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Original research
Digital biomarkers for psoriatic arthritis: a qualitative focus group study on patient-perceived opportunities and barriers
  1. Patty de Groot1,
  2. Wendy Wagenaar2,
  3. Jasper Foolen3,
  4. Ilja Tchetverikov4,
  5. Yvonne P.M. Goekoop-Ruiterman5,
  6. Marijn Vis1,
  7. Marc R. Kok6,
  8. Laura C. Coates7 and
  9. Jolanda J. Luime1
  1. 1Department of Rheumatology, Erasmus MC, Rotterdam, Zuid-Holland, The Netherlands
  2. 2Tranzo, Tilburg University, Tilburg, Noord-Brabant, The Netherlands
  3. 3Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Noord-Brabant, The Netherlands
  4. 4Department of Rheumatology, Albert Schweitzer Hospital, Dordrecht, Zuid-Holland, The Netherlands
  5. 5Department of Rheumatology, Haga Hospital, Den Haag, Zuid-Holland, The Netherlands
  6. 6Department of Rheumatology and Clinical Immunology, Maasstad Hospital, Rotterdam, Zuid-Holland, The Netherlands
  7. 7Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
  1. Correspondence to Patty de Groot; patty.degroot{at}erasmusmc.nl

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.

  • Arthritis, Psoriatic
  • Qualitative research
  • Machine Learning
  • Health services research

Data availability statement

Data are available upon reasonable request.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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WHAT IS ALREADY KNOWN ON THIS TOPIC

  • Projections regarding the supply and demand of rheumatology care indicate it shall be impossible to meet future demands with the healthcare system as is. Various studies have examined the barriers and facilitators of remote care and measurement of various diseases by means of wearable devices. These studies outline the importance of involving patients in the development of remote monitoring systems.

WHAT THIS STUDY ADDS

  • Following Design Thinking methodology, our qualitative study inquired about the disease experience of psoriatic arthritis (PsA) patients and their initial attitudes towards the concept of digital biomarkers (dBMs).

  • The results of the semistructured focus groups, underpinned by the literature, provide an overview of the complexity of measuring PsA disease activity by means of digital devices. Additionally, they help construct an early vision for a healthcare system that includes dBMs by identifying opportunities, barriers and fears.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

  • This study is a first step towards the development of dBMs for PsA. The symptoms, triggers and behaviours identified are essential for the selection of measurement technologies to be investigated. Furthermore, the opportunities, barriers and fears will be translated to requirements and thus will shape the dBMs and their implementation in clinical trials and practice.

Introduction

With the ageing and increased life expectancy of our global population, an increasing number of patients require chronic health monitoring. Psoriatic arthritis (PsA) is such a chronic disease.1 PsA is an inflammatory disorder characterised by recurrent fluctuations in pain, fatigue and joint swelling and stiffness. It has unique clinical features, such as enthesitis, dactylitis and psoriasis, that differentiate it from other rheumatic and musculoskeletal diseases. The disease is heterogeneous with regard to its physical and psychosocial burden and could result in a substantial reduction in quality of life.2–4 Contrary to the growth of the PsA patient population, the rheumatology workforce is in decline.1 5 Workforce projections indicate that it will be impossible to meet future rheumatology healthcare demands with the current healthcare system.5 6

The integration of remote monitoring within rheumatology clinics has been identified as a possible solution to the escalating healthcare demands. However, as there is no easy gold standard to determine disease activity on tissue level, we currently still rely on the physical assessment by the physician. Therefore, PsA patients are monitored for research and care purposes by traditional intermittent follow-up visits, which require patients to come to the clinic. Since the 1990s, significant advancements have been made in assessing PsA disease activity, driven by the pressing need for reliable measures in clinical trials.7–9 A plethora of (composite) measures were established, specifically for PsA, consisting of components measurable by clinicians and patients.10 There is inherent subjectivity in both the clinician- and patient-reported measures,11–15 which is highlighted by the persisting lack of consensus on how to measure disease activity.

