Maaike Kleinsmann

Background: Health apps, which comprise medical and wellness apps, hold potential to improve prevention, diagnosis, treatment, and management of disease. Yet, recommendation and prescription rates by health care professionals (HCPs) are low. Trusted standardized health app quality reports providing the information HCPs need to recommend or prescribe a specific app for an individual patient and guidelines from medical societies are considered crucial to enable this digital transformation of medicine. The CEN-ISO 82304‐2 (hereinafter “82304‐2”) Technical Specification, an initiative of the European Commission, includes a research-based health app quality assessment framework comprising 81 quality requirements. Results of 82304‐2 app assessments are summarized in an intuitive “health app quality label.” The 82304‐2 quality label’s potential to increase HCP willingness to recommend health apps was recently confirmed. To adequately enable decision-making and thus app recommendations, 82304‐2 proposes a more detailed “health app quality report” to complement the 82304‐2 quality label. Objective: This study aimed to design the 82304‐2 health app quality report that satisfies the information needs of individual HCPs in decision-making on an individual health app for an individual patient. Methods: A participatory design approach was applied. In an 18-month process of participatory prototyping with 9 HCPs with digital health expertise, the 82304‐2 quality report was iteratively designed. A convenience sample of 31 HCPs indicated the priority 82304‐2 quality requirements they considered useful in decision-making on recommending an app, and thus needed detailed quality information. Final feedback meetings with the 9 HCPs and 8 medical societies were used to finalize the 82304‐2 quality report design. Web-based questions in these meetings, feedback from the Dutch Patient Federation, and a comparative content analysis and the Health Education Materials Assessment Tool were used to evolve to and evaluate the final 82304‐2 quality report design. Results: In total, 37% (30/81) of the 82304‐2 quality requirements were prioritized by >50% of the HCPs. The final 82304‐2 quality report design provides detailed information for 90% (27/30) of the prioritized quality requirements. The reporting detail for 2 quality requirements requires more research. The final feedback meetings, the Patient Federation feedback, comparative content analysis, and Health Education Materials Assessment Tool provide indicative proof of the usefulness and usability of the quality report design. Conclusions: We succeeded in our aim to design the 82304‐2 health app quality report and found promising potential for its distinctive usefulness for HCPs and patients in recommending and considering a health app, respectively, and for medical societies in creating guidance. Further efforts are needed to test its effectiveness, fine-tune multistakeholder and intercontinental usefulness and usability, support medical societies in providing guidance and potentially training on recommending health apps, and advance from the current design to a scalable fully functional version of the quality report and associated open access database.

The intersection of neuroscience and artificial intelligence (AI) offers new avenues for understanding and replicating human creativity. However, current AI systems struggle to capture the depth, emotion, and cognitive complexity inherent in human artistic expression. In response, we propose MindCanvas, an AI framework that integrates fMRI with diffusion models to generate artwork directly from neural signals. MindCanvas decodes brain activity, reconstructs mental images, and refines them through text prompts, producing not only the final artwork but also a dynamic video that captures the strokeby-stroke creative process. Two user studies demonstrated the effectiveness of the model in translating neural activity into visually compelling and cognitively resonant artworks. By maintaining coherence between neural signals and artistic output, MindCanvas addresses key limitations in existing AI art systems, offering a novel approach that mirrors the evolving and emotional nature of human creativity. Our results underscore the potential of merging neuroscience and AI to create art that transcends technical inputs, moving toward a deeper, more holistic representation of human creativity.

1. Visual blends refers to a graphic design technique that combines distinct visual elements from multiple images into a cohesive composition, preserving their recognizability and enabling meaningf...

