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For automated documentation systems to be meaningful in pediatric rehabilitation, they must accurately capture and summarize information about a child's or youth's involvement in daily life activities. We present attention-ASP, a neuro-symbolic framework that combines Transformer attention with Answer Set Programming (ASP) to capture involvement-level information from interview-based text. By encoding domain-specific vocabularies as ASP programs, our model guides attention heads to focus on contextual cues such as place, time, activity, object, and people. Results show that symbolic reasoning over attention improves alignment with expert assessments, offering a promising direction for advancing clinical documentation tools in pediatric rehabilitation.

Introduction – Modern personal technologies, such as smartphone apps with artificial intelligence (AI) capabilities, have a significant potential for helping people make necessary changes in their behavior (e.g., adopt healthier lifestyles). Current research highlights that realizing this potential through the design and use of personal technologies calls for a critical reappraisal of the role of healthcare interventions as the driving force of behavior change and requires a more explicit focus on human agency and experience.

Methods – This paper contributes to this line of investigation by developing and presenting a conceptual framework, informed by activity theory, which views behavior change as an outcome of the combined agencies of healthcare professionals, technology designers, and, most importantly, the persons themselves.

Results – According to the framework, the process of behavior change can be represented as a transformation, achieved through an interplay between the activity systems of intervention, development, and empowerment. In addition to presenting the conceptual framework, we offer insights into how these ideas can be implemented through examples of digital companions.

Discussion – Implications of the analysis for the design of personal technologies for supporting healthier lifestyles, with a special focus on intelligent digital companions, are discussed.

Introduction: This study aimed to explore the perspectives of occupational therapists and individuals with lived experience of mental health challenges regarding which aspects of participation in meaningful activities should be represented in digital twins, and how these aspects should be visualized.

Methods: We conducted a qualitative descriptive study involving 14 semi-structured interviews with occupational therapists and individuals with lived experience of mental health challenges. Interviews were transcribed verbatim and analyzed using inductive content analysis.

Results: Participants identified four main aspects to visualize in digital twins focusing on participation in meaningful activities: 1) the degree of being present and in-the-moment, 2) related or resulting experiences of being present and in-the-moment (including relaxation and calmness; fulfillment, purpose, joy, and playfulness; feeling vitalized; connection with oneself, others, and the world), 3) the energy needed and the energy gained from participation, and 4) the influence of the context. In addition, results revealed two main approaches for how these aspects should be visualized: 1) symbols and charts to visualize the now-situation, and 2) graphs for visualization over time.

Discussion and conclusion: Results identified four aspects of a participation in meaningful activities to be represented in digital twins. Those align with, and extend, existing literature on participation and recovery experiences. For the visualization of those aspects in digital twins, participants emphasized the importance of integrating both immediate feedback and longitudinal tracking of participation experiences.

There is broad consensus that disciplinary higher education must include artificial intelligence (AI) content tailored to the needs of different domains. Such an approach to higher education will help cultivate the skills, knowledge and critical thinking necessary for the socially beneficial development and integration of AI into the routines, organisations and infrastructures that shape society. Such an approach to higher education further aligns with broader policy and legal recommendations and requirements for upskilling, reskilling, AI literacy and interdisciplinary education to enable individuals to live with, work with, contribute to developing, and navigate AI technologies.

The paper provides insights on how an empirical approach to the pressing question of educating AI broadly in higher education can be rewardingly pursued. We focus on the findings from an interdisciplinary small-scale qualitative study. The study is based on a workshop conducted in 2024 in Uppsala University within the WASP-ED programme – a nation-wide educational and interdisciplinary programme aimed at increasing the capability and capacity of Swedish universities in providing relevant and scalable education in AI.

The aim of the workshop was to lay the ground for the development of course syllabi on AI -focused curricula across disciplines and academic institutions in Swedish higher education. 13 researchers across nine academic institutions participated in the workshop. The researchers, primarily from the social sciences and humanities, are all engaged in interdisciplinary scholarship related to AI.

The paper presents the theoretical grounding of the workshop and its methodological design, and outlines the analytical steps taken to identify major pedagogical principles and topics in AI that could be developed and integrated into educational curricula. The results outline five themes that emerged during the workshop: AI, diversity and human rights; Educating on the foundations of AI; Pushing the boundaries of theories and methodology; Building better AI systems; and Educating professionals within certain disciplines – changing professions.

We compiled the themes into a blueprint of an advanced level 60-credit programme, which could be developed into a 120-credit master’s programme. The programme consists of four modules: Foundations of AI in Society; AI in the Wild; Pushing Boundaries Building better AI; and Thesis. The participants agreed on three pedagogical principles to align the programme content and courses with societal needs: Learning by doing; Real world challenges; Engaging stakeholders. We evaluated the blueprint by mapping it to the WASP-ED AI Curriculum and identified different opportunities to extend the blueprint into a master’s programme.

We suggest that the blueprint can be used by educational institutions to create courses and programmes aimed at developing disciplinary education as well as fostering multidisciplinary understanding of AI in society. Furthemore, we suggest that the methods through which the blueprint was developed offer valuable insights on how interdisciplinary education on AI can be productively developed.

A qualitative study is presented aimed to explore how person-tailored stories generated by a storytelling system agent built on a combination of argumentation theory and large language models (LLM) can support a person in reflecting on activities promoting health and potential lifestyle changes. We conducted a formative evaluation with ten domain experts to explore perceived purposes, benefits and risks. They saw both potential opportunities, if applied with a clear purpose for their target groups, and risks in using LLM-based stories for health reflection if not carefully designed to adapt to an individual's needs. The results will guide further design and implementation of the storytelling functionality, and studies involving older adults.

