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. 2024 Oct 22;10(4):e004699.
doi: 10.1136/rmdopen-2024-004699.

Digital biomarkers for psoriatic arthritis: a qualitative focus group study on patient-perceived opportunities and barriers

Patty de Groot  1 , Wendy Wagenaar  2 , Jasper Foolen  3 , Ilja Tchetverikov  4 , Yvonne P M Goekoop-Ruiterman  5 , Marijn Vis  6 , Marc R Kok  7 , Laura C Coates  8 , Jolanda J Luime  6
Affiliations

Digital biomarkers for psoriatic arthritis: a qualitative focus group study on patient-perceived opportunities and barriers

Patty de Groot et al. RMD Open. .

Abstract

Objectives: The widespread adoption of wearables, for example, smartphones and smartwatches in the daily lives of the general population, allows passive monitoring of physiological and behavioural data in the real world. This qualitative study explores the perspective of psoriatic arthritis (PsA) patients towards these so-called digital biomarkers (dBMs).

Methods: As part of a Design Thinking approach, six focus groups were conducted involving 27 PsA patients. The semistructured topic guide included disease activity, coping strategies, care needs, and potential advantages and disadvantages of dBMs. Thematic analysis followed an abductive coding method.

Results: PsA daily permeates patients' lives, both physically and mentally. Participants discussed how their lives are focused on minimising the impact of the disease on their daily routines. Their attempts to gain control over their disease highly depend on trial and error. Flare-ups are related to physiological as well as behavioural micro and macro changes. Understanding these changes could enable the detection of (early) flare. Participants elicited pros and cons of the use of dBMs, discussed their intended use and made practical remarks. This led to three main themes: 'Perceived dBM opportunities', 'Mapping Disease activity' and 'Perceived dBM barriers and pitfalls'.

Conclusion: PsA patients are receptive to dBMs for tracking the disease symptoms. Disease activity is regarded multifaceted and thus, dBMs should include a broad range of features to truly reflect the disease activity status. Reducing the time of trial and error in learning to manage the disease is regarded beneficial. Establishing and maintaining the relationship with their attending physicians is a prerequisite, even if remote patient monitoring becomes an alternative for some physical hospital visits.

Keywords: Arthritis, Psoriatic; Health services research; Machine Learning; Qualitative research.

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Conflict of interest statement

Competing interests: Partially funded by the European Union. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or European Health and Digital Executive Agency. Neither the European Union nor the European Health and Digital Executive Agency can be held responsible for them. PdG, WW, JF, YPMGR, MRK and JL: no disclosures. IT has been paid as a speaker for Eli Lilly, Pfizer and UCB. MV: received grants/research support from Eli Lilly, Novartis and UCB and has been paid as a speaker for Abbvie, Eli Lilly, Novartis, Pfizer and UCB. LCC: received grants/research support from AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer and UCB; worked as a paid consultant for AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer and UCB and has been paid as a speaker for AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Medac, Novartis, Pfizer and UCB. LCC is supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. LCC is an associate editor at RMD Open.

Figures

Figure 1
Figure 1. The qualitative research methodology as adopted within this study. NL, Netherlands. UK, United Kingdom.
Figure 2
Figure 2. Coding tree illustrating the structure in the analysis with topics, codes and subcodes, subthemes and the final themes discussed in this paper.
Figure 3
Figure 3. Overview of symptoms, effects and medication side effects expressed by the participants during the focus group discussions.
Figure 4
Figure 4. Overview of triggers and prevention strategies mentioned by the participants during the focus group discussions.
Figure 5
Figure 5. Patients' perceived Opportunities and Barriers / Fears regarding the use of dBMs in healthcare. Categories presented are defined by the thematic analysis of the conducted focus groups.
See this image and copyright information in PMC

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