Futures for Health Research Data Platforms From the Participants’ Perspectives

In clinical cohort studies, researchers analyse the life history of population groups to understand the evolution of diseases. Health research data platforms came to facilitate such studies as they allow multiple projects to share access to cohorts’ non-identifiable health information. Some latest initiatives are also starting to include mobile-generated data in their research programmes. Although seemly beneficial, it is not yet clear how potential participants feel about contributing to the new platforms: there is a need to investigate potential factors related to the acceptance in this specific context. In this paper, previous works from related contexts were brought together and, along with a qualitative study, composed a participant-centred perspective of enablers and barriers for contribution. We found that there is an apparent misalignment between current implementations and participants’ preferences, leading us to propose design guidelines for future developments which can make participation more ethical and engaging.

[1]  Mohamed Abdelhamid,et al.  Greater patient health information control to improve the sustainability of health information exchanges , 2018, J. Biomed. Informatics.

[2]  Tom Rodden,et al.  Consent for all: revealing the hidden complexity of terms and conditions , 2013, CHI.

[3]  Dan Cosley,et al.  Privacy, Power, and Invisible Labor on Amazon Mechanical Turk , 2019, CHI.

[4]  Lucila Ohno-Machado,et al.  Comparison of consumers' views on electronic data sharing for healthcare and research , 2015, J. Am. Medical Informatics Assoc..

[5]  C. Sas,et al.  Technology acceptance in mHealth: a scoping review of definitions, models and measurement , 2020 .

[6]  P. Areán,et al.  Contemporary Views of Research Participant Willingness to Participate and Share Digital Data in Biomedical Research , 2019, JAMA network open.

[7]  J. Frost,et al.  Sharing Health Data for Better Outcomes on PatientsLikeMe , 2010, Journal of medical Internet research.

[8]  Stephen Voida,et al.  Personal Informatics in Interpersonal Contexts , 2018, Proc. ACM Hum. Comput. Interact..

[9]  H. Krumholz,et al.  Health Care and Precision Medicine Research: Analysis of a Scalable Data Science Platform , 2019, Journal of medical Internet research.

[10]  Wanda Pratt,et al.  Understanding quantified-selfers' practices in collecting and exploring personal data , 2014, CHI.

[11]  Mark S. Ackerman,et al.  Designing Healthcare That Works: A Sociotechnical Approach , 2017 .

[12]  Kenneth D. Mandl,et al.  Willingness to share personal health record data for care improvement and public health: a survey of experienced personal health record users , 2012, BMC Medical Informatics and Decision Making.

[13]  Lina A. Colucci,et al.  The quantified patient of the future: Opportunities and challenges. , 2015, Healthcare.

[14]  Leanne Chang,et al.  Follow me and like my beautiful selfies: Singapore teenage girls' engagement in self-presentation and peer comparison on social media , 2016, Comput. Hum. Behav..

[15]  Alistair Morrison,et al.  Student Perspectives on Digital Phenotyping: The Acceptability of Using Smartphone Data to Assess Mental Health , 2019, CHI.

[16]  Susan B. Newman,et al.  Improving informed consent: Stakeholder views , 2017, AJOB empirical bioethics.

[17]  Sean A. Munson,et al.  Finding the Right Fit: Understanding Health Tracking in Workplace Wellness Programs , 2017, CHI.

[18]  J. Wilbanks,et al.  The Rise of Citizen Science in Health and Biomedical Research , 2019, The American journal of bioethics : AJOB.

[19]  V. Montori,et al.  Patient and service user engagement in research: a systematic review and synthesized framework , 2015, Health expectations : an international journal of public participation in health care and health policy.

[20]  Hans-Theo Normann,et al.  The Willingness to Sell Personal Data , 2018, The Scandinavian Journal of Economics.

[21]  Patty Kostkova,et al.  Who Owns the Data? Open Data for Healthcare , 2016, Front. Public Health.

[22]  Paul Voigt,et al.  The EU General Data Protection Regulation (GDPR) , 2017 .

[23]  Robin M. Kowalski,et al.  Impression management: A literature review and two-component model. , 1990 .

[24]  Jakob E. Bardram,et al.  Sharing Access to Behavioural and Personal Health Data: Designers' Perspectives on Opportunities and Barriers , 2019, PervasiveHealth.

[25]  Elizabeth D. Mynatt,et al.  Comparing Health Information Sharing Preferences of Cancer Patients, Doctors, and Navigators , 2015, CSCW.

