The effects of mental fatigue on sport-specific motor performance among team sport athletes: A systematic scoping review

Paraxanthine provides greater improvement in cognitive function than caffeine after performing a 10-km run

RATIONALE

Intense exercise promotes fatigue and can impair cognitive function, particularly toward the end of competition when decision-making is often critical for success. For this reason, athletes often ingest caffeinated energy drinks prior to or during exercise to help them maintain focus, reaction time, and cognitive function during competition. However, caffeine habituation and genetic sensitivity to caffeine (CA) limit efficacy. Paraxanthine (PX) is a metabolite of caffeine reported to possess nootropic properties. This study examined whether ingestion of PX with and without CA affects pre- or post-exercise cognitive function.

METHODS

12 trained runners were randomly assigned to consume in a double-blind, randomized, and crossover manner 400 mg of a placebo (PL); 200 mg of PL + 200 mg of CA; 200 mg of PL + 200 mg of PX (ENFINITY®, Ingenious Ingredients); or 200 mg PX + 200 mg of CA (PX+CA) with a 7-14-day washout between treatments. Participants donated fasting blood samples and completed pre-supplementation (PRE) side effects questionnaires, the Berg-Wisconsin Card Sorting Test (BCST), and the Psychomotor Vigilance Task Test (PVTT). Participants then ingested the assigned treatment and rested for 60 minutes, repeated tests (PRE-EX), performed a 10-km run on a treadmill at a competition pace, and then repeated tests (POST-EX). Data were analyzed using General Linear Model (GLM) univariate analyses with repeated measures and percent changes from baseline with 95% confidence intervals.

RESULTS

BCST correct responses in the PX treatment increased from PRE-EX to POST-EX (6.8% [1.5, 12.1], p = 0.012). The error rate in the PL (23.5 [-2.8, 49.8] %, p = 0.078) and CA treatment (31.5 [5.2, 57.8] %, p = 0.02) increased from PRE-EX values with POST-EX errors tending to be lower with PX treatment compared to CA (-35.7 [-72.9, 1.4] %, p = 0.059). POST-EX perseverative errors with PAR rules were significantly lower with PX treatment than with CA (-26.9 [-50.5, -3.4] %, p = 0.026). Vigilance analysis revealed a significant interaction effect in Trial #2 mean reaction time values (p = 0.049, η p 2 = 0.134, moderate to large effect) with POST-EX reaction times tending to be faster with PX and CA treatment. POST-EX mean reaction time of all trials with PX treatment was significantly faster than PL (-23.2 [-43.4, -2.4] %, p = 0.029) and PX+CA (-29.6 [-50.3, -8.80] %, p = 0.006) treatments. There was no evidence that PX ingestion adversely affected ratings of side effects associated with stimulant intake or clinical blood markers.

CONCLUSIONS

Results provide some evidence that pre-exercise PX ingestion improves prefrontal cortex function, attenuates attentional decline, mitigates cognitive fatigue, and improves reaction time and vigilance. Adding CA to PX did not provide additional benefits. Therefore, PX ingestion may serve as a nootropic alternative to CA.

Mental Fatigue in Sport-From Impaired Performance to Increased Injury Risk

The literature describing the effects of mental fatigue (MF) has grown tremendously. This is accompanied by identification of a host of performance-determining parameters affected by MF. MF results from prolonged cognitive effort and predominantly affects physical, technical, tactical, and perceptual-cognitive dimensions of sport, while physiological parameters (eg, heart rate, lactate) and physical aspects of maximal and supramaximal efforts are predominantly unaffected. The aim of this paper was to provide an overview of the parameters described in the literature as influenced by MF. By identifying the different parameters, we not only see how they affect the performance of athletes but also raise concerns about the potentially increased injury risk due to MF. Preliminary evidence suggests that subsequent disturbances in balance, motor skills, and decision-making processes could potentially increase the vulnerability to injury. An abundance of lab-based studies looked into the effects of MF on performance; however, many questions remain about the mechanisms of origin and neurophysiological causes of MF, and only small steps have been taken to translate this knowledge into practice. Thus, there is a need for more research into the underlying mechanisms of MF and the role of the brain, as well as more applied research with a high ecological validity that also takes into account the potential increased risk of injury due to MF.

Effect of mental fatigue on hand force production capacities

Mental fatigue is common in society, but its effects on force production capacities remain unclear. This study aimed to investigate the impact of mental fatigue on maximal force production, rate of force development-scaling factor (RFD-SF), and force steadiness during handgrip contractions. Fourteen participants performed two randomized sessions, during which they either carried out a cognitively demanding task (i.e., a visual attention task) or a cognitively nondemanding task (i.e., documentary watching for 62 min). The mental fatigue was evaluated subjectively and objectively (performances and electroencephalography). Maximal voluntary contraction (MVC) force, RFD-SF, and force steadiness (i.e., force coefficient of variation at submaximal intensities; 25, 50, and 75% of MVC) were recorded before and after both tasks. The feeling of mental fatigue was much higher after completing the cognitively demanding task than after documentary watching (p < .001). During the cognitively demanding task, mental fatigue was evidenced by increased errors, missed trials, and decreased N100 amplitude over time. While no effect was reported on force steadiness, both tasks induced a decrease in MVC (p = .040), a force RFD-SF lower slope (p = .011), and a reduction in the coefficient of determination (p = .011). Nevertheless, these effects were not explicitly linked to mental fatigue since they appeared both after the mentally fatiguing task and after watching the documentary. The study highlights the importance of considering cognitive engagement and mental load when optimizing motor performance to mitigate adverse effects and improve force production capacities.

