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Published in: BMC Medical Informatics and Decision Making 1/2019

Open Access 01-12-2019 | Research article

Patients’ willingness to share digital health and non-health data for research: a cross-sectional study

Authors: Emily Seltzer, Jesse Goldshear, Sharath Chandra Guntuku, Dave Grande, David A. Asch, Elissa V. Klinger, Raina M. Merchant

Published in: BMC Medical Informatics and Decision Making | Issue 1/2019

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Abstract

Background

Patients generate large amounts of digital data through devices, social media applications, and other online activities. Little is known about patients’ perception of the data they generate online and its relatedness to health, their willingness to share data for research, and their preferences regarding data use.

Methods

Patients at an academic urban emergency department were asked if they would donate any of 19 different types of data to health researchers and were asked about their views on data types’ health relatedness. Factor analysis was used to identify the structure in patients’ perceptions of willingness to share different digital data, and their health relatedness.

Results

Of 595 patients approached 206 agreed to participate, of whom 104 agreed to share at least one types of digital data immediately, and 78% agreed to donate at least one data type after death. EMR, wearable, and Google search histories (80%) had the highest percentage of reported health relatedness. 72% participants wanted to know the results of any analysis of their shared data, and half wanted their healthcare provider to know.

Conclusion

Patients in this study were willing to share a considerable amount of personal digital data with health researchers. They also recognize that digital data from many sources reveal information about their health. This study opens up a discussion around reconsidering US privacy protections for health information to reflect current opinions and to include their relatedness to health.
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Literature
1.
go back to reference Hill K. How target figured out a teen girl was pregnant before her father did: Forbes; 2012. Hill K. How target figured out a teen girl was pregnant before her father did: Forbes; 2012.
5.
go back to reference Grande D, Mitra N, Shah A, Wan F, Asch DA. Public preferences about secondary uses of electronic health information. JAMA Intern Med. 2013;173:1798.CrossRef Grande D, Mitra N, Shah A, Wan F, Asch DA. Public preferences about secondary uses of electronic health information. JAMA Intern Med. 2013;173:1798.CrossRef
6.
go back to reference Nissenbaum H. Privacy in context: Technology, policy, and the integrity of social life. Stanford: Stanford University Press; 2009. Nissenbaum H. Privacy in context: Technology, policy, and the integrity of social life. Stanford: Stanford University Press; 2009.
7.
go back to reference Padrez KA, et al. Linking social media and medical record data: a study of adults presenting to an academic, urban emergency department. BMJ Qual Saf. 2016;25:414–23.CrossRef Padrez KA, et al. Linking social media and medical record data: a study of adults presenting to an academic, urban emergency department. BMJ Qual Saf. 2016;25:414–23.CrossRef
8.
go back to reference Fox S, Jones S. The Social Life of Health Information, Pew Research Center’s Internet & American Life Project; 2011. Fox S, Jones S. The Social Life of Health Information, Pew Research Center’s Internet & American Life Project; 2011.
9.
go back to reference Doherty C, Lang M. An Exploratory Survey of the Effects of Perceived Control and Perceived Risk on Information Privacy. In: 9th Annual Symposium on Information Assurance; 2014. Doherty C, Lang M. An Exploratory Survey of the Effects of Perceived Control and Perceived Risk on Information Privacy. In: 9th Annual Symposium on Information Assurance; 2014.
10.
go back to reference Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika. 1965;30:179–85.CrossRef Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika. 1965;30:179–85.CrossRef
11.
go back to reference Hayton JC, Allen DG, Scarpello V. Factor retention decisions in exploratory factor analysis: a tutorial on parallel analysis. Organ Res Methods. 2004;7:191–205.CrossRef Hayton JC, Allen DG, Scarpello V. Factor retention decisions in exploratory factor analysis: a tutorial on parallel analysis. Organ Res Methods. 2004;7:191–205.CrossRef
12.
go back to reference Adler NE, et al. Socioeconomic status and health: the challenge of the gradient. Am Psychol. 1994;49:15–24.CrossRef Adler NE, et al. Socioeconomic status and health: the challenge of the gradient. Am Psychol. 1994;49:15–24.CrossRef
13.
go back to reference Wong CA, Hernandez AF, Califf RM. Return of research results to study participants. JAMA. 2018;320:435.CrossRef Wong CA, Hernandez AF, Califf RM. Return of research results to study participants. JAMA. 2018;320:435.CrossRef
14.
go back to reference Barnaghi P, Sheth A, Henson C. From data to actionable knowledge: big data challenges in the web of things [guest editors’ introduction]. IEEE Intell Syst. 2013;28:6–11.CrossRef Barnaghi P, Sheth A, Henson C. From data to actionable knowledge: big data challenges in the web of things [guest editors’ introduction]. IEEE Intell Syst. 2013;28:6–11.CrossRef
15.
go back to reference Horvitz E, Mulligan D. Policy forum. Data, privacy, and the greater good. Science. 2015;349:253–5.CrossRef Horvitz E, Mulligan D. Policy forum. Data, privacy, and the greater good. Science. 2015;349:253–5.CrossRef
17.
