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Background: Ethical performance is one of the main components of maternal and fetal care. Nurturing and training students who meet professional ethics in midwifery is of utmost importance. It is essential to assess the level of adherence of students and graduates to the codes of ethics in order to determine the extent of education needs in this regard.

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Background: Multiple sclerosis and its progressive relapsing-remitting nature for MS patients is challenging and significantly affects the mental health of people with MS. We examined the direct effects of alexithymia and attachment on mental health and the indirect effect of attachment, alexithymia, loneliness, and perceived social support on the mental health of people with MS.

Materials And Methods: Three hundred and forty-five diagnosed with multiple sclerosis (MS) were deemed eligible for inclusion in the study and selected through the Iranian MS Association.

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Design and validation of the reflection skills self-assessment questionnaire (RSSAQ).

J Educ Health Promot

November 2024

Medical Education Research Center, Medical Education Department, Health Management and Safety Promotion Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran.

Background: Reflection is one of the main components of the medical sciences curriculum. It is one of the learner-centered educational strategies, leading to deep learning, and is necessary to attain professional capabilities. A pertinent challenge is how to assess reflection.

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Quality of life for patients on oncology treatments in the Kingdom of Saudi Arabia: a systematic review.

J Pharm Policy Pract

January 2025

Clinical Pharmacy Department, King Fahad Medical City, Riyadh, Saudi Arabia.

Background: Cancer cases in the Kingdom of Saudi Arabia (KSA) have tripled in recent years. Quality of Life (QoL) measurements are crucial for healthcare professionals because they reveal important information about how patients respond to drugs and their general health. This study aimed to collect and summarise articles exploring the QoL of patients undergoing oncology treatments in KSA.

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Contemporary research in 3D object detection for autonomous driving primarily focuses on identifying standard entities like vehicles and pedestrians. However, the need for large, precisely labelled datasets limits the detection of specialized and less common objects, such as Emergency Medical Service (EMS) and law enforcement vehicles. To address this, we leveraged the Car Learning to Act (CARLA) simulator to generate and fairly distribute rare EMS vehicles, automatically labelling these objects in 3D point cloud data.

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