Search

Individuals who want to earn a doctoral degree aim to change or develop their careers. Some potential doctoral students have a clear goal to pursue a doctoral degree, some are uncertain if they can manage the rigor associated with a doctorate program, and others might have already been involved in their program. This article aims to provide insights and strategies for current and future doctoral students in physical education teacher education (PETE) during their doctoral journey. The article provides top ten tips to help current and prospective PETE doctoral students to be successful.

On November 30, 2022, the emergence of a super-large artificial intelligence (AI) chatbot called ChatGPT (chat generative pre-trained transformer) astonished the world with its exceptional performance capabilities. ChatGPT is a trained AI chatbot developed by an American AI research laboratory called OpenAI. It provides users with a dialogueformat online chat that responds to and follows up on questions, admits mistakes, challenges incorrect premises, and rejects inappropriate requests. ChatGPT has evolved tremendously in just a few months (GPT-4 was released on March 14, 2023) to include multiple advanced features, such as image and infographic analysis, extended text processing, and safer and more accurate responses. Many experts, professionals, and scholars in various fields are looking at both the advantages and disadvantages of using this tool, and the field of kinesiology is no exception. Because technological advancement is inevitable, people working in a range of industries are considering how and to what extent they can incorporate ChatGPT and other tools that offer similar capabilities and features (e.g., Google Bard, Microsoft Bing, and Chatsonic) into their daily work. As in other fields of study, ChatGPT can be deployed to promote work efficiency for practitioners, learners, educators, and researchers within the field of kinesiology. Stakeholders should learn and stay updated with the latest version of ChatGPT to enhance overall performance in each subdiscipline of kinesiology while experimenting with its new features to obtain more accurate and productive responses. The purpose of this article is to discuss how ChatGPT can be used in the field of kinesiology, and more specifically in the areas of exercise science, physical activity and health promotion, physical education, and sport management, along with topics related to accuracy optimization, its use in higher education, challenges, concerns, ethical considerations, and future directions. [ABSTRACT FROM AUTHOR]

Background: Most studies assessing pathophysiological heterogeneity in asthma have been conducted in high-income countries (HICs), with little known about the prevalence and characteristics of different asthma inflammatory phenotypes in low-and middle-income countries (LMICs). This study assessed sputum inflammatory phenotypes in five centres, in Brazil, Ecuador, Uganda, New Zealand (NZ) and the United Kingdom (UK).Methods: We conducted a cross-sectional study of 998 asthmatics and 356 non-asthmatics in 2016-20. All centres studied children and adolescents (age range 8-20 years), except the UK centre which involved 26-27 year-olds. Information was collected using questionnaires, clinical characterization, blood and induced sputum.Results: Of 623 asthmatics with sputum results, 39% (243) were classified as eosinophilic or mixed granulocytic, i.e. eosinophilic asthma (EA). Adjusted for age and sex, with NZ as baseline, the UK showed similar odds of EA (odds ratio 1.04, 95% confidence interval 0.37-2.94) with lower odds in the LMICs: Brazil (0.73, 0.42-1.27), Ecuador (0.40, 0.24-0.66) and Uganda (0.62, 0.37-1.04). Despite the low prevalence of neutrophilic asthma in most centres, sputum neutrophilia was increased in asthmatics and non-asthmatics in Uganda.Conclusions: This is the first time that sputum induction has been used to compare asthma inflammatory phenotypes in HICs and LMICs. Most cases were non-eosinophilic, including in settings where corticosteroid use was low. A lower prevalence of EA was observed in the LMICs than in the HICs. This has major implications for asthma prevention and management, and suggests that novel prevention strategies and therapies specifically targeting non-eosinophilic asthma are required globally. [ABSTRACT FROM AUTHOR]

An imbalance in autonomic nervous system (ANS) activity may play a role in asthma, but it is unclear whether this is associated with specific pathophysiology. This study assessed ANS activity by measuring heart rate variability (HRV) in eosinophilic (EA) and non-eosinophilic asthma (NEA) and people without asthma. HRV, combined hypertonic saline challenge/sputum induction, exhaled nitric oxide (FeNO), skin prick tests to measure atopy, and spirometry tests were conducted in teenagers and young adults (14–21 years) with (n = 96) and without (n = 72) generally well-controlled asthma. HRV parameters associated with sympathetic and parasympathetic ANS branches were analyzed. EA and NEA were defined using a 2.5% sputum eosinophil cut-point. Airway hyperreactivity (AHR) was defined as ≥15% reduction in FEV1 following saline challenge. HRV parameters did not differ between asthmatics and non-asthmatics or EA and NEA. They were also not associated with markers of inflammation, lung function or atopy. However, increased absolute low frequency (LFµs2; representing increased sympathetic nervous system (SNS) activity) was found in asthmatics who used β-agonist medication compared to those who did not (median: 1611, IQR 892–3036 vs 754, 565–1592; p < 0.05) and increased normalized low frequency (LF nu) was found in those with AHR compared to without AHR (64, 48–71 vs 53, 43–66; p < 0.05). ANS activity (as measured using HRV analysis) is not associated with pathophysiology or inflammatory phenotype in young asthmatics with generally well-controlled asthma. However, enhanced SNS activity can be detected in asthmatics with AHR or who use β-agonist medication. [ABSTRACT FROM AUTHOR]