Background: Little is known about the public health professionals engaged in educating and training new or future researchers in public health. Research in this direction identifies their issues, concerns, challenges, and needs. This study focused on the professional development challenges of Chinese public health professionals.
Methods: Snowball sampling was utilized. A total of 265 public health professionals participated. An instrument of 6 dimensions (burnout, sleep issue, mood issue, friends' support, exercise, and challenges) was developed, revised, and administered online. Two different approaches, the conventional and data screening approaches, were applied. The former started with item quality analyses, whereas the latter began with data quality checks. The chi-square tests of associations and logistic regressions were performed on both approaches.
Results And Discussion: 19.25% of the participants were detected and deleted as careless respondents. Using both approaches, six professional development challenges except one ("Multidisciplinary learning") were significantly associated with various demographic features. The two approaches produced different models though they converged sometimes. The latent variables of exercise predicted professional development challenges more frequently than other latent variables. Regarding correct classification rates, results from the data screening approach were comparable to those from the conventional approach.
Conclusion: The latent variables of exercise, such as "Exercise effects," "Expectations of exercise," and "Belief in exercise," might be understudied. More research is necessary for professional development challenges using exercise as a multidimensional construct. Based on the current study, screening and deleting careless responses in survey research is necessary.
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http://dx.doi.org/10.3389/fpubh.2023.1250606 | DOI Listing |
BMC Med Educ
January 2025
Medical Education Research Center, Health Management and Safety Promotion Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran.
Aim: This study aims to determine and compare the achieved competencies of graduating nursing students of public and private universities in Iran.
Background: The main responsibility of nursing education is to train nurses who possess the necessary competencies to provide safe and high-quality care. Given that a significant proportion of nursing education in Iran is the responsibility of private universities, it is essential to ensure that nursing graduates acquire the required competencies.
Trials
January 2025
Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
Background: Leptospirosis is a zoonotic bacterial infection occurring worldwide. It is of particular public health concern due to its global distribution, epidemic potential and high mortality without appropriate treatment. The method for the management of leptospirosis, particularly in severe disease, is clouded by methodological inconsistency and a lack of standardized outcome measures.
View Article and Find Full Text PDFBMC Med Educ
January 2025
Medical Education Department, Education Development Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Aim: The present study aimed to explore the unprofessional behavior of educators, senior students, and peers in the education process of dental and oral health services.
Method: This qualitative study employed a conventional content analysis approach. The undergraduate students (n = 21) were recruited to participate in the study through purposive sampling.
BMC Public Health
January 2025
One Health Lesson Administrative Intern, Addis Ababa, Ethiopia.
Background: According to the World Health Organization (WHO), there were 1.19 million road traffic accident (RTA)-related deaths in 2021, with a significantly higher death rate in developing countries than in developed countries.
Objective: To assess the distribution of causes of death and associated organ injuries in RTA-related fatalities.
Sci Rep
January 2025
Department of Information Systems, College of Computing and Informatics, The University of Sharjah, Sharjah, UAE.
This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. The incorporation of nanotechnology, through the addition of nanoparticles to conventional fuels, improves fuel atomization, combustion efficiency, and emission control. Simultaneously, LSTM models are employed to analyze and predict the complex spray behavior under diverse operational and geometric conditions.
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