[26]  Martina Ziefle,et al.  Users' Willingness to Share Data on the Internet: Perceived Benefits and Caveats , 2016, IoTBD.

[27]  Christopher A. Le Dantec,et al.  Exploring Trust in Digital Civics , 2018, Conference on Designing Interactive Systems.

[28]  Helena M. Mentis,et al.  Sharing medical data vs. health knowledge in chronic illness care , 2012, CHI Extended Abstracts.

[29]  Selma Sabanovic,et al.  The effect of monitoring by cameras and robots on the privacy enhancing behaviors of older adults , 2012, 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[30]  Nadir Weibel,et al.  ExtraSensory App: Data Collection In-the-Wild with Rich User Interface to Self-Report Behavior , 2018, CHI.

[31]  Simone Fischer-Hübner,et al.  Usable Transparency Enhancing Tools : A Literature Review , 2017 .

[32]  Tiffany C. Veinot,et al.  User acceptance of location-tracking technologies in health research: Implications for study design and data quality , 2018, J. Biomed. Informatics.

[33]  Nicholas D. Lane,et al.  Scaling health analytics to millions without compromising privacy using deep distributed behavior models , 2017, PervasiveHealth.

[34]  Carolyn Petersen,et al.  The Future of Patient Engagement in the Governance of Shared Data , 2016, EGEMS.

[35]  Amy Maxmen Google spin-off deploys wearable electronics for huge health study , 2017, Nature.

[36]  Nigel Shadbolt,et al.  The Quantified Patient in the Doctor's Office: Challenges & Opportunities , 2016, CHI.

[37]  David Coyle,et al.  Privacy, boundaries and smart homes for health: An ethnographic study , 2018, Health & place.

[38]  Euan A Ashley,et al.  The precision medicine initiative: a new national effort. , 2015, JAMA.

[39]  M. Angela Sasse,et al.  Would You Sell Your Mother's Data? Personal Data Disclosure in a Simulated Credit Card Application , 2012, WEIS.

[40]  S. Fullerton,et al.  Informed Consent in Genome-Scale Research: What Do Prospective Participants Think? , 2012, AJOB primary research.

[41]  H. Raghav Rao,et al.  Exploring factors impacting sharing health-tracking records , 2015 .

[42]  Oded Nov,et al.  Open Humans: A platform for participant-centered research and personal data exploration , 2018, bioRxiv.

[43]  Sean A. Munson,et al.  Beyond Abandonment to Next Steps: Understanding and Designing for Life after Personal Informatics Tool Use , 2016, CHI.

[44]  Salil S. Kanhere,et al.  A survey on privacy in mobile participatory sensing applications , 2011, J. Syst. Softw..

[45]  Mildred K Cho,et al.  Beyond Consent: Building Trusting Relationships With Diverse Populations in Precision Medicine Research , 2018, The American journal of bioethics : AJOB.

[46]  P. Sankar,et al.  The Precision Medicine Initiative’s All of Us Research Program: an agenda for research on its ethical, legal, and social issues , 2016, Genetics in Medicine.

[47]  Richmond Y. Wong,et al.  An Interface without A User: An Exploratory Design Study of Online Privacy Policies and Digital Legalese , 2018, Conference on Designing Interactive Systems.

[48]  Norman A. Johnson,et al.  Personality traits and concern for privacy: an empirical study in the context of location-based services , 2008, Eur. J. Inf. Syst..

[49]  Predrag V. Klasnja,et al.  Exploring Privacy Concerns about Personal Sensing , 2009, Pervasive.

[50]  U. Hegerl,et al.  Smartphone-Based Monitoring of Objective and Subjective Data in Affective Disorders: Where Are We and Where Are We Going? Systematic Review , 2017, Journal of medical Internet research.

[51]  H. Nissenbaum A Contextual Approach to Privacy Online , 2011, Daedalus.

[52]  Richard J. Whiddett,et al.  Patients' attitudes towards sharing their health information , 2006, Int. J. Medical Informatics.

[53]  Access control for home data sharing: evaluating social acceptability , 2010, CHI.

[54]  Marcello Ienca,et al.  On the responsible use of digital data to tackle the COVID-19 pandemic , 2020, Nature Medicine.

[55]  Loren G. Terveen,et al.  Capturing, sharing, and using local place information , 2007, CHI.

[56]  K. Shojania,et al.  Informed consent documents do not encourage good-quality decision making. , 2012, Journal of clinical epidemiology.

