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van Kessel R, Ranganathan S, Anderson M, McMillan B, Mossialos E. Exploring potential drivers of patient engagement with their health data through digital platforms: A scoping review. Int J Med Inform 2024; 189:105513. [PMID: 38851132 DOI: 10.1016/j.ijmedinf.2024.105513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 04/11/2024] [Accepted: 06/02/2024] [Indexed: 06/10/2024]
Abstract
BACKGROUND Patient engagement when providing patient access to health data results from an interaction between the available tools and individual capabilities. The recent digital advancements of the healthcare field have altered the manifestation and importance of patient engagement. However, a comprehensive assessment of what factors contribute to patient engagement remain absent. In this review article, we synthesised the most frequently discussed factors that can foster patient engagement with their health data. METHODS A scoping review was conducted in MEDLINE, Embase, and Google Scholar. Relevant data were synthesized within 7 layers using a thematic analysis: (1) social and demographic factors, (2) patient ability factors, (3) patient motivation factors, (4) factors related to healthcare professionals' attitudes and skills, (5) health system factors, (6) technological factors, and (7) policy factors. RESULTS We identified 5801 academic and 200 Gy literature records, and included 292 (4.83%) in this review. Overall, 44 factors that can affect patient engagement with their health data were extracted. We extracted 6 social and demographic factors, 6 patient ability factors, 12 patient motivation factors, 7 factors related to healthcare professionals' attitudes and skills, 4 health system factors, 6 technological factors, and 3 policy factors. CONCLUSIONS Improving patient engagement with their health data enables the development of patient-centered healthcare, though it can also exacerbate existing inequities. While expanding patient access to health data is an important step towards fostering shared decision-making in healthcare and subsequently empowering patients, it is important to ensure that these developments reach all sectors of the community.
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Affiliation(s)
- Robin van Kessel
- LSE Health, Department of Health Policy, London School of Economics and Political Science, London, United Kingdom; Department of International Health, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands; Digital Public Health Task Force, Association of School of Public Health in the European Region (ASPHER), Brussels, Belgium.
| | | | - Michael Anderson
- LSE Health, Department of Health Policy, London School of Economics and Political Science, London, United Kingdom; Centre for Primary Care and Health Services Research, University of Manchester, Manchester, United Kingdom.
| | - Brian McMillan
- Centre for Primary Care and Health Services Research, University of Manchester, Manchester, United Kingdom.
| | - Elias Mossialos
- LSE Health, Department of Health Policy, London School of Economics and Political Science, London, United Kingdom; Institute of Global Health Innovation, Imperial College London, London, United Kingdom.
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2
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Steffens S, Schröder K, Krüger M, Maack C, Streckfuss-Bömeke K, Backs J, Backofen R, Baeßler B, Devaux Y, Gilsbach R, Heijman J, Knaus J, Kramann R, Linz D, Lister AL, Maatz H, Maegdefessel L, Mayr M, Meder B, Nussbeck SY, Rog-Zielinska EA, Schulz MH, Sickmann A, Yigit G, Kohl P. The challenges of research data management in cardiovascular science: a DGK and DZHK position paper-executive summary. Clin Res Cardiol 2024; 113:672-679. [PMID: 37847314 PMCID: PMC11026239 DOI: 10.1007/s00392-023-02303-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 09/01/2023] [Indexed: 10/18/2023]
Abstract
The sharing and documentation of cardiovascular research data are essential for efficient use and reuse of data, thereby aiding scientific transparency, accelerating the progress of cardiovascular research and healthcare, and contributing to the reproducibility of research results. However, challenges remain. This position paper, written on behalf of and approved by the German Cardiac Society and German Centre for Cardiovascular Research, summarizes our current understanding of the challenges in cardiovascular research data management (RDM). These challenges include lack of time, awareness, incentives, and funding for implementing effective RDM; lack of standardization in RDM processes; a need to better identify meaningful and actionable data among the increasing volume and complexity of data being acquired; and a lack of understanding of the legal aspects of data sharing. While several tools exist to increase the degree to which data are findable, accessible, interoperable, and reusable (FAIR), more work is needed to lower the threshold for effective RDM not just in cardiovascular research but in all biomedical research, with data sharing and reuse being factored in at every stage of the scientific process. A culture of open science with FAIR research data should be fostered through education and training of early-career and established research professionals. Ultimately, FAIR RDM requires permanent, long-term effort at all levels. If outcomes can be shown to be superior and to promote better (and better value) science, modern RDM will make a positive difference to cardiovascular science and practice. The full position paper is available in the supplementary materials.
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Affiliation(s)
- Sabine Steffens
- Institute for Cardiovascular Prevention (IPEK), Ludwig-Maximilians-Universität, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
| | - Katrin Schröder
- Institute for Cardiovascular Physiology, Goethe University, Frankfurt Am Main, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site RheinMain, Frankfurt, Germany
| | - Martina Krüger
- Institute of Cardiovascular Physiology, University Hospital Düsseldorf, Düsseldorf, Germany
- Cardiovascular Research Institute Düsseldorf (CARID), Düsseldorf, Germany
| | - Christoph Maack
- Comprehensive Heart Failure Center (CHFC), University Clinic Würzburg, Würzburg, Germany
- Medical Clinic 1, University Clinic Würzburg, Würzburg, Germany
| | - Katrin Streckfuss-Bömeke
- Clinic for Cardiology and Pneumology, Georg-August University Göttingen, Göttingen, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Göttingen, Göttingen, Germany
- Institute of Pharmacology and Toxicology, University of Würzburg, Würzburg, Germany
| | - Johannes Backs
- Institute of Experimental Cardiology, University Hospital Heidelberg, Heidelberg, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | - Rolf Backofen
- Faculty of Medicine, Institute for Experimental and Clinical Pharmacology and Toxicology, Albert-Ludwigs-University, Freiburg, Germany
| | - Bettina Baeßler
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany
| | - Yvan Devaux
- Cardiovascular Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Ralf Gilsbach
- Institute of Experimental Cardiology, University Hospital Heidelberg, Heidelberg, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | - Jordi Heijman
- Department of Cardiology, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - Jochen Knaus
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Rafael Kramann
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen Medical Faculty, Aachen, Germany
- Department of Nephrology and Clinical Immunology, RWTH Aachen Medical Faculty, Aachen, Germany
- Department of Internal Medicine, Nephrology and Transplantation, Erasmus MC, Rotterdam, The Netherlands
| | - Dominik Linz
- Department of Cardiology, Maastricht University Medical Centre and Cardiovascular Research Institute Maastricht, Maastricht, The Netherlands
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Allyson L Lister
- Oxford E-Research Centre (OeRC), Department of Engineering Science, University of Oxford, Oxford, UK
| | - Henrike Maatz
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | - Lars Maegdefessel
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
- Department for Vascular and Endovascular Surgery, Klinikum Rechts Der Isar, Technical University Munich, Munich, Germany
- Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Manuel Mayr
- School of Cardiovascular Medicine and Sciences, King's College London British Heart Foundation Centre, London, UK
- Division of Cardiology, Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria
| | - Benjamin Meder
- DZHK (German Center for Cardiovascular Research), Partner Site Heidelberg/Mannheim, Heidelberg, Germany
- Department of Internal Medicine III (Cardiology, Angiology, and Pneumology), University Hospital Heidelberg, Heidelberg, Germany
| | - Sara Y Nussbeck
- Department of Medical Informatics, University Medical Center Göttingen (UMG), Göttingen, Germany
- Central Biobank UMG, UMG, Göttingen, Germany
| | - Eva A Rog-Zielinska
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg-Bad Krozingen, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Marcel H Schulz
- DZHK (German Centre for Cardiovascular Research), Partner Site RheinMain, Frankfurt, Germany
- Institute of Cardiovascular Regeneration, Goethe University, Frankfurt, Germany
| | - Albert Sickmann
- Leibniz-Institut Für Analytische Wissenschaften, ISAS, E.V., Dortmund, Germany
- Department of Chemistry, College of Physical Sciences, University of Aberdeen, Aberdeen, UK
- Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Gökhan Yigit
- Institute of Human Genetics, University Medical Center Göttingen, Göttingen, Germany
- German Center of Cardiovascular Research (DZHK), Partner Site Göttingen, Göttingen, Germany
| | - Peter Kohl
- Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg-Bad Krozingen, University of Freiburg, Freiburg, Germany.
- Faculty of Medicine, University of Freiburg, Freiburg, Germany.
- CIBSS Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany.
