Preferences regarding technology to unobtrusively monitor symptoms in rheumatoid arthritis: a qualitative study using focus group discussions

Abstract

Digital tools can be used for both self-tracking and telemonitoring of symptoms of rheumatoid arthritis. However, long-term monitoring can be a significant burden on patients, hindering implementation. The objective of this study is to understand patient preferences and barriers regarding long-term symptom monitoring. Five focus groups with 20 people with rheumatoid arthritis (RA) and 14 healthcare professionals were organised. Topics included motivations to monitor, motivators and barriers, willingness to put effort into monitoring, data collection, and privacy concerns. People with RA are interested in self-tracking to support self-management, and in optimizing hospital visits through telemonitoring. Monitoring has to be personalized, with a wearable and affordable device, to monitor a variety of symptoms. People are willing to invest up to 3 months to personalize settings. After that, long-term monitoring should be unobtrusive, not requiring active participation. Data should be processed and presented with clear feedback. Data should also be shared with healthcare professionals to improve disease management and to optimize hospital visits. Medical professionals see benefits as patients become better informed. Telemonitoring is perceived especially relevant if information on disease activity and medication side-effects can be obtained. People with RA see benefits for long-term monitoring, both with regard to self-tracking and telemonitoring. Even though they are willing to invest initial effort, for the long-term monitoring they prefer more unobtrusive types of monitoring. Similarly, medical professionals see benefits in only seeing patients when needed, however; they fear an overload on information which could raise the workload even further.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00296-025-06041-9.

Introduction

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease resulting in swelling and reduced joint function [1]. People with RA experience fatigue, pain, and diminished mobility, reducing quality of life, which affects people’s physical and mental well-being, personal autonomy, social functioning, and ability to work [2–4].

Current treatment focuses on managing disease activity through treat-to-target strategies with DMARDs and biologicals [1]. People with RA visit the outpatient clinic regularly to monitor disease activity and, where necessary, adjust their treatment. Besides this, people with RA receive support in self-management [5].

Telemonitoring of disease activity may reduce the frequency of visits provided disease activity is stable and under control, without side-effects or complications. Telemonitoring is promising, although the effects on healthcare expenditure and the workload of healthcare providers are unknown [6, 7].

Even if disease activity is under control, up to 70% of people with RA report fatigue [8]. Fatigue is complex, as it is multidimensional, i.e. physical, cognitive, emotional, and social [9] and multifactorial, i.e. linked with pain, stress and activity [10, 11]. Healthcare providers have little recourse to reduce or manage fatigue. People with RA report that its unpredictability causes difficulty in managing the consequences of fatigue in daily life [12].

Self-tracking of symptoms may increase patient empowerment and patient education, giving patients more control over their health and healthcare [13]. Several medical and consumer products, including wearable or implantable devices, sensors, and camera systems are available [14–20]. Effective self-management requires daily monitoring of relevant factors. However, daily monitoring of a chronic disease such as RA is a long-term commitment. To facilitate long-term monitoring, understanding preferences of people with RA with regard to monitoring is essential. Therefore, this study aims to analyse their preferences regarding long-term home-monitoring of fatigue.

Methods

Participants

A convenience sample of people diagnosed with RA aged 16 and above were invited between October 2023 and December 2023. Flyers were distributed through email among the online citizen science community of the Citizenlab at the University of Twente and in Medisch Spectrum Twente hospital, both in Enschede, The Netherlands and rheumatologists actively informed their patients. Inclusion continued until sufficient participants were found for 4 focus groups. A fifth focus group was organized with healthcare professionals at the hospital’s rheumatology department.

Ethical approval

Ethical approval was granted by the HSS Ethics Committee at the University of Twente (req.nr. 231122; granted on 23-08-2023). Participants were given information about the study and provided verbal informed consent prior to participation. People with RA received travel expenses and a 20 euro gift voucher. Healthcare professionals did not receive compensation but participated during office hours.

Focus group discussions

We organized 2-hour focus group discussions, each led by 2–3 researchers. We organized two focus groups at the university and two online through Zoom. Each focus group was led by researcher RW and assisted by JH, GT and HV.

We focused the discussion on one specific symptom, fatigue, for which participants recognized that for a complete overview it requires monitoring additional factors, since they are related and influence each other [9–11].