The emergence of new sensor-based devices and the widespread adoption of mobile technologies in the daily lives of the general population could potentially revolutionise how we track health information. Objective, quantifiable, physiological and behavioural data, collected and measured by means of digital devices (eg, physical activity measured with the smartphone accelerometer)— Digital Biomarkers (dBMs)—can support continuous measurements outside the physical confines of the clinical environment.16 The application of machine learning and artificial intelligence could help to interpret, infer and predict health states in various ways and hereby present an opportunity to reduce the number of redundant clinic visits and alleviate strain on the healthcare system.

Our research team endeavours to develop dBMs for PsA disease activity monitoring. However, this vision hinges on the use of consumer-oriented devices for real-world data collection. Since all patients have particular informational and decision-making needs to manage their disease, patient participation is deemed essential during dBM development.17 18 Therefore, a human-centred problem-solving approach that leverages empathy and collective idea generation, Design Thinking, is adopted by following the CAPTAIN framework.19–21 This qualitative study aims to explore the perspective of PsA patients towards dBMs and to identify critical factors that contribute to the development of dBMs for this specific patient population. It concerns the first phase of the Design Thinking approach and revolves around the PsA patients’ viewpoint of disease activity, disease management and care needs.

Methods

Study design

This study is a qualitative exploratory study based on focus groups discussions among PsA patients. Figure 1 depicts the steps undertaken during the study. A topic guide structured around the Common Sense Model of Self-Regulation22 (online supplement S1) was developed and evaluated with two patient research partners (PRPs) diagnosed with PsA. The topic guide covered: personal experiences with disease activity; disease management and coping mechanisms; care needs and preferences and the concept of dBMs to measure disease activity.

Figure 1

The qualitative research methodology as adopted within this study. NL, Netherlands. UK, United Kingdom.

After validation by the PRPs, the topic guide was applied in focus groups through 90-min video conferences. Dutch PsA patients were consecutively sampled through invitation by rheumatologists from various hospitals in the South-West of the Netherlands between April and October 2022. Patients required a PsA diagnosis, by the expert opinion of their rheumatologist, established at least 1 year ago. This timeframe ensured patients had multiple encounters with their rheumatologists and established some self-management strategies on participation. In the UK, convenience sampling was applied, where participants were invited by email from an existing pool of PRPs. All patients gave informed consent.

Interviews were moderated by one researcher (PdG) and five alternating observers (LD, JL, FS, AP and BH). All researchers were affiliated with the Rheumatology Department of the Erasmus Medical Centre. The moderator began each focus group with a short introduction about herself, the research aim and the ground rules to create a safe and confidential environment. To facilitate a dynamic discussion between the individual participants, sufficient time was given for the participants to familiarise with each other. Additionally, individual participants were encouraged to share their personal experiences by the moderator. After each session, a short debriefing between the moderator and observer took place and a summary was shared with the participants (member check).

Analysis

Focus groups were analysed by two researchers: PdG and JL. PdG and JL are both female researchers at the Erasmus Medical Centre, conducting research into the development of dBMs for PsA patients. PdG is a PhD student with a background in Medical Design and Engineering and has been trained in user research. JL is an epidemiologist with prior experience in qualitative research and Design Thinking.

All interviews were audio-recorded and transcribed verbatim using the Amberscript automatic speech recognition software and manual editing by PdG. Transcripts were then analysed following an abductive approach as described by Thompson.23 The researchers first familiarised themselves with the data by reading through the transcripts line-by-line and identifying meaningful segments of the text. Afterwards, transcripts were uploaded to ATLAS.ti for extensive coding. Investigator triangulation was applied after coding each transcript, consulting theory when necessary, until a final codebook that included themes and subthemes was developed. Finally, after iteratively coding until the satisfaction of the investigators, a consensus meeting was executed with the PRPs and a rheumatologist to discuss and verify the research findings. Reporting of these research findings was guided by the Consolidated Criteria for Reporting Qualitative Research (online supplement S2).

Ethical approval was waivered by the Erasmus Medical Centre Medical Ethics Review Committee (MEC-2021–0884). Findings were verified with UK PRPs within the patient and public involvement advisory sessions also held online.

