Amy Rathbone, Simone Stumpf, Caroline Claisse, Elizabeth Sillence, Lynne Coventry, Richard D. Brown, Abigail C. Durrant
Abstract
The use of digital technology amongst people living with a range of long-term health conditions to support self-management has increased dramatically. More recently, digital health technologies to share and exchange personal health data with others have been investigated. Sharing personal health data with others is not without its risks: sharing data creates threats to the privacy and security of personal data and plays a role in trust, adoption and continued use of digital health technology. Our work aims to inform the design of these digital health technologies by investigating the reported intentions of sharing health data with others, the associated user experiences when using these digital health technologies and the trust, identity, privacy and security (TIPS) considerations for designing digital health technologies that support the trusted sharing of personal health data to support the self-management of long-term health conditions. To address these aims, we conducted a scoping review, analysing over 12,000 papers in the area of digital health technologies. We conducted a reflexive thematic analysis of 17 papers that described digital health technologies that support sharing of personal health data, and extracted design implications that could enhance the future development of trusted, private and secure digital health technologies.
Introduction
The use of digital technology amongst people living with a range of long-term health conditions (LTHCs) to support self-management [1–3] has increased dramatically. Online forums and social networking sites in which people living with LTHCs can share their experiences and expertise with their peers–other people living with the same condition–have been extensively investigated in terms of the informational, emotional and social support they can offer [3–8]. More recently, digital health technologies to share and exchange health data have been investigated, either through electronic patient health records (ePHRs) between patient and healthcare professionals [9–11], or through personally generated health data shared with others [11,12]. Personally generated health data is tracked through patients’ own devices, such as mobile apps, fitness trackers and other wearables, mostly through manual entry but increasingly tracking can be automated. This data is often obtained in the context of tracking and storing medication adherence, symptoms, side effects, and other activities and experiences, in a variety of ways [13–16] as part of individuals’ self-management of their condition(s). Thus, this includes data on patients’ physical activities such as steps and hours of sleep, emotional states such as mood and medical history such as symptoms they experienced. With the advent of novel wearable technology, it might also include more complex data such as heart rate and sleep patterns.
Materials and method
We adopted a scoping review using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) extension [30]. The checklist consists of 20 essential and two optional reporting items. The method was supported by adopting a critical-reflective approach within the research team, to account for the interdisciplinary nature of the subject matter and the speed of digital health technology advances. Our team itself was comprised of experts in Health Psychology, Interaction Design and Computer Science, working together in the interdisciplinary field of Human Computer Interaction (HCI); and we adopted an interpretative stance to reflect on how the differing disciplinary perspectives of paper authors and researchers may shape their (and our, within the review team) choice of methodology, and use of language, terminology in study protocols, analyses, and reports of work. Our critical-reflective approach to the review was facilitated via regular meetings wherein the team discussed and reflected upon all steps of the scoping review method.
Results
Through applying the selection strategy, we removed duplicates (n = 10,950), leaving 1,228 records remaining. Abstracts (n = 46) and books/theses (n = 41) were removed. Reviews identified by title read (n = 128) and by abstract read (n = 74) were removed. From the remaining 939 records, removals were made for ‘other’ reasons (e.g., protocols (n = 24), editorials (n = 9), no access (n = 22)). Records in which the abstract did not specify the inclusion of a digital health technology were excluded from the review (n = 110). The full text of the remaining 774 publications were reviewed, according to our selection strategy described earlier. From these, publications that did not include users with LTHCs who engaged in sharing their own personally generated health data with healthcare professionals or others were removed (n = 516). Publications with no reference to trust, identity, privacy or security (TIPS) of data sharing were removed (n = 225). For example, we excluded [34] because it contained no references to TIPS and we excluded [35] because there was no personally generated health data or involved people with LTHCs. While [36] deals with gathering and analysing personally generated health data, it does not focus on TIPS or the sharing of this data hence it was excluded. Finally, publications in which the reported data was not the direct perspective of the user (n = 16) were removed. Overall, there were 17 studies eligible for inclusion in the review, as presented in Fig 1.
Discussion
Our review adds to the continuing and evolving body of work that investigates digital health technology in the self-management of patient’s conditions [1–3,11,12]. While some of the research has started to investigate ePHRs, we focussed our review on digital health technology that supports sharing personally generated health data with others, which, to date, is an area that has not received much attention.
Our review of published works in the digital health technology space that directly report on and address TIPS in their designs has yielded only a small set of papers. Given the plethora of digital health technologies that are being developed based on personally generated health data and that these data may need to be shared, it is surprising that there are so few publications that investigate this topic. While there are more and more systems being designed that allow patients to share data with others–healthcare professionals, other patients, or even other organisations–through digital health technology platforms, the evidence base for making design choices during systems development is relatively poor. While there is increasing attention given to this topic, we argue that there needs to be more empirically backed research on how to design digital health technologies that support the sharing of personally generated health data so that we can develop successful, evidenced-based self-management solutions.
Conclusion
We have reported a scoping review of literature between 2008 and 2022 on the design of digital health technologies for sharing data with others, and the implications for intentions, user experience and TIPS. Conducting a thematic analysis of the 17 publications yielded the following insights:
• Sharing data was seen as a way to improve self-management of conditions by individuals, however, sharing behaviour was self-centric rather than focused on benevolence to others.
• While there seem to be positive aspects of instantaneous access and benevolence to sharing data, many fear misuse through Theft or Accidental Disclosure. Sharing data can also give rise to fears of being judged about their Self-Management Practices. This might place barriers in terms of privacy, security and indeed trust.
• Design features relating to trust were focused on host credibility and personalisation. It was found that mutual disclosure of sharing data can inspire trust.
Citation: Rathbone A, Stumpf S, Claisse C, Sillence E, Coventry L, Brown RD, et al. (2023) People with long-term conditions sharing personal health data via digital health technologies: A scoping review to inform design. PLOS Digit Health 2(5): e0000264. https://doi.org/10.1371/journal.pdig.0000264
Editor: Baki Kocaballi, University of Technology Sydney, AUSTRALIA
Received: October 31, 2022; Accepted: April 27, 2023; Published: May 24, 2023
Copyright: © 2023 Rathbone et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All data are in the manuscript and/or supporting information files.
Funding: AR, CC and RDB were researchers funded by UKRI EPSRC (EP/R033900/1). SS, CC, ES, LC, RDB and ACD were investigators receiving a grant by UKRI EPSRC (EP/R033900/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000264#sec016
