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Enhancing prehospital decision-making: exploring user needs and design considerations for clinical decision support systems.
BMC Med Inform Decis Mak
January 2025
School of Medicine, University of Colorado, Aurora, CO, USA.
Background: In prehospital emergency care, providers face significant challenges in making informed decisions due to factors such as limited cognitive support, high-stress environments, and lack of experience with certain patient conditions. Effective Clinical Decision Support Systems (CDSS) have great potential to alleviate these challenges. However, such systems have not yet been widely adopted in real-world practice and have been found to cause workflow disruptions and usability issues.
View Article and Find Full Text PDFA Mobile Health Intervention to Support Collaborative Decision-Making in Mental Health Care: Development and Usability.
JMIR Form Res
January 2025
Early Intervention in Psychosis Advisory Unit for South-East Norway, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
Background: Shared decision-making between clinicians and service users is crucial in mental health care. One significant barrier to achieving this goal is the lack of user-centered services. Integrating digital tools into mental health services holds promise for addressing some of these challenges.
View Article and Find Full Text PDFPSA Screening: Shared Decision-Making Is a Flawed Approach.
Am Fam Physician
January 2025
Lancaster General Hospital Family Medicine Residency, Pennsylvania.
Parents' Experiences and Views About Use of Wearable Technology for Research and Treatment Monitoring of Children with Neurodevelopmental Disorders.
J Dev Behav Pediatr
January 2025
Department of Paediatrics, The University of Melbourne, Melbourne, Australia.
Objective: Wearable technology has potential benefits for clinical measurement with children who have neurodevelopmental disorders (NDDs). However, this cohort may experience sensory processing disorder, behavioral dysregulation, and cognitive challenges. For effective and considerate implementation, the experiences and views of parents of children with NDDs on this topic need in-depth investigation.
View Article and Find Full Text PDFValidating a novel measure for assessing patient openness and concerns about using artificial intelligence in healthcare.
Learn Health Syst
January 2025
Bioethics Research Center, Division of General Medical Sciences, Department of Medicine Washington University School of Medicine St. Louis Missouri USA.
Objectives: Patient engagement is critical for the effective development and use of artificial intelligence (AI)-enabled tools in learning health systems (LHSs). We adapted a previously validated measure from pediatrics to assess adults' openness and concerns about the use of AI in their healthcare.
Study Design: Cross-sectional survey.
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