Results

Six focus groups were conducted across the Netherlands and the UK between April 2022 and May 2023. In total, 27 people participated (56% female; aged 31–78; time since diagnosis 1–44 years). Of the participants, 22 were Dutch (55% female; aged 31–71; time since diagnosis 1–34 years) and five were British (60% female; aged 38–78; time since diagnosis 5–44 years). Characteristics within focus groups and of individuals are described in table 1 and online supplement S3, respectively. All participants possessed the digital skills to join an online video call.

Table 1

Demographics of the conducted focus group interviews. NL, Netherlands. UK, United Kingdom.

Based on the thematic analysis of the four Dutch transcripts, a codebook was developed containing 27 codes, revealing five concepts, which together build-up three overarching themes: ‘Perceived dBM Opportunities’, ‘Mapping Disease Activity’ and ‘Perceived dBM Barriers and Pitfalls’, as illustrated in figure 2. Following the codebook, analysis of the UK focus groups confirmed thematic saturation as no new themes emerged from that data. Also, within the themes no major differences in opinions and experiences between countries were identified. The first theme ‘Perceived dBM Opportunities’ captures participants’ difficulties in disease management, unmet needs in the care process, the benefits of e-health and the perceived advantages if dBMs were to be developed. The second theme ‘Mapping Disease Activity’ contains all text excerpts which relate to the symptoms, behaviours and sentiments which should be captured to make up an adequate dBM. The last theme ‘Perceived dBM Barriers and Pitfalls’ amounts to all statements which express caution towards or highlight impracticalities of dBMs.

Figure 2

Coding tree illustrating the structure in the analysis with topics, codes and subcodes, subthemes and the final themes discussed in this paper.

Theme 1: perceived dBM opportunities

PsA daily permeates the lives of patients both physically and mentally. Participants discussed how their lives since diagnosis are focused on relieving the physical and emotional burdens of their illness as much as possible. In their attempts to gain control over their disease, participants highly depend on trial and error. ‘Trial and error’ is applied for symptom recognition, trigger identification, treatment strategies and the adoption of various behaviour and lifestyle changes.

Figure 3

Overview of symptoms, effects and medication side effects expressed by the participants during the focus group discussions.

Figure 4

Overview of triggers and prevention strategies mentioned by the participants during the focus group discussions.

  • Every time I am in doubt, because the symptoms have changed so much, or may change. Then I think: “I'm exaggerating” or “I'm doing too much” or… I always start blaming myself first.—P2

  • Initially I experienced that as well; ‘small joints’ make you think of your fingers and toes, then you learn it can also affect larger ones, because at some point a large joint starts acting up. What P2 says, I can relate to. I doubt myself at first, but then you get the confirmation.—P4

According to the participants, dBMs could potentially expedite this process of ‘trial and error’. With the proper measurements, visualisations and notifications, participants envisioned the possibility of gaining more insight into their personal disease manifestation and the impact of certain activities earlier on. Personalised feedback from the dBMs can assist in setting boundaries and nudge them to intervene timely during early flare or adopt certain lifestyle changes.

  • When things settle down for a while, I think, “well, yeah, I actually feel okay.” That’s my pitfall. Then I want to do as much as possible because I don't know how long it will last.—P15

  • Very interesting, I noticed this illness requires a lot of learning by experience. Others already know; “if I do this, I'll suffer the next day or next week.” I think such a measurement technology can provide insight at multiple levels; in the hospital, with big data, multiple people, analytics. And on a personal level. If I have a party today and drink a lot of beer, that it shows up in the analysis; “okay, beer actually has a lot of impact.” What impact do fatty foods have? What impact does a bad night’s sleep have? You can learn a lot from that data quickly, which would otherwise take maybe ten years to learn through experience.—P6

Participants noted that dBMs could also contribute to science and thereby advance the treatment of future PsA patients. By means of big data and artificial intelligence, dBMs may facilitate early diagnosis, flare prediction, personalised medicine and scientific proof for lifestyle interventions. Patients opt to live life with minimal medication and articulated an unmet need for guidance on lifestyle changes to further alleviate their symptoms. However, as understood by the participants, scarce scientific evidence, in particular for dietary regimens, physical exercises or alternative interventions, impedes healthcare professionals from providing these tailored recommendations.

