Ideation is a critical step in the engineering design process, enabling designers to develop creative and innovative concepts and prototypes. Currently, the ideation workflow requires designers to generate new designs based on product requirements, heavily relying on their personal expertise and experience. To advance human-AI collaboration design and assist designers in the idea-generation process, this paper proposes an Object Combination Generative Adversarial Network (OC-GAN) for combinational creativity. The proposed method includes an image encoder module and a cross-domain object combination generator module. The image encoder module captures and encodes image structure information into latent space, while the cross-domain object combination generator module leverages GANs to combine object images based on user preferences, producing new design images. A design case study is used to evaluate the new ideation approach and reveal not only strong cross-domain concept combination capabilities but also improvement in designers' workflow and provision of novelty to the design case. Highlights An AI approach to improve the efficiency of idea generation in the design process. A case study evaluates its support for idea generation and design creativity. The OC-GAN is used for multi-domain object image combining tasks. Exemplifies the feasibility of human-AI collaboration design for enhancing creativity.

Typeface design plays a vital role in graphic and communication design. Different typefaces are suitable for different contexts and can convey different emotions and messages. Typeface design still relies on skilled designers to create unique styles for specific needs. Recently, generative adversarial networks (GANs) have been applied to typeface generation, but these methods face challenges due to the high annotation requirements of typeface generation datasets, which are difficult to obtain. Furthermore, machine-generated typefaces often fail to meet designers’ specific requirements, as dataset annotations limit the diversity of the generated typefaces. In response to these limitations in current typeface generation models, we propose an alternative approach to the task. Instead of relying on dataset-provided annotations to define the typeface style vector, we introduce a transformer-based language model to learn the mapping between a typeface style description and the corresponding style vector. We evaluated the proposed model using both existing and newly created style descriptions. Results indicate that the model can generate high-quality, patent-free typefaces based on the input style descriptions provided by designers.

Aims: Most hospitals still lag behind in their policies to stimulate healthier dietary choices by their patients. This study investigates whether a multicomponent nudging intervention, designed to prompt healthy food choices, can influence dietary choices of hospitalised patients.

Methods: This pre-postintervention study included a baseline phase and an intervention phase (7+7 months) and was carried out at the cardiology ward of a large hospital. All 2419 cardiac patients admitted to the ward during this period, and their 7559 meals were part of this study. The nudging intervention consisted of choice architecture, visual cues and informational nudges (eg, traffic light menus, posters). Data on dietary choices (vegetarian, fish, meat, side salad and fruit salad) were collected from the electronic food ordering system. As a secondary outcome, the intention to eat healthy after discharge was measured using the 20-item long Dutch Dietary Intention Evaluation Tool.

Results: During the intervention period, there was a statistically significant increase in the selection of vegetarian meals (20.1% vs 16.3%, p<0.001), fish meals (24.6% vs 18.7%, p<0.001), side salads (54.5% vs 49.5%, p<0.001) and fruit salads (12.8% vs 8.6%, p<0.001) when compared with the baseline period. In addition, patients in the intervention period expressed a significantly higher intention to eat healthy after discharge compared with the baseline period (β=0.167, SE=0.083, p=0.045).

Conclusion: This study demonstrates that a straightforward, easily implementable nudging intervention effectively promotes healthy dietary choices among in-hospital cardiac patients and enhances their intention to eat healthy after discharge.

Background: Telemedicine in neonatal care (TeleNeonatology) has the potential to improve neonatal outcomes, address capacity challenges and influence the emotional burden on parents. TeleNeonatology allows for real-time audiovisual communication between healthcare providers at different neonatal intensive care units (NICUs). Despite the high potential for multiple neonatal use-cases, TeleNeonatology is primarily being used for neonatal resuscitation and has yet to be widely implemented in Europe. Our study aims to evaluate both implementation strategies and effectiveness of TeleNeonatology in a pilot study in The Netherlands.

Methods: A pre-post implementation study with hybrid type III design will be conducted from 1 January 2023 to 31 December 2024. The year 2023 will serve as a baseline period pre-implementation. From 1 January 2024, a TeleNeonatology device will be integrated within all communication between the NICU-level IV of the Erasmus MC hospital and the NICU-level II at Amphia Hospital. Outcomes of the implementation of the TeleNeo programme will be evaluated using a mixed-methods approach evaluating implementation outcomes, service outcomes and client outcomes. Feasibility, the primary implementation outcome, will be evaluated via a validated questionnaire for parents and personnel. Secondary implementation outcomes will be barriers and facilitators of implementation, based on semi-structured interviews and focus groups. A cost minimisation analysis, using decision trees, will be evaluated as service outcomes. Client outcomes will be assessed via parent-reported transfer experience questionnaires and interviews and the clinical outcomes NICU-level III transfer rate and length of stay.

Ethics and dissemination: This study was reviewed by the Medical Ethical Committee of the Erasmus Medical Centre, who confirmed that the rules laid down in the Medical Research Involving Human Subjects Act do not apply (identification number: MEC-2023–0561). Results will be published in peer-reviewed journals in two separate scientific articles: the primary evaluation and the cost evaluation.