As the motivation for long-term monitoring could potentially influence preferences [21, 22], for instance by being more willing to share data for one goal than for the other, we started two focus groups with the motivation ‘monitoring to gain insight and to improve self-management, i.e. self-tracking’, and three focus groups, including the one with healthcare professionals, on the motivation ‘reducing or better planning of hospital visits, i.e. telemonitoring’.

The topic list followed categories of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), which is designed to understand and predict individuals’ acceptance and use of a new technology [23]. After discussions with a rheumatologist and a person with RA, the final topics were:

1. Reasons for utilization of technology and expected benefits.

2. Motivators and barriers for the adoption of technologies.

3. Level of effort patients were willing to invest in using these technologies.

4. Data collection, sharing, interpretation and privacy.

Procedure

Prior to the focus groups, participants received information on examples of technologies that can be used to monitor symptoms (see Table 1). We explained that the aim was to present a range of technologies with different attributes including their purpose, levels of privacy, ease of use, product owner, and types of technology to feed the discussion (Table 1).

Table 1.

Summary of the potential technologies that were presented to the participants as a means to inform the focus group discussions

Technology	Use	Type of data collection	Means	Data sharing	Onboarding effort	User involvement in data collection, and receiving results	Costs (purchasing/monthly fee)
Technology 1	App to record picture or movie; process into characteristics such as finger stiffness or fatigue	Fatigue; heart rate; finger joint stiffness	App; protected server	You; provider	Download app; register; calibrate camera	Record movie; View processed data	?/?
Technology 2	Sensors underneath your mattrass; process into characteristics such as sleep quality	Sleep quality; heart rate; respiration; motion patterns indicative for joint stiffness	Sensors; app; protected server	You; provider; pdf sharing with clinician	Install sensors: download app; register; connect bluetooth with sensors and app; manual provided	View processed data	150 euro/-
Technology 3	Automated medicine dispenser at home which allows additional interaction with user and devices	Medicine intake; answers to preset questions	Device; app; protected server	You; provider; next of kin; caregiver	Install device; place medicine; download app; register; couple app and device; set questions; give access to others; couple to other devices; manual provided	Answer preset questions; use other device(s); view processed data	70 euro / 20 euro
Technology 4	Sensors integrated in household items such as a lamp or picture frame	Answers to preset questions; temperature; motion patterns indicative for joint stiffness	Sensors; app; protected server	You; provider; next of kin; caregiver	Install device; place medicine; download app; register; couple app and device; set questions; give access to others; couple to other devices; manual provided	Answer preset questions; view processed data	399 euro / 12 euro
Technology 5	App to record typing patterns when smartphone is used	Finger joint stiffness; fatigue;	App; protected server	You; provider	Download app; register; manual provided	View processed data	? / ?

Some of the technologies have no known costs yet. This was reflected by ‘?/?’

Each session consisted of (1) a welcome and introduction, (2) presentation of one of the motivations for long-term monitoring, (3) the different technologies and their attributes (Table 1), (4) discussions on the 4 categories of the UTAUT2. All discussions started with brainwriting, yet some organically morphed into a lively discussion.

Analysis

Discussions were audio-recorded and detailed notes were taken by all researchers present. Audio-recordings were transcribed verbatim using Amberscript. A combined deductive and inductive content analysis was applied [24]. Themes were created based on the UTAUT-2 model, following the topic list. After familiarization with the text, open coding was applied. Thereafter, these codes were iteratively used to create categories, which were placed within the themes (Table 2). The coding was done by a single researcher, after which the codes were discussed with 2 other researchers. As the conversations with patients were more comprehensive, we present the results from the healthcare providers briefly.

Table 2.

Summary of the categories with for each category the factors that play a role in the acceptance and or willingness to use self-tracking and telemonitoring for people with RA and healthcare professionals

Theme	Categories for patients	Categories for healthcare providers
1. Reasons for utilization of technology	Optimizing frequency to outpatient clinic	Optimizing timing of medical consultations
		Monitoring disease activity
		Monitoring medication side-effects
	Self-management through gaining more insight	Patient education
2. Expected benefits	Improving quality of life	Reduced workload
	Enhance quality of medical consultations	Better quality care for patients
	Monitor effects of interventions
	Further research on RA
3. Motivators and barriers to the adoption of technologies	Personal relevance	Reduced work load
	Personalisation of devices	Data integration in hospital records
	Personalisation of symptom monitoring	Tailored monitoring for individual patients
	Personalisation of feedback	Informative data summarization
	Personalized data sharing	Consolidation of personal contact
	Reliability
	Affordability	Affordability
4. Effort that people are willing to invest	Installation stage: effort to install and understand technology	Installation stage: effort to install and understand technology
	Initialisation stage: effort to personalize data collection (< 3 months)	Initialisation stage: effort to optimize health care through observing summarized data
	Long-term monitoring stage: no effort to collect data, only interact on personal demand or through personalized feedback	Long-term monitoring stage: effort to optimize health care through observing summarized data or receive warnings
5. Data collection and privacy	Privacy and legal issues	Privacy and legal issues
	Data sharing with healthcare professionals	Data collection through medical and consumer-grade products
	Data sharing with technology providers
	Data sharing with researchers
	Data sharing with health insurance companies