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Baines R, Stevens S, Austin D, Anil K, Bradwell H, Cooper L, Maramba ID, Chatterjee A, Leigh S. Patient and Public Willingness to Share Personal Health Data for Third-Party or Secondary Uses: Systematic Review. J Med Internet Res 2024; 26:e50421. [PMID: 38441944 PMCID: PMC10951832 DOI: 10.2196/50421] [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: 06/30/2023] [Revised: 12/01/2023] [Accepted: 12/18/2023] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND International advances in information communication, eHealth, and other digital health technologies have led to significant expansions in the collection and analysis of personal health data. However, following a series of high-profile data sharing scandals and the emergence of COVID-19, critical exploration of public willingness to share personal health data remains limited, particularly for third-party or secondary uses. OBJECTIVE This systematic review aims to explore factors that affect public willingness to share personal health data for third-party or secondary uses. METHODS A systematic search of 6 databases (MEDLINE, Embase, PsycINFO, CINAHL, Scopus, and SocINDEX) was conducted with review findings analyzed using inductive-thematic analysis and synthesized using a narrative approach. RESULTS Of the 13,949 papers identified, 135 were included. Factors most commonly identified as a barrier to data sharing from a public perspective included data privacy, security, and management concerns. Other factors found to influence willingness to share personal health data included the type of data being collected (ie, perceived sensitivity); the type of user requesting their data to be shared, including their perceived motivation, profit prioritization, and ability to directly impact patient care; trust in the data user, as well as in associated processes, often established through individual choice and control over what data are shared with whom, when, and for how long, supported by appropriate models of dynamic consent; the presence of a feedback loop; and clearly articulated benefits or issue relevance including valued incentivization and compensation at both an individual and collective or societal level. CONCLUSIONS There is general, yet conditional public support for sharing personal health data for third-party or secondary use. Clarity, transparency, and individual control over who has access to what data, when, and for how long are widely regarded as essential prerequisites for public data sharing support. Individual levels of control and choice need to operate within the auspices of assured data privacy and security processes, underpinned by dynamic and responsive models of consent that prioritize individual or collective benefits over and above commercial gain. Failure to understand, design, and refine data sharing approaches in response to changeable patient preferences will only jeopardize the tangible benefits of data sharing practices being fully realized.
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Affiliation(s)
- Rebecca Baines
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | - Sebastian Stevens
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
- Prometheus Health Technologies Ltd, Newquay, United Kingdom
| | - Daniela Austin
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | | | - Hannah Bradwell
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | - Leonie Cooper
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | | | - Arunangsu Chatterjee
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
- School of Medicine, University of Leeds, Leeds, United Kingdom
| | - Simon Leigh
- Prometheus Health Technologies Ltd, Newquay, United Kingdom
- Warwick Medical School, University of Warwick, Conventry, United Kingdom
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4
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Shandhi MMH, Singh K, Janson N, Ashar P, Singh G, Lu B, Hillygus DS, Maddocks JM, Dunn JP. Assessment of ownership of smart devices and the acceptability of digital health data sharing. NPJ Digit Med 2024; 7:44. [PMID: 38388660 PMCID: PMC10883993 DOI: 10.1038/s41746-024-01030-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 02/05/2024] [Indexed: 02/24/2024] Open
Abstract
Smart portable devices- smartphones and smartwatches- are rapidly being adopted by the general population, which has brought forward an opportunity to use the large volumes of physiological, behavioral, and activity data continuously being collected by these devices in naturalistic settings to perform research, monitor health, and track disease. While these data can serve to revolutionize health monitoring in research and clinical care, minimal research has been conducted to understand what motivates people to use these devices and their interest and comfort in sharing the data. In this study, we aimed to characterize the ownership and usage of smart devices among patients from an expansive academic health system in the southeastern US and understand their willingness to share data collected by the smart devices. We conducted an electronic survey of participants from an online patient advisory group around smart device ownership, usage, and data sharing. Out of the 3021 members of the online patient advisory group, 1368 (45%) responded to the survey, with 871 female (64%), 826 and 390 White (60%) and Black (29%) participants, respectively, and a slight majority (52%) age 58 and older. Most of the respondents (98%) owned a smartphone and the majority (59%) owned a wearable. In this population, people who identify as female, Hispanic, and Generation Z (age 18-25), and those completing higher education and having full-time employment, were most likely to own a wearable device compared to their demographic counterparts. 50% of smart device owners were willing to share and 32% would consider sharing their smart device data for research purposes. The type of activity data they are willing to share varies by gender, age, education, and employment. Findings from this study can be used to design both equitable and cost-effective digital health studies, leveraging personally-owned smartphones and wearables in representative populations, ultimately enabling the development of equitable digital health technologies.
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Affiliation(s)
| | - Karnika Singh
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | - Perisa Ashar
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Geetika Singh
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Baiying Lu
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - D Sunshine Hillygus
- Department of Political Science, Trinity College of Arts & Sciences, Duke University, Durham, NC, USA
- Sanford School of Public Policy, Duke University, Durham, NC, USA
| | | | - Jessilyn P Dunn
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Duke University, Department of Biostatistics & Bioinformatics, Durham, NC, USA.
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5
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Deisenhofer AK, Barkham M, Beierl ET, Schwartz B, Aafjes-van Doorn K, Beevers CG, Berwian IM, Blackwell SE, Bockting CL, Brakemeier EL, Brown G, Buckman JEJ, Castonguay LG, Cusack CE, Dalgleish T, de Jong K, Delgadillo J, DeRubeis RJ, Driessen E, Ehrenreich-May J, Fisher AJ, Fried EI, Fritz J, Furukawa TA, Gillan CM, Gómez Penedo JM, Hitchcock PF, Hofmann SG, Hollon SD, Jacobson NC, Karlin DR, Lee CT, Levinson CA, Lorenzo-Luaces L, McDanal R, Moggia D, Ng MY, Norris LA, Patel V, Piccirillo ML, Pilling S, Rubel JA, Salazar-de-Pablo G, Schleider JL, Schnurr PP, Schueller SM, Siegle GJ, Uher R, Watkins E, Webb CA, Wiltsey Stirman S, Wynants L, Youn SJ, Zilcha-Mano S, Lutz W, Cohen ZD. Implementing precision methods in personalizing psychological therapies: Barriers and possible ways forward. Behav Res Ther 2024; 172:104443. [PMID: 38086157 DOI: 10.1016/j.brat.2023.104443] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 11/21/2023] [Accepted: 11/27/2023] [Indexed: 12/26/2023]
Affiliation(s)
| | | | | | | | | | | | | | | | - Claudi L Bockting
- AmsterdamUMC, Department of Psychiatry, Research Program Amsterdam Public Health and Centre for Urban Mental Health, University of Amsterdam, the Netherlands
| | | | | | | | | | | | | | - Kim de Jong
- Leiden University, Institute of Psychology, USA
| | | | | | | | | | | | | | - Jessica Fritz
- University of Cambridge, UK; Philipps University of Marburg, Germany
| | | | - Claire M Gillan
- School of Psychology, Trinity College Institute for Neuroscience, And Global Brain Health Institute, Trinity College Dublin, USA
| | | | | | | | | | | | | | | | | | | | | | | | - Mei Yi Ng
- Florida International University, USA
| | | | | | | | | | | | | | - Jessica L Schleider
- Stony Brook University and Feinberg School of Medicine Northwestern University, USA
| | - Paula P Schnurr
- National Center for PTSD and Geisel School of Medicine at Dartmouth, USA
| | | | | | | | | | | | | | | | - Soo Jeong Youn
- Reliant Medical Group, OptumCare and Harvard Medical School, USA
| | | | | | - Zachary D Cohen
- University of California, Los Angeles and University of Arizona, USA.
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6
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Tolentino DA, Costa DK, Jiang Y. Determinants of American Adults' Use of Digital Health and Willingness to Share Health Data to Providers, Family, and Social Media: A Cross-sectional Study. Comput Inform Nurs 2023; 41:892-902. [PMID: 37310724 PMCID: PMC10713855 DOI: 10.1097/cin.0000000000001025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
With the global pandemic driving the adoption of digital health, understanding the predictors or determinants of digital health usage and information sharing gives an opportunity to advocate for broader adoption. We examined the prevalence and predictors of digital health usage and information-sharing behaviors among American adults. Data were from the Health Information National Trends Survey 5 Cycle 4. More than two-thirds used a digital resource for health-related activities (eg, to check test results). About 81% were willing to share their digital data with their provider, 75% with family, and 58% with friends. Only 14% shared health information on social media. Gender, education, device types, and performance expectancy of digital health were common factors associated with both digital health usage and information-sharing behaviors. Other predictors included rurality, patient portal access, income, and having a chronic disease. Of note, we found that Asian American Pacific Islanders, compared with Whites, were less likely to share information with providers. Performance expectancy was a significant determinant of information sharing. Those diagnosed with diabetes were 4% less likely to share information with their providers. With the growing digital divide, there is a need to advocate for more usable and accessible digital health to assist with person-centered care.