[57]  Bongshin Lee,et al.  Self-tracking for Mental Wellness: Understanding Expert Perspectives and Student Experiences , 2017, CHI.

[58]  Wendy A. Wolf,et al.  Public and Biobank Participant Attitudes toward Genetic Research Participation and Data Sharing , 2010, Public Health Genomics.

[59]  William Odom,et al.  Keeping and Discarding Personal Data: Exploring a Design Space , 2019, Conference on Designing Interactive Systems.

[60]  Michael Morrison,et al.  Dynamic consent: a patient interface for twenty-first century research networks , 2014, European Journal of Human Genetics.

[61]  Corina Sas,et al.  Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement , 2019, Journal of medical Internet research.

[62]  D. Jeste,et al.  Enhancing Informed Consent for Research and Treatment , 2001, Neuropsychopharmacology.

[63]  Katherine I. Morley,et al.  Attitudes of publics who are unwilling to donate DNA data for research , 2019, European journal of medical genetics.

[64]  Travis D. Breaux,et al.  Empirical Measurement of Perceived Privacy Risk , 2018, ACM Trans. Comput. Hum. Interact..

[65]  Matthew Chalmers,et al.  Improving consent in large scale mobile HCI through personalised representations of data , 2014, NordiCHI.

[66]  S. M. Arnsten Intrinsic motivation. , 1990, The American journal of occupational therapy : official publication of the American Occupational Therapy Association.

[67]  Yvonne Rogers,et al.  A City in Common: A Framework to Orchestrate Large-scale Citizen Engagement around Urban Issues , 2017, CHI.

[68]  K. Muto,et al.  For what am I participating? The need for communication after receiving consent from biobanking project participants: experience in Japan , 2011, Journal of Human Genetics.

[69]  J. Sloan,et al.  Patient engagement in research: a systematic review , 2014, BMC Health Services Research.

[70]  Daniel R. Horne,et al.  The Privacy Paradox: Personal Information Disclosure Intentions versus Behaviors , 2007 .

[71]  Henrik Toft Sørensen,et al.  The Danish Civil Registration System as a tool in epidemiology , 2014, European Journal of Epidemiology.

[72]  Gabriella M. Harari,et al.  An Evaluation of Students’ Interest in and Compliance With Self-Tracking Methods , 2017 .

[73]  Steven Cummins,et al.  Associations between fast food and physical activity environments and adiposity in mid-life: cross-sectional, observational evidence from UK Biobank , 2017, The Lancet. Public health.

[74]  Leah Findlater,et al.  Sharing automatically tracked activity data: implications for therapists and people with mobility impairments , 2017, PervasiveHealth.

[75]  Richard O. Sinnott,et al.  Advancing the ethical use of digital data in human research: challenges and strategies to promote ethical practice , 2018, Ethics and Information Technology.

[76]  Mark Barnes,et al.  A Global, Neutral Platform for Sharing Trial Data. , 2016, The New England journal of medicine.

[77]  Michael J Pencina,et al.  Supporting open access to clinical trial data for researchers: The Duke Clinical Research Institute-Bristol-Myers Squibb Supporting Open Access to Researchers Initiative. , 2016, American heart journal.

[78]  L. Mikesell,et al.  From subject to participant: ethics and the evolving role of community in health research. , 2015, American journal of public health.

[79]  William R. King,et al.  A meta-analysis of the technology acceptance model , 2006, Inf. Manag..

[80]  Nadir Weibel,et al.  Ethical and regulatory challenges of research using pervasive sensing and other emerging technologies: IRB perspectives , 2017, AJOB empirical bioethics.

[81]  Andrea Hartzler,et al.  Participant-centric initiatives: Tools to facilitate engagement in research , 2012, Applied & translational genomics.

[82]  Anna L. Cox,et al.  Why Do You Need This?: Selective Disclosure of Data Among Citizen Scientists , 2019, CHI.

[83]  Lucy Van Kleunen,et al.  Being (In)Visible: Privacy, Transparency, and Disclosure in the Self-Management of Bipolar Disorder , 2020, CHI.

[84]  Jodi Forlizzi,et al.  A stage-based model of personal informatics systems , 2010, CHI.

[85]  C. Mann,et al.  Observational research methods. Research design II: cohort, cross sectional, and case-control studies , 2003, Emergency medicine journal : EMJ.

[86]  A. Middleton Society and personal genome data , 2018, Human molecular genetics.