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.

eHealth development faces the challenge of generating evidence about health effectiveness in real-world settings. Designers can potentially support this challenge but must understand health approaches to evidence generation about health outcomes. This case study investigates how health and care professionals conceptualise health outcomes and their evidence generation in eHealth. Our results identify three key conceptual dimensions: effect, meaning, and collection. We discuss how these inform future design competencies to support evidence generation about health outcomes in eHealth design.

Background: Type 2 diabetes (T2D) tremendously affects patient health and health care globally. Changing lifestyle behaviors can help curb the burden of T2D. However, health behavior change is a complex interplay of medical, behavioral, and psychological factors. Personalized lifestyle advice and promotion of self-management can help patients change their health behavior and improve glucose regulation. Digital tools are effective in areas of self-management and have great potential to support patient self-management due to low costs, 24/7 availability, and the option of dynamic automated feedback. To develop successful eHealth solutions, it is important to include stakeholders throughout the development and use a structured approach to guide the development team in planning, coordinating, and executing the development process. Objective: The aim of this study is to develop an integrated, eHealth-supported, educational care pathway for patients with T2D. Methods: The educational care pathway was developed using the first 3 phases of the Center for eHealth and Wellbeing Research roadmap: the contextual inquiry, the value specification, and the design phase. Following this roadmap, we used a scoping review about diabetes self-management education and eHealth, past experiences of eHealth practices in our hospital, focus groups with health care professionals (HCPs), and a patient panel to develop a prototype of an educational care pathway. This care pathway is called the Diabetes Box (Leiden University Medical Center) and consists of personalized education, digital educational material, self-measurements of glucose, blood pressure, activity, and sleep, and a smartphone app to bring it all together. Results: The scoping review highlights the importance of self-management education and the potential of telemonitoring and mobile apps for blood glucose regulation in patients with T2D. Focus groups with HCPs revealed the importance of including all relevant lifestyle factors, using a tailored approach, and using digital consultations. The contextual inquiry led to a set of values that stakeholders found important to include in the educational care pathway. All values were specified in biweekly meetings with key stakeholders, and a prototype was designed. This prototype was evaluated in a patient panel that revealed an overall positive impression of the care pathway but stressed that the number of apps should be restricted to one, that there should be no delay in glucose value visualization, and that insulin use should be incorporated into the app. Both patients and HCPs stressed the importance of direct automated feedback in the Diabetes Box. Conclusions: After developing the Diabetes Box prototype using the Center for eHealth and Wellbeing Research roadmap, all stakeholders believe that the concept of the Diabetes Box is useful and feasible and that direct automated feedback and education on stress and sleep are essential. A pilot study is planned to assess feasibility, acceptability, and usefulness in more detail.

This research explores the dynamic nature of family involvement in remote patient management for cardiovascular disease and its impact on lifestyle behaviour changes. Through an interview study with patients and family members, we categorise family involvement into three types: Inform, Integrate, and Influence, highlighting the dynamic and heterogeneous nature of family involvement across different phases and activities. Overall, we emphasise the need for personalised and adaptable interventions to cater to the diversity of families and propose a modular approach to remote monitoring design.

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.

Background:
Neonatal intensive care unit admissions of newborns are emotional and stressful for parents, influencing their mental and physical well-being and resulting in high rates of psychological morbidities. Significant research has been undertaken to understand and quantify the burden of a newborn’s medical journey on parents’ well-being. Simultaneously, an increase has been observed in the development and implementation of telemedicine interventions, defined as the remote delivery of health care. Telemedicine is used as an overarching term for different technological interventions grouped as real-time audio-visual communication, remote patient monitoring, and asynchronous communication. Various telemedicine interventions have been proposed and developed but scarcely with the primary goal of improving parental well-being during their newborn’s medical journey.

Objective:
This study aims to identify telemedicine interventions with the potential to improve parents’ well-being and to present the methods used to measure their experience.

Methods:
A scoping review was conducted, including empirical studies evaluating telemedicine in neonatal care that either measured parental well-being or included parents in the evaluation. Abstract and title screening, full-text screening, and data extraction were performed by three researchers. Two researchers were needed to reach decisions on both the inclusion and extraction of articles.

Results:
The review included 50 out of 737 screened articles. Telemedicine interventions focused mainly on daily visits at the neonatal intensive care unit and discharge preparedness for parents. Surveys were the primary tool used for outcome measurement (36/50, 72%). Aspects of parents’ well-being were evaluated in 62% (31/50) of studies. Telemedicine interventions developed to provide education and support showed a potential to improve self-efficacy and discharge preparedness and decrease anxiety and stress when they included a real-time telemedicine component.

Conclusions:
This scoping review identified specific telemedicine interventions, such as real-time audio-visual communication and eHealth apps, that have the potential to improve parental well-being by enhancing self-efficacy and discharge preparedness, and reducing anxiety and stress. However, more insights are needed to understand how these interventions affect well-being. Parents should be included in future research in both the development and evaluation stages. It is important to not only measure parents’ perceptions but also focus on the impact of a telemedicine intervention on their well-being.