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Affiliation(s)
| | | | - Yun Jiang
- School of Nursing, University of Michigan, Ann Arbor
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7
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Benevento M, Mandarelli G, Carravetta F, Ferorelli D, Caterino C, Nicolì S, Massari A, Solarino B. Measuring the willingness to share personal health information: a systematic review. Front Public Health 2023; 11:1213615. [PMID: 37546309 PMCID: PMC10397406 DOI: 10.3389/fpubh.2023.1213615] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 07/05/2023] [Indexed: 08/08/2023] Open
Abstract
Background In the age of digitalization and big data, personal health information is a key resource for health care and clinical research. This study aimed to analyze the determinants and describe the measurement of the willingness to disclose personal health information. Methods The study conducted a systematic review of articles assessing willingness to share personal health information as a primary or secondary outcome. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis protocol. English and Italian peer-reviewed research articles were included with no restrictions for publication years. Findings were narratively synthesized. Results The search strategy found 1,087 papers, 89 of which passed the screening for title and abstract and the full-text assessment. Conclusion No validated measurement tool has been developed for willingness to share personal health information. The reviewed papers measured it through surveys, interviews, and questionnaires, which were mutually incomparable. The secondary use of data was the most important determinant of willingness to share, whereas clinical and socioeconomic variables had a slight effect. The main concern discouraging data sharing was privacy, although good data anonymization and the high perceived benefits of sharing may overcome this issue.
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Affiliation(s)
- Marcello Benevento
- Department of Interdisciplinary Medicine, University of Bari, Bari, Italy
| | | | | | - Davide Ferorelli
- Department of Interdisciplinary Medicine, University of Bari, Bari, Italy
| | - Cristina Caterino
- Department of Interdisciplinary Medicine, University of Bari, Bari, Italy
| | - Simona Nicolì
- Department of Interdisciplinary Medicine, University of Bari, Bari, Italy
| | - Antonella Massari
- Department of Economics, Management and Business Law, University of Bari, Bari, Italy
| | - Biagio Solarino
- Department of Interdisciplinary Medicine, University of Bari, Bari, Italy
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8
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Kim J, Im E, Kim H. From intention to action: The factors affecting health data sharing intention and action. Int J Med Inform 2023; 175:105071. [PMID: 37099875 DOI: 10.1016/j.ijmedinf.2023.105071] [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: 11/30/2022] [Revised: 02/12/2023] [Accepted: 04/11/2023] [Indexed: 04/28/2023]
Abstract
INTRODUCTION Effective prevention and treatment of diseases requires utilization of health-related lifestyle data, which has thus become increasingly important. According to some studies, participants were willing to share their health data for use in medical care and research. Although intention does not always accurately reflect action, few studies have examined the question of whether data-sharing intention leads to data-sharing action. OBJECTIVE The aim of this study was to examine the extent of actualizing data-sharing intention to data-sharing action and to identify the factors that influence data-sharing intention and action. METHODS A web-based survey of members of a university examined the data-sharing intention and issues of concern when making decisions on data sharing. The participants were asked to deposit their armband data for use in research at the end of the survey. A comparison of data-sharing intention and action in relation to the participants' characteristics was performed. Factors having a significant effect on data-sharing intention and action were identified using logistic regressions. RESULTS Of 386 participants, 294 expressed willingness to share health data. However, only 73 participants deposited their armband data. The primary reason for refusal to deposit armband data was the inconvenience of the data transfer process (56.3%). Appropriate compensation had a significant effect on data-sharing intention (OR: 3.3, CI: 1.86-5.75) and action (OR: 2.8, CI: 1.14-8.21). The compensation for data sharing (OR:2.8, CI:1.14-8.21) and familiarity with data (OR:3.1, CI:1.36-8.21) were significant predictors of data sharing action, however, data-sharing intention was not (OR: 1.5, CI:0.65-3.72). CONCLUSION Despite expressing willingness to share their health data, the participants' intention was not actualized to data-sharing behavior for depositing armband data. Implementation of a streamlined data transfer process and providing appropriate compensation might facilitate data-sharing. These findings could be useful in development of strategies to facilitate sharing and reuse of health data.
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Affiliation(s)
- Jinsol Kim
- Seoul National University, College of Nursing, Seoul, Korea
| | - Eunyoung Im
- Seoul National University, College of Nursing, Seoul, Korea
| | - Hyeoneui Kim
- Seoul National University, College of Nursing, Seoul, Korea; Seoul National University, The Research Institute of Nursing Science, Seoul, Korea.
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9
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Handa M, Afzal O, Beg S, SanapNasik S, Kaundal RK, Verma RK, Mishra A, Shukla R. Harnessing personalized tailored medicines to digital-based data-enriched edible pharmaceuticals. Drug Discov Today 2023; 28:103555. [PMID: 36931386 DOI: 10.1016/j.drudis.2023.103555] [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: 09/18/2022] [Revised: 02/26/2023] [Accepted: 03/09/2023] [Indexed: 03/17/2023]
Abstract
Tailoring drug products to personalized medicines poses challenges for conventional dosage forms. The prominent reason is the restricted availability of flexible dosage strengths in the market. Inappropriate dosage strengths lead to adverse drug reactions or compromised therapeutic effects. The situation worsens when the drug has a narrow therapeutic window. To overcome these challenges, data-enriched edible pharmaceuticals (DEEP) are novel concepts for designing solid oral products. DEEP have individualized doses and information embedded in quick response (QR) code form. When data are presented in a QR code, the information is printed with edible ink that contains the drug in tailored doses required for the patients.
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Affiliation(s)
- Mayank Handa
- Department of Pharmaceutics, National Institute of Pharmaceutical Education and Research-Raebareli, Lucknow, UP 226002, India
| | - Obaid Afzal
- Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, AlKharj, Saudi Arabia
| | - Sarwar Beg
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.
| | - Sachin SanapNasik
- Department of Pharmaceutics, National Institute of Pharmaceutical Education and Research-Raebareli, Lucknow, UP 226002, India
| | - Ravinder K Kaundal
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research Raebareli (NIPER-R), Lucknow, UP 226002, India
| | - Rahul K Verma
- Institute of Nano Science and Technology (INST), SAS Nagar, Punjab 140306, India
| | - Awanish Mishra
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER)-Guwahati, Changsari, Guwahati 781101, Assam, India
| | - Rahul Shukla
- Department of Pharmaceutics, National Institute of Pharmaceutical Education and Research-Raebareli, Lucknow, UP 226002, India.
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10
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Bonn SE, Alexandrou C, Trolle Lagerros Y. A Digital Platform and Smartphone App to Increase Physical Activity in Patients With Type 2 Diabetes: Overview Of a Technical Solution. JMIR Form Res 2023; 7:e40285. [PMID: 36917156 PMCID: PMC10131920 DOI: 10.2196/40285] [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: 06/14/2022] [Revised: 11/17/2022] [Accepted: 02/28/2023] [Indexed: 03/16/2023] Open
Abstract
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.1186/s12889-018-5026-4.
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Affiliation(s)
- Stephanie E Bonn
- Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Christina Alexandrou
- Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden.,Division of Society and Health, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Ylva Trolle Lagerros
- Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.,Obesity Specialist Center, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
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11
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Hendricks-Sturrup R, Lu CY. An Assessment of Perspectives and Concerns Among Research Participants of Childbearing Age Regarding the Health-Relatedness of Data, Online Data Privacy, and Donating Data to Researchers: Survey Study. J Med Internet Res 2023; 25:e41937. [PMID: 36897637 PMCID: PMC10039398 DOI: 10.2196/41937] [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: 08/15/2022] [Revised: 11/26/2022] [Accepted: 02/24/2023] [Indexed: 03/11/2023] Open
Abstract
BACKGROUND The June 2022 US Supreme Court decision to ban abortion care in Dobbs v Jackson Women's Health Organization sparked ominous debate about the privacy and safety of women and families of childbearing age with digital footprints who actively engage in family planning, including abortion and miscarriage care. OBJECTIVE To assess the perspectives of a subpopulation of research participants of childbearing age regarding the health-relatedness of their digital data, their concerns about the use and sharing of personal data online, and their concerns about donating data from various sources to researchers today or in the future. METHODS An 18-item electronic survey was developed using Qualtrics and administered to adults (aged ≥18 years) registered in the ResearchMatch database in April 2021. Individuals were invited to participate in the survey regardless of health status, race, gender, or any other mutable or immutable characteristics. Descriptive statistical analyses were conducted using Microsoft Excel and manual queries (single layer, bottom-up topic modeling) and used to categorize illuminating quotes from free-text survey responses. RESULTS A total of 470 participants initiated the survey and 402 completed and submitted the survey (for an 86% completion rate). Nearly half the participants (189/402, 47%) self-reported to be persons of childbearing age (18 to 50 years). Most participants of childbearing age agreed or strongly agreed that social media data, email data, text message data, Google search history data, online purchase history data, electronic medical record data, fitness tracker and wearable data, credit card statement data, and genetic data are health-related. Most participants disagreed or strongly disagreed that music streaming data, Yelp review and rating data, ride-sharing history data, tax records and other income history data, voting history data, and geolocation data are health-related. Most (164/189, 87%) participants were concerned about fraud or abuse based on their personal information, online companies and websites sharing information with other parties without consent, and online companies and websites using information for purposes that are not explicitly stated in their privacy policies. Free-text survey responses showed that participants were concerned about data use beyond scope of consent; exclusion from health care and insurance; government and corporate mistrust; and data confidentiality, security, and discretion. CONCLUSIONS Our findings in light of Dobbs and other related events indicate there are opportunities to educate research participants about the health-relatedness of their digital data. Developing strategies and best privacy practices for discretion regarding digital-footprint data related to family planning should be a priority for companies, researchers, families, and other stakeholders.
