Objectives
This systematic review examines how design methodologies support Shared Decision Making (SDM), identifies the most suitable for future use, explores types of methodologies used, challenges faced, and the impact on patients, clinicians, and care pathways.

Methods
Studies were searched on Medline, Web of Science, Scopus and grey literature (Google Scholar, CORDIS) up to July 2024, following PRISMA guidelines.

Results
were analysed to identify patient involvement, design strategies, SDM solutions, and their impact on care paths, professionals, and patients.

Results
Out of 2499 studies and 39 grey literature projects identified, 22 studies (reported in 35 publications) were selected, primarily from the USA and Europe (2015 onward). User-Centered Design predominated, involving health professionals more than patients. IPDAS standards were common. Evaluations showed improved patient experience and SDM role, with a potential increase in healthcare professionals' workload.

Conclusion
Although design methodologies are used in SDM implementation, improvement is needed. Service Design can enhance implementation by analysing the entire SDM process, while co-creative approaches develop patient-focused solutions that integrate smoothly into health professionals' workflows.

Practical implications
Introducing SDM in healthcare is complex, but design methodologies can help by analysing stakeholder needs, providing a broader care path view, and facilitating SDM implementation.@en

Background:
Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience–measuring methods and tools exists.

Objective:
This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.

Methods:
Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By “RPM interventions,” we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique.

Results:
In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation.

Conclusions:
At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain.@en

Challenges in implementing digital health in clinical practice hinder its potential. The complexities posed by implementation could benefit from using design practices. To explore the current role of design practices in digital health implementation, designers in the Netherlands were interviewed. The preliminary results indicate that designers contribute to digital health implementation processes, especially in the early stages. Design practices are mainly used for engaging the users, testing concepts, aligning the ideas of stakeholders, and adapting interventions to fit within the contexts.

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Designers are increasingly collaborating with data scientists to apply smart data technologies to understand large-scale user behavior during their design research. This is useful in specific impact domains with vulnerable users and unfamiliar contexts, such as healthcare design. Patient journey mapping is the most common design tool for developing and communicating patient-centred perspectives in healthcare design. However, creating a traditional patient journey map is labor intensive. Consequently, they often represent the experiences of a limited number of patients and, therefore, have limitations in including an extensive group patient experience. To overcome these challenges, we present a new data-driven and hybrid intelligent design approach that utilizes tens of thousands of online patient stories and machine-learning techniques through collaboration with data scientists. We set up two studies in the field of oncology and demonstrate that combining the two machine-learning techniques allows for quantifying the experiences of a wide range of patients, detecting relationships between co-occurring experiences within the journey, and detecting new design opportunities/directions. In these studies, designers gained a large-scale, yet qualitative and inspiring, understanding of a complex context in healthcare with reduced time and cost investments@en

Treatment decision-making can be complex, notably when there are multiple treatments available, with different (probabilities of) benefits and harms, for example, survival and side effects.1 It is precisely in these complex situations that the preferences of the patient are of utmost importance, as the trade-offs of benefits and harms are subjective and concern patients' lives.2 In such trade-offs, shared decision making (SDM) has gained momentum as a strategy to include both the best available evidence and the patient's preferences.3

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To support shared decision-making (SDM), in- itiatives are often focussed mainly on communication in the en- counter and the use of decision aids. Our previous research (Griffioen et al. Cancer Med 2021) revealed: decision-making as a sequence of (un)planned moments before, during, after the con- sultation; work for patients and relatives to acquire/understand/re- call information; often unclear roles and tasks, and unexpected energy drains (due to, e.g., changes in the trajectory). We aimed to develop a service design methodology to improve SDM. The entire patient journey is considered a service. All ‘touch points’ (leaflets, devices, etc.) become parts of a consistent service, supporting stakeholders’ decision making. We used oncology as a case.@en

Digital health technologies, powered by digital data, provide an opportunity to improve the efficacy and efficiency of health systems at large. However, little is known about different approaches to the use of data for digital health design, or about their possible relations to system-level dynamics. In this contribution, we identify four existing approaches to the use of data for digital health design, namely the silent, the overt, the data-enabled, and the convergent. After characterising the approaches, we provide real-life examples of each. Furthermore, we compare the approaches in terms of selected desirable characteristics of the design process, highlighting relative advantages and disadvantages. Finally, we reflect on the system-level relevance of the differentiation between the approaches and point towards future research directions. Overall, the contribution provides researchers and practitioners with a broad conceptual framework to examine data-related challenges and opportunities in digital health design.