[87]  Cicely Marston,et al.  Patient and public attitudes towards informed consent models and levels of awareness of Electronic Health Records in the UK , 2015, Int. J. Medical Informatics.

[88]  Jakob E. Bardram,et al.  Double-Loop Health Technology , 2018 .

[89]  Rachel Conrad Bracken,et al.  Trust and privacy in the context of user-generated health data , 2017, Big Data Soc..

[90]  Lujo Bauer,et al.  Access Control for Home Data Sharing: Attitudes, Needs and Practices , 2010, CHI.

[91]  Carman Neustaedter,et al.  Help Me Help You: Shared Reflection for Personal Data , 2016, GROUP.

[92]  Paul Voigt,et al.  The Eu General Data Protection Regulation (Gdpr): A Practical Guide , 2017 .

[93]  J. Pawlikowski,et al.  Public Attitudes toward Biobanking of Human Biological Material for Research Purposes: A Literature Review , 2019, International journal of environmental research and public health.

[94]  Sharon F. Terry,et al.  Power to the People: Participant Ownership of Clinical Trial Data , 2011, Science Translational Medicine.

[95]  Jeong-Whun Kim,et al.  Prescribing 10,000 Steps Like Aspirin: Designing a Novel Interface for Data-Driven Medical Consultations , 2017, CHI.

[96]  Harlan M Krumholz,et al.  Data Sharing and Cardiology: Platforms and Possibilities. , 2017, Journal of the American College of Cardiology.

[97]  Nidhi Bhatnagar,et al.  A Case for Participatory Disease Surveillance of the COVID-19 Pandemic in India , 2020, JMIR public health and surveillance.

[98]  Patient engagement in clinical research through mobile technology , 2014 .

[99]  C. Petersen Through Patients' Eyes: Regulation, Technology, Privacy, and the Future , 2018, Yearbook of Medical Informatics.

[100]  Pierre Lévy,et al.  A Design Approach towards Affording the Trend of Privacy , 2019, Conference on Designing Interactive Systems.

[101]  Jones Albuquerque,et al.  Participatory Surveillance Based on Crowdsourcing During the Rio 2016 Olympic Games Using the Guardians of Health Platform: Descriptive Study , 2020, JMIR public health and surveillance.

[102]  C. Ohmann,et al.  Evaluation of repositories for sharing individual-participant data from clinical studies , 2019, Trials.

[103]  Wijnand A. IJsselsteijn,et al.  Design Beyond the Numbers: Sharing, Comparing, Storytelling and the Need for a Quantified Us , 2016, IxD&A.

[104]  Maurizio Marchese,et al.  Information Design in An Aged Care Context: Views of Older Adults on Information Sharing in a Care Triad , 2019, PervasiveHealth.

[105]  Alessandro Blasimme,et al.  Elements of Trust in Digital Health Systems: Scoping Review , 2018, Journal of medical Internet research.

[106]  Paul Dourish,et al.  Unpacking "privacy" for a networked world , 2003, CHI '03.

[107]  Deborah E. White,et al.  Thematic Analysis , 2017 .

[108]  Jakob E. Bardram,et al.  Designing mobile health technology for bipolar disorder: a field trial of the monarca system , 2013, CHI.

[109]  Q. Zheng,et al.  Implementation of National Health Informatization in China: Survey About the Status Quo , 2018, JMIR medical informatics.

[110]  P. Elliott,et al.  UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age , 2015, PLoS medicine.

[111]  Geraldine Fitzpatrick,et al.  Reflecting on reflection: framing a design landscape , 2010, OZCHI '10.

[112]  Jeffrey C Murray,et al.  Active choice but not too active: Public perspectives on biobank consent models , 2011, Genetics in Medicine.

[113]  Jonathan Rose,et al.  Patient Willingness to Consent to Mobile Phone Data Collection for Mental Health Apps: Structured Questionnaire , 2018, JMIR mental health.

[114]  Yang Wang,et al.  What matters to users?: factors that affect users' willingness to share information with online advertisers , 2013, SOUPS.

[115]  Gillian R. Hayes,et al.  Developing a model for understanding patient collection of observations of daily living: a qualitative meta-synthesis of the Project HealthDesign program , 2014, Personal and Ubiquitous Computing.

[116]  Sean A Munson,et al.  More Than Telemonitoring: Health Provider Use and Nonuse of Life-Log Data in Irritable Bowel Syndrome and Weight Management , 2015, Journal of medical Internet research.