Results

Participants

The people with RA who participated in the focus groups comprised of fourteen women and six men, with an average age of 59 years (range 38–77), with 3–6 participants per session. The average disease duration was 18 years (range 4–43 years), and they scored their current RA symptom severity 4.9 on a scale from 0 to 10 (range 1–8). The focus group with healthcare professionals included 11 rheumatologists, a nurse specialist, an intern, and a research manager .

The themes correspond with the topic list, and the motivations we introduced in the focus groups. The inductive coding provided several categories, that could all be placed under the themes, for patients and healthcare providers, separately (Table 2).

Theme 1: reasons for technology use

Even though we only mentioned one motivation in each focus group, the participants mentioned the other motivation as well. We did not find different preferences or requirements for the two motivations. Therefore, no sub-analysis was performed.

Optimizing frequency to outpatient clinic: Participants stated that they generally visit the clinic twice a year, and the number of visits temporarily increases in case of flare-ups, side-effects, or changes in medication. When patients feel well, they generally want to avoid being confronted with their chronic disease through hospital visits, as well as the burden of travel. Therefore, participants confirmed the benefits of telemonitoring provided this results in less visits when feeling well, and timely visits when they experience issues.

“Fine to have less visits, although I would need to have the assurance that I can get a consultation within a week if I need one” (Participant focus group 4).

Self-management through gaining more insight: Participants confirmed that they see symptom monitoring as a way to improve their quality of life. According to the participants, symptoms such as fatigue are unpredictable and suddenly overwhelms them. They state that this makes planning daily, work-related, and social activities challenging. Long-term high frequency monitoring of symptoms could help recognize (complex) patterns that aid to predict the likelihood of elevated fatigue levels. This self-tracking could also assist in recognizing gradual development of symptoms that otherwise remain unnoticed until causing damage or significantly impacting quality of life.

“But this fatigue, it sometimes just happens, like a warm blanket that encapsulates me, and I’ll be so tired. […]. So yes, to monitor the fatigue and understand what causes it, I’d use technology to do that.” (Participant focus group 3).

For the healthcare professionals, the telemonitoring would aid their core tasks; minimizing disease activity and managing medication side effects. They mentioned that data could possibly replace (some of the) patient-reported outcome measures (PROMS), lowering effort for patients. However, they did not foresee that such data will replace physical examination (e.g. DAS-28). Healthcare providers believe that visits remain important as clinical judgement is largely based on holistic observations of the patients, including their ease of walking, attitudes, the look in their eyes,. Healthcare professionals confirmed the benefits for patient education by obtaining more insight via telemonitoring.

“I think quite a few variables remain relatively stable over time, that you can also monitor from a distance”. (Participant focus group 5)

Theme 2: expected benefits

People with RA mentioned 4 main benefits for long-term monitoring for self-tracking and telemonitoring.

Improving quality of life: Participants expected that self-tracking would provide them with a detailed understanding of symptoms that fluctuate over time. They expect that in turn, this enables them to predict their symptoms and plan daily, work-related and social activities accordingly. They expect this to significantly enhance their quality of life, especially if this can be strengthened by algorithms to help predict and inform patients.

“Sometimes I’m really fatigued without noticing it. So yes, it would be helpful if the fatigue is automatically recognized and you receive a signal”. (Participant focus group 1)

Enhance quality of medical consultations: Participants expressed that providing high quality data during a visit provides a complete overview of the past 6 months, whereas they now often focus on the most recent period. Furthermore, they think that healthcare providers take them more seriously if data supports their narrative.

“I now complete a questionnaire before I see my rheumatologist, but then you have to recall when certain symptoms started. If you monitor, you know”. (Participant focus group 2)

Monitor effects of interventions: Participants hope that close monitoring helps to highlight the effects of medication changes or of changes in lifestyle on symptoms, potentially reducing the period necessary to finetune medication and dosage, resulting in fewer side-effects.