Background: Clinical decision support systems (CDSS) have the potential to improve patient safety and reduce costs in primary care. However, CDSS adoption remains limited due to development and implementation challenges. CDSSs are complex interventions involving multiple interacting components that require technological innovation and behavioral and organizational change. Additionally, the primary care context is considered a complex system with high care demand, fragmented structures, and many independent yet interdependent organizations. Established determinant frameworks for implementing and scaling up complex health care interventions support the identification of implementation determinants. However, they offer limited guidance on the underlying processes of these determinants, such as the implementation processes involved in complex interorganizational collaboration in primary care. Objective: This study examined how an interorganizational collaboration in Dutch primary care ( Gezonde zorg, Gezonde regio [ GzGr ]) achieved an iterative CDSS development and implementation. We aimed to identify the mechanisms that supported the collaboration in overcoming challenges. Methods: We performed an exploratory process-level case study. Data were collected through 15 semistructured interviews. The nonadoption, abandonment, scale-up, spread, and sustainability framework was used to ensure comprehensive topic coverage during the interviews, but not as an analytical framework. We triangulated the interviews with internal and external documents and expert input. Using a thematic, inductive approach, we developed a chronological overview of the collaboration and identified mechanisms offering insights into how GzGr navigated complexity in the development and implementation of CDSS. Results: We identified two mechanisms: (1) enacting an interorganizational value model and (2) iterative, co-creative experimentation. First, GzGr was driven by a coalition of the willing (ie, individuals willing to take an extra step), with shared goals that prioritized collective benefit while respecting organizational values. They established shared principles that translated the broad GzGr mission into concrete CDSS development choices, while also guiding strategic expansion by involving mission-aligned, innovative organizations. Second, after initial prototypes, GzGr established an iterative learning and improvement experimentation for both the technology and the collaboration. This process allowed for rapid feedback, validation of added value, and ongoing refinement. Additionally, this experimentation approached the development and implementation phase as a continuous process involving multistakeholders, supporting both the technology and the collaboration. Conclusions: This study identified 2 mechanisms that sustained interorganizational collaboration and CDSS development. These mechanisms connected collaborative and technical changes across people, technology, and organizational levels, enabling technological viability, stakeholder value, and multilevel support. The mechanisms operated both within and between organizations through iterative cycles of development and implementation. Practical implications include involving multilevel, innovative, and influential stakeholders; maintaining alignment through an orchestrating actor; and adopting an iterative approach between development and implementation. Our findings extend existing determinant frameworks by offering process-level insights into how such mechanisms help overcome challenges in the development and implementation of CDSS within interorganizational collaborations.

To address capacity problems at tertiary-level neonatal intensive care units (NICUs) within current staffing limitations, our study aims to demonstrate the

Design Science is the discipline that studies the creation of artifacts – products, services, and systems and their embedding in our physical, virtual, psychological, economic, and social environments. This editorial is a collective effort of the Design Science Journal’s editorial board members, past and present. The journal’s inaugural 2015 editorial, “Design Science: Why, What and How,” reflected the thoughts and vision of that first editorial board for the new journal and the discipline it represented. The present contribution offers the reflections of editors who served the journal in the past 10 years. The individual contributions were not primed and are presented here unedited for conformity or consistency. Differently from the 2015 editorial, there is no effort to synthesize the individual contributions, leaving the task to our readers, who can draw their own conclusions about the Design Science Journal and community accomplishments to date, and the challenges ahead.

BACKGROUND Health apps, which comprise both medical and wellness apps, hold potential to improve prevention, diagnosis, treatment, and management of disease. Yet, adoption by health care professionals (HCP) including recommendation and prescription rates are low, even in countries where these apps are reimbursed. Professional guidelines from medical societies and trusted standardized health app quality assessment reports providing the information HCPs need to recommend or prescribe a specific app for an individual patient are crucial to enable this digital transformation of medicine. The CEN-ISO/TS 82304-2 (hereinafter “82304-2”) Technical Specification, an initiative of the European Commission, includes a research-based health app quality assessment framework comprising 81 quality requirements. Results of 82304-2 app assessments are summarized in a “health app quality label”. The 82304-2 label’s potential to increase willingness to recommend health apps was recently confirmed. However, to adequately inform HCPs for recommending and prescribing high-quality apps a more detailed “health app quality report” is required in addition to the 82304-2 label. OBJECTIVE To codesign the 82304-2 health app quality report by including the information detail that satisfies the information needs of individual HCPs in decision-making on a health app. METHODS A Participatory Design approach was applied to generate the report. In an 18-month process of participatory prototyping with 9 HCPs with digital health expertise the 82304-2 health app quality report was iteratively developed, designed, and validated. A convenience sample of 31 HCPs indicated the priority 82304-2 health app quality requirements that would inform their decision-making on recommending an app and as such need detailed quality information. Final feedback meetings with the 9 HCPs with digital health expertise and 8 medical societies were used to finalize the 82304-2 report design. Web-based questions in these meetings, as well as a comparative content analysis and the Health Education Materials Assessment Tool (HEMAT) were used to indicatively evaluate the 82304-2 report design. RESULTS In total 30/81 (37%) of the 82304-2 quality requirements were prioritized by >50% of the HCPs. The final 82304-2 report design provides detailed information for 27/30 (90%) of the prioritized 82304-2 quality requirements. The reporting detail for two 82304-2 quality requirements requires more research. The final feedback meetings, comparative content analysis and HEMAT provide indicative proof of the usefulness and usability of the 82304-2 report design. CONCLUSIONS We succeeded in our aim to design the 82304-2 health app quality report and found promising potential for its distinctive usefulness for HCPs and medical societies. Further efforts are needed to test and fine-tune its multi-stakeholder and intercontinental usefulness and usability, to support medical societies in providing guidance and potentially training on recommending health apps, and to advance from the current design to a scalable fully-functional version of the 82304-2 report and associated open access database.

