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This study describes factors influencing occupational therapists' implementation of mobile applications into driving rehabilitation post-stroke. A qualitative descriptive design was used to analyze interview data from twenty ( = 20) occupational therapists working in stroke rehabilitation. Key factors include awareness of emerging applications, workplace technology policies, patient impairment levels and technological proficiency, and the involvement of caregivers in patient training. The ability to observe cognitive-perceptual abilities when utilizing mobile applications provided key insights into patient progress. Further investigation is necessary to explore methods for remotely monitoring outcomes in driving rehabilitation.
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http://dx.doi.org/10.1080/07380577.2024.2437819 | DOI Listing |
J Eval Clin Pract
September 2025
Pediatric Allergy and Immunology Department, Akdeniz University Hospital, Akdeniz University, Antalya, Türkiye.
Aims And Objectives: To evaluate the efficacy of YoungAsthma, a nurse-led, web-based mHealth intervention on asthma control and self-efficacy among adolescents with asthma utilizing decision tree analysis.
Background: Asthma is a prevalent chronic condition in pediatric populations, necessitating sustained management for optimal disease control.
Design: A randomized controlled clinical trial.
ACS Appl Mater Interfaces
September 2025
University of Science and Technology of China, Hefei, Anhui 230027, People's Republic of China.
The development of ultrablack coatings with exceptional absorption (>98%) has historically faced significant scientific and engineering challenges, primarily due to limitations in material selection, structural design, and practical durability. Considering the difficulties in practical applications of ultrablack materials with micro/nano structures and the limitations of planar ultrablack coatings in optical performance, we introduce an innovative integration of conventional planar ultrablack coatings with a specifically engineered trilayer antireflection architecture. This hybrid system incorporates a refractive index distribution (1.
View Article and Find Full Text PDFLight Sci Appl
September 2025
State Key Laboratory of Flexible Electronics, Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications (NUPT), Nanjing, 210023, China.
As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components.
View Article and Find Full Text PDFZhonghua Jie He He Hu Xi Za Zhi
September 2025
Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Guangzhou Medical University, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory He
Cough is a common symptom of many respiratory diseases, and parameters such as frequency, intensity, type and duration play important roles in disease screening, diagnosis and prognosis. Among these, cough frequency is the most widely applied metric. In current clinical practice, cough severity is primarily assessed based on patients' subjective symptom descriptions in combination with semi-structured questionnaires.
View Article and Find Full Text PDFZhonghua Jie He He Hu Xi Za Zhi
September 2025
Pulmonary and Critical Care Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China.
To explore the feasibility and accuracy of predicting respiratory tract infections (RTIs) using physiological data obtained from consumer-grade smartwatches. The study used smartwatches and paired mobile applications to continuously collect physiological parameters while participants slept. A personalized baseline model was established using multi-day data, followed by the construction of RTIs risk prediction algorithm based on deviations from physiological parameter trends.
View Article and Find Full Text PDF