“I now manually register all my medication, when I take it, the dosage, and how I feel after. That really helps to determine when I need to take medication, or when I can forego it. Insight really helps”. (Participant focus group 1).

Further research: Participants believe that monitoring executed by a large patient population generates a rich dataset that can be used for future research, further improving care.

“That is important to me that new technologies are developed that I can use, perhaps even to stay self-sufficient for a longer period of time”. (Participant focus group 4).

Healthcare providers see benefits for technology to reduce their workload and to provide better care to their patients.

“Especially considering the aging population and less personnel, I think we need technology to help us”. (Participant focus group 5)

Theme 3. Motivators and barriers to the adoption of technologies

Personal relevance: People with RA need to believe they will personally benefit from the effort that they put into long-term monitoring (> 1 year). In some cases, a trial period up to 3 months to experience the potential benefits was suggested.

“I would only use technology if it would help me to improve my social life and to help recognize beforehand that I’m developing fatigue”. (Participant focus group 2)

Personalization of devices: People with RA mentioned that they prefer a choice between different devices to monitor a specific symptom (see examples in Table 1); as not everyone is comfortable using certain technologies. Additionally, they prefer to use a single device for all measurements. Optimally, the device is one that most people already use e.g. smartwatches or smartphones (Technology 1 and 5, Table 1) are preferred compared to at home devices such as Technology 2, 3 and 4 (Table 1). Furthermore, they are concerned that devices at home can record other residents and visitors, which raises privacy concerns. User-friendliness is part of the decision process, so easy-to-use apps and clear and understandable dashboards are key.

Personalization of symptom monitoring: As participants expect that different factors are relevant to different patients, personalization of monitoring is important. They mentioned that at first a broad range of factors need to be monitored, which may include different types of activities, pain, stress, sleep, fatigue, disease activity. Subsequently, long-term monitoring should be personalized, to avoid unnecessary effort. For some, gamification would help to increase user experience. Gamification is mostly relevant during the initial data collection period, where active participation is necessary.

“You need to recognize patterns. It could be fatigue, pain, joint pain, sleep disorders, nutrition, in combination with the medication that you take. You need to recognize all these relations before you draw conclusions”. (Participant focus group 2)

Personalization of feedback: People with RA stress the importance of receiving feedback from monitoring, for instance by providing a dashboard showing aggregated results. They embrace coaching or advice to prevent symptoms.

“Some sort of prediction for the rest of the week. If the technology starts to understand me, so it can say: your fatigue is quite high, perhaps you should take that into account for the coming week. So I get a signal that I have reached my max, and I can more consciously choose activities.” (Participant focus group 1).

Personalized data sharing: Integration of monitoring data with hospital records was highly desired. This would increase its relevance to conversations with their healthcare professionals. The option to share the data with multiple healthcare professionals was deemed important considering comorbidities.

“So you want to share your data with specific people. Definitely your healthcare provider. And I can imagine that some people also want to share with certain family members. And yes, I want to decide that myself”. (Participant focus group 1)

Reliability: Participants preferred that their healthcare providers inform them on available technology, to ensure reliable and trustworthy technology.

“I believe that you researchers would test it before you let us use it. So that would make me trust you. And I trust that more than a statement from [commercial party].” (Participant focus group 4).

Affordability: The willingness-to-pay threshold depends strongly on the financial situation of a person and perceived benefits. They prefer free or reimbursed options, unless additional insights and relevance are gained from a paid alternative. People expressed that, especially considering inclusiveness, technology should be affordable or reimbursed. In case of reimbursement, people are willing to share certain information about their condition with insurers.

“It would also depend on the costs if I would use it. You see, I have been unfit for work and am dependent on benefits. So the high costs for some of the [technologies in Table 1] would make them unattainable for me.” (Participant focus group 3).

For healthcare professionals, personal contact remains important to understand the context of a patient when interpreting data. Some doctors value patient contacts and are less interested in a shift to more data-driven patient care. However, they are open to the possibility of replacing (part of the) face-to-face visits as long as it results in lower workload. This requires data to be integrated into patient records to assist the normal workflow of decision-making. With telemonitoring, professionals expect a shift of responsibility towards patients. They doubt whether all patients are able and willing to take this responsibility. Therefore, they are hesitant to consider telemonitoring for all patients. This will be more important in efforts to optimize outpatient visits than it is when providing more insights to patients. In either telemonitoring or self-tracking, healthcare providers expressed concern that more data might also mean that patients will more often contact the hospital if they notice a change in the data.