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Affiliation(s)
- Rachele Hendricks-Sturrup
- Duke-Margolis Center for Health Policy, Washington, DC, United States
- Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA, United States
- Department of Interdisciplinary Health Studies, Ohio University, Athens, GA, United States
| | - Christine Y Lu
- Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA, United States
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12
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Deruelle T, Kalouguina V, Trein P, Wagner J. Is there a "pandemic effect" on individuals' willingness to take genetic tests? Eur J Hum Genet 2023; 31:360-362. [PMID: 36352012 PMCID: PMC9646467 DOI: 10.1038/s41431-022-01223-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 10/17/2022] [Accepted: 10/24/2022] [Indexed: 11/11/2022] Open
Abstract
In this cross-sectional, semi-longitudinal and quasi-experimental study, our goal was to determine the effect of data storage conditions on willingness to take a genetic test. We compared individuals' preferences regarding how they want to store health data collected from genetic tests through two survey experiments fielded in Switzerland in March 2020 and January 2022. We tested for differences whether genetic data are presented as private goods or public goods. Results confirm our initial research expectation: more control over storage increases willingness, so does framing genetic data as private good. However, they also show that the willingness to take a genetic test has noticeably increased between 2020 and 2022. Our results point toward a "pandemic effect" which would have increased willingness take a genetic test, nevertheless, more data are needed to understand this putative effect.
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Affiliation(s)
| | | | | | - Joël Wagner
- University of Lausanne, Lausanne, Switzerland
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13
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Gupta R, Iyengar R, Sharma M, Cannuscio CC, Merchant RM, Asch DA, Mitra N, Grande D. Consumer Views on Privacy Protections and Sharing of Personal Digital Health Information. JAMA Netw Open 2023; 6:e231305. [PMID: 36862410 PMCID: PMC9982693 DOI: 10.1001/jamanetworkopen.2023.1305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/03/2023] Open
Abstract
IMPORTANCE Digital health information has many potential health applications, but privacy is a growing concern among consumers and policy makers. Consent alone is increasingly seen as inadequate to safeguard privacy. OBJECTIVE To determine whether different privacy protections are associated with consumers' willingness to share their digital health information for research, marketing, or clinical uses. DESIGN, SETTING, AND PARTICIPANTS This 2020 national survey with an embedded conjoint experiment recruited US adults from a nationally representative sample with oversampling of Black and Hispanic individuals. Willingness to share digital information across 192 different scenarios reflecting the product of 4 possible privacy protections, 3 uses of information, 2 users of information, and 2 sources of digital information was evaluated. Each participant was randomly assigned 9 scenarios. The survey was administrated between July 10 and July 31, 2020, in Spanish and English. Analysis for this study was conducted between May 2021 and July 2022. MAIN OUTCOMES AND MEASURES Participants rated each conjoint profile on a 5-point Likert scale measuring their willingness to share their personal digital information (with 5 indicating the most willingness to share). Results are reported as adjusted mean differences. RESULTS Of the 6284 potential participants, 3539 (56%) responded to the conjoint scenarios. A total of 1858 participants (53%) were female, 758 (21%) identified as Black, 833 (24%) identified as Hispanic, 1149 (33%) had an annual income less than $50 000, and 1274 (36%) were 60 years or older. Participants were more willing to share health information with the presence of each individual privacy protection, including consent (difference, 0.32; 95% CI, 0.29-0.35; P < .001), followed by data deletion (difference, 0.16; 95% CI, 0.13-0.18; P < .001), oversight (difference, 0.13; 95% CI, 0.10-0.15; P < .001), and transparency of data collected (difference, 0.08; 95% CI, 0.05-0.10; P < .001). The relative importance (importance weight on a 0%-100% scale) was greatest for the purpose of use (29.9%) but when considered collectively, the 4 privacy protections together were the most important (51.5%) factor in the conjoint experiment. When the 4 privacy protections were considered separately, consent was the most important (23.9%). CONCLUSIONS AND RELEVANCE In this survey study of a nationally representative sample of US adults, consumers' willingness to share personal digital health information for health purposes was associated with the presence of specific privacy protections beyond consent alone. Additional protections, including data transparency, oversight, and data deletion may strengthen consumer confidence in sharing their personal digital health information.
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Affiliation(s)
- Ravi Gupta
- Johns Hopkins University School of Medicine, Baltimore, Maryland
- Hopkins Business of Health Initiative, Johns Hopkins University, Baltimore, Maryland
- Center for Health Services and Outcomes Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | - Meghana Sharma
- Perelman School of Medicine, Division of General Internal Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
| | - Carolyn C. Cannuscio
- Perelman School of Medicine, Department of Family Medicine and Community Health, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
| | - Raina M. Merchant
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Perelman School of Medicine, Department of Emergency Medicine, University of Pennsylvania, Philadelphia
| | - David A. Asch
- Wharton School, University of Pennsylvania, Philadelphia
- Perelman School of Medicine, Division of General Internal Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
| | - Nandita Mitra
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Perelman School of Medicine, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia
| | - David Grande
- Perelman School of Medicine, Division of General Internal Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
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14
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Mangal S, Niño de Rivera S, Choi J, Reading Turchioe M, Benda N, Sharko M, Myers A, Goyal P, Dugdale L, Masterson Creber R. Returning study results to research participants: Data access, format, and sharing preferences. Int J Med Inform 2023; 170:104955. [PMID: 36565546 PMCID: PMC9869800 DOI: 10.1016/j.ijmedinf.2022.104955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 10/28/2022] [Accepted: 12/02/2022] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Research participants have a growing expectation for transparency with their collected information; however, there is little guidance on participant preferences for receiving health information and how researchers should return this information to participants. METHODS We conducted a cross-sectional online survey with a representative sample of 502 participants in the United States. Participants were asked about their preferences for receiving, sharing, and the formatting of health information collected for research purposes. RESULTS Most participants wanted their health information returned (84 %) to use it for their own knowledge and to manage their own health. Email was the most preferred format for receiving health data (67 %), followed by online website (44 %), and/or paper copy (32 %). Data format preferences varied by age, education, financial resources, subjective numeracy, and health literacy. Around one third of Generation Z (25 %), Millennials (30 %), and Generation X (29 %) participants preferred to receive their health information with a mobile app. In contrast, very few Baby Boomers (12 %) and none from the Silent Generation preferred the mobile app format. Having a paper copy of the data was preferred by 38 % of participants without a college degree compared to those with a college degree. Preferences were highest for sharing all health information with doctors and nurses (77 %), and some information with friends and family (66 %). CONCLUSION Study findings support returning research information to participants in multiple formats, including email, online websites, and paper copy. Preferences for whom to share information with varied by stakeholders and by sociodemographic characteristics. Researchers should offer multiple formats to participants and tailor data sharing options to participants' preferences. Future research should further explore combinations of individual characteristics that may further influence data sharing and format preferences.
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Affiliation(s)
- Sabrina Mangal
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA; Department of Biobehavioral Nursing and Health Informatics, University of Washington School of Nursing, Seattle, WA, USA.
| | - Stephanie Niño de Rivera
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA; Columbia University School of Nursing, New York, NY, USA
| | - Jacky Choi
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Meghan Reading Turchioe
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA; Columbia University School of Nursing, New York, NY, USA
| | - Natalie Benda
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA; Columbia University School of Nursing, New York, NY, USA
| | - Marianne Sharko
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Annie Myers
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA; Columbia University School of Nursing, New York, NY, USA
| | - Parag Goyal
- Department of Medicine, Weill Cornell Medicine, New York, New York, USA
| | - Lydia Dugdale
- Department of Medicine, Columbia University, New York, NY, USA
| | - Ruth Masterson Creber
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York, USA; Columbia University School of Nursing, New York, NY, USA
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15
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Cumyn A, Ménard JF, Barton A, Dault R, Lévesque F, Ethier JF. Patients and Members of the Public’s Wishes Regarding Transparency in the Context of Secondary Use of Health Data: A Scoping Review (Preprint). J Med Internet Res 2022; 25:e45002. [PMID: 37052967 PMCID: PMC10141314 DOI: 10.2196/45002] [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: 12/12/2022] [Revised: 02/09/2023] [Accepted: 03/03/2023] [Indexed: 03/06/2023] Open
Abstract
BACKGROUND Secondary use of health data has reached unequaled potential to improve health systems governance, knowledge, and clinical care. Transparency regarding this secondary use is frequently cited as necessary to address deficits in trust and conditional support and to increase patient awareness. OBJECTIVE We aimed to review the current published literature to identify different stakeholders' perspectives and recommendations on what information patients and members of the public want to learn about the secondary use of health data for research purposes and how and in which situations. METHODS Using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we conducted a scoping review using Medline, CINAHL, PsycINFO, Scopus, Cochrane Library, and PubMed databases to locate a broad range of studies published in English or French until November 2022. We included articles reporting a stakeholder's perspective or recommendations of what information patients and members of the public want to learn about the secondary use of health data for research purposes and how or in which situations. Data were collected and analyzed with an iterative thematic approach using NVivo. RESULTS Overall, 178 articles were included in this scoping review. The type of information can be divided into generic and specific content. Generic content includes information on governance and regulatory frameworks, technical aspects, and scientific aims. Specific content includes updates on the use of one's data, return of results from individual tests, information on global results, information on data sharing, and how to access one's data. Recommendations on how to communicate the information focused on frequency, use of various supports, formats, and wording. Methods for communication generally favored broad approaches such as nationwide publicity campaigns, mainstream and social media for generic content, and mixed approaches for specific content including websites, patient portals, and face-to-face encounters. Content should be tailored to the individual as much as possible with regard to length, avoidance of technical terms, cultural competence, and level of detail. Finally, the review outlined 4 major situations where communication was deemed necessary: before a new use of data, when new test results became available, when global research results were released, and in the advent of a breach in confidentiality. CONCLUSIONS This review highlights how different types of information and approaches to communication efforts may serve as the basis for achieving greater transparency. Governing bodies could use the results: to elaborate or evaluate strategies to educate on the potential benefits; to provide some knowledge and control over data use as a form of reciprocity; and as a condition to engage citizens and build and maintain trust. Future work is needed to assess which strategies achieve the greatest outreach while striking a balance between meeting information needs and use of resources.