Aim: To gain a comprehensive understanding of participation, particularly the construct ‘involvement’, in daily life activities from the perspective of children and young people with childhood-onset disabilities. Method: We conducted a scoping review of literature from PubMed, CINAHL, and PsycINFO. We included articles if they examined the experiences of involvement in activities from the perspective of children and young people with childhood-onset disabilities, used qualitative methods, and were published in peer-reviewed journals after 2001. Data (e.g. age, narratives on involvement) from included studies were extracted, mapped, and thematically synthesized. Results: Of 5241 articles, 30 met the inclusion criteria. We identified six concepts representing the experience of involvement in activities from the perspective of children and young people with childhood-onset disabilities. One concept reflected a continuum of inner dedication or investment in activities, ranging from non-involvement to involvement overload, which can be understood as the in-the-moment experience of involvement, representing the core of the involvement experience. Five additional ideas captured how children and young people process, interpret, and reflect on their experiences of involvement. Interpretation: Results can inform paediatric rehabilitation measures and interventions focused on involvement. Future research should explore children and young people's involvement in undesirable activities and whether the concepts of involvement vary by context (e.g. country, activity setting) and personal factors (e.g. age, type of disability).

Introduction: Peer-to-peer sharing of personal health data on social media is increasingly used as a strategy to support public health goals. Such sharing is often assumed to motivate individuals to adopt or maintain healthy behaviors. However, the social and ethical implications of sharing-based interventions remain insufficiently examined. This paper offers an empirical and theoretical contribution by foregrounding the socio-technical contexts of sharing and analyzing how sharing-based interventions may drive social change. Building on these insights, it also outlines ethical considerations for researchers and stakeholders.

Method: We conducted 22 semi-structured interviews with participants in a regional public health intervention in Sweden. Interviews focused on participants' experiences of receiving personal health data and their reflections on sharing such data on social media. Analysis was guided by reflexive thematic analysis and informed by theoretical perspectives on the socio-technical embeddedness of health data and sharing practices.

Results: Participants understood health data as both personal and communal. Although many expressed discomfort with disclosing sensitive health information online, the peer-to-peer sharing model fostered a perceived moral obligation to share data for collective benefit.

Discussion: The tension between personal boundaries and perceived communal obligations raises important ethical concerns, particularly when individuals feel pressured to share data they would prefer to keep private. Our findings underscore the need for ethical frameworks that address social pressures, consent, and the emotional dimensions of data sharing. To support sustainable and ethical public health practices, further qualitative research is essential—particularly to understand how individuals navigate obligations and risks in technology-mediated care, and how these dynamics shape values such as autonomy, well-being, and collective responsibility.

This paper addresses a conceptual and formal limitation in the International Classification of Functioning, Disability and Health (ICF), where activity and participation are treated as a unified construct, creating ambiguity in rehabilitation contexts. We propose an ontology keeping the ICF structure but formally separating these concepts, enabling more precise participation assessment. A case-based query analysis demonstrates how the unified ICF model may yield false positives in participation documentation, while the refined ontology supports nuanced evaluation. Implementation details and future evaluation are discussed.

Metaphors have for long time been used for describing and explaining the roles of technology in human activity. Such descriptions are embedding an increasing level of ambience, where technology is expected to sense, interpret, and adapt to an individual's needs and wishes, while at the same time, the demands for transparency and accountability is making way for new regulations and guidelines for systems based on artificial intelligence (AI).The purpose of this research is to explore social roles of humans and AI systems, and to identify open research questions and challenges when designing for transparency and sense of control. 

A socio-technical relationship framework was developed for assessing the social roles of AI systems, and for designing for change in roles and relationships. The framework was developed based on activity theory, metaphors for human-technology interaction, and emergent research on human-AI collaboration. By focusing on meaningful shared activity, the situations when technology is socially and personally relevant can be distinguished from the situations where technology is functionally relevant.The identified roles are partly overlapping and fluent depending on the situation, which increases the need for transparency and accountability, and consequently, AI techniques that allows explainability, negotiation and adaptation of the enacted roles.The framework is exemplified in two case studies to elicit role transformations in a work and a home environment respectively, where an individual's changing need for supporting development of capabilities and autonomy through AI-based technology are addressed.

We identify a number of open research questions and propose to apply the framework to capture and design for developing capability in humans and AI systems, collaborative capabilities in human-AI teaming, and for eliciting the ethical and moral consequences of AI systems operating within a person’s zone of development.

Medical and health disciplines are facing a change of their clinical practices with the integration of new transformative technologies including artificial intelligence (AI). There is an interest to elevate knowledge and skills in designing and developing adaptive technology for clients, patients and practices. In this study the possibility to integrate education on human-centered AI in the education on advanced level of nurses, physiotherapists and occupational therapists was explored. A blueprint of a 3-course AI education on human-centered AI for health and wellbeing was developed and evaluated at two universities. The course contents range from theory to practical exercises with application to clinical practice on AI, responsible AI design and AI technology, with a structured progression between each level. The evaluation showed that the proposed courses could be integrated into the existing master programs to different extent, from full integration in 120-credit programs to limited integration in 60-credit programs. It was concluded that the proposed education is feasible and desirable to integrate, and future work will continue the development.