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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: 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.

Clinical documentation is vital for continuity of care but increasingly burdensome due to administrative demands. This study applies a co-design approach grounded in human-centered AI principles to inform AI-supported documentation system for rehabilitation. Two virtual workshops with seven Swiss occupational therapists identified needs for structured, profession-specific summaries, integration of evidence-based resources, and GDPR-compliant systems with transparent logic. Participants also expressed concerns about automation limiting clinical reasoning and observational detail. These insights will guide subsequent design phases involving physiotherapists and patients.

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.

This cross-sectional online survey presents preliminary results examining Swiss occupational and physical therapists' (OTs/PTs) documentation burden and attitudes toward artificial intelligence (AI) support. Among 292 respondents (219 PTs, 73 OTs; mean clinical experience = 15.3 years), 41% reported frustration about the amount of documentation, and 48% stated that documentation delays other tasks. One in five (20.5%) use AI tools, and most rated their AI literacy as moderate or low. Nearly half indicated no institutional guidelines on AI usage.

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).

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.

Purpose: To examine (1) how much participation is represented in the benchmark Unified Medical Language System (UMLS) resource, and (2) to what extent that representation reflects the definition of child and youth participation and/or its related constructs per the family of Participation-Related Constructs framework.

Materials and methods: We searched and analysed UMLS concepts related to the term “participation.” Identified UMLS concepts were rated according to their representation of participation (i.e., attendance, involvement, both) as well as participation-related constructs using deductive content analysis.

Results: 363 UMLS concepts were identified. Of those, 68 had at least one English definition, resulting in 81 definitions that were further analysed. Results revealed 2 definitions (2/81; 3%; 2/68 UMLS concepts) representing participation “attendance” and 18 definitions (18/81; 22%; 14/68 UMLS concepts) representing participation “involvement.” No UMLS concept definition represented both attendance and involvement (i.e., participation). Most of the definitions (11/20; 55%; 9/16 UMLS concepts) representing attendance or involvement also represent a participation-related construct.

Conclusion(s): The representation of participation within the UMLS is limited and poorly aligned with the contemporary definition of child and youth participation. Expanding ontological resources to represent child and youth participation is needed to enable better data analytics that reflect contemporary paediatric rehabilitation practice.

The aim of this research is to explore collaborative AI systems to promote healthy lifestyle changes. With a focus onolder adults, a participatory design process was initiated, involving a team of researchers in occupational therapywith expertise in engagement in meaningful activities such as among older adults, human-agent interaction,and artificial intelligence. The scenario of collaboratively assessing past activities and planning activities of thecoming week - between the human and AI agent -guided the development of a novel, person-tailored storytellingsystem, based on argumentation theory. A framework was developed, integrating semantic user models, dialoguetypes, and structured argumentation to guide personalised story generation towards motivational and reflectivegoals. The formative evaluation highlighted critical challenges, including narrative inconsistency and hallucinatedcontent, motivating the future inclusion of reflective AI components. This work contributes to the methodologicalfoundations of designing trustworthy, purpose-driven storytelling systems that can be extended for futureHuman-AI collaboration.

In pediatric rehabilitation services, one intervention approach involves using solution-focused caregiver strategies to support children in their daily life activities. The manual sharing of these strategies is not scalable, warranting need for an automated approach to recognize and select relevant strategies. We introduce CareCorpus, a dataset of 780 real-world strategies written by caregivers. Strategies underwent dual-annotation by three trained annotators according to four established rehabilitation classes (i.e., environment/context, n=325 strategies; a child’s sense of self, n=151 strategies; a child’s preferences, n=104 strategies; and a child’s activity competences, n=62 strategies) and a no-strategy class (n=138 instances) for irrelevant or indeterminate instances. The average percent agreement was 80.18%, with a Cohen’s Kappa of 0.75 across all classes. To validate this dataset, we propose multi-grained classification tasks for detecting and categorizing strategies, and establish new performance benchmarks ranging from F1=0.53-0.79. Our results provide a first step towards a smart option to sort caregiver strategies for use in designing pediatric rehabilitation care plans. This novel, interdisciplinary resource and application is also anticipated to generalize to other pediatric rehabilitation service contexts that target children with developmental need.