Background: In cardiovascular care, illness and recovery affect both patients and their families, particularly within home-based remote patient management (RPM). A recent scientific statement from the American Heart Association highlighted the importance of family involvement, identifying digital technologies as a key enabling opportunity. Despite this, research into the needs of families and the implications of RPM remains limited. Objective: This study explored the lived experiences and unmet needs of patients with cardiovascular disease (CVD) and their relatives within RPM-supported cardiac care, using perioperative care and myocardial infarction as representative trajectories. Based on the identified gaps, we proposed a set of features for remote patient and family management (RPFM) interventions to address these needs. Methods: This qualitative study was conducted at a Dutch university hospital with over a decade of experience in RPM across CVD pathways. A human-centered design approach was employed, including focus groups with 24 participants (13 patients with CVD and 11 relatives). Data analysis followed a framework analysis approach, combining inductive theme identification with deductive mapping onto existing frameworks. Care experiences and unmet needs were identified inductively and segmented along the Family Systems Illness Model’s phases of illness. The needs were subsequently categorized deductively into the domains of the Supportive Care Framework. Based on these user-informed insights, RPFM features were generated through author ideation and internal team consensus. Finally, these experiences, needs, and features were synthesized into a visual journey map illustrating key care moments across 3 phases: preadmission, admission, and postadmission. Results: We identified 47 unmet needs across 6 domains: informational (n=13), psychoemotional (n=13), social (n=7), physical (n=7), practical (n=6), and spiritual (n=1). The most significant gaps, described as “black holes” in care and support, emerged during the preoperative waiting period and early home recovery, which were characterized by a lack of information and psychoemotional support. To address the identified unmet needs, we generated 33 RPFM intervention feature ideas. These RPFM features were mapped across care phases and grouped into 7 categories: dynamic pathway navigation (n=8), on-demand support and information (n=5), family well-being modules (n=5), medical translation and consultation support (n=4), safety and assurance monitoring (n=4), collaborative lifestyle management (n=4), and peer support platform (n=3). Conclusions: This study identified experience gaps in RPM-supported cardiac care. It showed that most unmet needs for care and support extend beyond hospital admission and discharge and that most health behaviors and recovery occur in the home context, within the patient’s relational ecosystem with loved ones. The proposed RPFM features provide preliminary directions for exploration toward a transition from individually focused monitoring to inclusive, family-centered care and management.

BACKGROUND In cardiovascular care, illness and recovery affect patients and their families, particularly within home-based Remote Patient Management (RPM). A recent American Heart Association scientific statement highlighted the importance of involving family systems, identifying digital technologies as a key opportunity. Despite this, research into families' needs and RPM implications remains limited. OBJECTIVE This study explored the lived experiences of patients and relatives across RPM-supported perioperative and myocardial infarction care trajectories. Based on these experiences, we co-designed actionable recommendations for Remote Patient and Family Management (RPFM) to address identified gaps. METHODS This qualitative study was conducted at a Dutch university hospital with over a decade of RPM experience. A multi-step co-design approach was employed, including focus groups with 24 participants (13 patients, 11 relatives). Subsequent thematic analysis and expert consensus discussions informed the identification of unmet needs and the development of actionable RPFM recommendations. RESULTS Experiences were summarised in a family-centred journey map. We identified 59 unmet needs across six domains: informational (n=17), psycho-emotional (n=17), social (n=11), physical (n=7), practical (n=6), and spiritual (n=1). The most significant gaps, described as ‘black holes’ in care and support, emerged during pre-admission and early post-discharge. Based on these needs, 74 RPFM recommendations were co-created. CONCLUSIONS This study highlights experience-based opportunities to enhance RPM-supported cardiac care, particularly in terms of informational and psycho-emotional support for families. Drawing on extensive RPM experience, we advocate a shift toward RPFM. For this, we propose a strategy that offers guidance for developing RPFM across cardiovascular and other care contexts.

EHealth systems, such as digital care applications or remote monitoring devices, can improve health outcomes using user-centered design principles to create medical devices that adapt to users’ needs and contexts. Data-enabled design (DED) builds on these principles by leveraging user-generated data to iteratively refine systems based on real-world use, enabling adaptive and context-sensitive solutions. However, its exploratory and iterative nature conflicts with the rigid protocols required in clinical trials to evaluate safety and effectiveness. This study revises DED in alignment with clinical trial requirements, identifying four key challenges and proposing a four-phase Clinical Data-Enabled Design (C-DED) framework. This framework reconciles exploratory design with trial methodological demands, supporting the development of safe, effective, and user-centered eHealth medical devices.