, to benefit from data-intensive medicine, particularly from AI technologies, one must first and foremost have access to data. It has been previously argued that the conventionally used “consent or anonymize approach” undermines data-intensive medicine, and worse, may ultimately harm patients. Yet, this is still a dominant approach in European countries and framed as an either-or choice. In this paper, we contrast the different data governance approaches in the EU and their advantages and disadvantages in the context of healthcare AI. We detail the ethical trade-offs inherent to data-intensive medicine, particularly the balancing of data privacy and data access, and the subsequent prioritization between AI and other effective health interventions. If countries wish to allocate resources to AI, they also need to make corresponding efforts to improve (secure) data access. We conclude that it is unethical to invest significant amounts of public funds into AI development whilst at the same time limiting data access through strict privacy measures, as this constitutes a waste of public resources. The “AI revolution” in healthcare can only realise its full potential if a fair, inclusive engagement process spells out the values underlying (trans) national data governance policies and their impact on AI development, and priorities are set accordingly.
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Affiliation(s)
- Marieke Bak
- Department of Ethics, Law and Humanities, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Vince Istvan Madai
- QUEST Center for Responsible Research, Berlin Institute of Health (BIH), Charité Universitätsmedizin Berlin, Berlin, Germany.,School of Computing and Digital Technology, Faculty of Computing, Engineering and the Built Environment, Birmingham City University, Birmingham, United Kingdom
| | - Marie-Christine Fritzsche
- Institute of History and Ethics in Medicine, TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Michaela Th Mayrhofer
- ELSI Services and Research, Biobanking and BioMolecular Resources Research Infrastructure European Research Infrastructure Consortium (BBMRI-ERIC), Graz, Austria
| | - Stuart McLennan
- Institute of History and Ethics in Medicine, TUM School of Medicine, Technical University of Munich, Munich, Germany
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Abstract
Much of precision medicine is driven by big health data research-the analysis of massive datasets representing the complex web of genetic, behavioral, environmental, and other factors that impact human well-being. There are some who point to the Common Rule, the regulation governing federally funded human subjects research, as a regulatory panacea for all types of big health data research. But how well does the Common Rule fit the regulatory needs of this type of research? This article suggests that harms that may arise from artificial intelligence and machine-learning technologies used in big health data research-and the increased likelihood that this research will affect public policy-mean it is time to consider whether the current human research regulations prohibit comprehensive, ethical review of big health data research that may result in group harm.
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Affiliation(s)
| | - Sara Meeder
- Director of Human Research Protections at Maimonides Medical Center
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28
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Wetzel AJ, Koch R, Preiser C, Müller R, Klemmt M, Ranisch R, Ehni HJ, Wiesing U, Rieger MA, Henking T, Joos S. Ethical, Legal, and Social Implications of Symptom Checker Apps in Primary Health Care (CHECK.APP): Protocol for an Interdisciplinary Mixed Methods Study. JMIR Res Protoc 2022; 11:e34026. [PMID: 35576570 PMCID: PMC9152714 DOI: 10.2196/34026] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 02/18/2022] [Accepted: 03/30/2022] [Indexed: 12/19/2022] Open
Abstract
Background Symptom checker apps (SCAs) are accessible tools that provide early symptom assessment for users. The ethical, legal, and social implications of SCAs and their impact on the patient-physician relationship, the health care providers, and the health care system have sparsely been examined. This study protocol describes an approach to investigate the possible impacts and implications of SCAs on different levels of health care provision. It considers the perspectives of the users, nonusers, general practitioners (GPs), and health care experts. Objective We aim to assess a comprehensive overview of the use of SCAs and address problematic issues, if any. The primary outcomes of this study are empirically informed multi-perspective recommendations for different stakeholders on the ethical, legal, and social implications of SCAs. Methods Quantitative and qualitative methods will be used in several overlapping and interconnected study phases. In study phase 1, a comprehensive literature review will be conducted to assess the ethical, legal, social, and systemic impacts of SCAs. Study phase 2 comprises a survey that will be analyzed with a logistic regression. It aims to assess the user degree of SCAs in Germany as well as the predictors for SCA usage. Study phase 3 will investigate self-observational diaries and user interviews, which will be analyzed as integrated cases to assess user perspectives, usage pattern, and arising problems. Study phase 4 will comprise GP interviews to assess their experiences, perspectives, self-image, and concepts and will be analyzed with the basic procedure by Kruse. Moreover, interviews with health care experts will be conducted in study phase 3 and will be analyzed by using the reflexive thematical analysis approach of Braun and Clark. Results Study phase 1 will be completed in November 2021. We expect the results of study phase 2 in December 2021 and February 2022. In study phase 3, interviews are currently being conducted. The final study endpoint will be in February 2023. Conclusions The possible ethical, legal, social, and systemic impacts of a widespread use of SCAs that affect stakeholders and stakeholder groups on different levels of health care will be identified. The proposed methodological approach provides a multifaceted and diverse empirical basis for a broad discussion on these implications. Trial Registration German Clinical Trials Register (DRKS) DRKS00022465; https://tinyurl.com/yx53er67 International Registered Report Identifier (IRRID) DERR1-10.2196/34026
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Affiliation(s)
- Anna-Jasmin Wetzel
- Institute of General Practice and Interprofessional Care, University Hospital Tübingen, Tübingen, Germany
| | - Roland Koch
- Institute of General Practice and Interprofessional Care, University Hospital Tübingen, Tübingen, Germany
| | - Christine Preiser
- Institute of Occupational and Social Medicine and Health Services Research, University Hospital Tübingen, Tübingen, Germany
| | - Regina Müller
- Institute of Ethics and History of Medicine, University Tübingen, Tübingen, Germany
| | - Malte Klemmt
- Institute of Applied Social Science, University of Applied Science Würzburg-Schweinfurt, Würzburg, Germany
| | - Robert Ranisch
- Faculty of Health Science Brandenburg, University of Potsdam, Potsdam, Germany
| | - Hans-Jörg Ehni
- Institute of Ethics and History of Medicine, University Tübingen, Tübingen, Germany
| | - Urban Wiesing
- Institute of Ethics and History of Medicine, University Tübingen, Tübingen, Germany
| | - Monika A Rieger
- Institute of Occupational and Social Medicine and Health Services Research, University Hospital Tübingen, Tübingen, Germany
| | - Tanja Henking
- Institute of Applied Social Science, University of Applied Science Würzburg-Schweinfurt, Würzburg, Germany
| | - Stefanie Joos
- Institute of General Practice and Interprofessional Care, University Hospital Tübingen, Tübingen, Germany
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29
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Spranger J, Niederberger M. Big Data in der Gesundheitsförderung und Prävention. PRÄVENTION UND GESUNDHEITSFÖRDERUNG 2022. [PMCID: PMC8247614 DOI: 10.1007/s11553-021-00871-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Zusammenfassung
Hintergrund
Die Nutzung großer und vielfältiger Datenmengen (Big Data) kann zur Gewinnung gesundheitsbezogener Erkenntnisse führen. Die Relevanz untermauern aktuelle Erfordernisse, bspw. in Zusammenhang mit der Digitalisierung, der Gesundheitsversorgung in Ausnahmesituationen und der zunehmenden Bedeutung von Personalisierungsprozessen in der Gesundheitsforschung. Das Potenzial von Big Data zur Erforschung vulnerabler Gruppen ist strittig, jedoch vor dem Hintergrund relativ stabiler sozialbedingter gesundheitlicher Ungleichheit besonders relevant.
