Blekinge Institute of Technology

Boundary artefacts are shared artefacts that support collaboration by allowing different groups to interpret the same information in different ways. Software development activities benefit from them, as a single artefact can support stakeholders across different organisational boundaries. When these artefacts contain inconsistencies, such as incorrect information, practitioners’ trust in them may decrease, leading to inefficiencies in task execution. This study developed and evaluated a guideline to support the creation of boundary artefacts in software engineering contexts. We conducted a longitudinal, multi-phase study embedded in an industrial setting. The guideline was developed based on a literature review and prior findings from a previous case study and was then submitted for practitioner evaluation. A post-implementation analysis of the guideline was carried out after a period without researcher intervention. Our guideline consists of 10 principles grouped into three categories: (1) Scope: stakeholders, boundaries, and terminology; (2) Structure: artefact format, transference, granularity, and additions; and (3) Management: evaluation, ownership, governance, and integration. Practitioner evaluations suggested that these principles support the creation of reliable, predictable, and functional boundary artefacts. However, practitioners also noted challenges during use, including the time-consuming nature of the activity and difficulties in understanding the concept of boundary artefact. Overall, the guideline was well received. After the non-intervention period, it was adopted as a standard by the partner company for artefacts such as security testing, standards documentation, and requirements specifications. Adoption challenges persisted, including cultural barriers and comprehension issues. Further applications across different artefacts could clarify how the principles influence their reliability, functionality, and predictability.

Abstract Climate change requires us to fundamentally change the way we plan and develop our cities and regions. This raises questions about the role and capacity of spatial planning in general and the agency and expertise of planners in particular. Based on 27 qualitative interviews with Swedish planning professionals, we identify four key constraints: the increasing politicisation and complexity of planning practice, a cultivated practice of bypassing planners’ expertise and a loss of control over their own professional sphere. Our findings suggest that the Swedish planning community is ‘congealed’ rather than agile when it comes to promoting zero-carbon cities and regions.

This study addresses the persistent challenges that students face in understanding redox reactions, particularly the link between symbolic and particulate representations in electrochemistry. The purpose was to explore whether physical modeling with clay could enhance the conceptual understanding of electron transfer and oxidation–reduction processes. Two groups of Swedish upper secondary students participated in instructional sessions: Group A used clay models to visualize electron movement, while Group B relied solely on symbolic notation. Data were collected through a written test and follow-up interviews. Results indicate that Group A outperformed Group B in tasks involving metal displacement and identifying the number of electrons transferred in a more complex reaction combining redox and acid–base processes. However, differences were minimal in synthesis reactions and fundamental conceptual questions. Both groups exhibited widespread alternative understandings, although Group A demonstrated fewer alternative understandings and greater accuracy in applying the concept of charge. The findings suggest that clay modeling can support the visualization of electron transfer and reduce alternative understandings but does not independently foster deeper conceptual understanding. The effective integration of modeling with explicit instruction on particulate-level reasoning and scientific terminology is essential in bridging representational gaps in electrochemistry.

Integrating artificial intelligence (AI) with immersive analytics (IA) represents a promising means of leveraging advanced computational techniques to enhance data visualization and analysis. This study examines the state-of-the-art of AI-IA integration by addressing three key research issues: the significant application domains, the AI techniques used and their combinations, and current challenges and future directions. Results of reviewing 43 relevant studies reveal that AI-IA integration is still in its early stages, as existing research has mainly focused on a limited range of data types and application scenarios. By analyzing the application domains, this systematic literature review supports previous findings of important applications in the fields of education, manufacturing, and healthcare. At the same time, it identifies emerging applications that have progressed from XR and AI domains to AI-IA integration, such as sports events, assistive systems, urban planning, and disaster management. We contribute to extending established visual analytics (VA) pipelines into XR environments with integrated AI techniques. AI techniques are identified as contributing in five ways to this IA pipeline. Our contribution also includes identifying four key challenges and seven opportunities for future exploration. The review concludes that combining AI and IA holds the potential to create innovative applications using advanced AI and immersive visualization techniques. We present an overview of these applications and address key issues for future development.