go back to reference Guntuku SC, Yaden DB, Kern ML, Ungar LH, Eichstaedt JC. Detecting depression and mental illness on social media: an integrative review. Curr Opin Behav Sci. 2017;18:43–9.CrossRef Guntuku SC, Yaden DB, Kern ML, Ungar LH, Eichstaedt JC. Detecting depression and mental illness on social media: an integrative review. Curr Opin Behav Sci. 2017;18:43–9.CrossRef
19.
go back to reference Merolli M, Gray K, Martin-Sanchez F. Health outcomes and related effects of using social media in chronic disease management: a literature review and analysis of affordances. J Biomed Inform. 2013;46:957–69.CrossRef Merolli M, Gray K, Martin-Sanchez F. Health outcomes and related effects of using social media in chronic disease management: a literature review and analysis of affordances. J Biomed Inform. 2013;46:957–69.CrossRef
20.
21.
go back to reference Wicks P, et al. Sharing health data for better outcomes on PatientsLikeMe. J Med Internet Res. 2010;12:e19.CrossRef Wicks P, et al. Sharing health data for better outcomes on PatientsLikeMe. J Med Internet Res. 2010;12:e19.CrossRef
22.
go back to reference Coppersmith G, Leary R, Crutchley P, Fine A. Natural language processing of social media as screening for suicide risk. Biomed Inform Insights. 2018;10:117822261879286.CrossRef Coppersmith G, Leary R, Crutchley P, Fine A. Natural language processing of social media as screening for suicide risk. Biomed Inform Insights. 2018;10:117822261879286.CrossRef
23.
go back to reference Office for Civil Rights, HHS. Standards for privacy of individually identifiable health information. Final rule. Fed Regist. 2002;67:53181–273. Office for Civil Rights, HHS. Standards for privacy of individually identifiable health information. Final rule. Fed Regist. 2002;67:53181–273.
24.
go back to reference Zettler PJ, Sherkow JS, Greely HT. 23andMe, the Food and Drug Administration, and the future of genetic testing. JAMA Intern Med. 2014;174:493.CrossRef Zettler PJ, Sherkow JS, Greely HT. 23andMe, the Food and Drug Administration, and the future of genetic testing. JAMA Intern Med. 2014;174:493.CrossRef
25.
26.
go back to reference Kalf RRJ, et al. Variations in predicted risks in personal genome testing for common complex diseases. Genet Med. 2014;16:85–91.CrossRef Kalf RRJ, et al. Variations in predicted risks in personal genome testing for common complex diseases. Genet Med. 2014;16:85–91.CrossRef
28.
go back to reference DeGroot JM, Vik TA. “We were not prepared to tell people yet”: confidentiality breaches and boundary turbulence on Facebook. Comput Human Behav. 2017;70:351–9.CrossRef DeGroot JM, Vik TA. “We were not prepared to tell people yet”: confidentiality breaches and boundary turbulence on Facebook. Comput Human Behav. 2017;70:351–9.CrossRef
29.
go back to reference Wong CA, Hernandez AF, Califf RM. Return of research results to study participants: uncharted and untested. JAMA. 2018;320:435-6.CrossRef Wong CA, Hernandez AF, Califf RM. Return of research results to study participants: uncharted and untested. JAMA. 2018;320:435-6.CrossRef
30.
go back to reference Padrez KA, Asch DA, Merchant RM. The patient diarist in the digital age. J Gen Intern Med. 2015;30:708-9.CrossRef Padrez KA, Asch DA, Merchant RM. The patient diarist in the digital age. J Gen Intern Med. 2015;30:708-9.CrossRef
31.
go back to reference Chen C, Haddad D, Selsky J, et al. Making sense of mobile health data: an open architecture to improve individual- and population-level health. J Med Internet Res. 2012;14(4):e112.CrossRef Chen C, Haddad D, Selsky J, et al. Making sense of mobile health data: an open architecture to improve individual- and population-level health. J Med Internet Res. 2012;14(4):e112.CrossRef
32.
go back to reference Lupton D. The digitally engaged patient: self-monitoring and self-care in the digital health era. Soc Theory Health. 2013;11:256–70.CrossRef Lupton D. The digitally engaged patient: self-monitoring and self-care in the digital health era. Soc Theory Health. 2013;11:256–70.CrossRef
33.
go back to reference Estabrooks PA, Boyle M, Emmons KM, et al. Harmonized patient-reported data elements in the electronic health record: supporting meaningful use by primary care action on health behaviors and key psychosocial factors. JAMIA. 2012;19(4):575–82.PubMed Estabrooks PA, Boyle M, Emmons KM, et al. Harmonized patient-reported data elements in the electronic health record: supporting meaningful use by primary care action on health behaviors and key psychosocial factors. JAMIA. 2012;19(4):575–82.PubMed
34.
go back to reference Brennan PF, Downs S, Casper G. Project HealthDesign: rethinking the power and potential of personal health records. J Biomed Inform. 2010;43(5 Suppl):S3–5.CrossRef Brennan PF, Downs S, Casper G. Project HealthDesign: rethinking the power and potential of personal health records. J Biomed Inform. 2010;43(5 Suppl):S3–5.CrossRef
35.
go back to reference Brennan PF, Casper G, Downs S, Aulahk V. Project HealthDesign: enhancing action through information. Stud Health Technol Inform. 2009;146:214–8.PubMed Brennan PF, Casper G, Downs S, Aulahk V. Project HealthDesign: enhancing action through information. Stud Health Technol Inform. 2009;146:214–8.PubMed
Metadata
Title
Patients’ willingness to share digital health and non-health data for research: a cross-sectional study
Authors
Emily Seltzer
Jesse Goldshear
Sharath Chandra Guntuku
Dave Grande
David A. Asch
Elissa V. Klinger
Raina M. Merchant
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2019
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-019-0886-9

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