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Introduction: This study investigates the effects of teacher verbal encouragement (VE) on strength, endurance, and psychophysiological responses, aiming to enhance teaching strategies in sports science education. Methods: Forty-eight sports science students, aged 21.3 ± 0.5 years, participated in this study. The sample was randomly divided into two groups, and a counterbalancing procedure was implemented. Participants completed strength and endurance testing sessions under normal conditions in the first week and repeated similar sessions in the second week with teacher VE. Strength was assessed using the 1RM bench press, squat, and deadlift tests, while endurance was evaluated through 8-minute time trials (8MTT: burpees, box jumps, hand-release push-ups, and sit-ups). Perceived exertion and physical activity enjoyment were investigated using self-reporting instruments. Results: The key findings showed that participants lifted greater weights in the 1RM bench press (p < 0.01; r = 0.45, medium to large effect), squat (p<0.001; Hedges' g = 1.36, large effect), and deadlift tests (p < 0.001; r = 0.79, large effect) and completed a greater number of repetitions in the 8MTT (p<0.001; r = 0.87, large effect) under VE. Perceived exertion was found to be lower under normal conditions (p<0.05; r = 0.29, small effect), yet physical activity enjoyment significantly increased under VE (p < 0.05; r = 0.81, large effect). Discussion: In conclusion, implementing teacher VE in sports science education can contribute to improved strength and endurance training outcomes and student psychophysiological response. [ABSTRACT FROM AUTHOR]

The article explores the potential impact of artificial-intelligence chatbots (AICs) on cognitive health. It discusses the interactive and personalized nature of AICs and how they can lead to a deeper cognitive reliance on the chatbots. The article introduces the concept of "AICs induced cognitive atrophy" (AICICA), which refers to the potential deterioration of cognitive abilities resulting from an overreliance on AICs. It emphasizes the need for further research to assess the prevalence and patterns of AICICA, explore long-term cognitive effects, and develop interventions to mitigate AICICA. The article also acknowledges the positive contributions of AICs as external cognitive tools but highlights the importance of a balanced approach and critical thinking skills to avoid potential negative effects. [Extracted from the article]

Objective: Research in sports medicine and exercise science has experienced significant growth over recent years. With this expansion, there has been a concomitant rise in ethical challenges specific to these disciplines. While various ethical guidelines exist for numerous scientific fields, a comprehensive set tailored specifically for sports medicine and exercise science is lacking. Aiming to bridge this gap, this paper proposes a comprehensive, updated set of ethical guidelines specifically targeted at researchers in sports medicine and exercise science, providing them with a thorough framework to ensure research integrity. Methods: A collaborative approach was adopted, involving contributions from a diverse group of international experts in the field. A thorough review of existing ethical guidelines was conducted, followed by the identification and detailed examination of 15 specific ethical topics relevant to the discipline. Each topic was discussed in terms of its definition, consequences, and preventive measures. Results: The research in sports medicine and exercise science has grown significantly, bringing to the fore ethical challenges unique to these disciplines. Our comprehensive review identifies 15 key ethical challenges: plagiarism, data falsification, role of artificial intelligence chatbots in academic writing, overstating results, excessive/strategic self-citation, duplicate publications, nondisclosure of conflicts of interest, image manipulation, misuse of peer review, ghost and gift authorship, inadequate data retention, data fabrication, falsification of IRB approvals, lack of informed consent, and unethical human or animal experimentation. For each identified challenge, we propose practical solutions and best practices, enriched by the diverse perspectives of our collaborative international expert panel. This endeavor aims to offer a foundational set of ethical guidelines tailored to the nuanced needs of sports medicine and exercise science, ensuring research integrity and promoting ethical responsibility across these vital fields. Conclusion: This article represents a seminal contribution to the establishment of essential ethical guidelines specifically designed for the fields of sports medicine and exercise science. This article charts a clear course for researchers, clinicians, and policymakers by integrating these ethical principles at the heart of our scholarly and clinical activities. Consequently, it envisions a future where the principles of research integrity and ethical responsibility consistently inform every scientific discovery and every clinical engagement. [ABSTRACT FROM AUTHOR]