After examining 4247 articles in 10 journals between 2010 and 2020, we found only 11.7% ( n = 497) included explicit policy recommendations, and just 1.4% ( n = 60) had explicit policy implications subsections. We analysed these 60 articles using behaviourally anchored rating scales (BARS) to assess four key aspects of the policy implications for quality and practicality. Policy implications were generally based on methodologically transparent research, but often lacked rigour in detailing policy and regulatory requirements, and typically demanded significant resources for implementation. Our results contribute to theory by improving our understanding of the why, when and how of policy implications of entrepreneurship research. Also, our BARS framework allows for a differentiation between quality and practical applicability, thereby reframing assumptions by showing that impactful policy implications require both methodological quality and implementation feasibility. Overall, the research–policy gap in entrepreneurship results not merely from disengagement but also research–policy misalignment in content and form.

This study explores women's experiences of a novel prehabilitation intervention, integrating early vaginal dilator therapy before and during pelvic radiotherapy. This qualitative study included sixteen women scheduled for pelvic radiotherapy. All participants received a pre-treatment intervention with individualized information and support to start vaginal dilator therapy prior to radiotherapy. Semi-structured interviews were conducted with all sixteen women before or during treatment. Of these, ten also participated in follow-up interviews after radiotherapy. Data were analyzed using reflexive thematic analysis. Four themes were constructed reflecting women's experiences of the new prehabilitation intervention: (1) Regaining control while facing the unknown, (2) Navigating identity, (3) Conceptualizing vaginal and sexual health, and (4) Building trust. Women found that vaginal dilator therapy during prehabilitation enabled a sense of control and readiness for upcoming sexual and vaginal health concerns. The early support was perceived as timely, acceptable, and empowering, regardless of women's initial motivation to engage. None of the women preferred to only receive the information after treatment, reflecting the value of proactive care. Integrating vaginal dilator therapy into prehabilitation may enhance preparedness, promote self-care, and reduce distress during pelvic radiotherapy. Further research is needed to confirm benefits and tailor support to individual needs.

Diversity, equity and inclusion (DEI) are recognised as essential components of nursing education and clinical practice. The DEI framework aims to broaden knowledge and reduce health disparities. However, the ways in which DEI is applied may vary across national and educational settings due to its context-sensitive nature. The present study aimed to explore how Swedish undergraduate nursing students in their final semester described the phenomenon of DEI within the context of their education. Data were collected through sentence-completion involving 43 participants. The completed sentences were analysed using content analysis, and the study is reported in accordance with COREQ (i.e. Consolidated Criteria for Reporting Qualitative Research) guidelines. Three main categories emerged: 1) Recognising diversity as a foundation of nursing education and practice; 2) Advancing equity in nursing education and person-centred systems of care; and 3) Promoting inclusive practices in nursing education and healthcare delivery. The participating students viewed DEI as interconnected and multifaceted concepts, demonstrating reflective awareness and an ethically grounded understanding of DEI principles as integral to nursing education and practice. The findings highlight the importance of context-sensitive approaches to integrating DEI into nursing education and clinical practice.

This paper introduces a generative framework for individual agent behavioral modelling based on artificial personalities (APs), which has been defined as distinct distributions over decision strategies in the given task. Using Markov Chain Monte Carlo (MCMC) sampling method, we generate action sequences that embody each AP's internal decision dynamics. The framework is evaluated through a numberguessing task, where five APs are compared based on two performance metrics: the length of the action sequence and a curiosity score, which quantifies deviation from the optimal solution. Results show that while agents demonstrated comparable task efficiency, their curiosity levels varied significantly, reflecting diverse exploratory tendencies. These findings support the feasibility of encoding strategic individuality in artificial agents, enabling richer behavioral modeling for applications in simulation, multi-agent coordination, and human-AI interaction.