[117]  Association between TV viewing and heart disease mortality: observational study using negative control outcome , 2020, Journal of Epidemiology & Community Health.

[118]  W. Axinn,et al.  Willingness to Participate in Research during Pregnancy , 2012, Field methods.

[119]  Coye Cheshire,et al.  Sensing is Believing: What People Think Biosensors Can Reveal About Thoughts and Feelings , 2019, Conference on Designing Interactive Systems.

[120]  Jeong-Whun Kim,et al.  "My Doctor is Keeping an Eye on Me!": Exploring the Clinical Applicability of a Mobile Food Logger , 2016, CHI.

[121]  René F. Kizilcec How Much Information?: Effects of Transparency on Trust in an Algorithmic Interface , 2016, CHI.

[122]  Daniel J. Solove A Taxonomy of Privacy , 2006 .

[123]  Ryan M. Kelly,et al.  Biometric Mirror: Exploring Values and Attitudes towards Facial Analysis and Automated Decision-Making , 2019, DIS 2019.

[124]  Jennifer Preece,et al.  Dynamic changes in motivation in collaborative citizen-science projects , 2012, CSCW.

[125]  M. Siegrist The Influence of Trust and Perceptions of Risks and Benefits on the Acceptance of Gene Technology , 2000, Risk analysis : an official publication of the Society for Risk Analysis.

[126]  Melanie Volkamer,et al.  What Deters Jane from Preventing Identification and Tracking on the Web? , 2014, WPES.

[127]  Richard Schulz,et al.  Disability, Age, and Informational Privacy Attitudes in Quality of Life Technology Applications: Results from a National Web Survey , 2009, TACC.

[128]  Rachael Fleurence,et al.  How the Patient-Centered Outcomes Research Institute is engaging patients and others in shaping its research agenda. , 2013, Health affairs.

[129]  Bashar Nuseibeh,et al.  Assessing the Privacy of mHealth Apps for Self-Tracking: Heuristic Evaluation Approach , 2018, JMIR mHealth and uHealth.

[130]  Adam N. Joinson,et al.  Privacy, Trust, and Self-Disclosure Online , 2010, Hum. Comput. Interact..

[131]  Lujo Bauer,et al.  Comparing Hypothetical and Realistic Privacy Valuations , 2018, WPES@CCS.

[132]  Oscar Mayora-Ibarra,et al.  Mobile phones as medical devices in mental disorder treatment: an overview , 2014, Personal and Ubiquitous Computing.

[133]  Eric Gilbert,et al.  User Attitudes towards Algorithmic Opacity and Transparency in Online Reviewing Platforms , 2019, CHI.

[134]  Michiel Verlinden,et al.  Toward a Tiered Model to Share Clinical Trial Data and Samples in Precision Oncology , 2018, Front. Med..

[135]  Mika Raento,et al.  Designing for privacy and self-presentation in social awareness , 2008, Personal and Ubiquitous Computing.

[136]  Jae-Wook Song,et al.  Observational Studies: Cohort and Case-Control Studies , 2010, Plastic and reconstructive surgery.

[137]  Tamsin Ford,et al.  Ethical practice in internet research involving vulnerable people: lessons from a self-harm discussion forum study (SharpTalk) , 2011, Journal of Medical Ethics.

[138]  Mario Macis,et al.  Economic Rewards to Motivate Blood Donations , 2013, Science.

[139]  Ann Blandford,et al.  Semi-structured qualitative studies , 2013 .

[140]  Rui Wang,et al.  Using Smartphones to Collect Behavioral Data in Psychological Science , 2016, Perspectives on psychological science : a journal of the Association for Psychological Science.

[141]  F. Collins,et al.  A new initiative on precision medicine. , 2015, The New England journal of medicine.

[142]  K. Goddard,et al.  Biobank Recruitment: Motivations for Nonparticipation. , 2009, Biopreservation and biobanking.

[143]  David Gefen,et al.  The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online , 2010, Decis. Support Syst..

[144]  G. Goodwin,et al.  Experiences of Remote Mood and Activity Monitoring in Bipolar Disorder: A Qualitative Study , 2017, European Psychiatry.

[145]  Michael Riegler,et al.  Mental health monitoring with multimodal sensing and machine learning: A survey , 2018, Pervasive Mob. Comput..

[146]  Helena M. Mentis,et al.  Crafting a View of Self-Tracking Data in the Clinical Visit , 2017, CHI.