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Using artificial intelligence for exercise prescription in personalised health promotion: A critical evaluation of OpenAI's GPT-4 model.
Dergaa, I, Saad, HB, El Omri, A, Glenn, JM, Clark, CCT, Washif, JA, Guelmami, N, Hammouda, O, Al-Horani, RA, Reynoso-Sánchez, LF, et al
Biology of sport. 2024;(2):221-241
Abstract
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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The effect of caffeine, nap opportunity and their combination on biomarkers of muscle damage and antioxidant defence during repeated sprint exercise.
Romdhani, M, Souissi, N, Dergaa, I, Moussa-Chamari, I, Chaabouni, Y, Mahdouani, K, Abene, O, Driss, T, Chamari, K, Hammouda, O
Biology of sport. 2022;(4):1033-1042
Abstract
To investigate the effect of 20 min nap opportunity (N20), 5 mg · kg-1 of caffeine (CAF) and their combination (CAF+N20) on the biochemical response (energetic biomarkers, biomarkers of muscle damage and enzymatic antioxidants) to the running-based anaerobic sprint test. Fourteen highly trained male athletes completed in a double-blind, counterbalanced and randomized order four test sessions: no nap with placebo (PLA), N20, CAF and CAF+N20. Compared to PLA, all treatments enhanced maximum and mean powers. Minimum power was higher [(mean difference) 58.6 (95% confidence interval = 1.31-116) Watts] after CAF and [102 (29.9-175) Watts] after CAF+N20 compared to N20. Also, plasma glucose was higher after CAF [0.81 (0.18-1.45) mmol · l-1] and CAF+N20 [1.03 (0.39-1.64) mmol · l-1] compared to N20. However, plasma lactate was higher [1.64 (0.23-3.03) mmol · l-1] only after N20 compared to pre-exercise, suggesting a higher anaerobic glycolysis during N20 compared to PLA, CAF and CAF+N20. Caffeine ingestion increased post-exercise creatine kinase with [54.3 (16.7-91.1) IU · l-1] or without napping [58.9 (21.3-96.5) IU · l-1] compared to PLA. However, superoxide dismutase was higher after napping with [339 (123-554) U · gHB-1] or without caffeine [410 (195-625) U · gHB-1] compared to PLA. Probably because of the higher aerobic glycolysis contribution in energy synthesis, caffeine ingestion resulted in better repeated sprint performance during CAF and CAF+N20 sessions compared to N20 and PLA. Caffeine ingestion resulted in higher muscle damage, and the short nap enhanced antioxidant defence with or without caffeine ingestion.
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Effects of home confinement on mental health and lifestyle behaviours during the COVID-19 outbreak: insights from the ECLB-COVID19 multicentre study.
Ammar, A, Trabelsi, K, Brach, M, Chtourou, H, Boukhris, O, Masmoudi, L, Bouaziz, B, Bentlage, E, How, D, Ahmed, M, et al
Biology of sport. 2021;38(1):9-21
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Plain language summary
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the respiratory syndrome coronavirus 2 (SARS-CoV-2). To curb the spread of the 2020 pandemic, social distancing, self-isolation and nationwide lockdown measures were put in place. These measures along with hygiene care are recognized as the most effective ways to curb the spread of disease. However; the weakening of social contacts can result in anxiety, frustration, panic attacks, loss or sudden increase of appetite, insomnia, depression, mood swings, delusions, fear, sleep disorders, and suicidal/domestic violence. The purpose of the study is to provide scientific data to help identify risk factors for the psychosocial strain during the COVID-19 outbreak. The study is an international cross-disciplinary online survey and was circulated in April 2020. 1047 replies were analysed from this preliminary phase. The results show a significant difference in all tested parameters and therefore reveal a large burden for mental wellbeing combined with a tendency towards an unhealthy lifestyle during, compared to before, the confinement enforced by the COVID-19 pandemic. These results highlight the importance for policy makers to consider strategies to promote wellbeing during future confinements.
Abstract
Although recognised as effective measures to curb the spread of the COVID-19 outbreak, social distancing and self-isolation have been suggested to generate a burden throughout the population. To provide scientific data to help identify risk factors for the psychosocial strain during the COVID-19 outbreak, an international cross-disciplinary online survey was circulated in April 2020. This report outlines the mental, emotional and behavioural consequences of COVID-19 home confinement. The ECLB-COVID19 electronic survey was designed by a steering group of multidisciplinary scientists, following a structured review of the literature. The survey was uploaded and shared on the Google online survey platform and was promoted by thirty-five research organizations from Europe, North Africa, Western Asia and the Americas. Questions were presented in a differential format with questions related to responses "before" and "during" the confinement period. 1047 replies (54% women) from Western Asia (36%), North Africa (40%), Europe (21%) and other continents (3%) were analysed. The COVID-19 home confinement evoked a negative effect on mental wellbeing and emotional status (P < 0.001; 0.43 ≤ d ≤ 0.65) with a greater proportion of individuals experiencing psychosocial and emotional disorders (+10% to +16.5%). These psychosocial tolls were associated with unhealthy lifestyle behaviours with a greater proportion of individuals experiencing (i) physical (+15.2%) and social (+71.2%) inactivity, (ii) poor sleep quality (+12.8%), (iii) unhealthy diet behaviours (+10%), and (iv) unemployment (6%). Conversely, participants demonstrated a greater use (+15%) of technology during the confinement period. These findings elucidate the risk of psychosocial strain during the COVID-19 home confinement period and provide a clear remit for the urgent implementation of technology-based intervention to foster an Active and Healthy Confinement Lifestyle AHCL).
