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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.
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Introduction: Despite the progress in the management of the pandemic caused by COVID-19, it is necessary to continue exploring and explaining how this situation affected the athlete population around the world to improve their circumstances and reduce the negative impact of changes in their lifestyle conditions that were necessitated due to the pandemic. The aim of this study was to analyze the moderating influence of physical activity (PA) and dietary habits on the impact of the COVID-19 pandemic experience on sleep quality in elite and amateur athletes. Materials and methods: A total of 1,420 elite (40.1%) and amateur (59.9%) athletes (41% women; 59% men) from 14 different countries participated in a cross-sectional design study. Data were collected using a battery of questionnaires that identified sociodemographic data, sleep quality index, PA levels, dietary habits, and the athletes' perception of their experience during the COVID-19 pandemic. Means and standard deviations were calculated for each variable. The analysis of variances and the correlation between variables were carried out with non-parametric statistics. A simple moderation effect was calculated to analyze the interaction between PA or dietary habits on the perception of the COVID-19 experience effect on sleep quality in elite and amateur athletes. Results: The PA level of elite athletes was higher than amateur athletes during COVID-19 (p < 0.001). However, the PA level of both categories of athletes was lower during COVID-19 than pre-COVID-19 (p < 0.01). In addition, amateurs had a higher diet quality than elite athletes during the pandemic (p = 0.014). The perception of the COVID-19 experience as controllable was significantly higher (p = 0.020) among elite athletes. In addition, two moderating effects had significant interactions. For amateur athletes, the PA level moderated the effect of controllable COVID-19 experience on sleep quality [F (3,777) = 3.05; p = 0.028], while for elite athletes, the same effect was moderated by dietary habits [F (3,506) = 4.47, p = 0.004]. Conclusion: Elite athletes had different lifestyle behaviors compared to amateurs during the COVID-19 lockdown. Furthermore, the relevance of maintaining high levels of PA for amateurs and good quality dietary habits by elite athletes was noted by the moderating effect that both variables had on the influence of the controllable experience during the COVID-19 pandemic on sleep quality.
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BACKGROUND: Although several studies have shown that the Coronavirus Disease 2019 (COVID-19) lockdown has had negative impacts on mental health and eating behaviors among the general population and athletes, few studies have examined the long-term effects on elite and sub-elite athletes. The present study aimed to investigate the long-term impact of COVID-19 lockdown on mental health and eating behaviors in elite versus sub-elite athletes two years into the pandemic. A cross-sectional comparative study was conducted between March and April 2022, involving athletes from 14 countries, using a convenient non-probabilistic and snowball sampling method. A total of 1420 athletes (24.5 ± 7.9 years old, 569 elites, 35% women, and 851 sub-elites, 45% women) completed an online survey-based questionnaire. The questionnaire included a sociodemographic survey, information about the COVID-19 pandemic, the Depression, Anxiety and Stress Scale-21 Items (DASS-21) for mental health assessment, and the Rapid Eating Assessment for Participants (REAP-S) for assessing eating behavior. RESULTS: The results showed that compared to sub-elite athletes, elite athletes had lower scores on the DASS-21 (p = .001) and its subscales of depression (p = .003), anxiety (p = .007), and stress (p < .001), as well as a lower REAP-S score indicating lower diet quality (p = .013). CONCLUSION: In conclusion, two years into the pandemic, elite athletes were likelier to have better mental health profiles than sub-elite athletes but surprisingly had lower diet quality.
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BACKGROUND: Monitoring recovery-stress balance in sport is becoming more relevant to prevent training maladaptation and reach the optimal performance for each athlete. The use of questionnaires that identify the athlete's recovery-stress state have much acceptance in sports due to reliability and useful, furthermore for its low cost. Identifying possible differences between sport modalities and sex is important to determine specific needs and possible intervention ways to keep a recovery-stress balance. The aim was to analyze the differences in the recovery-stress state and mood states by sex and sport type during the competitive phase in young Mexican athletes. As a secondary objective, the psychometric properties of the Mexican version of the Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) were analyzed. METHODS: A cross-sectional study was carried on with 461 athletes (61% women and 39% men), 17.95 (±1.2) years old, from six sports disciplines. The RESTQ-Sport and Profile of Mood States (POMS) were applied in a single moment. Differences by sex and sports modality were analyzed. RESTQ-Sport's confirmatory factor analysis was performed after the stress and recovery theoretical structure of two stress (general and sport) and two recovery (general and sport) dimensions, and last, the concurrent validation with the POMS was carried on. RESULTS: Significant differences by sex were found in the General Recovery and Sport Stress dimensions of the RESTQ-Sport as well as Vigor factor of the POMS, being higher for men; furthermore, both the Sport Recovery dimension of RESTQ-Sport and Cholera and the Fatigue and Depression factors from POMS also had differences by sport type, showing a less recovery and high stress for individual sport athletes. Goodness-of-fit indexes of the model for the RESTQ-Sport were acceptable. Pearson's correlation between questionnaires was moderate (p < 0.05). CONCLUSION: The recovery-stress state shows differences in the function of sex and sport modality. More special attention is suggested for women and individual sport athletes. The higher punctuation for men compared with women in sport stress dimension did not negatively affect the recovery-stress balance for male athletes. Finally, the Mexican context adaptation of the RESTQ-Sport provides a psychometric instrument suitable to assess the recovery-stress balance in Mexican athletes.