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In this study, we envision engineering design activities for collective computing, an upcoming era of complex systems of massive social interaction through a wide variety of connected computing devices. A literature review reveals how collective computing, compared to the previous eras of personal and ubiquitous computing, may lead to new design tasks and design processes, as well as new roles for designers. Based on this review, new design activities for the collective computing era are envisioned, and further revised in an interview study with 24 informants. The result is a vision for design in the collective computing era, with actionable guidance for designers in terms of a coherent set of new design activities proposed in relation to advances in computing.

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Beslissingen over medische behandelingen worden steeds vaker gezamenlijk genomen door de arts, de patiënt en diens naasten. In deze gedeelde besluitvorming (of Shared Decision Making - SDM) over diagnose en behandeling worden ook de waarden en voorkeuren van patiënten meegenomen (Stiggelbout et al., 2015). Onderzoek heeft aangetoond dat gedeelde besluitvorming voordelen oplevert voor patiënten en zorgprofessionals, zoals meer vertrouwen in de beslissing, grotere tevredenheid met het consult en betere therapietrouw van de patiënt (Shay & Lafata, 2014). Toch blijft een effectieve implementatie van gedeelde besluitvorming beperkt, ondanks de ontwikkeling van keuzehulpen en aandacht voor gedeelde besluitvorming in de medische opleidingen. Een goede implementatie van gedeelde besluitvorming in de complexe zorgpraktijk blijkt moeilijk.@en

To unravel the complex challenges addressed by design, oftentimes it can be
necessary for researchers to participate in design processes rather than make
observations from outside. However, ‘participation’ has different meanings in
different kinds of design research, and research outcomes will depend on the
form of participation chosen. Through a Dimensional Analysis, we establish
seven dimensions on how participation in design research can be classified in
terms of 1) the researcher-designer role, 2) the aim of the project, 3) the main
contribution, 4) the activities of the researcher, 5) if it is a single or multi-case
study, 6) the scientific reporting on the project, and 7) the kind of knowledge
produced. This overview aims to assist researchers in communicating how
choices for a particular participatory approach contribute to knowledge
production in design research.@en

Purpose: Solutions to improve the implementation of shared decision making (SDM) in oncology often focus on the consultation, with limited effects. In this study, we used a service design perspective on the care path of locally advanced pancreatic cancer (LAPC). We aimed to understand how experiences of patients, their significant others, and medical professionals over the entire care path accumulate to support their ability to participate in SDM. Participants and methods: We used qualitative interviews including design research techniques with 13 patients, 13 significant others, and 11 healthcare professionals, involved in the diagnosis or treatment of LAPC. The topic list was based on the literature and an auto-ethnography of the illness trajectory by a caregiver who is also a service design researcher. We conducted a thematic content analysis to identify themes influencing the ability to participate in SDM. Results: We found four interconnected themes: (1) Decision making is an ongoing and unpredictable process with many decision moments, often unannounced. The unpredictability of the disease course, tumor response to treatment, and consequences of choices on the quality of life complicate decision making; (2) Division of roles, tasks, and collaboration among professionals and between professionals and patients and/or their significant others is often unclear to patients and their significant others; (3) It involves “work” for patients and their significant others to obtain and understand information; (4) In “their disease journey,” patients are confronted with unexpected energy drains and energy boosts, that influence their level of empowerment to participate in SDM. Conclusion: The service design perspective uncovered how the stage for SDM is often set outside the consultation, which might explain the limited effect currently seen of interventions focusing on consultation itself. Our findings serve as a starting point for (re)designing care paths to improve the implementation of SDM in oncology.

