Christiane Grünloh

Rheumatic and musculoskeletal diseases (RMDs) cause several restrictions in daily living. Self-management is an important aspect of managing RMDs. However, little is known about the self-management strategies that are currently applied in daily life. This study aimed to identify the current self-management strategies that people with RMDs apply through a citizen science approach. An online survey was iteratively developed together with people with RMDs. The survey was distributed among people with all types of RMDs. Survey responses were collected within Qualtrics, and once anonymized, analysed using Atlas.ti. General self-management strategies and motivations to start performing a strategy were deductively coded by two reviewers, after consultations with patient partners. 250 complete surveys were collected. 91.2% of the respondents were female. 1305 self-management strategies were mentioned, and 669 elaborations were given. Most participants applied self-management strategies within the ‘physical activity’ category in their daily lives (e.g., walking, biking). Motivations to start performing a certain self-management strategy mostly originated from the bodily functioning dimension (e.g., reducing pain). 1275 facilitators to start a self-management strategy were mentioned, which were mostly related to the ‘support’ category. Barriers (N = 480) were most frequent in the ‘condition-related’ category. Self-management is an important aspect of managing a person’s condition in daily life. People choose one or several strategies based on the challenge they are facing, depending on their feasibility and preferences in line with their personal context. The comprehensive overview of strategies informs both patients and healthcare professionals to support a personalized self-management journey.

Background: Chronic obstructive pulmonary disease (COPD) is a common chronic incurable disease. Treatment of COPD often focuses on symptom management and progression prevention using pharmacological and nonpharmacological therapies (eg, medication, inhaler use, and smoking cessation). Self-management is an important aspect of managing COPD. Self-management interventions are increasingly delivered through eHealth, which may help people with COPD engage in self-management. However, little is known about the actual content of these eHealth interventions. Objective: This literature review aimed to investigate the state-of-the-art eHealth self-management technologies for COPD. More specifically, we aimed to investigate the functionality, modality, technology readiness level, underlying theories of the technology, the positive health dimensions addressed, the target population characteristics (ie, the intended population, the included population, and the actual population), the self-management processes, and behavior change techniques. Methods: A scoping review was performed to answer the proposed research questions. The databases PubMed, Scopus, PsycINFO (via EBSCO), and Wiley were searched for relevant articles. We identified articles published between January 1, 2012, and June 1, 2022, that described eHealth self-management interventions for COPD. Identified articles were screened for eligibility using the web-based software Rayyan.ai. Eligible articles were identified, assessed, and categorized by the reviewers, either directly or through a combination of methods, using Atlas.ti version 9.1.7.0. Thereafter, data were charted accordingly and presented with the purpose of giving an overview of currently available literature while highlighting existing gaps. Results: A total of 101 eligible articles were included. This review found that most eHealth technologies (91/101, 90.1%) enable patients to self-monitor their symptoms using (smart) measuring devices (39/91, 43%), smartphones (27/91, 30%), or tablets (25/91, 27%). The self-management process of “taking ownership of health needs” (94/101, 93.1%), the behavior change technique of “feedback and monitoring” (88/101, 87%), and the positive health dimension of “bodily functioning” (101/101, 100%) were most often addressed. The inclusion criteria of studies and the actual populations reached show that a subset of people with COPD participate in eHealth studies. Conclusions: The current body of literature related to eHealth interventions has a strong tendency toward managing the physical aspect of COPD self-management. The necessity to specify inclusion criteria to control variables, combined with the practical challenges of recruiting diverse participants, leads to people with COPD being included in eHealth studies that only represent a subgroup of the whole population. Therefore, future research should be aware of this unintentional blind spot, make efforts to reach the underrepresented population, and address multiple dimensions of the positive health paradigm.

Stakeholder involvement is crucial to ensure health technologies meet stakeholders’ needs and values. A method to elicit these values is the patient journey value map (PJVM). A disadvantage of this method is its high burden for participants. In this paper, we adapted the PJVM method to minimise the burden and evaluated whether with this adaptation, values of stroke survivors can be elicited. We conducted interviews (N=6) and an interactive session with seven stroke survivors. Our approach showed that this adaptation in PJVM still allows to elicit end-users’ values throughout the patient journey, but in a less time-consuming manner and with less effort for participants. The method enabled stroke survivors to identify and articulate their values. This study contributes by showing that the adapted PJVM method is a useful and flexible method when investigating values in healthcare in the real world.