Ziel der Arbeit
In der Studie wird untersucht, wie Expert*innen im Bereich der Analyse von Gesundheitsdaten das Potenzial von Big Data in der Gesundheitsförderung und Prävention, insbesondere zur Erforschung vulnerabler Gruppen, einschätzen.
Material und Methode
In einer Delphi-Studie wurden Expert*innen in zwei Runden mit einem Onlinefragebogen befragt, um Konsens und Dissens über das Potenzial von Big Data zu identifizieren.
Ergebnisse und Schlussfolgerung
Aus Sicht der Expert*innen birgt Big Data ein Potenzial für die Gesundheitsförderung und Prävention, insbesondere im klinischen Setting und durch die Personalisierung gesundheitsbezogener Maßnahmen. Vor allem Menschen mit seltenen Erkrankungen und ältere Personen könnten durch Big-Data-Analysen profitieren, bspw. durch beschleunigte Diagnoseprozesse oder personalisierte digitale Gesundheitsanwendungen. Uneinig sind sich die Expert*innen über den Umfang, in welchem es Forschungseinrichtungen, Krankenversicherungen oder Unternehmen, erlaubt sein soll, derartige Daten zu nutzen oder zu teilen.
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Affiliation(s)
- Julia Spranger
- Forschungsmethoden in der Gesundheitsförderung und Prävention, Pädagogische Hochschule Schwäbisch Gmünd, Oberbettringer Straße 200, 73525 Schwäbisch Gmünd, Deutschland
| | - Marlen Niederberger
- Forschungsmethoden in der Gesundheitsförderung und Prävention, Pädagogische Hochschule Schwäbisch Gmünd, Oberbettringer Straße 200, 73525 Schwäbisch Gmünd, Deutschland
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30
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McLennan S, Rachut S, Lange J, Fiske A, Heckmann D, Buyx A. Practices and attitudes of Bavarian stakeholders regarding the secondary-use of health data for research purposes during the COVID-19 pandemic: a qualitative interview study (Preprint). J Med Internet Res 2022; 24:e38754. [PMID: 35696598 PMCID: PMC9239567 DOI: 10.2196/38754] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 05/28/2022] [Accepted: 05/29/2022] [Indexed: 01/14/2023] Open
Abstract
Background The COVID-19 pandemic is a threat to global health and requires collaborative health research efforts across organizations and countries to address it. Although routinely collected digital health data are a valuable source of information for researchers, benefiting from these data requires accessing and sharing the data. Health care organizations focusing on individual risk minimization threaten to undermine COVID-19 research efforts, and it has been argued that there is an ethical obligation to use the European Union’s General Data Protection Regulation (GDPR) scientific research exemption during the COVID-19 pandemic to support collaborative health research. Objective This study aims to explore the practices and attitudes of stakeholders in the German federal state of Bavaria regarding the secondary use of health data for research purposes during the COVID-19 pandemic, with a specific focus on the GDPR scientific research exemption. Methods Individual semistructured qualitative interviews were conducted between December 2020 and January 2021 with a purposive sample of 17 stakeholders from 3 different groups in Bavaria: researchers involved in COVID-19 research (n=5, 29%), data protection officers (n=6, 35%), and research ethics committee representatives (n=6, 35%). The transcripts were analyzed using conventional content analysis. Results Participants identified systemic challenges in conducting collaborative secondary-use health data research in Bavaria; secondary health data research generally only happens when patient consent has been obtained, or the data have been fully anonymized. The GDPR research exemption has not played a significant role during the pandemic and is currently seldom and restrictively used. Participants identified 3 key groups of barriers that led to difficulties: the wider ecosystem at many Bavarian health care organizations, legal uncertainty that leads to risk-adverse approaches, and ethical positions that patient consent ought to be obtained whenever possible to respect patient autonomy. To improve health data research in Bavaria and across Germany, participants wanted greater legal certainty regarding the use of pseudonymized data for research purposes without the patient’s consent. Conclusions The current balance between enabling the positive goals of health data research and avoiding associated data protection risks is heavily skewed toward avoiding risks; so much so that it makes reaching the goals of health data research extremely difficult. This is important, as it is widely recognized that there is an ethical imperative to use health data to improve care. The current approach also creates a problematic conflict with the ambitions of Germany, and the federal state of Bavaria, to be a leader in artificial intelligence. A recent development in the field of German public administration known as norm screening (Normenscreening) could potentially provide a systematic approach to minimize legal barriers. This approach would likely be beneficial to other countries.