  • Certainly for me in the big picture, it’s important that based on this data you could arrive to a kind of prediction model, much faster. Meaning, when you can see a certain pattern, you can prescribe a certain strategy in terms of medication, for example, a strategic therapy, so to say.—P14

  • I am on the same page as P23. I prefer not to take much medication, if it is unnecessary. It also has side effects […] so I would like to use medication as little as possible.—P19

A subgroup of participants indicates that dBMs may help reduce their number of consultations. These participants also preferred remote over physical consultations. They felt confident about their ability to recognise and manage early disease exacerbations and knew how to approach their healthcare professional if needed. This would be time-saving for them and their physician.

  • In Covid times, everything went by phone and I was actually fine with that. Coincidentally, I'm visiting the hospital again tomorrow. Then I would actually like to ask if next time it can just be by phone again. If you have no complaints, that saves a lot of time, from both sides I think. I already know all the questions that will be brought up and I know how I feel.—P8

Theme 2: mapping disease activity

The real-world remote measurement of PsA requires a new take on the manifestation of the disease. Flare-ups are related to physiological as well as behavioural micro and macro changes, and understanding these changes could enable the detection of (early) flare. Figures 3 and 4 provide an overview of all symptoms, triggers, effects and behaviour changes mentioned.

Measuring and managing flares

Participants pointed out that disease activity highly fluctuates over time. These fluctuations are unpredictable and can develop rapidly or gradually over several days. Rarely, symptoms are completely absent.

  • Since diagnosis, I haven't had a moment when it wasn't there. Sure, to a lesser extent, yes. […] But a week later I can get another upheaval where I'm set back, and have to let go of what I was doing. So, it remains present, always.—P6

While the manifestation of PsA varied greatly among individuals, patients could easily describe their own distinction between the states of high and low disease activity. The reported indicators included increased pain, fatigue, stiffness and/or joint swelling. These symptoms showed in adjusting posture, reducing walking speed, or tossing and turning during sleep.

  • I get pain in my hands and feet, and I get incredibly stiff. When I wake up, I am as stiff as a board, which can last all day over the course of a couple of days.—P2

  • The joint gets thick and feels a little throbbing and warm. It varies each time where it is located. Other than that, I get very tired, and my forgetfulness gets even worse.—P16

Participants outlined various coping mechanisms to handle flare-ups. For many, a first incentive is to toughen it out, hoping the complaints eventually subside. Some may resort to painkillers or explore alternative therapies like cannabis oil or meditation to suppress their symptoms. However, when the flare becomes uncontainable, they are forced to take action. Behavioural adaptations involve changing activity patterns: staying at home more, refraining from social activities, changing their manner of transportation, for example, from walking or cycling to taking the bus, and increasing their resting time, etc. Additionally, participants change their sleep/wake cycles. They intend to go to bed earlier and will rise earlier. The early rise can be unintentional: early wakening due to pain and/or stiffness or intentional: taking additional time to prepare for the day.

Managing flare obliges participants to make sacrifices and reminds them of being chronically ill. This causes a shift in emotional well-being, which is noticeable in their mood through increased irritability or sadness, decreased sociability or depression. Over time, participants determine which sacrifices are worth the physical improvement and when to prioritise their emotional needs.

  • The frustration it brings, simply because you get those restrictions imposed again based on what your body wants or doesn't want. Yeah, I think they notice that at home from time to time. Not directly because I am complaining about what is bothering me, but in the way of how sociable my presence is.—P3

  • I don't really reach out to anyone anymore. I mean normally, I'm very active, social, calling people and stuff, but at those moments, yeah, when they call I just start talking about them. I don't actually say anything, which is a bit stupid.—P17

Besides taking action when disease flares, participants listed coping mechanisms aimed at preventing disease exacerbations by avoiding identified triggers. Their preventative lifestyle changes regard dietary restrictions, pacing physical and social activities, avoiding stress, choosing travel destinations wisely and actively working on controlling emotions. Often these preventative actions also required substantial sacrifices, such as career changes or home adjustments, impacting both patients and their surroundings.

