Evidence map›Paper›PMID 37224154›Full record

ArticlePLOS digital health2023

People with long-term conditions sharing personal health data via digital health technologies: A scoping review to inform design.

Amy Rathbone, Simone Stumpf, Caroline Claisse, Elizabeth Sillence, Lynne Coventry, Richard D Brown, Abigail C Durrant

Abstract readScoping Review
In one paragraph

Article in PLOS digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. CRoP: Context-wise Robust Static Human-Sensing Personalization.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Amy RathboneOpen Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.
Simone StumpfSchool of Computing Science, University of Glasgow, Glasgow, United Kingdom.ORCID https://orcid.org/0000-0001-6482-1973
Caroline ClaisseOpen Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.
Elizabeth SillenceDepartment of Psychology, Northumbria University, Newcastle upon Tyne, United Kingdom.
Lynne CoventrySchool of Design and Informatics, Abertay University, Dundee, United Kingdom.ORCID https://orcid.org/0000-0002-6600-8414
Richard D BrownDepartment of Psychology, Northumbria University, Newcastle upon Tyne, United Kingdom.
Abigail C DurrantOpen Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID37224154
PMCPMC10208494

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.