Purpose: Chronic obstructive pulmonary disease (COPD) has a high burden on patients, tremendously affecting their quality of life. For patients to be more pro-active, self-management is important. To support patients in their self-management, health data collection is needed for monitoring, which can be used for risk predictions and personalised coaching. Within the RE-SAMPLE project, we want to include these features in an eHealth technology. This study aims to investigate the attitudes of people with COPD towards health monitoring, risk predictions and virtual coaching. Methods: We conducted workshops and interviews with persons diagnosed with COPD. Six persons participated in the workshops which focused on topics for virtual coaching. Ten persons participated in the interviews focusing on monitoring, risk prediction and virtual coaching. Results: In general, participants were positive towards the concepts health monitoring, risk predictions and virtual coaching within a self-management eHealth technology. However, most participants felt that persons who are more recently diagnosed with COPD would benefit more from using such a technology. People who are dealing with COPD for several years already know or think they know how to self-manage their disease and what helps them and what not. Conclusion: Based on our findings, we discuss several implications for design of self-management eHealth technologies for COPD: personalization in context and level of details, supporting people to reflect on their behaviour and patterns detected in the monitoring, balance accountability and paternalism when it comes to coaching, and finally explainable AI concerning risk predictions. Furthermore, we want to argue that in these types of studies, it is also important to include people newly diagnosed with COPD to have more inclusive results.

Action research (AR) is a participatory research approach that works in iterative cycles that are conducted in practice. However, some cycles of AR can take a long time, slowing down the speed of iterations. Therefore, in this study we investigate the use of a relatively new method for AR: the flash mob. Flash mob studies lend themselves to spontaneous, unplanned participation, by collecting large amounts of data in a short time, while also analyzing and reporting quickly on findings. To investigate the applicability of the flash mob as a method for AR in eHealth projects, we conducted three flash mob studies in two research projects and drew recommendations based on observations, reflections and short pre- and post-surveys. Outcomes show that the flash mob is a potential method for AR, as it is situated in a practical setting where stakeholders can easily be involved, and its pace could speed up the AR cycles. To further improve the applicability for AR, our main recommendations include: promoting the flash mob adequately to increase participation and improve the involvement of ‘champions’; tracking interactions outside the flash mob (e.g., comments and questions from bystanders); and choosing an accessible and visible location, taking into account the activities associated with the location.

BACKGROUND Chronic obstructive pulmonary disease (COPD) is a common chronic incurable disease. Treatment of COPD often focuses on symptom management and progression prevention using pharmacological and nonpharmacological therapies (eg, medication, inhaler use, and smoking cessation). Self-management is an important aspect of managing COPD. Self-management interventions are increasingly delivered through eHealth, which may help people with COPD engage in self-management. However, little is known about the actual content of these eHealth interventions. OBJECTIVE This literature review aimed to investigate the state-of-the-art eHealth self-management technologies for COPD. More specifically, we aimed to investigate the functionality, modality, technology readiness level, underlying theories of the technology, the positive health dimensions addressed, the target population characteristics (ie, the intended population, the included population, and the actual population), the self-management processes, and behavior change techniques. METHODS A scoping review was performed to answer the proposed research questions. The databases PubMed, Scopus, PsycINFO (via EBSCO), and Wiley were searched for relevant articles. We identified articles published between January 1, 2012, and June 1, 2022, that described eHealth self-management interventions for COPD. Identified articles were screened for eligibility using the web-based software Rayyan.ai. Eligible articles were identified, assessed, and categorized by the reviewers, either directly or through a combination of methods, using Atlas.ti version 9.1.7.0. Thereafter, data were charted accordingly and presented with the purpose of giving an overview of currently available literature while highlighting existing gaps. RESULTS A total of 101 eligible articles were included. This review found that most eHealth technologies (91/101, 90.1%) enable patients to self-monitor their symptoms using (smart) measuring devices (39/91, 43%), smartphones (27/91, 30%), or tablets (25/91, 27%). The self-management process of “taking ownership of health needs” (94/101, 93.1%), the behavior change technique of “feedback and monitoring” (88/101, 87%), and the positive health dimension of “bodily functioning” (101/101, 100%) were most often addressed. The inclusion criteria of studies and the actual populations reached show that a subset of people with COPD participate in eHealth studies. CONCLUSIONS The current body of literature related to eHealth interventions has a strong tendency toward managing the physical aspect of COPD self-management. The necessity to specify inclusion criteria to control variables, combined with the practical challenges of recruiting diverse participants, leads to people with COPD being included in eHealth studies that only represent a subgroup of the whole population. Therefore, future research should be aware of this unintentional blind spot, make efforts to reach the underrepresented population, and address multiple dimensions of the positive health paradigm.