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Affiliation(s)
- Stuart McLennan
- Institute of History and Ethics in Medicine, TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Sarah Rachut
- TUM Center for Digital Public Services, Department Governance, TUM School of Social Sciences and Technology, Technical University of Munich, Munich, Germany
| | - Johannes Lange
- Institute of History and Ethics in Medicine, TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Amelia Fiske
- Institute of History and Ethics in Medicine, TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Dirk Heckmann
- TUM Center for Digital Public Services, Department Governance, TUM School of Social Sciences and Technology, Technical University of Munich, Munich, Germany
| | - Alena Buyx
- Institute of History and Ethics in Medicine, TUM School of Medicine, Technical University of Munich, Munich, Germany
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31
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Shen FX, Silverman BC, Monette P, Kimble S, Rauch SL, Baker JT. An Ethics Checklist for Digital Health Research in Psychiatry: Viewpoint. J Med Internet Res 2022; 24:e31146. [PMID: 35138261 PMCID: PMC8867294 DOI: 10.2196/31146] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 08/23/2021] [Accepted: 10/29/2021] [Indexed: 01/23/2023] Open
Abstract
Background Psychiatry has long needed a better and more scalable way to capture the dynamics of behavior and its disturbances, quantitatively across multiple data channels, at high temporal resolution in real time. By combining 24/7 data—on location, movement, email and text communications, and social media—with brain scans, genetics, genomics, neuropsychological batteries, and clinical interviews, researchers will have an unprecedented amount of objective, individual-level data. Analyzing these data with ever-evolving artificial intelligence could one day include bringing interventions to patients where they are in the real world in a convenient, efficient, effective, and timely way. Yet, the road to this innovative future is fraught with ethical dilemmas as well as ethical, legal, and social implications (ELSI). Objective The goal of the Ethics Checklist is to promote careful design and execution of research. It is not meant to mandate particular research designs; indeed, at this early stage and without consensus guidance, there are a range of reasonable choices researchers may make. However, the checklist is meant to make those ethical choices explicit, and to require researchers to give reasons for their decisions related to ELSI issues. The Ethics Checklist is primarily focused on procedural safeguards, such as consulting with experts outside the research group and documenting standard operating procedures for clearly actionable data (eg, expressed suicidality) within written research protocols. Methods We explored the ELSI of digital health research in psychiatry, with a particular focus on what we label “deep phenotyping” psychiatric research, which combines the potential for virtually boundless data collection and increasingly sophisticated techniques to analyze those data. We convened an interdisciplinary expert stakeholder workshop in May 2020, and this checklist emerges out of that dialogue. Results Consistent with recent ELSI analyses, we find that existing ethical guidance and legal regulations are not sufficient for deep phenotyping research in psychiatry. At present, there are regulatory gaps, inconsistencies across research teams in ethics protocols, and a lack of consensus among institutional review boards on when and how deep phenotyping research should proceed. We thus developed a new instrument, an Ethics Checklist for Digital Health Research in Psychiatry (“the Ethics Checklist”). The Ethics Checklist is composed of 20 key questions, subdivided into 6 interrelated domains: (1) informed consent; (2) equity, diversity, and access; (3) privacy and partnerships; (4) regulation and law; (5) return of results; and (6) duty to warn and duty to report. Conclusions Deep phenotyping research offers a vision for vastly more effective care for people with, or at risk for, psychiatric disease. The potential perils en route to realizing this vision are significant; however, and researchers must be willing to address the questions in the Ethics Checklist before embarking on each leg of the journey.
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Affiliation(s)
- Francis X Shen
- Harvard Medical School, Boston, MA, United States.,Law School, University of Minnesota, Minneapolis, MN, United States
| | - Benjamin C Silverman
- Harvard Medical School, Boston, MA, United States.,Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
| | - Patrick Monette
- Harvard Medical School, Boston, MA, United States.,Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
| | - Sara Kimble
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
| | - Scott L Rauch
- Harvard Medical School, Boston, MA, United States.,Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
| | - Justin T Baker
- Harvard Medical School, Boston, MA, United States.,Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
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32
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Khalili-Mahani N, Holowka E, Woods S, Khaled R, Roy M, Lashley M, Glatard T, Timm-Bottos J, Dahan A, Niesters M, Hovey RB, Simon B, Kirmayer LJ. Play the Pain: A Digital Strategy for Play-Oriented Research and Action. Front Psychiatry 2021; 12:746477. [PMID: 34975566 PMCID: PMC8714795 DOI: 10.3389/fpsyt.2021.746477] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/11/2021] [Indexed: 12/26/2022] Open
Abstract
The value of understanding patients' illness experience and social contexts for advancing medicine and clinical care is widely acknowledged. However, methodologies for rigorous and inclusive data gathering and integrative analysis of biomedical, cultural, and social factors are limited. In this paper, we propose a digital strategy for large-scale qualitative health research, using play (as a state of being, a communication mode or context, and a set of imaginative, expressive, and game-like activities) as a research method for recursive learning and action planning. Our proposal builds on Gregory Bateson's cybernetic approach to knowledge production. Using chronic pain as an example, we show how pragmatic, structural and cultural constraints that define the relationship of patients to the healthcare system can give rise to conflicted messaging that impedes inclusive health research. We then review existing literature to illustrate how different types of play including games, chatbots, virtual worlds, and creative art making can contribute to research in chronic pain. Inspired by Frederick Steier's application of Bateson's theory to designing a science museum, we propose DiSPORA (Digital Strategy for Play-Oriented Research and Action), a virtual citizen science laboratory which provides a framework for delivering health information, tools for play-based experimentation, and data collection capacity, but is flexible in allowing participants to choose the mode and the extent of their interaction. Combined with other data management platforms used in epidemiological studies of neuropsychiatric illness, DiSPORA offers a tool for large-scale qualitative research, digital phenotyping, and advancing personalized medicine.
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Affiliation(s)
- Najmeh Khalili-Mahani
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Division of Social & Transcultural Psychiatry, McGill University, Montreal, QC, Canada
- Culture and Mental Health Research Unit, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
- Technoculture, Arts and Game Centre, Milieux Institute for Art, Culture and Technology, Concordia University, Montreal, QC, Canada
| | - Eileen Holowka
- Technoculture, Arts and Game Centre, Milieux Institute for Art, Culture and Technology, Concordia University, Montreal, QC, Canada
| | | | - Rilla Khaled
- Technoculture, Arts and Game Centre, Milieux Institute for Art, Culture and Technology, Concordia University, Montreal, QC, Canada
| | - Mathieu Roy
- Department of Psychology, McGill University, Montreal, QC, Canada
| | - Myrna Lashley
- Division of Social & Transcultural Psychiatry, McGill University, Montreal, QC, Canada
- Culture and Mental Health Research Unit, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
| | - Tristan Glatard
- Department of Computer Science, Concordia University, Montreal, QC, Canada
- PERFORM Centre, Concordia University, Montreal, QC, Canada
| | - Janis Timm-Bottos
- Department of Creative Art Therapies, Concordia University, Montreal, QC, Canada
| | - Albert Dahan
- Department of Anesthesiology, Leiden University Medical Centre, Leiden University, Leiden, Netherlands
| | - Marieke Niesters
- Department of Anesthesiology, Leiden University Medical Centre, Leiden University, Leiden, Netherlands
| | | | - Bart Simon
- Technoculture, Arts and Game Centre, Milieux Institute for Art, Culture and Technology, Concordia University, Montreal, QC, Canada
- Department of Sociology, Concordia University, Montreal, QC, Canada
| | - Laurence J. Kirmayer
- Division of Social & Transcultural Psychiatry, McGill University, Montreal, QC, Canada
- Culture and Mental Health Research Unit, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
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33
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Ferretti A, Ienca M, Velarde MR, Hurst S, Vayena E. The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study. J Empir Res Hum Res Ethics 2021; 17:129-143. [PMID: 34779661 PMCID: PMC8721531 DOI: 10.1177/15562646211053538] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Big data trends in health research challenge the oversight mechanism of the Research Ethics Committees (RECs). The traditional standards of research quality and the mandate of RECs illuminate deficits in facing the computational complexity, methodological novelty, and limited auditability of these approaches. To better understand the challenges facing RECs, we explored the perspectives and attitudes of the members of the seven Swiss Cantonal RECs via semi-structured qualitative interviews. Our interviews reveal limited experience among REC members with the review of big data research, insufficient expertise in data science, and uncertainty about how to mitigate big data research risks. Nonetheless, RECs could strengthen their oversight by training in data science and big data ethics, complementing their role with external experts and ad hoc boards, and introducing precise shared practices.
