IntroductionModern 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 […]
Disclosure in the era of generative artificial intelligence
Generative artificial intelligence (AI) has rapidly become embedded in academic writing, assisting with tasks ranging from language editing to drafting text and producing evidence. Despite the wide range of AI use, the expectations for disclosure remain inconsistent. Several journals use binary disclosure statements that fail to distinguish minor language assistance from uses that have a […]
Promotion and preservation of mobility and autonomy in old age through smart rollators—a qualitative study
BackgroundDiseases and health limitations associated with ageing often result in loss of mobility and reduced social participation. The ongoing demographic shift towards an increasingly ageing population, combined with a declining number of healthcare professionals, highlights the need to integrate digital assistive solutions to reduce workload and healthcare costs. Smart rollators (SRs) equipped with sensor-based assistance […]
A randomized factorial experiment to optimize the design of a culturally tailored breast cancer screening outreach chatbot intervention
IntroductionThe main objective of this study is to assess the effects of chatbot persona and communication style on trust and intention to use for scheduling breast cancer screening (BCS).MethodsWe conducted a mixed-methods analysis of a randomized factorial experiment to evaluate different chatbot designs for a BCS intervention. The study protocol is registered on ClinicalTrials.gov (NCT05472064). […]
Trustworthy intelligent rooms: integrating blockchain, federated learning, and data-centric AI for healthcare 4.0
IntroductionIntelligent room systems are experiencing a surge in demand within the Healthcare 4.0 ecosystem. The integration of Federated Learning (FL) and Data-Centric AI has led to substantial enhancements in the predictive capabilities of machine learning models while maintaining data privacy. However, centralized aggregation in FL remains a single point of failure and is vulnerable to […]
AI-driven mental health decision support linked to clinician resilience and preparedness
ObjectivesMental health services are facing unprecedented demand, placing significant pressure on clinicians to conduct timely and effective patient assessments. Rising staff turnover and burnout threatens service quality across many countries. This study examined whether providing clinical information, collected via an artificial intelligence (AI)—enabled decision support tool for mental health assessments in the UK’s National Health […]
Big data integration for enhanced epidemiological research: insights and directions from NHLBI’s workshop
The landscape of epidemiological research is experiencing a technological transformation, driven by the rapid expansion of big data and advancements in artificial intelligence (AI) and machine learning (ML). This workshop explored the opportunities and challenges associated with integrating diverse data sources into population-based research at different levels, including electronic health records (EHRs), genomic and omics […]
Construction of patient trajectories to model clinical trial outcomes: application to myasthenia gravis
IntroductionAccurate prediction of patient outcomes in clinical trials is crucial for the timely assessment of treatment efficacy. This study proposes a novel approach to predict patient response using longitudinal clinical data.MethodsWe construct temporal trajectories from longitudinal data and extrapolate these trajectories to forecast individual patient outcomes. Additionally, we assess when new patients align with established […]
An embodied cognition based model of medical experts’ tacit knowledge: structure, hierarchies, and transformation
BackgroundTacit knowledge plays a crucial role in clinical decision-making and medical innovation, particularly through experience-based and practice-oriented expertise. However, existing research has not yet provided a sufficiently integrated framework to explain how such knowledge is structured and transformed within medical practice.MethodsGrounded in embodied cognition theory, this study constructs a medical experts’ tacit knowledge model encompassing […]
Effectiveness of the mobile application Holidaily in reducing work-related rumination when returning to work after vacation: a randomized controlled trial
BackgroundVacations reliably improve indicators of mental health, largely by providing relief from work-related stress. Low levels of work-related rumination, a key transdiagnostic factor linked to burnout and depression, are considered prerequisites for successful recovery both during vacations and in daily working life. However, such benefits are typically short-lived, with a rapid “fade-out” upon return to […]
Effectiveness of digital and mobile-based interventions on sleep quality among nurses: a systematic review and meta-analysis
BackgroundNurses frequently endure diminished sleep quality, sleeplessness, and psychological distress due to high-intensity shifts and persistent work pressure. Digital health interventions are increasingly utilised to enhance sleep behaviour; however, systematic information about their real benefits on the nursing population remains insufficient.ObjectiveTo assess the efficacy of digital and mobile interventions on sleep and associated psychological consequences […]
An interpretable, clinically grounded framework for digital speech biomarker development in neurodegenerative diseases
IntroductionCommunication ability—a key determinant of quality of life—is frequently affected and progressively declines in neurodegenerative diseases. Effective management of progressive communication disorders requires a personalized approach to deliver timely interventions tailored to the evolving profiles of communicative impairment, thereby supporting functional communication throughout the disease course. To this end, reliable tools capable of detecting and […]