  • With me, it acts up a lot when I am stressed, very stressed, or when I go through something, I get physically ill, or there is a lot of stress. Then, I can have an immediate flare, just like that. Which is also my biggest fear.—P19

  • If I ingest certain nutrients, I know I'll have a problem a day later. […] So I always try to be mindful of those, to try to avoid them.—P10

Theme 3: perceived barriers and pitfalls

During the focus groups, participants discussed the advantages and disadvantages of using dBMs, their intended use, and made practical observations. Statements were organised following the thematic analysis and are illustrated in 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.

The expected usefulness of a dBM health service was one topic of debate. Value propositions may be different during different disease phases. Participants pointed out that after diagnosis they felt overwhelmed with information. Although dBMs may help expedite the process of trial and error, it should be considered whether, at this point, patients are in the right headspace to process all the information that is measured and evaluated by the dBM system. Moreover, participants suggested that there might be limited additional benefit for patients who are already experienced in assessing their own disease activity and are relatively stable.

  • There are advantages and disadvantages, of course. I think it depends on the stage of your illness. As P10 said, if you've been dealing with it for many years and you already know what to do, where to look, what to watch out for. Maybe, it is more for people like me; we are new to the disease and “what should we pay more attention to during our daily activities?” As P11 said. Overall, I don't think it’s a bad idea, but I would assess it per situation.—P7

  • It might give you, a bit faster, a little more insight into what’s happening. But so much happens at the beginning that I wonder if all that information would be of any use at that point.—P11

The discussions elicited different preferences for physical versus remote consultations. In COVID-19 times, all patients received remote consultations. Some participants experienced an inability to convey the full extent of their complaints through tele-appointments and favoured physical assessments by their physicians. This inability was accounted to their tendency to downplay their symptoms or to insecurities about their own disease assessment. A good reciprocal patient–physician relationship was deemed essential for receiving proper treatment of their disease. Once this relation is established and there is mutual understanding, it is easier to have remote consultations.

  • It just remains difficult, in my opinion, to explain it well and clearly, so that my physician also understands. Then eventually, when you've had phone contact, they still want to see you. So then, I'd better just have those appointments every three or four months. In this case that’s okay too.—P20

  • That I try to conceal my symptoms. […] and when you get there, yeah, the first thing your physician will say is: “please sit down.” Because my rheumatologist knows me by now, and he also knows that I play nice and too often say that I'm fine, while my joints and body tell otherwise.—P18

Participants anticipated many confounding factors that could interfere with disease measurements and trigger a false-positive detection of increased disease activity. These expected false-positives were perceived as intrusive in the patient’s personal life. Additionally, some patients expressed concerns about the potential disconnect between their personal experiences and dBM findings, fearing the additional energy required to convince healthcare professionals of their complaints. Patients underscored the importance of verifying the detected disease activity themselves before the dBMs trigger any actions.

  • My sports or exercise activities are also partly determined by how busy a certain period is, or that I've been busy with other things for a while, and not always by physical complaints. Also, I don't particularly like the idea that when I have a quiet week, I immediately have the rheumatologist on the phone saying, “gee, what’s the matter, has your rheumatism flared up again?”—P3

  • I would fear this being just another one of those things that just doesn't measure what bothers me. So, that I would have to prove for the umpteenth time that there really is something going on. I would find it frightening.— P2

Following this, participants verbalised that they did not want to be disturbed by the dBMs’ data collection in their day-to-day lives. Using dBMs needs to be physically and mentally effortless. Participants did not want to be constantly confronted with their disease by surveys, alerts or reminders and feared that dBMs might trigger compulsive measurement of disease activity or generate stress. Additionally, not all patients felt they had the skills to access, interpret and use acquired data. Developers need to be conscious of the feedback that will be provided to the user and their potential consequences.