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Affiliation(s)
- Agata Ferretti
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, 27219ETH Zürich, Switzerland
| | - Marcello Ienca
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, 27219ETH Zürich, Switzerland.,College of Humanities, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
| | - Minerva Rivas Velarde
- Department of Radiology and Medical Informatics, Faculty of Medicine, 27212University of Geneva, Switzerland
| | - Samia Hurst
- Institute for Ethics, History, and the Humanities, Faculty of Medicine, 27212University of Geneva, Switzerland
| | - Effy Vayena
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, 27219ETH Zürich, Switzerland
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34
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Thambawita V, Isaksen JL, Hicks SA, Ghouse J, Ahlberg G, Linneberg A, Grarup N, Ellervik C, Olesen MS, Hansen T, Graff C, Holstein-Rathlou NH, Strümke I, Hammer HL, Maleckar MM, Halvorsen P, Riegler MA, Kanters JK. DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine. Sci Rep 2021; 11:21896. [PMID: 34753975 PMCID: PMC8578227 DOI: 10.1038/s41598-021-01295-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 10/26/2021] [Indexed: 11/09/2022] Open
Abstract
Recent global developments underscore the prominent role big data have in modern medical science. But privacy issues constitute a prevalent problem for collecting and sharing data between researchers. However, synthetic data generated to represent real data carrying similar information and distribution may alleviate the privacy issue. In this study, we present generative adversarial networks (GANs) capable of generating realistic synthetic DeepFake 10-s 12-lead electrocardiograms (ECGs). We have developed and compared two methods, named WaveGAN* and Pulse2Pulse. We trained the GANs with 7,233 real normal ECGs to produce 121,977 DeepFake normal ECGs. By verifying the ECGs using a commercial ECG interpretation program (MUSE 12SL, GE Healthcare), we demonstrate that the Pulse2Pulse GAN was superior to the WaveGAN* to produce realistic ECGs. ECG intervals and amplitudes were similar between the DeepFake and real ECGs. Although these synthetic ECGs mimic the dataset used for creation, the ECGs are not linked to any individuals and may thus be used freely. The synthetic dataset will be available as open access for researchers at OSF.io and the DeepFake generator available at the Python Package Index (PyPI) for generating synthetic ECGs. In conclusion, we were able to generate realistic synthetic ECGs using generative adversarial neural networks on normal ECGs from two population studies, thereby addressing the relevant privacy issues in medical datasets.
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Affiliation(s)
- Vajira Thambawita
- SimulaMet, 0167, Oslo, Norway. .,Oslo Metropolitan University, 0167, Oslo, Norway.
| | | | - Steven A Hicks
- SimulaMet, 0167, Oslo, Norway.,Oslo Metropolitan University, 0167, Oslo, Norway
| | - Jonas Ghouse
- University of Copenhagen, 2200, Copenhagen N, Denmark
| | | | - Allan Linneberg
- University of Copenhagen, 2200, Copenhagen N, Denmark.,Bispebjerg and Frederiksberg Hospital, 2400, Copenhagen NV, Denmark
| | - Niels Grarup
- University of Copenhagen, 2200, Copenhagen N, Denmark
| | | | | | - Torben Hansen
- University of Copenhagen, 2200, Copenhagen N, Denmark
| | | | | | | | - Hugo L Hammer
- SimulaMet, 0167, Oslo, Norway.,Oslo Metropolitan University, 0167, Oslo, Norway
| | - Mary M Maleckar
- SimulaMet, 0167, Oslo, Norway.,Oslo Metropolitan University, 0167, Oslo, Norway
| | - Pål Halvorsen
- SimulaMet, 0167, Oslo, Norway.,Oslo Metropolitan University, 0167, Oslo, Norway
| | - Michael A Riegler
- SimulaMet, 0167, Oslo, Norway. .,UiT The Arctic University of Norway, Tromsø, Norway.
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35
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Karabekmez ME. Data Ethics in Digital Health and Genomics. New Bioeth 2021; 27:320-333. [PMID: 34747348 DOI: 10.1080/20502877.2021.1996965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
The digital revolution has disruptively reshaped the way health services are provided and how research is conducted. This transformation has produced novel ethical challenges. The digitalization of health records, bioinformatics, molecular medicine, wearable biomedical technologies, biotechnology, and synthetic biology has created new biological data niches. How these data are shared, stored, distributed, and analyzed has created ethical problems regarding privacy, trust, accountability, fairness, and justice. This study investigates issues related to data-sharing permissions, fairness in secondary data distribution, and commercial and political conflicts of interest among individuals, companies, and states. In conclusion, establishing an agency to act as deputy trustee on behalf of individuals is recommended to intermediate the complex nature of informed consent. Focusing on decentralized digital technologies is recommended in order to catalyze the utilization of data and prevent discrimination without circulating data unnecessarily.
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36
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Althobaiti K. Surveillance in Next-Generation Personalized Healthcare: Science and Ethics of Data Analytics in Healthcare. New Bioeth 2021; 27:295-319. [PMID: 34720071 DOI: 10.1080/20502877.2021.1993055] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Advances in science and technology have allowed for incredible improvements in healthcare. Additionally, the digital revolution in healthcare provides new ways of collecting and storing large volumes of patient data, referred to as big healthcare data. As a result, healthcare providers are now able to use data to gain a deeper understanding of how to treat an individual in what is referred to as personalized healthcare. Regardless, there are several ethical challenges associated with big healthcare data that affect how personalized healthcare is delivered. To highlight these issues, this article will review the role of big data in personalized healthcare while also discussing the ethical challenges associated with it. The article will also discuss public health surveillance, its implications, and the challenges associated with collecting participants' information. The article will proceed by highlighting next generation technologies, including robotics and 3D printing. The article will conclude by providing recommendations on how patient privacy can be protected in next-generation personalized healthcare.
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Affiliation(s)
- Kamal Althobaiti
- Centre for Global Health Ethics, Duquesne University, Pittsburgh, PA, USA
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The Role of Big Data in Aging and Older People’s Health Research: A Systematic Review and Ecological Framework. SUSTAINABILITY 2021. [DOI: 10.3390/su132111587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Big data has been prominent in studying aging and older people’s health. It has promoted modeling and analyses in biological and geriatric research (like cellular senescence), developed health management platforms, and supported decision-making in public healthcare and social security. However, current studies are still limited within a single subject, rather than flourished as interdisciplinary research in the context of big data. The research perspectives have not changed, nor has big data brought itself out of the role as a modeling tool. When embedding big data as a data product, analysis tool, and resolution service into different spatial, temporal, and organizational scales of aging processes, it would present as a connection, integration, and interaction simultaneously in conducting interdisciplinary research. Therefore, this paper attempts to propose an ecological framework for big data based on aging and older people’s health research. Following the scoping process of PRISMA, 35 studies were reviewed to validate our ecological framework. Although restricted by issues like digital divides and privacy security, we encourage researchers to capture various elements and their interactions in the human-environment system from a macro and dynamic perspective rather than simply pursuing accuracy.