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One of the essential aspects of a company's design is its source of competitive advantage. Extrapolating from Raymond Loewy's famous design strategy acronym, MAYA—the Most Advanced Yet Acceptable Principle—and treating the firm as the object of design, this article explains the competitive advantage of firms from a design perspective. Our design-based recommendation for the competitive advantage of firms is to focus on shaping heterogeneity-based advantages of the firm in ways its paying customers would deem valuable. The novelty and conventionality dynamics of its industry will influence the degree of heterogeneity of the firm. Firms can shape their heterogeneity-based advantages through policies relating to organizational structure, routines, and product portfolio to name a few. Going beyond the role of a design in creating rents above and beyond what other firms can imagine, our claim focuses on the ways in which heterogeneity is a fundamental driver of its competitive advantage. If correct, the design-based view suggests that the ideal level of heterogeneity of the firm relative to current competitive conditions and evolution paths adopted by the firm and its competitors is more fundamental to firm profitability than its resources.

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This article explores how junior design professionals cope with value-based conflicts. We interviewed 22 design professionals about past and current value-based conflicts and the coping strategies adopted. Applying a grounded theory approach, we identified 11 types of coping strategies employed by junior design professionals. Our findings allowed us to clarify the nature of the coping process and localise value-based conflicts in the process of collaborative practice. During the coping process, professionals learn how to handle value-based conflicts through emotional release, developing a broader action repertoire, and engaging in timely action. We also identified transitions between specific coping strategies as junior designers learned from past conflicts and developed as a professional.

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Identity development of design students is a dynamic entanglement between personal and professional identities. Yet, literature primarily focuses on professional identity, based on institutionalized definitions of design to which students must conform. In contrast, we explore personal motivations for wanting to become a designer. An instrumental case study explores how an undergraduate design student develops personal principles for good design, and a personal vision for designing. Results show these principles and underlying vision are applied in the student’s design work, leading to development of a holistic identity (personal and professional). Finally, we note this exercise necessitated a plural and dynamic understanding of design (education). We therefore encourage design students and educators to co-design educational spaces and processes to stimulate enriched potentiality of design culture.@en

This contribution explores the potential of lead user research for early-stage designing for intelligent ecosystems through a literature review and a single case study concerning a lead user research initiative on blood pressure monitoring. The results suggest advantages of executing lead user research in early-stage designing for intelligent ecosystems from the points of view envisioning broad initial ecosystem boundaries, developing first intelligence components, and overcoming research challenges related to technical issues.@en

Junior design professionals experience conflicts in collaboration with others, with value differences being one of the issues influen-cing such conflicts. In a retrospective interview study with 22 design professionals, we collected 32 cases of perceived conflicts. We used a grounded theory approach to analyse these cases, resulting in five conflict categories that group 24 distinct value differences arising in 10 critical moments, an event that causes the value-based conflict. Thus, value differences are underlying the perceived conflicts of junior design professionals on many different occasions during collaboration with others. Conclusions are drawn on setting up guidelines for addressing values in co-design practices and sup-porting junior designers in their professional development.@en

This paper aims to envision design activities –design task, design process, and designer–for the collective computing era, an upcomingdominance of applications where many people interact with each other through many computing devices(Abowd, 2016). To achieve this aim, thetypical design activities over the last two computing eras, personal and ubiquitous, are studied through a literature review. Based on the activities shift discovered there, new design activities for collective computing are envisioned. This study urgesdesigners to change the way to work with user-data: from referring the small but in-depth ethnographical user-centeredliving-lab data (during the ubiquitous computing era), to create an understanding about both the individual user and the society or crowd as a whole(collective computing era). These different types of data provide designers with a rich understanding on the usersin their contexts, both as individual and community levels. Also, the design process that authors envision is a process of co-exploration (merge of problem exploration and solution delivery), and co-evolution (the constant reflection back and forth with exchange of information) of design problem and solution spaces. Moreover, the designersin collective computing erahave to take ethical and privacyissues into account. They have to create plans for dealing with the uncontrollability of the data generated and uncertainty about the social impact of the design that come with it. This research cantrigger the designers to innovate and remodel their workat the forefront of new computing technologies.@en