Background. The increasing cognizance of complexity in systems has brought into focus important questions about the methods and tools we use to address them. Games for design, where games and computer simulations are used together to create concrete and tangible designs in a pluralistic way, with multiple stakeholders within the game is a new area for simulation gaming. Aim. In this article about gaming for design, embedded in the design science approach towards game science, we raise important philosophical questions about this new area, as well as attempt to address practical questions at the application level. We attempt to bridge the analytical science and design science approaches to games, and analyze them through meta-constructs of games such as fidelity, abstraction and resolution. Results. Results from two applications, through analysis of game play and debriefing of game sessions from two applications, COMPLEX and ProtoWorld are gathered and analyzed to understand the respresentational requirements for simulations and games. Conclusion. Results point to the need for rigor in gaming, particularly when modeling reference systems and rigor in assessing effects, both during game play and while debriefing. Results also point to expanded definitions of meta-constructs of games, as well as to their linked nature.

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Mainstream discourse in urban planning is in transition, due to shifts from a technical to a communicative perspective, and increased scrutiny and criticism of models and simulations. The cognizance of complexity in urban systems is imposing limitations on modeling. The added benefits of today's data and computational power make simulations harder to validate and understand. Reconciling the movements towards a communicative and exploratory approach as compared to a technical and predictive approach requires new methods for planning process and posits new requirements and functions for simulations. Based on distributed simulation and gaming simulation, the paper presents a framework to support the exploration of simulated and realistic virtual worlds in a participatory fashion, enabling new approaches to urban planning. The development and evaluation of the framework casts simulations in a new perspective and explores the context of use of simulations in planning and design.

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Background Home care is facing increasing demand due to an aging population. Several challenges have been identified in the provision of home care, such as the need for support and tailoring support to individual needs. Goal-oriented interventions, such as reablement, may provide a solution to some of these challenges. The reablement approach targets adaptation to disease and relearning of everyday life skills and has been found to improve health-related quality of life while reducing service use. Objective The objective of this study is to characterize home care system variables (elements) and their relationships (connections) relevant to home care staff workload, home care user needs and satisfaction, and the reablement approach. This is to examine the effects of improvement and interventions, such as the person-centered reablement approach, on the delivery of home care services, workload, work-related stress, home care user experience, and other organizational factors. The main focus was on Swedish home care and tax-funded universal welfare systems. Methods The study used a mixed methods approach where a causal loop diagram was developed grounded in participatory methods with academic health care science research experts in nursing, occupational therapy, aging, and the reablement approach. The approach was supplemented with theoretical models and the scientific literature. The developed model was verified by the same group of experts and empirical evidence. Finally, the model was analyzed qualitatively and through simulation methods. Results The final causal loop diagram included elements and connections across the categories: stress, home care staff, home care user, organization, social support network of the home care user, and societal level. The model was able to qualitatively describe observed intervention outcomes from the literature. The analysis suggested elements to target for improvement and the potential impact of relevant studied interventions. For example, the elements “workload” and “distress” were important determinants of home care staff health, provision, and quality of care. Conclusions The developed model may be of value for informing hypothesis formulation, study design, and discourse within the context of improvement in home care. Further work will include a broader group of stakeholders to reduce the risk of bias. Translation into a quantitative model will be explored.

In recent studies, small cell lung cancer (SCLC) treatment guidelines based on Veterans’ Administration Lung Study Group limited/extensive disease staging and resulted in broad and inseparable prognostic subgroups. Evidence suggests that the eight versions of tumor, node, and metastasis (TNM) staging can play an important role to address this issue. The aim of the present study was to improve the detection of prognostic subgroups from a real‐word data (RWD) cohort of patients and analyze their patterns using a development pipeline with thoracic oncologists and machine learning methods. The method detected subgroups of patients informing unsupervised learning (partition around medoids) including the impact of covariates on prognosis (Cox regression and random survival forest). An analysis was carried out using patients with SCLC (n = 636) with stage IIIA–IVB according to TNM classification. The analysis yielded k = 7 compacted and well‐separated clusters of patients. Performance status (Eastern Cooperative Oncology Group‐Performance Status), lactate dehydrogenase, spreading of metastasis, cancer stage, and CRP were the baselines that characterized the subgroups. The selected clustering method outperformed standard clustering techniques, which were not capable of detecting meaningful subgroups. From the analysis of cluster treatment decisions, we showed the potential of future RWD applications to understand disease, develop individualized therapies, and improve healthcare decision making.

Abstract-Gamification has been successfully applied in many domains, but mostly for simple, isolated and operational tasks. The hope for gamification as a method to radically change and improve behavior, to provide incentives for sustained engagement has proven to be more difficult to get right. Applying gamification in large networked organizations with heterogeneous tasks remains a challenge. Applying gamification in such enterprise environments posits different requirements, and a match between these requirements and the institution needs to be investigated before venturing into the design and implementation of gamification. The current paper contributes a study where the authors investigate the feasibility of implementing gamification in Trafikverket, the Swedish transport administration. Through an investigation of the institutional arrangements around data collection, procurement processes and links to institutional structures, the study finds areas within Trafikverket where gamification could be successfully applied, and suggests gaps and methods to apply gamification in other areas.