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Chauhan C, Gullapalli RR. Ethics of AI in Pathology: Current Paradigms and Emerging Issues. THE AMERICAN JOURNAL OF PATHOLOGY 2021; 191:1673-1683. [PMID: 34252382 PMCID: PMC8485059 DOI: 10.1016/j.ajpath.2021.06.011] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 06/18/2021] [Accepted: 06/24/2021] [Indexed: 02/06/2023]
Abstract
Deep learning has rapidly advanced artificial intelligence (AI) and algorithmic decision-making (ADM) paradigms, affecting many traditional fields of medicine, including pathology, which is a heavily data-centric specialty of medicine. The structured nature of pathology data repositories makes it highly attractive to AI researchers to train deep learning models to improve health care delivery. Additionally, there are enormous financial incentives driving adoption of AI and ADM due to promise of increased efficiency of the health care delivery process. AI, if used unethically, may exacerbate existing inequities of health care, especially if not implemented correctly. There is an urgent need to harness the vast power of AI in an ethically and morally justifiable manner. This review explores the key issues involving AI ethics in pathology. Issues related to ethical design of pathology AI studies and the potential risks associated with implementation of AI and ADM within the pathology workflow are discussed. Three key foundational principles of ethical AI: transparency, accountability, and governance, are described in the context of pathology. The future practice of pathology must be guided by these principles. Pathologists should be aware of the potential of AI to deliver superlative health care and the ethical pitfalls associated with it. Finally, pathologists must have a seat at the table to drive future implementation of ethical AI in the practice of pathology.
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Affiliation(s)
- Chhavi Chauhan
- American Society of Investigative Pathology, Rockville, Maryland
| | - Rama R Gullapalli
- Department of Pathology, University of New Mexico, Albuquerque, New Mexico; Department of Chemical and Biological Engineering, University of New Mexico, Albuquerque, New Mexico.
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Gagnon M, Payne A, Guta A. What are the ethical implications of using prize-based contingency management in substance use? A scoping review. Harm Reduct J 2021; 18:82. [PMID: 34348710 PMCID: PMC8335458 DOI: 10.1186/s12954-021-00529-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 07/25/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The area of substance use is notable for its early uptake of incentives and wealth of research on the topic. This is particularly true for prize-based contingency management (PB-CM), a particular type of incentive that uses a fishbowl prize-draw design. Given that PB-CM interventions are gaining momentum to address the dual public health crises of opiate and stimulant use in North America and beyond, it is imperative that we better understand and critically analyze their implications. PURPOSE The purpose of this scoping review paper is to identify the characteristics of PB-CM interventions for people who use substances and explore ethical implications documented in the literature as well as emerging ethical implications that merit further consideration. METHODS The PRISMA-ScR checklist was used in conjunction with Arksey and O'Malley's methodological framework to guide this scoping review. We completed a two-pronged analysis of 52 research articles retrieved through a comprehensive search across three key scholarly databases. After extracting descriptive data from each article, we used 9 key domains to identify characteristics of the interventions followed by an analysis of ethical implications. RESULTS We analyzed the characteristics of PB-CM interventions which were predominantly quantitative studies aimed at studying the efficacy of PB-CM interventions. All of the interventions used a prize-draw format with a classic magnitude of 50%. Most of the interventions combined both negative and positive direction to reward processes, behaviors, and/or outcomes. One ethical implication was identified in the literature: the risk of gambling relapse. We also found three emerging ethical implications by further analyzing participant characteristics, intervention designs, and potential impact on the patient-provider relationship. These implications include the potential deceptive nature of PB-CM, the emphasis placed on the individual behaviors to the detriment of social and structural determinants of health, and failures to address vulnerability and power dynamics. CONCLUSIONS This scoping review offers important insights into the ethics on PB-CM and its implications for research ethics, clinical ethics, and public health ethics. Additionally, it raises important questions that can inform future research and dialogues to further tease out the ethical issues associated with PB-CM.
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Affiliation(s)
- Marilou Gagnon
- Canadian Institute for Substance Use Research, University of Victoria, 2300 McKenzie Ave, Victoria, BC, V8N 5M8, Canada.
- School of Nursing, University of Victoria, 3800 Finnerty Road, Victoria, BC, V8P 5C2, Canada.
| | - Alayna Payne
- Canadian Institute for Substance Use Research, University of Victoria, 2300 McKenzie Ave, Victoria, BC, V8N 5M8, Canada
| | - Adrian Guta
- School of Social Work, University of Windsor, 167 Ferry Street, Windsor, ON, N9A 0C5, Canada
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Ranisch R. Consultation with Doctor Twitter: Consent Fatigue, and the Role of Developers in Digital Medical Ethics. THE AMERICAN JOURNAL OF BIOETHICS : AJOB 2021; 21:24-25. [PMID: 34152918 DOI: 10.1080/15265161.2021.1926595] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
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Jungkunz M, Köngeter A, Mehlis K, Winkler EC, Schickhardt C. Secondary Use of Clinical Data in Data-Gathering, Non-Interventional Research or Learning Activities: Definition, Types, and a Framework for Risk Assessment. J Med Internet Res 2021; 23:e26631. [PMID: 34100760 PMCID: PMC8241435 DOI: 10.2196/26631] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 03/10/2021] [Accepted: 05/06/2021] [Indexed: 12/16/2022] Open
Abstract
Background The secondary use of clinical data in data-gathering, non-interventional research or learning activities (SeConts) has great potential for scientific progress and health care improvement. At the same time, it poses relevant risks for the privacy and informational self-determination of patients whose data are used. Objective Since the current literature lacks a tailored framework for risk assessment in SeConts as well as a clarification of the concept and practical scope of SeConts, we aim to fill this gap. Methods In this study, we analyze each element of the concept of SeConts to provide a synthetic definition, investigate the practical relevance and scope of SeConts through a literature review, and operationalize the widespread definition of risk (as a harmful event of a certain magnitude that occurs with a certain probability) to conduct a tailored analysis of privacy risk factors typically implied in SeConts. Results We offer a conceptual clarification and definition of SeConts and provide a list of types of research and learning activities that can be subsumed under the definition of SeConts. We also offer a proposal for the classification of SeConts types into the categories non-interventional (observational) clinical research, quality control and improvement, or public health research. In addition, we provide a list of risk factors that determine the probability or magnitude of harm implied in SeConts. The risk factors provide a framework for assessing the privacy-related risks for patients implied in SeConts. We illustrate the use of risk assessment by applying it to a concrete example. Conclusions In the future, research ethics committees and data use and access committees will be able to rely on and apply the framework offered here when reviewing projects of secondary use of clinical data for learning and research purposes.
