Background: The grit concept encompasses passion, i.e., the degree in which people maintain their passion for the same goal over long periods of time, and perseverance, i.e., the degree to which people make an effort to achieve the same goal over time. Studies show that people with higher grit have better outcomes in a variety of areas, including academic achievements.
Objectives: To examine whether grit may be used as an admission tool for predicting academic success and non-dropout among nursing students at a college, and whether it can be identified in a cultural context (Jewish and Arab students).
Design: A descriptive, exploratory study was employed.
Setting: The study was implemented in the Department of Nursing at a college in Israel.
Participants: 237 nursing students in their second, third, or fourth year of studies participated in the study.
Results: Grit meant that on average, scores out of 5 were quite high (passion = 3.56; perseverance = 4.00), with students rating themselves as being highly passionate about their studies and having high academic perseverance. Out of 100, the average college grade and clinical grade were relatively high as well (M = 84.66, range 68-95; M = 91.05, range 75-100 respectively), and were positively and significantly correlated. Significant weak positive correlations were found between the average college grade, passion scores, and total grit. No relationships were found for the clinical grade. The average college grade was found to be higher among Jewish students than among Arab ones, and higher among students who were born in Israel. Higher passion and higher total grit scores were predictive of a higher average college grade.
Conclusions: Passion and perseverance are qualities that may be associated with health professionals. Findings show cultural differences regarding grit. Therefore, larger studies are encouraged, in order to investigate such differences. Whether grit should be included in student assessment models remains to be determined.
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http://dx.doi.org/10.1016/j.nedt.2021.104844 | DOI Listing |
BMC Vet Res
January 2025
College of Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, China.
Background: Coccidia are among the primary pathogens causing diarrhea and even fatalities in lambs. With the increasing use of chemical drugs to treat coccidiosis, the problem of drug resistance is becoming more and more threatening. Therefore, there is an urgent need to identify novel alternative drugs for the treatment of the lamb coccidia.
View Article and Find Full Text PDFBMC Public Health
January 2025
School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongdansantiao, Dongcheng district, Beijing, 100730, China.
Introduction: Retirement represents a significant life transition and is associated with individual health outcomes. Previous studies on the health effects of retirement have yielded inconsistent conclusions. This study aimed to estimate the impact of retirement on the body mass index (BMI) and BMI-defined overweight and obesity.
View Article and Find Full Text PDFBMC Ophthalmol
January 2025
Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221006, China.
Objective: This study aims to investigate the correlation between the development of diabetic retinopathy (DR) and the changes in corneal sub-basal nerve plexus (SNP) and corneal dendritic cells (DCs).
Methods: 58 patients with type 2 diabetes mellitus (T2DM) and 30 age- and sex-matched healthy participants underwent assessment of the corneal nerve. The DR group was divided into no diabetic retinopathy (NDR) and 29 eyes with mild to moderate non-proliferative diabetic retinopathy (NPDR).
Sci Rep
January 2025
School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, 510665, China.
With the rapid development of Internet of Things (IoT) technology, embedded devices in various computer vision scenarios can realize real-time target detection and recognition tasks, such as intelligent manufacturing, automatic driving, smart home, and so on. YOLOv8, as an advanced deep learning model in the field of target detection, has attracted much attention for its excellent detection speed, high precision, and multi-task processing capability. However, since IoT embedded devices typically own limited computing resources, direct deployment of YOLOv8 is a big challenge, especially for real-time detection tasks.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Computer Science and Engineering, University Institute of Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya (State Technological University of Madhya Pradesh), Madhya Pradesh, Bhopal, 462033, India.
The most common carcinoma-related cause of death among women is breast cancer. Early detection is crucial, and the manual screening method may lead to a delayed diagnosis, which would delay treatment and put lives at risk. Mammography imaging is advised for routine screening to diagnose breast cancer at an early stage.
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