“It would be relevant if you get data in an easily interpretable manner, integrated in our existing software. Perhaps a dashboard with a traffic light system.” (Participant focus group 5).

Theme 4. Effort that people are willing to invest

In relation to effort, people with RA distinguish between an installation stage, initialization stage and long-term monitoring stage.

Installation stage: Participants recognize that – as with any new technology – they need to start by installing technology at home or installing an app. Time and effort need to be invested to onboard (Table 1 Column ‘onboarding effort’). They are willing to invest time to install and understand the technology. They mention that technical support and clear instructions are important to be as inclusive as possible.

“I am not very active with technology. So I think I would need support to get started.” (Participant focus group 1).

Initialization stage: In the discussion, it became clear that a broad range of factors need to be collected at first, including surveys and recordings, to understand which information is relevant for specific individuals. To this end, people are willing to interact once a day for a period of up to 3 months. This can be repeated in case of a strong flare-up or a change in a person’s situation. People are more inclined to interact daily during changing conditions; such as people who were recently diagnosed, or people with changes in their personal situation or disease progression.

“It also depends on how often per day you need to provide data. But I think it would be worth it to collect data daily for three months to gain more later on. If I have to invest now, to maybe have profit for 30 years, I’d be willing to do so.” (Participant focus group 1).

Long-term monitoring stage: Since RA can last years, people with RA prefer not to be constantly reminded of their condition. So, they prefer automated data collection and processing (Table 1 Technologies 1, 2, 4 and 5). They only want interaction with technology to view dashboards on personal demand, when they actively request feedback, or receive a warning or coaching.

“I am happy to collect data for a few weeks, several times per day. But if that is something you have to continue to do, that would change my opinion. You’d want it to monitor in the background and give you a signal like that you’ve already done a lot this morning, maybe be cautious this afternoon.” (Participant focus group 1).

For healthcare providers, it is most important that monitoring aids in reducing their workload. They are willing to invest time to learn new procedures. They will view the dashboards before consults with patients and are open to warnings from the system in case of detected flare-ups.

“Normally, new technology requires some time investment at the start. I am happy to invest that time if it would reduce the number of patients we have to see, as this means we can provide higher quality care.” (Participant focus group 5).

Theme 5. Data collection and privacy

Privacy and legal issues: The participants mentioned that all monitoring activities should adhere to current legislation, and that privacy and data security need to be protected. They consider data regarding disease symptoms sensitive. They want to be in control of who can view or use the (processed) data. For some data types, such as photo and video material, only the processed data should be shared. Transparency and clear explanations would help people to trust data security. People with RA are generally willing to install apps on their smartphone, and smartwatch.

Data sharing with healthcare professionals: All participants with RA see added value in enabling their healthcare providers to see their (processed) data. They find it important that data can be integrated into their hospital records. Those with comorbidities request that data can also be shared with other healthcare providers.

Data sharing with technology providers: Participants were not unanimous when it came to commercial parties, with some being less willing to share sensitive health data with them. People with RA are open to use both medically certified technology and consumer technology mentioned in Table 1, although trust is higher in medically certified technology. In case of consumer technology, transparency is considered important and they would like clear information on validity, reliability, and ownership of the data, and who has access to it. They also want to know whether health data can be connected to their personal identifiable data. They would be more vigilant to understand and safeguard data security. They expect to receive such information from their healthcare providers.

Data sharing with researchers: Participants are generally willing to share their data with researchers, on a project-to-project basis. Transparency is important regarding the affiliation of the researchers.

“I wouldn’t find it necessary to give permission for each specific research, but perhaps every time a new partner is involved that would get access to the data” (Participant focus group 1).

Data sharing with health insurance companies: People with RA were hesitant to share data with health insurance companies, although they are willing to share some data if this is necessary to get reimbursement for use of the technology.

“Insurance companies already know a lot, they already know that you visit your rheumatologist. So sharing a little more to get reimbursed would be okay.” (Participant focus group 3).

Healthcare providers are only open to the idea of monitoring when (processed) data from either medically certified or consumer technology are integrated in patient records and are in compliance with general legal issues.

“But you don’t want to have different systems for everything. It does not work that way. The hospital has restrictions, rules, and procedures regarding data and privacy.” (Participant focus group 5).