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Affiliation(s)
- Martin Jungkunz
- Section for Translational Medical Ethics, Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Anja Köngeter
- Section for Translational Medical Ethics, Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Katja Mehlis
- Section for Translational Medical Ethics, Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Eva C Winkler
- Section for Translational Medical Ethics, Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany
| | - Christoph Schickhardt
- Section for Translational Medical Ethics, National Center for Tumor Diseases, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Sheikh A, Anderson M, Albala S, Casadei B, Franklin BD, Richards M, Taylor D, Tibble H, Mossialos E. Health information technology and digital innovation for national learning health and care systems. Lancet Digit Health 2021; 3:e383-e396. [PMID: 33967002 DOI: 10.1016/s2589-7500(21)00005-4] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 07/24/2020] [Accepted: 01/04/2021] [Indexed: 01/01/2023]
Abstract
Health information technology can support the development of national learning health and care systems, which can be defined as health and care systems that continuously use data-enabled infrastructure to support policy and planning, public health, and personalisation of care. The COVID-19 pandemic has offered an opportunity to assess how well equipped the UK is to leverage health information technology and apply the principles of a national learning health and care system in response to a major public health shock. With the experience acquired during the pandemic, each country within the UK should now re-evaluate their digital health and care strategies. After leaving the EU, UK countries now need to decide to what extent they wish to engage with European efforts to promote interoperability between electronic health records. Major priorities for strengthening health information technology in the UK include achieving the optimal balance between top-down and bottom-up implementation, improving usability and interoperability, developing capacity for handling, processing, and analysing data, addressing privacy and security concerns, and encouraging digital inclusivity. Current and future opportunities include integrating electronic health records across health and care providers, investing in health data science research, generating real-world data, developing artificial intelligence and robotics, and facilitating public-private partnerships. Many ethical challenges and unintended consequences of implementation of health information technology exist. To address these, there is a need to develop regulatory frameworks for the development, management, and procurement of artificial intelligence and health information technology systems, create public-private partnerships, and ethically and safely apply artificial intelligence in the National Health Service.
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Affiliation(s)
- Aziz Sheikh
- Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK.
| | - Michael Anderson
- Department of Health Policy, London School of Economics and Political Science, London, UK
| | - Sarah Albala
- UCL Institute for Innovation and Public Purpose, University College London, London, UK
| | - Barbara Casadei
- Radcliffe Department of Medicine, BHF Centre for Research Excellence, NIHR Biomedical Research Centre, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Bryony Dean Franklin
- UCL School of Pharmacy, University College London, London, UK; NIHR Imperial Patient Safety Translational Research Centre, Imperial College Healthcare NHS Trust, London, UK
| | - Mike Richards
- Department of Health Policy, London School of Economics and Political Science, London, UK; The Health Foundation, London, UK
| | - David Taylor
- UCL School of Pharmacy, University College London, London, UK
| | - Holly Tibble
- Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
| | - Elias Mossialos
- Department of Health Policy, London School of Economics and Political Science, London, UK; Institute of Global Health Innovation, Imperial College London, London, UK
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Jha AK, Mithun S, Rangarajan V, Wee L, Dekker A. Emerging role of artificial intelligence in nuclear medicine. Nucl Med Commun 2021; 42:592-601. [PMID: 33660696 DOI: 10.1097/mnm.0000000000001381] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The role of artificial intelligence is increasing in all branches of medicine. The emerging role of artificial intelligence applications in nuclear medicine is going to improve the nuclear medicine clinical workflow in the coming years. Initial research outcomes are suggestive of increasing role of artificial intelligence in nuclear medicine workflow, particularly where selective automation tasks are of concern. Artificial intelligence-assisted planning, dosimetry and procedure execution appear to be areas for rapid and significant development. The role of artificial intelligence in more directly imaging-related tasks, such as dose optimization, image corrections and image reconstruction, have been particularly strong points of artificial intelligence research in nuclear medicine. Natural Language Processing (NLP)-based text processing task is another area of interest of artificial intelligence implementation in nuclear medicine.
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Affiliation(s)
- Ashish Kumar Jha
- Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Nuclear Medicine and Molecular Imaging, Tata Memorial Hospital
| | - Sneha Mithun
- Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Nuclear Medicine and Molecular Imaging, Tata Memorial Hospital
- Homi Bhabha National Institute (HBNI), Deemed University, Mumbai, India
| | - Venkatesh Rangarajan
- Department of Nuclear Medicine and Molecular Imaging, Tata Memorial Hospital
- Homi Bhabha National Institute (HBNI), Deemed University, Mumbai, India
| | - Leonard Wee
- Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Andre Dekker
- Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre, Maastricht, The Netherlands
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Martani A, Geneviève LD, Egli SM, Erard F, Wangmo T, Elger BS. Evolution or Revolution? Recommendations to Improve the Swiss Health Data Framework. Front Public Health 2021; 9:668386. [PMID: 34136456 PMCID: PMC8200489 DOI: 10.3389/fpubh.2021.668386] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 04/29/2021] [Indexed: 11/23/2022] Open
Abstract
Background: Facilitating access to health data for public health and research purposes is an important element in the health policy agenda of many countries. Improvements in this sense can only be achieved with the development of an appropriate data infrastructure and the implementations of policies that also respect societal preferences. Switzerland is a revealing example of a country that has been struggling to achieve this aim. The objective of the study is to reflect on stakeholders' recommendations on how to improve the health data framework of this country. Methods: We analysed the recommendations collected as part of a qualitative study including 48 expert stakeholders from Switzerland that have been working principally with health databases. Recommendations were divided in themes and subthemes according to applied thematic analysis. Results: Stakeholders recommended several potential improvements of the health data framework in Switzerland. At the general level of mind-set and attitude, they suggested to foster the development of an explicit health data strategy, better communication and the respect of societal preferences. In terms of infrastructure, there were calls for the creation of a national data center, the improvement of IT solutions and the use of a Unique Identifier for patient data. Lastly, they recommended harmonising procedures for data access and to clarify data protection and consent rules. Conclusion: Recommendations show several potential improvements of the health data framework, but they have to be reconciled with existing policies, infrastructures and ethico-legal limitations. Achieving a gradual implementation of the recommended solutions is the preferable way forward for Switzerland and a lesson for other countries that are also seeking to improve health data access for public health and research purposes.
