Consumer Willingness to Share Personal Digital Information for Health-Related Uses

Key Points Question What factors are associated with consumers’ willingness to share their digital information for health-related uses? Findings In this survey study of 3543 US adults, consumer willingness to share digital data was associated with a range of factors, most importantly the source and type of data. Certain data (eg, financial, social media, public cameras) were viewed as more sensitive than electronic health record data, but underlying views on digital health privacy were strongly associated with consumer views on sharing any digital information. Meaning In this study, many consumers were reluctant to share their digital data for health-related uses, suggesting that new privacy protections may be needed to increase consumer trust.

[1]  A. Tele,et al.  Mental health service preferences of patients and providers: a scoping review of conjoint analysis and discrete choice experiments from global public health literature over the last 20 years (1999–2019) , 2021, BMC Health Services Research.

[2]  D. Asch,et al.  Consumer Views on Health Applications of Consumer Digital Data and Health Privacy Among US Adults: Qualitative Interview Study , 2021, Journal of medical Internet research.

[3]  R. Merchant,et al.  Consumer Views on Using Digital Data for COVID-19 Control in the United States , 2021, JAMA network open.

[4]  L. Sharp,et al.  Using Fitbit as an mHealth Intervention Tool to Promote Physical Activity: Potential Challenges and Solutions , 2021, JMIR mHealth and uHealth.

[5]  K. Mandl,et al.  Privacy protections to encourage use of health-relevant digital data in a learning health system , 2021, npj Digital Medicine.

[6]  C. Vandelanotte,et al.  Effects of an Activity Tracker and App Intervention to Increase Physical Activity in Whole Families—The Step It Up Family Feasibility Study , 2020, International journal of environmental research and public health.

[7]  Grace Fox,et al.  "To protect my health or to protect my health privacy?" A mixed-methods investigation of the privacy paradox , 2020, J. Assoc. Inf. Sci. Technol..

[8]  Sharath Chandra Guntuku,et al.  Tracking Mental Health and Symptom Mentions on Twitter During COVID-19 , 2020, Journal of General Internal Medicine.

[9]  D. Asch,et al.  Health Policy and Privacy Challenges Associated With Digital Technology , 2020, JAMA network open.

[10]  Timothy R. Huerta,et al.  Differences Between Races in Health Information Seeking and Trust Over Time: Evidence From a Cross-Sectional, Pooled Analyses of HINTS Data , 2020, American journal of health promotion : AJHP.

[11]  Masooda N. Bashir,et al.  Use of apps in the COVID-19 response and the loss of privacy protection , 2020, Nature Medicine.

[12]  Pouyan Esmaeilzadeh The Effects of Public Concern for Information Privacy on the Adoption of Health Information Exchanges (HIEs) by Healthcare Entities , 2019, Health communication.

[13]  Sharath Chandra Guntuku,et al.  Patients’ willingness to share digital health and non-health data for research: a cross-sectional study , 2019, BMC Medical Informatics and Decision Making.

[14]  Sharath Chandra Guntuku,et al.  Evaluating the predictability of medical conditions from social media posts , 2019, PloS one.

[15]  Lorrie Faith Cranor,et al.  Disposition toward privacy and information disclosure in the context of emerging health technologies , 2019, J. Am. Medical Informatics Assoc..

[16]  Jeffrey A. Linder,et al.  Quality and Experience of Outpatient Care in the United States for Adults With or Without Primary Care , 2019, JAMA internal medicine.

[17]  D. Asch,et al.  Facebook language predicts depression in medical records , 2018, Proceedings of the National Academy of Sciences.

[18]  T. Penzel,et al.  New technology to assess sleep apnea: wearables, smartphones, and accessories , 2018, F1000Research.

[19]  C. Vandelanotte,et al.  Randomised controlled trial using a theory-based m-health intervention to improve physical activity and sleep health in adults: the Synergy Study protocol , 2018, BMJ Open.

[20]  Scout Calvert,et al.  Opportunities and challenges in the use of personal health data for health research , 2016, J. Am. Medical Informatics Assoc..

[21]  Nandita Mitra,et al.  Public preferences about secondary uses of electronic health information. , 2013, JAMA internal medicine.

[22]  Alessandro Acquisti,et al.  Misplaced Confidences , 2013, WEIS.

[23]  Rainu Kaushal,et al.  Low-income, ethnically diverse consumers' perspective on health information exchange and personal health records , 2011, Informatics for health & social care.

[24]  Thomas A. Horan,et al.  Personal health records , 2011, Health Informatics J..

[25]  Mario Callegaro,et al.  Computing Response Metrics for Online Panels , 2008 .

[26]  D. Collins Pretesting survey instruments: An overview of cognitive methods , 2003, Quality of Life Research.

[27]  Paul E. Green,et al.  Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice , 1990 .

[28]  P. Green,et al.  Conjoint Analysis in Consumer Research: Issues and Outlook , 1978 .