Discussion

People with RA and healthcare providers both see the potential of monitoring for improving individual patients’ quality of life through detailed insight into their personal symptoms and to optimize frequencies of hospital visits, provided certain preconditions are met. They are only willing to engage with long-term monitoring if it results in personal benefits through detecting and predicting an increase of symptom levels to optimize treatment and to support self-management of daily, work-related and social activities.

To achieve personal benefit, relevant symptoms and related factors to be measured include disease activity, flare-ups, joint stiffness, medication side effects, sleep, fatigue, pain, stress, physical, cognitive and social activity. For symptoms like fatigue, the multidimensional and multifactorial nature complicates monitoring [25, 26], and predicting fatigue on a daily basis is even more difficult [27]. When analyzing examples of available commercial technologies (Table 1), no single technology is currently able to measure all symptoms. Research is ongoing to expand monitoring options through for instance biomarkers or disease activity [28, 29]. These are important for effective self-management, telemonitoring and optimizing medical treatment [30]. Further, participants expressed a desire for the monitoring to be complemented by coaching or advice [21].

An important caveat with long-term monitoring is the required effort. Even if patients see personal benefits, they still emphasized that close monitoring should be as unobtrusive as possible. Due to the longitudinal nature of the condition, patients are unwilling to be engaged with their condition on a frequent basis and often express hesitation to continuously complete patient-reported outcome measures [21, 22], resulting in low compliance [31, 32]. An important finding in our study is that patients are willing to invest up to 3 months of intensive data collection either at the start of monitoring, in case of a flare-up, or other changes in their situation, as long as this results in long-term benefits. For the same reason, participants expressed a preference for a single device, yet we expect that healthcare professionals can assign a range of technologies (Table 1) to provide relevant and trustworthy information on a subset of symptoms. We therefore argue that future monitoring systems should move away from patient-reported outcome measures and rely more on factors that can be monitored in the background, such as technologies 1, 2, or 5 (Table 1). To that end, more unobtrusive measures need to be developed to cover all relevant symptoms and activities. An additional benefit of unobtrusive measures is the low digital skill level that is requires, potentially reducing the health inequality gap [13].

Healthcare professionals similarly mention a willingness to invest time at the start to understand the monitoring data, if this results in long-term benefits and data is integrated in electronic patient records for easy access. They expect benefits when monitoring includes symptoms that directly influences their treatment decisions, including disease activity and medication side effects. In that case [33], telemonitoring could optimize timing of and replace part of the outpatient clinic visits [13, 33, 34]. However, currently, there are no unobtrusive methods to monitor the necessary symptoms in a home setting, which emphasizes the need for future research. An additional challenge is the linking of patient-collected data into electronic patient records [35].

The strong preferences of both patients and healthcare providers stresses the importance of co-creation with all stakeholders in the monitoring process to align tools with their values, needs, and capabilities [36].

An additional concern from healthcare providers is the effect on health care utilization, as more information might result in patients contacting their healthcare providers more frequently. This might either be beneficial, for instance if it results in earlier detection of flare-ups, or detrimental, if it results in unnecessary concerns in patients. Therefore, the feedback that patients receive about their data should be informative and concise, to support the most fitting actions regarding healthcare utilization [37].

This paper provides detailed insight in the preferences of both patients and healthcare providers regarding long-term monitoring in RA. The results are based on a select sample from the Netherlands. Although, we see similarities with studies in other countries, generalizing the outcomes to other countries should be done carefully, as reimbursement is common in NL whereas it is less common in other countries. To facilitate concrete discussions, we used monitoring of fatigue as a use case in this paper to start conversations, so it is uncertain whether results would be different if different symptoms were used as a starting point.

In conclusion, people with RA express the need for a long-term, personalized monitoring system to improve self-management and optimize healthcare. They are willing to invest time at the onset, after which the monitoring should not require active participation. Healthcare professionals expect long-term monitoring technology to reduce their workload, providing them with opportunities to provide better care.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

All authors contributed to the conception and design of the study, and data collection. Analysis was performed by RW. The first draft of the manuscript was written by RW and all authors commented on earlier versions of the manuscript. All authors have read and approved the final manuscript.

Funding

This project was partially funded by the BMS Strategic Research Fund of the University of Twente. The funder was not involved with the project and had no influence on the content of the project.

Data availability

The metadata for the project is available at 4TU.ResearchData 10.4121/b6be7e95-3eb0-4e72-90bd-6b68b301bedb.

Declarations

Conflict of interest

The authors have no relevant financial or non-financial interests to disclose.