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Affiliation(s)
- Andrea Martani
- Institute for Biomedical Ethics, University of Basel, Basel, Switzerland
| | | | - Sophia Mira Egli
- Master Student, Faculty of Medicine, University of Basel, Basel, Switzerland
| | - Frédéric Erard
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tenzin Wangmo
- Institute for Biomedical Ethics, University of Basel, Basel, Switzerland
| | - Bernice Simone Elger
- Institute for Biomedical Ethics, University of Basel, Basel, Switzerland.,University Center of Legal Medicine, University of Geneva, Geneva, Switzerland
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Voigt I, Inojosa H, Dillenseger A, Haase R, Akgün K, Ziemssen T. Digital Twins for Multiple Sclerosis. Front Immunol 2021; 12:669811. [PMID: 34012452 PMCID: PMC8128142 DOI: 10.3389/fimmu.2021.669811] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 04/16/2021] [Indexed: 12/16/2022] Open
Abstract
An individualized innovative disease management is of great importance for people with multiple sclerosis (pwMS) to cope with the complexity of this chronic, multidimensional disease. However, an individual state of the art strategy, with precise adjustment to the patient's characteristics, is still far from being part of the everyday care of pwMS. The development of digital twins could decisively advance the necessary implementation of an individualized innovative management of MS. Through artificial intelligence-based analysis of several disease parameters - including clinical and para-clinical outcomes, multi-omics, biomarkers, patient-related data, information about the patient's life circumstances and plans, and medical procedures - a digital twin paired to the patient's characteristic can be created, enabling healthcare professionals to handle large amounts of patient data. This can contribute to a more personalized and effective care by integrating data from multiple sources in a standardized manner, implementing individualized clinical pathways, supporting physician-patient communication and facilitating a shared decision-making. With a clear display of pre-analyzed patient data on a dashboard, patient participation and individualized clinical decisions as well as the prediction of disease progression and treatment simulation could become possible. In this review, we focus on the advantages, challenges and practical aspects of digital twins in the management of MS. We discuss the use of digital twins for MS as a revolutionary tool to improve diagnosis, monitoring and therapy refining patients' well-being, saving economic costs, and enabling prevention of disease progression. Digital twins will help make precision medicine and patient-centered care a reality in everyday life.
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Affiliation(s)
| | | | | | | | | | - Tjalf Ziemssen
- Center of Clinical Neuroscience, Department of Neurology, University Hospital Carl Gustav Carus, Technical University of Dresden, Dresden, Germany
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Abdullah YI, Schuman JS, Shabsigh R, Caplan A, Al-Aswad LA. Ethics of Artificial Intelligence in Medicine and Ophthalmology. Asia Pac J Ophthalmol (Phila) 2021; 10:289-298. [PMID: 34383720 PMCID: PMC9167644 DOI: 10.1097/apo.0000000000000397] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND This review explores the bioethical implementation of artificial intelligence (AI) in medicine and in ophthalmology. AI, which was first introduced in the 1950s, is defined as "the machine simulation of human mental reasoning, decision making, and behavior". The increased power of computing, expansion of storage capacity, and compilation of medical big data helped the AI implementation surge in medical practice and research. Ophthalmology is a leading medical specialty in applying AI in screening, diagnosis, and treatment. The first Food and Drug Administration approved autonomous diagnostic system served to diagnose and classify diabetic retinopathy. Other ophthalmic conditions such as age-related macular degeneration, glaucoma, retinopathy of prematurity, and congenital cataract, among others, implemented AI too. PURPOSE To review the contemporary literature of the bioethical issues of AI in medicine and ophthalmology, classify ethical issues in medical AI, and suggest possible standardizations of ethical frameworks for AI implementation. METHODS Keywords were searched on Google Scholar and PubMed between October 2019 and April 2020. The results were reviewed, cross-referenced, and summarized. A total of 284 references including articles, books, book chapters, and regulatory reports and statements were reviewed, and those that were relevant were cited in the paper. RESULTS Most sources that studied the use of AI in medicine explored the ethical aspects. Bioethical challenges of AI implementation in medicine were categorized into 6 main categories. These include machine training ethics, machine accuracy ethics, patient-related ethics, physician-related ethics, shared ethics, and roles of regulators. CONCLUSIONS There are multiple stakeholders in the ethical issues surrounding AI in medicine and ophthalmology. Attention to the various aspects of ethics related to AI is important especially with the expanding use of AI. Solutions of ethical problems are envisioned to be multifactorial.
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Affiliation(s)
| | - Joel S Schuman
- Department of Ophthalmology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY
- Department of Electrical and Computer Engineering, NYU Tandon School of Engineering, Brooklyn, NY
- Department of Physiology and Neuroscience, NYU Langone Health, NYU Grossman School of Medicine, New York, NY
- Center for Neural Science, NYU College of Arts and Science, New York, NY
| | - Ridwan Shabsigh
- SBH Health System and Weill Cornell Medical College, New York, NY
| | - Arthur Caplan
- Department of Population Health, NYU Langone Health, NYU Grossman School of Medicine, New York, NY
| | - Lama A Al-Aswad
- Department of Ophthalmology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY
- Department of Population Health, NYU Langone Health, NYU Grossman School of Medicine, New York, NY
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Ferretti A, Ienca M, Sheehan M, Blasimme A, Dove ES, Farsides B, Friesen P, Kahn J, Karlen W, Kleist P, Liao SM, Nebeker C, Samuel G, Shabani M, Rivas Velarde M, Vayena E. Ethics review of big data research: What should stay and what should be reformed? BMC Med Ethics 2021; 22:51. [PMID: 33931049 PMCID: PMC8085804 DOI: 10.1186/s12910-021-00616-4] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 04/15/2021] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND Ethics review is the process of assessing the ethics of research involving humans. The Ethics Review Committee (ERC) is the key oversight mechanism designated to ensure ethics review. Whether or not this governance mechanism is still fit for purpose in the data-driven research context remains a debated issue among research ethics experts. MAIN TEXT In this article, we seek to address this issue in a twofold manner. First, we review the strengths and weaknesses of ERCs in ensuring ethical oversight. Second, we map these strengths and weaknesses onto specific challenges raised by big data research. We distinguish two categories of potential weakness. The first category concerns persistent weaknesses, i.e., those which are not specific to big data research, but may be exacerbated by it. The second category concerns novel weaknesses, i.e., those which are created by and inherent to big data projects. Within this second category, we further distinguish between purview weaknesses related to the ERC's scope (e.g., how big data projects may evade ERC review) and functional weaknesses, related to the ERC's way of operating. Based on this analysis, we propose reforms aimed at improving the oversight capacity of ERCs in the era of big data science. CONCLUSIONS We believe the oversight mechanism could benefit from these reforms because they will help to overcome data-intensive research challenges and consequently benefit research at large.
