Heart failure (HF) is characterized by a progressive clinical course marked by frequent exacerbations and repeated hospitalizations, leading to considerably high morbidity and mortality rates. Patients with HF present with a constellation of bothersome symptoms, which range from physical to psychological and mental manifestations. With the transition to more advanced HF stages, symptoms become increasingly more debilitating, interfere with activities of daily living and disrupt multiple domains of life, including physical functioning, psychological status, emotional state, cognitive function, intimate relationships, lifestyle status, usual role activities, social contact and support. By inflicting profuse limitations in numerous aspects of life, HF exerts a profoundly negative impact on health-related quality of life (HRQOL). It is therefore not surprising that patients with HF display lower levels of HRQOL compared not only to the general healthy population but also to patients suffering from other chronic diseases. On top of this, poor HRQOL in patients with HF becomes an even greater concern considering that it has been associated with unfavorable long-term outcomes and poor prognosis. Nevertheless, HRQOL may differ significantly among patients with HF. Indeed, it has consistently been reported that women with HF display poorer HRQOL compared to men, while younger patients with HF tend to exhibit lower levels of HRQOL than their older counterparts. Moreover, patients presenting with higher New York Heart Association (NYHA) functional class (III–IV) have significantly more impaired HRQOL than those in a better NYHA class (I–II). Furthermore, most studies report worse levels of HRQOL in patients suffering from HF with preserved ejection fraction (HFpEF) compared to patients with HF with reduced ejection fraction (HFrEF) or HF with mildly reduced ejection fraction (HFmrEF). Last, but not least, differences in HRQOL have been noted depending on geographic location, with lower HRQOL levels having been recorded in Africa and Eastern Europe and higher in Western Europe in a recent large global study. Based on the observed disparities that have been invariably reported in the literature, this review article aims to provide insight into the underlying differences in HRQOL among patients with HF. Through an overview of currently existing evidence, fundamental differences in HRQOL among patients with HF are analyzed based on sex, age, NYHA functional class, ejection fraction and geographic location or ethnicity.

Background: Developmental coordination Disorder (DCD) is a prevalent and persistent neurodevelopmental condition characterized by motor learning difficulties that significantly affect daily functioning and participation. Despite growing interest in artificial intelligence (AI) applications within healthcare, the extent and nature of AI use in the evaluation and intervention of DCD remain unclear. Objective: This scoping review aimed to systematically map the existing literature on the use of AI and AI-assisted approaches in the evaluation, screening, monitoring, and intervention of DCD, and to identify current trends, methodological characteristics, and gaps in the evidence base. Methods: A scoping review was conducted in accordance with the PRISMA extension for Scoping Reviews (PRISMA-ScR) guidelines and was registered on the Open Science Framework. Systematic searches were performed in Scopus, PubMed, Web of Science, and IEEE Xplore, supplemented by snowballing. Peer-reviewed studies applying AI methods to DCD-relevant populations were included. Data was extracted and charted to summarize study designs, populations, AI methods, data modalities, clinical purposes, outcomes, and reported limitations. Results: Seven studies published between 2021 and 2025 met the inclusion criteria following a literature search covering the period from January 2010 to 2025. One study listed as 2026 was included based on its early access online publication in 2025. Most studies focused on AI applications for assessment, screening, and classification, using supervised machine learning or deep learning models applied to movement-based data, wearable sensors, video recordings, neurophysiological signals, or electronic health records. Only one randomized controlled trial evaluated an AI-assisted intervention. The evidence base was dominated by early-phase development and validation studies, with limited external validation, heterogeneous diagnostic definitions, and scarce intervention-focused research. Conclusions: Current AI research in DCD is primarily centered on evaluation and early identification, with comparatively limited evidence supporting AI-assisted intervention or rehabilitation. While existing findings suggest that AI has the potential to enhance objectivity and sensitivity in DCD assessment, significant gaps remain in clinical translation, intervention development, and implementation. Future research should prioritize theory-informed, clinician-centered AI applications, including adaptive intervention systems and decision-support tools, to better support occupational therapy and physiotherapy practice in DCD care.