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Affiliation(s)
- Annabelle Cumyn
- Département de médecine, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Jean-Frédéric Ménard
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Faculté de droit, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Adrien Barton
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Institut de recherche en informatique de Toulouse, Toulouse, France
| | - Roxanne Dault
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Frédérique Lévesque
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Jean-François Ethier
- Département de médecine, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
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A Survey of Research Participants’ Privacy-Related Experiences and Willingness to Share Real-World Data with Researchers. J Pers Med 2022; 12:jpm12111922. [DOI: 10.3390/jpm12111922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 11/07/2022] [Accepted: 11/15/2022] [Indexed: 11/19/2022] Open
Abstract
Background: Real-world data (RWD) privacy is an increasingly complex topic within the scope of personalized medicine, as it implicates several sources of data. Objective: To assess how privacy-related experiences, when adjusted for age and education level, may shape adult research participants’ willingness to share various sources of real-world data with researchers. Methods: An electronic survey was conducted in April 2021 among adults (≥18 years of age) registered in ResearchMatch, a national health research registry. Descriptive analyses were conducted to assess survey participant demographics. Logistic regression was conducted to assess the association between participants’ five distinct privacy-related experiences and their willingness to share each of the 19 data sources with researchers, adjusting for education level and age range. Results: A total of 598 ResearchMatch adults were contacted and 402 completed the survey. Most respondents were over the age of 51 years (49% total) and held a master’s or bachelor’s degree (63% total). Over half of participants (54%) had their account accessed by someone without their permission. Almost half of participants (49%) reported the privacy of their personal information being violated. Analyses showed that, when adjusted for age range and education level, participants whose reputations were negatively affected as a result of information posted online were more likely to share electronic medical record data (OR = 2.074, 95% CI: 0.986–4.364) and genetic data (OR = 2.302, 95% CI: 0.894–5.93) versus those without this experience. Among participants who had an unpleasant experience as a result of giving out information online, those with some college/associates/trade school compared to those with a doctoral or other terminal degree were significantly more willing to share genetic data (OR = 1.064, 95% CI: 0.396–2.857). Across all privacy-related experiences, participants aged 18 to 30 were significantly more likely than those over 60 years to share music streaming data, ridesharing history data, and voting history data. Additionally, across all privacy-related experiences, those with a high school education were significantly more likely than those with a doctorate or other terminal degree to share credit card statement data. Conclusions: This study offers the first insights into how privacy-related experiences, adjusted for age range and education level, may shape ResearchMatch participants’ willingness to share several sources of real-world data sources with precision medicine researchers. Future work should further explore these insights.
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Durieux BN, DeCamp M, Lindvall C. 21st Century Cures Act: ethical recommendations for new patient-facing products. J Am Med Inform Assoc 2022; 29:1818-1822. [PMID: 35876830 PMCID: PMC9471700 DOI: 10.1093/jamia/ocac112] [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: 03/07/2022] [Accepted: 07/21/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Recent legislation ensuring patient access to their electronic health records represents a promising national commitment to patient empowerment. Access and interoperability rules seek to empower individuals as well as increase opportunities for data sharing by hospitals, apps, and other parties for research and innovation. However, there are trade-offs between data accessibility and oversight. Some third-party apps may not be covered by federal regulations, and receiving records directly from individuals may render some services in possession of health data. To promote consumer trust, these services should follow ethical standards regardless of regulatory status. ACTIONABLE PRINCIPLES This Perspective proposes 3 actionable principles, grounded in medical ethics, for services making use of health data: services should (1) provide informed, dynamic, regular consent, including control over data sharing, (2) promote inclusivity and equity, and (3) intentionally focus on consumer trust and the perception of value in the service provided.
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Affiliation(s)
- Brigitte N Durieux
- Department of Psychosocial Oncology and Palliative Care, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Matthew DeCamp
- Division of General Internal Medicine, Center for Bioethics and Humanities, University of Colorado, Aurora, Colorado, USA
| | - Charlotta Lindvall
- Department of Psychosocial Oncology and Palliative Care, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.,Harvard Medical School, Harvard University, Boston, Massachusetts, USA
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Fowe IE, Wallace NT, Rissi JJ. The Evolution and Typology of Learning Health System Hospitals and other Health Information Interested Hospitals in the US. PERSPECTIVES IN HEALTH INFORMATION MANAGEMENT 2022; 19:1b. [PMID: 36035327 PMCID: PMC9335161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
This study identifies the type, distribution, and interactions of US hospitals that identify as electronic-data-driven, patient-centric, and learning-focused. Such facilities, termed Health Information Interested (HII) hospitals in this study, meet the defining criteria for one or more of the following designations: learning health systems (LHS), Health Information Technology for Economic and Clinical Health (HITECH) meaningful use stage three compliant (MU3), Patient-Centered Outcomes Research Institute (PCORI) funded, or medical home/safety net (MH/SN) hospital. The American Hospital Association (AHA) IT supplemental survey and other supporting data spanning 2013 to 2018 were used to identify HII hospitals. HII hospitals increased from 19.9 percent to 62.4 percent of AHA reporting hospitals from 2013 to 2018. HII subcategories in 2018 such as the full LHS (37.2 percent) and MU3 (46.9 percent) were dominant, with 33.2 percent having both designations. This indicates increased interest in patient-centric, learning-focused care using electronic health data. This information can enable health information management (HIM) professionals to be aware of programs or approaches that can facilitate learning-focused, patient-centric care using electronic health data within health systems.
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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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James P, Trudel-Fitzgerald C, Lee HH, Koga HK, Kubzansky LD, Grodstein F. Linking Individual-Level Facebook Posts With Psychological and Health Data in an Epidemiological Cohort: Feasibility Study. JMIR Form Res 2022; 6:e32423. [PMID: 35389368 PMCID: PMC9030896 DOI: 10.2196/32423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 12/04/2021] [Accepted: 12/19/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Psychological factors (eg, depression) and related biological and behavioral responses are associated with numerous physical health outcomes. Most research in this area relies on self-reported assessments of psychological factors, which are difficult to scale because they may be expensive and time-consuming. Investigators are increasingly interested in using social media as a novel and convenient platform for obtaining information rapidly in large populations. OBJECTIVE We evaluated the feasibility of obtaining Facebook data from a large ongoing cohort study of midlife and older women, which may be used to assess psychological functioning efficiently with low cost. METHODS This study was conducted with participants in the Nurses' Health Study II (NHSII), which was initiated in 1989 with biennial follow-ups. Facebook does not share data readily; therefore, we developed procedures to enable women to download and transfer their Facebook data to cohort servers (for linkage with other study data they have provided). Since privacy is a critical concern when collecting individual-level data, we partnered with a third-party software developer, Digi.me, to enable participants to obtain their own Facebook data and to send it securely to our research team. In 2020, we invited a subset of the 18,519 NHSII participants (aged 56-73 years) via email to participate. Women were selected if they reported on the 2017-2018 questionnaire that they regularly posted on Facebook and were still active cohort participants. We included an exit survey for those who chose not to participate in order to gauge the reasons for nonparticipation. RESULTS We invited 309 women to participate. Few women signed the consent form (n=52), and only 3 used the Digi.me app to download and transfer their Facebook data. This low participation rate was observed despite modifying our protocol between waves of recruitment, including by (1) excluding active health care workers, who might be less available to participate due to the pandemic, (2) developing a Frequently Asked Questions factsheet to provide more information regarding the protocol, and (3) simplifying the instructions for using the Digi.me app. On our exit survey, the reasons most commonly reported for not participating were concerns regarding data privacy and hesitation sharing personal Facebook posts. The low participation rate suggests that obtaining individual-level Facebook data in a cohort of middle-aged and older women may be challenging. CONCLUSIONS In this cohort of midlife and older women who were actively participating for over three decades, we were largely unable to obtain permission to access individual-level data from participants' Facebook accounts. Despite working with a third-party developer to customize an app to implement safeguards for privacy, data privacy remained a key concern in these women. Future studies aiming to leverage individual-level social media data should explore alternate populations or means of sharing social media data.