Purpose: Nomophobia refers to a psychological state in which individuals experience anxiety or fear at the thought of being disconnected from their mobile phone. The Nomophobia Questionnaire was developed to assess dimensions of nomophobia among native English-speaking populations. The purpose of this study was to adapt and validate the Nomophobia Questionnaire in the Tunisian context based on Western Arabic dialects. Methods: This cross-sectional design using a non-probability sampling method was conducted from September 05 to October 06, 2022. A total of 644 participants, with an average age of 21.04 ± 1.59 years, completed a sociodemographic questionnaire and an Arabic version of the Nomophobia Questionnaire. Participants were divided into two groups to perform exploratory and confirmatory factor analysis. The first group consisted of 200 students (56% female and 44% male with an average age of 21.10 ± 1.64), with 33% (n = 66) freshmen, 41.5% second-year students (n = 83) and 25.5% (n = 51) of third-year students. The second group was collected one month later in the same establishment and was composed of 444 students (52% men and 48% female with an average age of 21.01 ± 1.57). Results: The results of the exploratory and confirmatory factor analysis showed that the 20 items and the second order four-factor structure should be retained. Confirmatory factor analysis of the Arabic version of the NMP-Q gave the following statistics: χ 2/df= 1.47; Fit Index = 0.997; Adjusted goodness-of-fit index = 0.996; Tucker-Lewis index = 1.003; Comparative Fit Index = 1; Root mean square error of approximation = 0.000 (90% CI 0– 0) and standardized mean residual = 0.030, indicating good model fit. McDonald's ω internal consistency indexes for the four factors, namely giving up convenience, not being able to access information, not being able to communicate, and losing connectedness were 0.821, 0.841, 0.851, and 0.897, respectively. These values demonstrated good scale consistency. Conclusion: The Arabic Version of the Nomophobia questionnaire has been found to be a reliable and valid psychometric tool, and can be effectively used to measure nomophobia in countries where western Arabic dialects are spoken. [ABSTRACT FROM AUTHOR]

The article highlights the potential risks associated with preprints in scientific research, particularly in the context of artificial intelligence. It emphasizes that preprints can disseminate inaccurate or incomplete information, which can lead to confusion and misinformation. The use of AI technologies like ChatGPT can further exacerbate these risks by generating misleading summaries and analyses of research. The article suggests implementing measures such as fact-checking procedures, human supervision, and limiting access to preprints to mitigate these risks and ensure responsible use of AI technologies. Additionally, the article discusses a study that exposed the lack of quality control in some open access journals, which charge authors a fee to publish their work. This raises concerns about the credibility and reliability of research published in these journals. [Extracted from the article]

The rise of artificial intelligence (AI) applications in healthcare provides new possibilities for personalized health management. AI-based fitness applications are becoming more common, facilitating the opportunity for individualised exercise prescription. However, the use of AI carries the risk of inadequate expert supervision, and the efficacy and validity of such applications have not been thoroughly investigated, particularly in the context of diverse health conditions. The aim of the study was to critically assess the efficacy of exercise prescriptions generated by OpenAI's Generative Pre-Trained Transformer 4 (GPT-4) model for five example patient profiles with diverse health conditions and fitness goals. Our focus was to assess the model's ability to generate exercise prescriptions based on a singular, initial interaction, akin to a typical user experience. The evaluation was conducted by leading experts in the field of exercise prescription. Five distinct scenarios were formulated, each representing a hypothetical individual with a specific health condition and fitness objective. Upon receiving details of each individual, the GPT-4 model was tasked with generating a 30-day exercise program. These AI-derived exercise programs were subsequently subjected to a thorough evaluation by experts in exercise prescription. The evaluation encompassed adherence to established principles of frequency, intensity, time, and exercise type; integration of perceived exertion levels; consideration for medication intake and the respective medical condition; and the extent of program individualization tailored to each hypothetical profile. The AI model could create general safety-conscious exercise programs for various scenarios. However, the AI-generated exercise prescriptions lacked precision in addressing individual health conditions and goals, often prioritizing excessive safety over the effectiveness of training. The AI-based approach aimed to ensure patient improvement through gradual increases in training load and intensity, but the model's potential to fine-tune its recommendations through ongoing interaction was not fully satisfying. AI technologies, in their current state, can serve as supplemental tools in exercise prescription, particularly in enhancing accessibility for individuals unable to access, often costly, professional advice. However, AI technologies are not yet recommended as a substitute for personalized, progressive, and health condition-specific prescriptions provided by healthcare and fitness professionals. Further research is needed to explore more interactive use of AI models and integration of real-time physiological feedback., Competing Interests: The authors declare no conflict of interest. The authors wish to affirm that this research was executed with complete academic integrity, free of any commercial or financial biases. Specifically, while we employed the paid version of ChatGPT 4.0 for its advanced capabilities in exercise prescription, this was not done with any intention to promote or encourage its use. Our choice of this platform was strictly to assess its potential in the realm of exercise prescription, without any sponsorship or incentives from the developers or associated entities of ChatGPT. No author has affiliations with OpenAI or any other commercial entities related to the content of the manuscript. Our sole commitment remains to transparent, unbiased evaluations that serve to advance the intersection of sports medicine and artificial intelligence., (Copyright © Biology of Sport 2024.)