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The Effect of Experimental Recuperative and Appetitive Post-lunch Nap Opportunities, With or Without Caffeine, on Mood and Reaction Time in Highly Trained Athletes.
Romdhani, M, Souissi, N, Dergaa, I, Moussa-Chamari, I, Abene, O, Chtourou, H, Sahnoun, Z, Driss, T, Chamari, K, Hammouda, O
Frontiers in psychology. 2021;:720493
Abstract
Purpose: To investigate the effects of placebo (PLA), 20 min nap opportunity (N20), 5mg·kg-1 of caffeine (CAF), and their combination (CAF+N20) on sleepiness, mood and reaction-time after partial sleep deprivation (PSD; 04h30 of time in bed; study 1 ) or after normal sleep night (NSN; 08h30 of time in bed; study 2 ). Methods: Twenty-three highly trained athletes ( study 1 ; 9 and study 2 ; 14) performed four test sessions (PLA, CAF, N20 and CAF+N20) in double-blind, counterbalanced and randomized order. Simple (SRT) and two-choice (2CRT) reaction time, subjective sleepiness (ESS) and mood state (POMS) were assessed twice, pre- and post-intervention. Results: SRT was lower (i.e., better performance) during CAF condition after PSD (pre: 336 ± 15 ms vs. post: 312 ± 9 ms; p < 0.001; d = 2.07; Δ% = 7.26) and NSN (pre: 350 ± 39 ms vs. post: 323 ± 32 ms; p < 0.001; d = 0.72; Δ% = 7.71) compared to pre-intervention. N20 decreased 2CRT after PSD (pre: 411 ± 13 ms vs. post: 366 ± 20 ms; p < 0.001; d = 2.89; Δ% = 10.81) and NSN (pre: 418 ± 29 ms vs. post: 375 ± 40 ms; p < 0.001; d = 1.23; Δ% = 10.23). Similarly, 2CRT was shorter during CAF+N20 sessions after PSD (pre: 406 ± 26 ms vs. post: 357 ± 17 ms; p < 0.001; d = 2.17; Δ% = 12.02) and after NSN (pre: 386 ± 33 ms vs. post: 352 ± 30 ms; p < 0.001; d = 1.09; Δ% = 8.68). After PSD, POMS score decreased after CAF (p < 0.001; d = 2.38; Δ% = 66.97) and CAF+N20 (p < 0.001; d = 1.68; Δ% = 46.68). However, after NSN, only N20 reduced POMS (p < 0.001; d = 1.05; Δ% = 78.65) and ESS (p < 0.01; d = 0.71; Δ% = 19.11). Conclusion: After PSD, all interventions reduced sleepiness and only CAF enhanced mood with or without napping. However, only N20 enhanced mood and reduced sleepiness after NSN. Caffeine ingestion enhanced SRT performance regardless of sleep deprivation. N20, with or without caffeine ingestion, enhanced 2CRT independently of sleep deprivation. This suggests a different mode of action of napping and caffeine on sleepiness, mood and reaction time.
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Caffeine Use or Napping to Enhance Repeated Sprint Performance After Partial Sleep Deprivation: Why Not Both?
Romdhani, M, Souissi, N, Moussa-Chamari, I, Chaabouni, Y, Mahdouani, K, Sahnoun, Z, Driss, T, Chamari, K, Hammouda, O
International journal of sports physiology and performance. 2021;(5):711-718
Abstract
PURPOSE To compare the effect of a 20-minute nap opportunity (N20), a moderate dose of caffeine (CAF; 5 mg·kg-1), or a moderate dose of caffeine before N20 (CAF+N) as possible countermeasures to the decreased performance and the partial sleep deprivation-induced muscle damage. METHODS Nine male, highly trained judokas were randomly assigned to either baseline normal sleep night, placebo, N20, CAF, or CAF+N. Test sessions included the running-based anaerobic sprint test, from which the maximum (Pmax), mean (Pmean), and minimum (Pmin) powers were calculated. Biomarkers of muscle, hepatic, and cardiac damage and of enzymatic and nonenzymatic antioxidants were measured at rest and after the exercise. RESULTS N20 increased Pmax compared with placebo (P < .01, d = 0.75). CAF+N increased Pmax (P < .001, d = 1.5; d = 0.94), Pmin (P < .001, d = 2.79; d = 2.6), and Pmean (P < .001, d = 1.93; d = 1.79) compared with placebo and CAF, respectively. Postexercise creatine kinase increased whenever caffeine was added, that is, after CAF (P < .001, d = 1.19) and CAF+N (P < .001, d = 1.36). Postexercise uric acid increased whenever participants napped, that is, after N20 (P < .001, d = 2.19) and CAF+N (P < .001, d = 2.50) and decreased after CAF (P < .001, d = 2.96). CONCLUSION Napping improved repeated-sprint performance and antioxidant defense after partial sleep deprivation. Contrarily, caffeine increased muscle damage without improving performance. For sleep-deprived athletes, caffeine before a short nap opportunity would be more beneficial for repeated sprint performance than each treatment alone.