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Affiliation(s)
- Peter James
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States
- Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA, United States
| | - Claudia Trudel-Fitzgerald
- Department of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, Boston, MA, United States
- Lee Kum Sheung Center for Health and Happiness, Harvard TH Chan School of Public Health, Boston, MA, United States
| | - Harold H Lee
- Department of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, Boston, MA, United States
- Lee Kum Sheung Center for Health and Happiness, Harvard TH Chan School of Public Health, Boston, MA, United States
| | - Hayami K Koga
- Department of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, Boston, MA, United States
| | - Laura D Kubzansky
- Department of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, Boston, MA, United States
- Lee Kum Sheung Center for Health and Happiness, Harvard TH Chan School of Public Health, Boston, MA, United States
| | - Francine Grodstein
- Department of Internal Medicine, Rush Medical College, Chicago, IL, United States
- Rush Alzheimer's Disease Center, Rush University, Chicago, IL, United States
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21
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Naeem I, Quan H, Singh S, Chowdhury N, Chowdhury M, Saini V, Tc T. Factors Associated With Willingness to Share Health Information: Rapid Review. JMIR Hum Factors 2022; 9:e20702. [PMID: 35138263 PMCID: PMC8867291 DOI: 10.2196/20702] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 11/30/2020] [Accepted: 10/11/2021] [Indexed: 11/25/2022] Open
Abstract
Background To expand research and strategies to prevent disease, comprehensive and real-time data are essential. Health data are increasingly available from platforms such as pharmaceuticals, genomics, health care imaging, medical procedures, wearable devices, and internet activity. Further, health data are integrated with an individual’s sociodemographic information, medical conditions, genetics, treatments, and health care. Ultimately, health information generation and flow are controlled by the patient or participant; however, there is a lack of understanding about the factors that influence willingness to share health information. A synthesis of the current literature on the multifactorial nature of health information sharing preferences is required to understand health information exchange. Objective The objectives of this review are to identify peer-reviewed literature that reported factors associated with health information sharing and to organize factors into cohesive themes and present a narrative synthesis of factors related to willingness to share health information. Methods This review uses a rapid review methodology to gather literature regarding willingness to share health information within the context of eHealth, which includes electronic health records, personal health records, mobile health information, general health information, or information on social determinants of health. MEDLINE and Google Scholar were searched using keywords such as electronic health records AND data sharing OR sharing preference OR willingness to share. The search was limited to any population that excluded health care workers or practitioners, and the participants aged ≥18 years within the US or Canadian context. The data abstraction process using thematic analysis where any factors associated with sharing health information were highlighted and coded inductively within each article. On the basis of shared meaning, the coded factors were collated into major themes. Results A total of 26 research articles met our inclusion criteria and were included in the qualitative analysis. The inductive thematic coding process revealed multiple major themes related to sharing health information. Conclusions This review emphasized the importance of data generators’ viewpoints and the complex systems of factors that shape their decision to share health information. The themes explored in this study emphasize the importance of trust at multiple levels to develop effective information exchange partnerships. In the case of improving precision health care, addressing the factors presented here that influence willingness to share information can improve sharing capacity for individuals and allow researchers to reorient their methods to address hesitation in sharing health information.
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Affiliation(s)
- Iffat Naeem
- O'Brien Institute of Public Health, University of Calgary, Calgary, AB, Canada
| | - Hude Quan
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Shaminder Singh
- School of Nursing and Midwifery, Faculty of Health, Community and Education, Mount Royal University, Calgary, AB, Canada
| | - Nashit Chowdhury
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Mohammad Chowdhury
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Vineet Saini
- O'Brien Institute of Public Health, University of Calgary, Calgary, AB, Canada.,Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Research and Innovation - Provincial Population and Public Health, Alberta Health Services, Calgary, AB, Canada
| | - Turin Tc
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Family Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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22
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Grande D, Mitra N, Iyengar R, Merchant RM, Asch DA, Sharma M, Cannuscio CC. Consumer Willingness to Share Personal Digital Information for Health-Related Uses. JAMA Netw Open 2022; 5:e2144787. [PMID: 35072717 PMCID: PMC8787615 DOI: 10.1001/jamanetworkopen.2021.44787] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
IMPORTANCE Consumers routinely generate digital information that reflects on their health. OBJECTIVE To evaluate the factors associated with consumers' willingness to share their digital health information for research, health care, and commercial uses. DESIGN, SETTING, AND PARTICIPANTS This national survey with an embedded conjoint experiment recruited US adults from a nationally representative sample, with oversampling of Black and Hispanic panel members. Participants were randomized to 15 scenarios reflecting use cases for consumer digital information from a total of 324 scenarios. Attributes of the conjoint analysis included 3 uses, 3 users, 9 sources of digital information, and 4 relevant health conditions. The survey was conducted from July 10 to 31, 2020. MAIN OUTCOMES AND MEASURES Participants rated each conjoint profile on a 5-point Likert scale (1-5) measuring their willingness to share their personal digital information (with 5 indicating the most willingness to share). Results reflect mean differences in this scale from a multivariable regression model. RESULTS Among 6284 potential participants, 3543 (56%) responded. A total of 1862 participants (53%) were female, 759 (21%) identified as Black, 834 (24%) identified as Hispanic, and 1274 (36%) were 60 years or older. In comparison with information from electronic health care records, participants were less willing to share information about their finances (coefficient, -0.56; 95% CI, -0.62 to -0.50), places they visit from public cameras (coefficient, -0.28; 95% CI, -0.33 to -0.22), communication on social media (coefficient, -0.20; 95% CI -0.26 to -0.15), and their search history from internet search engines (coefficient, -0.11; 95% CI, -0.17 to -0.06). They were more willing to share information about their steps from applications on their phone (coefficient, 0.22; 95% CI, 0.17-0.28). Among the conjoint attributes, the source of information (importance weight: 59.1%) was more important than the user (17.3%), use (12.3%), and health condition (11.3%). Four clusters of consumers emerged from the sample with divergent privacy views. While the context of use was important, these 4 groups expressed differences in their overall willingness to share, with 337 participants classified as never share; 1116 classified as averse to sharing (mean rating, 1.64; 95% CI, 1.62-1.65); 1616 classified as uncertain about sharing (mean rating, 2.84; 95% CI, 2.81-2.86); and 474 classified as agreeable to sharing (mean rating, 4.18; 95% CI, 4.16-4.21). Respondents who identified as White and non-Hispanic, had higher income, and were politically conservative were more likely to be in a cluster that was less willing to share (ie, never or averse clusters). CONCLUSIONS AND RELEVANCE These findings suggest that although consumers' willingness to share personal digital information for health purposes is associated with the context of use, many have strong underlying privacy views that affect their willingness to share. New protections may be needed to give consumers confidence to be comfortable sharing their personal information.