  • At first I was wondering in what way you want to measure all of that. If you go by the number of steps, I would have to constantly take my mobile phone with me, which I forget nine out of ten times. […] So if there would be another way, through a smartwatch or something equivalent, then yes, I'd be all for it.—P12

  • I also had one of those heart rate monitors on my phone and it would measure restlessness or stress. Well. I bought a new phone. Doesn't have that thing on it because it made me dead nervous. […] In my case, because I'm quite sensitive to it, it starts to control my life.—P15

Redesigning the care path to optimise the benefits of dBMs was regarded a must for those patients favouring remote consultations. Participants discussed remote care in relation to the current process of blood sampling, medication pick-ups at the hospital and access to care in case of a flare. These activities require the participants to visit the hospital and would disrupt the convenience of remote consultations.

  • Where I do have some concerns, so to speak, is that the moment it flares up, my estimation is my physician won't see me within a day. This means you're a couple of days further, then an appointment needs to be scheduled and then there’s a good chance that it’s already improved by the time you actually have the consultation. So, whether it is doable, time-wise, that is, that you can see your rheumatologist in time.—P9

Discussion

This qualitative study concerns the first phase of Design Thinking which evolves around the PsA patients’ viewpoint of disease activity, disease management and care needs in the digital age. Patients’ disease experiences are highly heterogeneous in manifestation and the corresponding behavioural changes to prevent or contain exacerbations. Much time and energy is spent on developing coping strategies by means of trial and error. Participants see potential in dBMs to help ameliorate this process, offering insights in their disease manifestations over time and advancing scientific understanding of the disease. Participants expressed concerns about how accurately dBMs will capture their personal experiences and inherently the impact on their patient–physician interaction. dBMs should be deployed as an additional tool to tailor care and empower patients, requiring an individualistic approach of dBM analysis to generate patient-specific reports and advice. Therefore, they should measure physiological as well as behavioural micro and macro changes, for example, heart rate, physical activity patterns, posture or mood changes.

Patient experiences of PsA complaints and management have previously been investigated through qualitative research.4 24–26 Consistent with our findings, Moverly et al show that to identify and manage (pre-)flare, PsA patients need to get acquainted with the various factors associated with their disease, such as symptoms, triggers, physical effects and psychological effects that influence their state of being.24 Over time, patients learn to recognise minor disease fluctuations which help them to predict an upcoming flare and estimate its severity. Based on this understanding, patients will develop strategies to manage their (pre-)flare state. A first incentive of patients, as also established by Chisholm et al, is to push through, hide or avoid aspects of their condition, which culminates a brain-vs-body conflict about whether to be active or to take rest.27 These constant trade-offs between desire and reality without any specific guidelines to follow, as also observed in our study, make it a frustrating process for patients to develop appropriate coping mechanisms. Patients often feel like they are navigating uncharted territory.

Trial and error is at the centre of developing self-management strategies for PsA. Research shows that this uncertainty creates significant stress and anxiety among PsA patients, impacting negatively their psychological state, coping strategies and physical health.4 26 If illness is perceived as highly uncontrollable and unpredictable, people are more likely to adopt emotion-based coping strategies rather than problem-based coping strategies. Improved understanding of disease management and symptom control positively impacts someone’s coping mechanisms.22 Insight in how the disease changes physical activity patterns, mood and sleep as measured with dBMs could help increase the perceived controllability of the disease. It would allow patients to establish cause-effect relations and adapt accordingly to contain or avoid exacerbations. Additionally, it could support communication with their healthcare professional.