This study investigates the impact of psychiatric interventions on occupational dysfunction in patients with major depressive disorder (MDD) and anxiety disorder (AD). Occupational dysfunction is a significant concern in these populations, severely impairing the ability to perform daily activities and fulfill work and social roles. This research seeks to evaluate how different psychiatric interventions, including pharmacotherapy and psychotherapy, affect patients’ occupational performance and overall quality of life. This study analyzed data from outpatients diagnosed with MDD and AD based on ICD-10 criteria. Participants were assessed before and after intervention using scales that measure anxiety, depression, and occupational task difficulty. Results demonstrated a significant improvement in patients’ ability to perform a wide range of tasks, including personal hygiene, work-related activities, and social engagement, following treatment. The study highlights the importance of a multidisciplinary approach, emphasizing that both pharmacotherapy and psychotherapy significantly contribute to reducing occupational dysfunction and enhancing quality of life. These findings underscore the need for tailored interventions that address the specific occupational challenges faced by individuals with MDD and AD, aiming for long-term functional recovery.

Background/Objectives: Interoception-based interventions aim to help individuals recognize and respond to internal bodily signals. Their contribution to executive functioning and behavioral regulation remains unclear. This scoping review mapped interventions and reported outcomes in children, adolescents, and young adults. Methods: PubMed, Scopus, and Web of Science were searched for English-language studies published between 2015 and 3 May 2026. The review followed Joanna Briggs Institute guidance and PRISMA-ScR reporting recommendations. Two reviewers independently screened records and extracted data. Findings were synthesized narratively; no formal critical appraisal was undertaken. Results: Nine studies included participants aged 4–23 years across clinical and nonclinical populations. Approaches included structured interoception curricula, acceptance-based exposure, and programs combining bodily awareness with other therapeutic components. Three studies assessed executive functioning using the Behavior Rating Inventory of Executive Function–Second Edition. Reported gains mainly concerned emotional and behavioral regulation, although improvements in some rated cognitive domains were also described. These findings did not establish improvements on performance-based executive function tasks. Other reported changes concerned anxiety, pain, eating, and social functioning. Findings were not uniformly positive: physiological outcomes were mixed, and one study reported increased worry about bodily sensations. Small samples, limited controlled comparisons, heterogeneous measures, and scarce follow-up data restricted interpretation. Conclusions: The literature reports preliminary improvements in regulation and selected behavioral outcomes but does not establish intervention effectiveness or the specific contribution of interoception. Controlled studies should assess both everyday regulation and executive task performance, isolate intervention components, and examine whether benefits persist.

Generative conversational AI can make health information easier to access, but its responses may still be unsupported, outdated, or poorly matched to the user. These risks are important in neurodevelopmental care, where occupational therapists and parents or caregivers require different levels of detail, language, and guidance. This narrative review used a structured multidisciplinary search to examine knowledge-base governance, retrieval-augmented generation, source verification, role adaptation, uncertainty communication, safety routing, privacy, human oversight, and lifecycle control. The evidence was synthesized into a sociotechnical reference architecture for adult-facing conversational AI serving occupational therapists and parents or caregivers. The architecture comprises five connected layers: intended use and request classification; knowledge governance and retrieval; claim-level verification; role-specific response design and safety review; and response delivery and lifecycle control. Occupational relevance, documentation, accountability, and continuous evaluation operate across the layers. Each layer is linked to operational requirements, responsible actors, and evaluation indicators. The framework is intended to guide future development and evaluation rather than function as a validated clinical tool. It excludes diagnosis, autonomous treatment planning, direct child-facing interaction, and replacement of occupational therapy assessment. The review provides a practical basis for developing conversational AI that is evidence-grounded, traceable, role-appropriate, and compatible with professional oversight.