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Affiliation(s)
- David Grande
- Division of General Internal Medicine, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
| | - Nandita Mitra
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia
| | | | - Raina M. Merchant
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Department of Emergency Medicine, University of Pennsylvania, Philadelphia
| | - David A. Asch
- Division of General Internal Medicine, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia
| | - Meghana Sharma
- Division of General Internal Medicine, University of Pennsylvania, Philadelphia
| | - Carolyn C. Cannuscio
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Department of Family Medicine and Community Health, University of Pennsylvania, Philadelphia
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23
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Nunes Vilaza G, Coyle D, Bardram JE. Public Attitudes to Digital Health Research Repositories: Cross-sectional International Survey. J Med Internet Res 2021; 23:e31294. [PMID: 34714253 PMCID: PMC8590194 DOI: 10.2196/31294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/16/2021] [Accepted: 09/20/2021] [Indexed: 12/05/2022] Open
Abstract
Background Digital health research repositories propose sharing longitudinal streams of health records and personal sensing data between multiple projects and researchers. Motivated by the prospect of personalizing patient care (precision medicine), these initiatives demand broad public acceptance and large numbers of data contributors, both of which are challenging. Objective This study investigates public attitudes toward possibly contributing to digital health research repositories to identify factors for their acceptance and to inform future developments. Methods A cross-sectional online survey was conducted from March 2020 to December 2020. Because of the funded project scope and a multicenter collaboration, study recruitment targeted young adults in Denmark and Brazil, allowing an analysis of the differences between 2 very contrasting national contexts. Through closed-ended questions, the survey examined participants’ willingness to share different data types, data access preferences, reasons for concern, and motivations to contribute. The survey also collected information about participants’ demographics, level of interest in health topics, previous participation in health research, awareness of examples of existing research data repositories, and current attitudes about digital health research repositories. Data analysis consisted of descriptive frequency measures and statistical inferences (bivariate associations and logistic regressions). Results The sample comprises 1017 respondents living in Brazil (1017/1600, 63.56%) and 583 in Denmark (583/1600, 36.44%). The demographics do not differ substantially between participants of these countries. The majority is aged between 18 and 27 years (933/1600, 58.31%), is highly educated (992/1600, 62.00%), uses smartphones (1562/1600, 97.63%), and is in good health (1407/1600, 87.94%). The analysis shows a vast majority were very motivated by helping future patients (1366/1600, 85.38%) and researchers (1253/1600, 78.31%), yet very concerned about unethical projects (1219/1600, 76.19%), profit making without consent (1096/1600, 68.50%), and cyberattacks (1055/1600, 65.94%). Participants’ willingness to share data is lower when sharing personal sensing data, such as the content of calls and texts (1206/1600, 75.38%), in contrast to more traditional health research information. Only 13.44% (215/1600) find it desirable to grant data access to private companies, and most would like to stay informed about which projects use their data (1334/1600, 83.38%) and control future data access (1181/1600, 73.81%). Findings indicate that favorable attitudes toward digital health research repositories are related to a personal interest in health topics (odds ratio [OR] 1.49, 95% CI 1.10-2.02; P=.01), previous participation in health research studies (OR 1.70, 95% CI 1.24-2.35; P=.001), and awareness of examples of research repositories (OR 2.78, 95% CI 1.83-4.38; P<.001). Conclusions This study reveals essential factors for acceptance and willingness to share personal data with digital health research repositories. Implications include the importance of being more transparent about the goals and beneficiaries of research projects using and re-using data from repositories, providing participants with greater autonomy for choosing who gets access to which parts of their data, and raising public awareness of the benefits of data sharing for research. In addition, future developments should engage with and reduce risks for those unwilling to participate.
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Affiliation(s)
- Giovanna Nunes Vilaza
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - David Coyle
- School of Computer Science, University College Dublin, Dublin, Ireland
| | - Jakob Eyvind Bardram
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
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24
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Taylor CO, Flaks-Manov N, Ramesh S, Choe EK. Willingness to Share Wearable Device Data for Research Among Mechanical Turk Workers: Web-Based Survey Study. J Med Internet Res 2021; 23:e19789. [PMID: 34673528 PMCID: PMC8569545 DOI: 10.2196/19789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 02/22/2021] [Accepted: 09/12/2021] [Indexed: 11/25/2022] Open
Abstract
Background Wearable devices that are used for observational research and clinical trials hold promise for collecting data from study participants in a convenient, scalable way that is more likely to reach a broad and diverse population than traditional research approaches. Amazon Mechanical Turk (MTurk) is a potential resource that researchers can use to recruit individuals into studies that use data from wearable devices. Objective This study aimed to explore the characteristics of wearable device users on MTurk that are associated with a willingness to share wearable device data for research. We also aimed to determine whether compensation was a factor that influenced the willingness to share such data. Methods This was a secondary analysis of a cross-sectional survey study of MTurk workers who use wearable devices for health monitoring. A 19-question web-based survey was administered from March 1 to April 5, 2018, to participants aged ≥18 years by using the MTurk platform. In order to identify characteristics that were associated with a willingness to share wearable device data, we performed logistic regression and decision tree analyses. Results A total of 935 MTurk workers who use wearable devices completed the survey. The majority of respondents indicated a willingness to share their wearable device data (615/935, 65.8%), and the majority of these respondents were willing to share their data if they received compensation (518/615, 84.2%). The findings from our logistic regression analyses indicated that Indian nationality (odds ratio [OR] 2.74, 95% CI 1.48-4.01, P=.007), higher annual income (OR 2.46, 95% CI 1.26-3.67, P=.02), over 6 months of using a wearable device (OR 1.75, 95% CI 1.21-2.29, P=.006), and the use of heartbeat and pulse tracking monitoring devices (OR 1.60, 95% CI 0.14-2.07, P=.01) are significant parameters that influence the willingness to share data. The only factor associated with a willingness to share data if compensation is provided was Indian nationality (OR 0.47, 95% CI 0.24-0.9, P=.02). The findings from our decision tree analyses indicated that the three leading parameters associated with a willingness to share data were the duration of wearable device use, nationality, and income. Conclusions Most wearable device users indicated a willingness to share their data for research use (with or without compensation; 615/935, 65.8%). The probability of having a willingness to share these data was higher among individuals who had used a wearable for more than 6 months, were of Indian nationality, or were of American (United States of America) nationality and had an annual income of more than US $20,000. Individuals of Indian nationality who were willing to share their data expected compensation significantly less often than individuals of American nationality (P=.02).
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Affiliation(s)
- Casey Overby Taylor
- Departments of Medicine and Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Natalie Flaks-Manov
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.,Department of Medicine, Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Shankar Ramesh
- College of Information Studies, University of Maryland, College Park, MD, United States
| | - Eun Kyoung Choe
- College of Information Studies, University of Maryland, College Park, MD, United States
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25
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Southwick L, Suh R, Kranzler E, Bradley M, Merchant RM. Characterizing Social Media and Digital Data Use in Mental Health Therapy from Patient and Therapist Perspectives (Preprint). JMIR Form Res 2021; 6:e32103. [PMID: 35797103 PMCID: PMC9305395 DOI: 10.2196/32103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 05/13/2022] [Accepted: 05/27/2022] [Indexed: 11/13/2022] Open
Abstract
Background Incorporating insights from social media into the patient-provider encounter is increasingly being explored in health care settings. Less is known about the utility of these data in mental health therapy. Objective This study aims to prospectively investigate and characterize how social media and digital data are used in mental health therapy from both the patient and mental health therapist perspective. Methods Patients enrolled in mental health therapy and mental health therapists were interviewed using a semistructured interview guide. All interviews were transcribed and coded using a deductive framework analysis. Themes and subthemes were identified. Participants completed a sociodemographic survey, while mental health therapists also completed a behavioral norms and elicitation survey. Results Seventeen participants, that is, 8 (48%) mental health therapists and 9 (52%) patients were interviewed. Overall, participants identified 4 themes and 9 subthemes. Themes were current data collection practices, social media and digital data in therapy, advantages of social media and digital data in therapy, and disadvantages of social media and digital data in therapy. Most subthemes were related to the advantages and disadvantages of incorporating digital data in mental health therapy. Advantage subthemes included convenience, objective, builds rapport, and user-friendliness while disadvantage subthemes were nonreflective, ethically ambiguous, and nongeneralizable. The mental health therapists' behavioral norms and elicitation survey found that injunctive and descriptive normative beliefs mapped onto 2 advantage subthemes: convenience and objectivity. Conclusions This qualitative pilot study established the advantages and disadvantages of social media and digital data use in mental health therapy. Patients and therapists highlighted similar concerns and uses. This study indicated that overall, both patients and therapists are interested in and are comfortable to use and discuss social media and digital data in mental health therapy.
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Affiliation(s)
| | - Rebecca Suh
- University of Pennsylvania, Philadelphia, PA, United States
| | | | - Megan Bradley
- University of Pennsylvania, Philadelphia, PA, United States
| | - Raina M Merchant
- University of Pennsylvania, Philadelphia, PA, United States
- Department of Emergency Medicine, Perelman School of Medicine, Philadelphia, PA, United States
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26
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Resnik P, Foreman A, Kuchuk M, Musacchio Schafer K, Pinkham B. Naturally occurring language as a source of evidence in suicide prevention. Suicide Life Threat Behav 2021; 51:88-96. [PMID: 32914479 DOI: 10.1111/sltb.12674] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
We discuss computational language analysis as it pertains to suicide prevention research, with an emphasis on providing non-technologists with an understanding of key issues and, equally important, considering its relation to the broader enterprise of suicide prevention. Our emphasis here is on naturally occurring language in social media, motivated by its non-intrusive ability to yield high-value information that in the past has been largely unavailable to clinicians.