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Affiliation(s)
- Agata Ferretti
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, ETH Zürich, Hottingerstrasse 10 (HOA), 8092, Zürich, Switzerland.
| | - Marcello Ienca
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, ETH Zürich, Hottingerstrasse 10 (HOA), 8092, Zürich, Switzerland
| | - Mark Sheehan
- The Ethox Centre, Department of Population Health, University of Oxford, Oxford, UK
| | - Alessandro Blasimme
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, ETH Zürich, Hottingerstrasse 10 (HOA), 8092, Zürich, Switzerland
| | - Edward S Dove
- School of Law, University of Edinburgh, Edinburgh, UK
| | | | - Phoebe Friesen
- Biomedical Ethics Unit, Department of Social Studies of Medicine, McGill University, Montreal, Canada
| | - Jeff Kahn
- Johns Hopkins Berman Institute of Bioethics, Baltimore, USA
| | - Walter Karlen
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | - Peter Kleist
- Cantonal Ethics Committee Zürich, Zürich, Switzerland
| | - S Matthew Liao
- Center for Bioethics, Department of Philosophy, New York University, New York, USA
| | - Camille Nebeker
- Research Center for Optimal Digital Ethics in Health (ReCODE Health), Herbert Wertheim School of Public Health and Longevity Science, University of California, San Diego, USA
| | - Gabrielle Samuel
- Department of Global Health and Social Medicine, King's College London, London, UK
| | - Mahsa Shabani
- Faculty of Law and Criminology, Ghent University, Ghent, Belgium
| | - Minerva Rivas Velarde
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Effy Vayena
- Health Ethics and Policy Lab, Department of Health Sciences and Technology, ETH Zürich, Hottingerstrasse 10 (HOA), 8092, Zürich, Switzerland
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Tusino S, Furfaro M. Rethinking the role of Research Ethics Committees in the light of Regulation (EU) No 536/2014 on clinical trials and the COVID-19 pandemic. Br J Clin Pharmacol 2021; 88:40-46. [PMID: 33891323 PMCID: PMC8251080 DOI: 10.1111/bcp.14871] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 04/12/2021] [Accepted: 04/15/2021] [Indexed: 01/20/2023] Open
Abstract
Research Ethics Committees (RECs)—or Institutional Review Boards (IRBs), as they are known in the US—were created about 50 years ago to independently assess the ethical acceptability of research projects involving human subjects, their fundamental role being the protection of the dignity and rights of research participants. In this paper we develop some critical reflections about the current situation of RECs. Our starting point is the definition of the role they should ideally play, a role that should necessarily include a collaborative approach and the focus on the ethics component of the review. This ideal is unfortunately quite far from reality: inadequacies in the functioning of RECs have been discussed for decades, along with reform proposals. Both in the US and in the European Union (EU), reforms that aim at the centralization of the review process were recently approved. Even though these reforms were needed, they nonetheless raise concerns. We focus on two such concerns, related in particular to Regulation (EU) No 536/2014: the risk of narrowing the scope of the ethics review and that of disregarding the local context. We argue that the COVID‐19 pandemic paved the way for the transition towards the centralized model and that an analysis of its impact on the research review process could provide some interesting insights into possible shortcomings of this new model. We conclude by identifying three objectives that define the role of a REC, objectives that any reform should preserve.
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Labude MK, Shen L, Zhu Y, Schaefer GO, Ong C, Xafis V. Perspectives of Singaporean biomedical researchers and research support staff on actual and ideal IRB review functions and characteristics: A quantitative analysis. PLoS One 2020; 15:e0241783. [PMID: 33382683 PMCID: PMC7774925 DOI: 10.1371/journal.pone.0241783] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 10/20/2020] [Indexed: 01/22/2023] Open
Abstract
Background Biomedical research is overseen by numerous Institutional Review Boards (IRBs) in Singapore but there has been no research that examines how the research review process is perceived by the local research community nor is there any systematic data on perceptions regarding the review process or other research ethics processes and IRB characteristics. The aim of this study was to ascertain general views regarding the overall perceived value of ethics review processes; to measure perceptions about local IRB functions and characteristics; to identify IRB functions and characteristics viewed as important; and to compare these views with those of other international studies. Methods An online survey was used with the main component being the IRB-Researcher Assessment Tool (IRB-RAT), a validated tool, to evaluate perceptions of ideal and actual IRB functions and characteristics held by Singaporean researchers and research support staff. Data were analysed descriptively first, with mean and SD of each item of IRB-RAT questionnaire reported, excluding the respondents whose answers were unknown or not applicable. The Wilcoxon Sign Rank test was used to compare the ideal and actual ratings of each IRB-RAT item, while the Mann-Whitney U test was used to compare the ratings of each IRB-RAT item between respondents with different characteristics. The Z-test was used to compare the mean ratings of our cohort with the mean ratings reported in the literature. The correlation between our mean ideal scores and those of two international studies also employing the IRB-RAT was examined. Results Seventy-one respondents completed the survey. This cohort generally held positive views of the impact of the ethics review process on: the quality of research; establishing and maintaining public trust in research; the protection of research participants; and on the scientific validity of research. The most important ideal IRB characteristics were timeliness, upholding participants’ rights while also facilitating research, working with investigators to find solutions when there are disagreements, and not allowing biases to affect reviews. For almost all 45 IRB-RAT statements, the rating of the importance of the characteristic was higher than the rating of how much that characteristic was descriptive of IRBs the respondents were familiar with. There was a significant strong correlation between our study’s scores on the ideal IRB characteristics and those of the first and largest published study that employed the IRB-RAT, the US National Validation (USNV) sample in Keith-Spiegel et al. [19]. Conclusions An understanding of the perceptions held by Singaporean researchers and research support staff on the value that the ethics review process adds, their perceptions of actual IRB functions and characteristics as well as what they view as central to high functioning IRBs is the first step to considering the aspects of the review process that might benefit from improvements. This study provides insight into how our cohort compares to others internationally and highlights strengths and areas for improvement of Singapore IRBs as perceived by a small sample of the local research community. Such insights provide a springboard for additional research and may assist in further enhancing good relations so that both are working towards the same end.
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Affiliation(s)
- Markus K. Labude
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- * E-mail: (MKL); (VX)
| | - Liang Shen
- Biostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yujia Zhu
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - G. Owen Schaefer
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Catherine Ong
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Division of Infectious Diseases, University Medicine Cluster, National University Health System, Singapore, Singapore
| | - Vicki Xafis
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- * E-mail: (MKL); (VX)
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Wang X, High A, Wang X, Zhao K. Predicting users' continued engagement in online health communities from the quantity and quality of received support. J Assoc Inf Sci Technol 2020. [DOI: 10.1002/asi.24436] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Xiangyu Wang
- Interdisciplinary Graduate Program in Informatics The University of Iowa Iowa City Iowa USA
| | - Andrew High
- Department of Communication Arts and Sciences Pennsylvania State University University Park Pennsylvania USA
| | - Xi Wang
- School of Information Central University of Finance and Economics Beijing China
| | - Kang Zhao
- Tipple College of Business The University of Iowa Iowa City Iowa USA
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