With the development of the theory and technology of computer science, machine or computer painting is increasingly being explored in the creation of art. Machine-made works are referred to as artificial intelligence (AI) artworks. Early methods of AI artwork generation have been classified as non-photorealistic rendering, and, latterly, neural style transfer methods have also been investigated. As technology advances, the variety of machine-generated artworks and the methods used to create them have proliferated. However, there is no unified and comprehensive system to classify and evaluate these works. To date, no work has generalized methods of creating AI artwork including learning-based methods for painting or drawing. Moreover, the taxonomy, evaluation, and development of AI artwork methods face many challenges. This article is motivated by these considerations. We first investigate current learning-based methods for making AI artworks and classify the methods according to art styles. Furthermore, we propose a consistent evaluation system for AI artworks and conduct a user study to evaluate the proposed system on different AI artworks. This evaluation system uses six criteria: beauty, color, texture, content detail, line, and style. The user study demonstrates that the six-dimensional evaluation index is effective for different types of AI artworks.

Public service organizations (PSOs) link on the one hand the government and the law, and on the other hand citizens, via the delivery of public services. Based on the state of the art of standards, principles and processes of human/user-centered service design, we analyze the practices in Dutch PSOs. The basis for this are practices documented on a weblog by a practitioner-researcher reporting and reflecting on four projects over five years. Based on this online journal we identified five themes that influence human/user-centered service design in PSO-practices. 1) Tension between collective and individual needs, 2) Public services should be inclusive for everyone, 3) A top down, hierarchical culture prevents user focus, 4) User feedback competes with policy implementation and IT-changes, and 5) PSOs are part of a larger service ecosystem. We conclude that to deliver truly human/user-centered public services, service design in PSOs should focus on more than just design process aspects and also take into account the law and policy making that precede the design and delivery of the service, as well as the institutional and (inter-) organizational perspective. For service design standards, principles and processes to be applicable to public design contexts, these should be expanded or customized to be able to deal with the specific dynamics of PSOs.

Evidence-based practices play an essential role in the development of eHealth systems. Prior research has investigated the challenge of shared understanding between professionals from the fields of health sciences and design and has highlighted the need for effective alignment of development and research practices in eHealth. However, there is a limited understanding of epistemological differences between these fields and how professionals conceptualise evidence. In this paper, we investigate how healthcare and design professionals think about evidence and how they implement evidence practices in their work. We interviewed eight professionals and used reflexive thematic analysis to identify the challenges and strategies associated with their evidence practices. Our results identify five shared evidence practices between healthcare and design professionals: stakeholder-driven, process-driven, problem-driven, effect-driven, and solution-driven. These five evidence practices indicate opportunities for closer alignment of development and research practices among healthcare and design professionals and offer a basis to create a shared understanding of evidence between both fields.

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

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.

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.

Background: Remote patient monitoring (RPM) interventions are being increasingly implemented in health care environments, given their benefits for different stakeholders. However, the effects of these interventions on the workflow of clinical staff are not always considered in RPM research and practice. Objective: This review explored how contemporary RPM interventions affect clinical staff and their workflows in perioperative settings. Methods: We conducted a scoping review of recent articles reporting the impact of RPM interventions implemented in perioperative settings on clinical staff and their workflow. The databases accessed were Embase and PubMed. A qualitative analysis was performed to identify the main problems and advantages that RPM brings to staff, in addition to the approaches taken to evaluate the impact of those interventions. Different themes were identified in terms of the challenges of RPM for clinical staff as well as in terms of benefits, risk-reduction strategies, and methods for measuring the impact of these interventions on the workflow of clinical staff. Results: A total of 1063 papers were found during the initial search, of which 21 (1.98%) met the inclusion criteria. Of the 21 included papers, 15 (71%) focused on evaluating new RPM systems, 4 (19%) focused on existing systems, and 2 (10%) were reviews. Conclusions: The reviewed literature shows that the impact on staff work experience is a crucial factor to consider when developing and implementing RPM interventions in perioperative settings. However, we noticed both underdevelopment and lack of standardization in the methods for assessing the impact of these interventions on clinical staff and their workflow. On the basis of the reviewed literature, we recommend the development of more robust methods for evaluating the impact of RPM interventions on staff experience in perioperative care; the adoption of a stronger focus on transition management when introducing these interventions in clinical practice; and the inclusion of longer periods of assessment, including the evaluation of long-term goals.

This paper unpacks how actors navigate the multiple organizational, interorganizational and industry contexts that are associated with system transformation programs for addressing wicked, societal problems. Because system transformation programs can only succeed when changes are implemented by multiple organizations, an increased understanding of integrating programs in multiple contexts is needed. We draw on a qualitative field study of an interorganizational program designed to help transform the Dutch healthcare system. We identified three practices of context navigation that actors used to integrate the program into multiple parent organizations and address emerging incongruencies among contexts. These are aligning contexts, prioritizing contexts, and adding contexts. Over time, these navigating practices promoted progress towards program objectives via multiple parallel collaborative paths. Our findings shed new light on the role of breakdowns and decoupled collaborative paths in programs oriented at contributing to system transformation.

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.