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Affiliation(s)
| | - April Foreman
- American Association of Suicidology, Washington, District of Columbia, USA
| | - Michelle Kuchuk
- Vibrant Emotional Health, New York, New York, USA.,National Suicide Prevention Lifeline, New York, New York, USA
| | | | - Beau Pinkham
- American Association of Suicidology, Washington, District of Columbia, USA.,National Suicide Prevention Lifeline, New York, New York, USA.,International Council for Helplines, Nashville, Tennessee, USA
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27
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Yoo DW, Birnbaum ML, Van Meter AR, Ali AF, Arenare E, Abowd GD, De Choudhury M. Designing a Clinician-Facing Tool for Using Insights From Patients' Social Media Activity: Iterative Co-Design Approach. JMIR Ment Health 2020; 7:e16969. [PMID: 32784180 PMCID: PMC7450381 DOI: 10.2196/16969] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 06/27/2020] [Accepted: 07/09/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Recent research has emphasized the need for accessing information about patients to augment mental health patients' verbal reports in clinical settings. Although it has not been introduced in clinical settings, computational linguistic analysis on social media has proved it can infer mental health attributes, implying a potential use as collateral information at the point of care. To realize this potential and make social media insights actionable to clinical decision making, the gaps between computational linguistic analysis on social media and the current work practices of mental health clinicians must be bridged. OBJECTIVE This study aimed to identify information derived from patients' social media data that can benefit clinicians and to develop a set of design implications, via a series of low-fidelity (lo-fi) prototypes, on how to deliver the information at the point of care. METHODS A team of clinical researchers and human-computer interaction (HCI) researchers conducted a long-term co-design activity for over 6 months. The needs-affordances analysis framework was used to refine the clinicians' potential needs, which can be supported by patients' social media data. On the basis of those identified needs, the HCI researchers iteratively created 3 different lo-fi prototypes. The prototypes were shared with both groups of researchers via a videoconferencing software for discussion and feedback. During the remote meetings, potential clinical utility, potential use of the different prototypes in a treatment setting, and areas of improvement were discussed. RESULTS Our first prototype was a card-type interface that supported treatment goal tracking. Each card included attribute levels: depression, anxiety, social activities, alcohol, and drug use. This version confirmed what types of information are helpful but revealed the need for a glanceable dashboard that highlights the trends of these information. As a result, we then developed the second prototype, an interface that shows the clinical state and trend. We found that focusing more on the changes since the last visit without visual representation can be more compatible with clinicians' work practices. In addition, the second phase of needs-affordances analysis identified 3 categories of information relevant to patients with schizophrenia: symptoms related to psychosis, symptoms related to mood and anxiety, and social functioning. Finally, we developed the third prototype, a clinical summary dashboard that showed changes from the last visit in plain texts and contrasting colors. CONCLUSIONS This exploratory co-design research confirmed that mental health attributes inferred from patients' social media data can be useful for clinicians, although it also revealed a gap between computational social media analyses and clinicians' expectations and conceptualizations of patients' mental health states. In summary, the iterative co-design process crystallized design directions for the future interface, including how we can organize and provide symptom-related information in a way that minimizes the clinicians' workloads.
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Affiliation(s)
- Dong Whi Yoo
- School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, United States
| | - Michael L Birnbaum
- The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, United States
- The Feinstein Institutes for Medical Research, Manhasset, NY, United States
- The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Anna R Van Meter
- The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, United States
- The Feinstein Institutes for Medical Research, Manhasset, NY, United States
- The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Asra F Ali
- The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, United States
| | - Elizabeth Arenare
- The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, United States
| | - Gregory D Abowd
- School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, United States
| | - Munmun De Choudhury
- School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, United States
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28
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Guntuku SC, Schwartz HA, Kashyap A, Gaulton JS, Stokes DC, Asch DA, Ungar LH, Merchant RM. Variability in Language used on Social Media prior to Hospital Visits. Sci Rep 2020; 10:4346. [PMID: 32165648 PMCID: PMC7067847 DOI: 10.1038/s41598-020-60750-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 02/10/2020] [Indexed: 11/30/2022] Open
Abstract
Forecasting healthcare utilization has the potential to anticipate care needs, either accelerating needed care or redirecting patients toward care most appropriate to their needs. While prior research has utilized clinical information to forecast readmissions, analyzing digital footprints from social media can inform our understanding of individuals' behaviors, thoughts, and motivations preceding a healthcare visit. We evaluate how language patterns on social media change prior to emergency department (ED) visits and inpatient hospital admissions in this case-crossover study of adult patients visiting a large urban academic hospital system who consented to share access to their history of Facebook statuses and electronic medical records. An ensemble machine learning model forecasted ED visits and inpatient admissions with out-of-sample cross-validated AUCs of 0.64 and 0.70 respectively. Prior to an ED visit, there was a significant increase in depressed language (Cohen's d = 0.238), and a decrease in informal language (d = 0.345). Facebook posts prior to an inpatient admission showed significant increase in expressions of somatic pain (d = 0.267) and decrease in extraverted/social language (d = 0.357). These results are a first step in developing methods to utilize user-generated content to characterize patient care-seeking context which could ultimately enable better allocation of resources and potentially early interventions to reduce unplanned visits.
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Affiliation(s)
| | | | | | - Jessica S Gaulton
- University of Pennsylvania, Philadelphia, PA, USA
- Children's Hospital of Pennsylvania, Philadelphia, PA, USA
| | | | - David A Asch
- University of Pennsylvania, Philadelphia, PA, USA
- Cpl Michael J Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Lyle H Ungar
- University of Pennsylvania, Philadelphia, PA, USA
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29
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Bradway M, Giordanengo A, Joakimsen R, Hansen AH, Grøttland A, Hartvigsen G, Randine P, Årsand E. Measuring the Effects of Sharing Mobile Health Data During Diabetes Consultations: Protocol for a Mixed Method Study. JMIR Res Protoc 2020; 9:e16657. [PMID: 32039818 PMCID: PMC7055770 DOI: 10.2196/16657] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 11/27/2019] [Accepted: 12/16/2019] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND There is rising demand for health care's limited resources. Mobile health (mHealth) could be a solution, especially for those with chronic illnesses such as diabetes. mHealth can increases patients' options to self-manage their health, improving their health knowledge, engagement, and capacity to contribute to their own care decisions. However, there are few solutions for sharing and presenting patients' mHealth data with health care providers (HCPs) in a mutually understandable way, which limits the potential of shared decision making. OBJECTIVE Through a six-month mixed method feasibility study in Norway, we aim to explore the impacts that a system for sharing patient-gathered data from mHealth devices has on patients and HCPs during diabetes consultations. METHODS Patients with diabetes will be recruited through their HCPs. Participants will use the Diabetes Diary mobile phone app to register and review diabetes self-management data and share these data during diabetes consultations using the FullFlow data-sharing system. The primary outcome is the feasibility of the system, which includes HCP impressions and expectations (prestudy survey), usability (System Usability Scale), functionalities used and data shared during consultations, and study-end focus group meetings. Secondary outcomes include a change in the therapeutic relationship, patient empowerment and wellness, health parameters (HbA1c and blood pressure), and the patients' own app-registered health measures (blood glucose, medication, physical activity, diet, and weight). We will compare measures taken at baseline and at six months, as well as data continuously gathered from the app. Analysis will aim to explain which measures have changed and how and why they have changed during the intervention. RESULTS The Full Flow project is funded for 2016 to 2020 by the Research Council of Norway (number 247974/O70). We approached 14 general practitioner clinics (expecting to recruit 1-2 general practitioners per clinic) and two hospitals (expecting to recruit 2-3 nurses per hospital). By recruiting through the HCPs, we expect to recruit 74 patients with type 2 and 33 patients with type 1 diabetes. Between November 2018 and July 2019, we recruited eight patients and 15 HCPs. During 2020, we aim to analyze and publish the results of the collected data from our patient and HCP participants. CONCLUSIONS We expect to better understand what is needed to be able to share data. This includes potential benefits that sharing patient-gathered data during consultations will have on patients and HCPs, both individually and together. By measuring these impacts, we will be able to present the possibilities and challenges related to a system for sharing mHealth data for future interventions and practice. Results will also demonstrate what needs to be done to make this collaboration between HCPs and patients successful and subsequently further improve patients' health and engagement in their care.
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Affiliation(s)
- Meghan Bradway
- Norwegian Center for E-health Research, University Hospital of North Norway, Tromsø, Norway
- Department of Clinical Medicine, University of Tromsø-The Arctic University of Norway, Tromsø, Norway
| | - Alain Giordanengo
- Norwegian Center for E-health Research, University Hospital of North Norway, Tromsø, Norway
- Department of Computer Science, University of Tromsø-The Arctic University of Norway, Tromsø, Norway
| | - Ragnar Joakimsen
- Department of Clinical Medicine, University of Tromsø-The Arctic University of Norway, Tromsø, Norway
- Department of Internal Medicine, University Hospital of North Norway, Tromsø, Norway
| | - Anne Helen Hansen
- Department of Community Medicine, University of Tromsø-The Arctic University of Norway, Tromsø, Norway
- Centre for Quality Improvement and Development, University Hospital of North Norway, Tromsø, Norway
| | - Astrid Grøttland
- Norwegian Center for E-health Research, University Hospital of North Norway, Tromsø, Norway
| | - Gunnar Hartvigsen
- Department of Computer Science, University of Tromsø-The Arctic University of Norway, Tromsø, Norway
- Faculty of Health and Sport Science, University of Agder, Grimstad, Norway
| | - Pietro Randine
- Norwegian Center for E-health Research, University Hospital of North Norway, Tromsø, Norway
- Department of Computer Science, University of Tromsø-The Arctic University of Norway, Tromsø, Norway
| | - Eirik Årsand
- Norwegian Center for E-health Research, University Hospital of North Norway, Tromsø, Norway
- Department of Computer Science, University of Tromsø-The Arctic University of Norway, Tromsø, Norway
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