The first aim of the present study was to investigate the applicability of the two-factor structure (perceptual-motor skills by 11 items, e.g., "fluent driving"; safety skills by 9 items, e.g., "conforming to the speed limits") of the Driver Skill Inventory (DSI) among British, Dutch, Finnish, Greek, Iranian, and Turkish drivers. It was also hypothesized that the combination of self reported high ratings of perceptual-motor skills and low ratings of safety skills creates a serious risk for dangerous driving and road accident involvement. The second aim of this study was, therefore, to investigate this asymmetric relationship between perceptual-motor and safety skills in traffic penalties and accident involvement. Two hundred and forty two drivers were chosen from each of the six countries, matched for age and sex. The results of exploratory factor analyses together with target rotation showed that the two-factor structure of DSI found in "safe" Northern and Western European countries were highly congruent. However, the safety skills factor of DSI in Greece, Iran, and Turkey was relatively incongruent in spite of high factor similarity found in perceptual-motor skills. The asymmetric relationship between perceptual-motor and safety skills on traffic penalties was found in Finland and Turkey. A negative relationship between safety skills and the number of accidents was found both in Greece and Iran while a positive relationship between perceptual-motor skills and the number of accidents was found only in Iran.
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http://dx.doi.org/10.1016/j.aap.2006.04.006 | DOI Listing |
Backgrounds: Biomedical research requires sophisticated understanding and reasoning across multiple specializations. While large language models (LLMs) show promise in scientific applications, their capability to safely and accurately support complex biomedical research remains uncertain.
Methods: We present , a novel question-and-answer benchmark for evaluating LLMs in biomedical research.
Curr Pharm Des
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Director Operations and Medical Writing, RYT Lifesciences Pvt Ltd, Ahmedabad, Gujrat, India.
Objective: This study aimed to evaluate the effectiveness and safety of Altibrain® in combination with standard Autism Spectrum Disorder (ASD) treatment compared to standard ASD treatment alone in individuals diagnosed with ASD.
Method: A randomized, open-label trial was conducted involving 120 participants aged 3 to 17 years, randomly assigned to either the Standard ASD Treatment group or the Altibrain® + Standard ASD Treatment group. Sixty patients were randomly allocated to each Standard ASD Treatment group or the Altibrain® + Standard ASD Treatment group.
Int J Nurs Pract
February 2025
Public Health Nursing Department, Nursing Faculty, Akdeniz University, Antalya, Turkey.
Background: Work environments that support patient safety initiatives are important for quality service and patient outcomes. The relationship between the leadership behaviours of nurse managers and safety culture, which has the potential to support these initiatives, constitutes one of the most important knowledge gaps.
Objectives: The study aimed to determine the relationship between nurses' perceived leadership behaviours and hospital safety culture and the factors affecting them.
Appl Nurs Res
February 2025
University of Helsinki and Helsinki University Hospital, Nursing Research Center, Tukholmankatu 8F, P.O. Box 442, FIN-00029 HUS, Finland; Lovisenberg Diaconal University College, Oslo, Norway. Electronic address:
Aims: This study aims to describe how newly hired nurses assess the quality of the orientation in acute care settings in a university hospital.
Background: Orientation for newly hired nurses in acute care settings, where special competence, ability to collaborate with different professional groups, and wide technical and technological skills are required, is crucial to ensure patient safety and high-quality standards in nursing care.
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Adv Nutr
January 2025
Pharmavite, LLC, West Hills, CA, USA. Electronic address:
Personalized Nutrition (PN) aims to provide tailored dietary recommendations to improve a person's health outcomes by integrating a multitude of individual-level information and support desired behavior changes. The field is rapidly evolving with technological advances. As new biomarkers are discovered, wearables and other devices can now provide up-to-the-minute insights, and artificial intelligence (AI) and machine learning (ML) models support recommendations and lifestyle behavior change.
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