We identified a number of attitudes and prerequisites to be taken into account to ensure the viability of dBMs as a future health service. These findings are supported by existing quantitative and qualitative studies conducted within and outside the context of rheumatology.28–32 Observed attitudes towards the concept of dBMs align with Rogers’ Diffusion of Innovation Model.33 At the end of early adopters, patients are eager to start with data collection and have strong beliefs about the capabilities of artificial intelligence on an individual and population level. Moving further along the curve, the early majority vouches for the use of dBMs solely for scientific purposes. They are willing to use dBMs when proposed by their clinician. This willingness to share data is congruent with recent findings in rheumatoid arthritis by MacBrayne et al in 2023.29 On the other end, some patients are simply not interested in dBMs. They fear dBMs will have a negative impact on their care, will be burdensome, generate stress and/or will intrude on their personal lives. It is their expectation the dBM will not be able to capture the data that aligns with their personal disease experience. dBMs should therefore include a broad range of facets that reflect the full extent of their disease activity status as was indicated in figures 3 and 4. These facets are similar to the symptoms and impacts identified in the conceptual patient experience model by Ogdie et al in 2020.25 Some of these facets can be translated to measurement technologies as recently done by Creagh et al in rheumatoid arthritis.34 Their weaRAble-PRO study demonstrates how dBMs could characterise meaningful aspects when combining various modalities of RA. To develop a successful dBM, the technology should thus be multifaceted and tailored to the needs and convenience of patients.28 31

The present study has several limitations that warrant consideration when interpreting the results. First, due to the qualitative nature of the research, the findings are context-specific and may not be generalisable beyond the studied population. Our conducted focus groups involved a small sample of PsA patients consecutively recruited for online focus groups. Participants thus required a certain level of technical skills for participation. Our sample population was disproportionally composed of participants with higher education levels. As education is one of the Social Determinants of Health as defined by the WHO and is known as an influencing factor in health-related decisions and lifestyle choices, this may have affected the generalisability of our results.35 36 Nevertheless, a wide range of demographics regarding disease duration, gender and age was established within the sessions. Findings were similar in the UK advisory groups and are consistent with findings in other studies.28–32 A second limitation is that findings are based on the expectations and imaginative abilities of participants. Because of the explorative set-up of the study, the exact modalities of the use of the dBMs could not be outlined or tested by participants (eg, What kind of data will be fed back to the user? Which activities would trigger an alert? How accurate is the dBM?). Attitudes may thus be different after gaining experience with a dBM system.

In conclusion, PsA patients are receptive to the concept of dBMs for tracking their disease symptoms over time. Disease activity is regarded multifaceted, and therefore, dBMs should include a broad range of features to truly reflect their 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 doctors a prerequisite, even if remote patient monitoring becomes an alternative for some physical visits in the hospital.

Data availability statement

Data are available upon reasonable request.

Ethics statements

Patient consent for publication

Ethics approval

This study involves human participants, but ethical approval was waivered by the Erasmus Medical Centre Medical Ethics Review Committee (MEC-2021-0884). The Medical Ethics Executive Committee concluded that * There is no medical-scientific questioning in the research protocol.* The participants are not subjected to an intervention/treatment, nor is any behaviour imposed on them, both as referred in the WMO, exempted from this study. Participants gave informed consent to participate in the study before taking part.

Acknowledgments

The authors gratefully thank all participating patients and participating centres from CICERO. Moreover, we wish to thank A. Pasma, L. Drost, F. Snijders and B. Hojeij for their roles as observers during the focus groups. Patient guidance was additionally provided by our PRPs E. Das-Cheppo and R. Bakker.

References

Supplementary materials

Footnotes

  • X @drlauracoates

  • Contributors PdG, JL and IT conceived, designed and executed the study; JF and WW were involved in the theme synthesis. MV, MRK, LCC and YPMGR contributed to the patient interviews. All authors contributed to the writing of the manuscript. JL was the guarantor. DeepLTranslate as well as Chat GPT was used to help translate the Dutch Quotes into English. Outputs were compared and manually adjusted. DeepL Write was used for grammatical optimisation. Chat GPT was used for some textual inspiration and textual improvements. All were reviewed and adjusted by the first author. JL acts as guarantor.

  • Funding This study was funded by Pfizer through an Investigator Sponsored Research grant. The UK interviews were financed under the iPROLEPSIS project (https://www.iprolepsis.eu) that receives funding from the European Union under Grant Agreement No. 101095697.

  • 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.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.