The effects of mental fatigue on fine motor performance in humans and its neural network connectivity mechanism: a dart throwing study

While it is well known that mental fatigue impairs fine motor performance, the investigation into its neural basis remains scant. Here, we investigate the impact of mental fatigue on fine motor performance and explore its underlying neural network connectivity mechanisms. A total of 24 healthy male university students were recruited and randomly divided into two groups: a mental fatigue group (MF) and a control group (Control). Both groups completed 50 dart throws, while electroencephalography (EEG) data were collected. Following the Stroop intervention, participants in the MF group exhibited a decrease in Stroop task accuracy and throwing performance, and an increase in reaction time along with VAS and NASA scores. The EEG data during dart-throwing revealed that the network connectivity strength of theta oscillations in the frontal and left central regions was significantly higher in the MF group compared with the Control group, while the network connectivity strength of alpha oscillations in the left parietal region was significantly enhanced. The interregional connectivity within the theta and alpha rhythm bands, particularly in the frontal-central-parietal network connections, also showed a significant increase in the MF group. Mental fatigue impairs dart throwing performance and is accompanied by increased connectivity in alpha and theta.

Ebbing Strength, Fading Power: Unveiling the Impact of Persistent Fatigue on Muscle Performance in COVID-19 Survivors

The total number of confirmed cases of COVID-19 caused by SARS-CoV-2 virus infection is over 621 million. Post-COVID-19 syndrome, also known as long COVID or long-haul COVID, refers to a persistent condition where individuals experience symptoms and health issues after the acute phase of COVID-19. The aim of this study was to assess the strength and fatigue of skeletal muscles in people recovered from COVID-19. A total of 94 individuals took part in this cross-sectional study, with 45 participants (referred to as the Post-COVID Cohort, PCC) and 49 healthy age-matched volunteers (Healthy Control Cohort, HCC). This research article uses the direct dynamometry method to provide a detailed analysis of post-COVID survivors' strength and power characteristics. The Biodex System 4 Pro was utilized to evaluate muscle strength characteristics during the fatigue test. The fatigue work in extensors and flexors was significantly higher in the PCC. The PCC also showed significantly less power in both extensors and flexors compared to the HCC. In conclusion, this study provides compelling evidence of the impact of post-COVID-19 fatigue on muscle performance, highlighting the importance of considering these effects in the rehabilitation and care of individuals recovering from the virus. PCC achieved lower muscle strength values than HCC.

Counteracting mental fatigue for athletes: a systematic review of the interventions

The deleterious effects of mental fatigue (MF) on athletes have been carefully studied in various sports, such as soccer, badminton, and swimming. Even though many researchers have sought ways to ameliorate the negative impact of MF, there is still a lack of studies that review the interventions used to counteract MF among athletes. This review aims to report the current evidence exploring the effects of interventions on MF and sport-specific performance, including sport-specific motor performance and perceptual-cognitive skills. Web of Science, Scopus, PubMed, and SPORTDicus (EBSCOhost) were combed through to find relevant publications. Additionally, the references and Google Scholar were searched for any grey literature. For the current review, we included only randomized controlled trials that involved athletes, a primary task to induce MF, interventions to counter MF with comparable protocols, and the outcomes of sport-specific motor performance and perceptual-cognitive skill. The selection criteria resulted in the inclusion of 10 articles. The manipulations of autonomous self-control exertion, person-fit, nature exposure, mindfulness, and transactional direct current stimulation showed that positive interventions counteract MF and improve sport-specific performance in different domains, including strength, speed, skill, stamina, and perceptual-cognitive skills. The selected interventions could significantly counteract MF and improve subsequent sport-specific performance. Moreover, self-regulation and attention resources showed the importance of the potential mechanisms behind the relevant interventions.

Effects of Contextual Variables on Match Load in a Professional Soccer Team Attending to the Different Season Periods

This study aimed to analyze the effects of contextual variables (i.e., match location and match outcome) and season periods on match load (i.e., internal and external load) in professional Brazilian soccer players. Thirty-six professional players from the same soccer team participated in this study. The season was split into four phases: matches 1-16 (i.e., Phase 1 = P1); matches 17-32 (i.e., Phase 2 = P2); matches 33-48, (i.e., Phase 3 = P3); matches 49-65 (i.e., Phase 4 = P4). Considering match outcome, when the team wins, Cognitive load, Emotional load, and Affective load were significantly higher in away vs. home matches (p < 0.05). Considering season phases, in P3, Mental Fatigue was significantly higher in drawing than in losing matches (p < 0.05). Additionally, considering the match outcome, when the team lost, Total Distance (TD)/min and TD > 19 km·h-1/min were significantly lower in P1 than P2 (p < 0.001), P3 (p < 0.001), and P4 (p < 0.001). These results suggest to strength and conditioning coaches the need to consider the outcome and location of the previous game when planning the week, as well as the phase of the season they are in to reduce fatigue and injury risk.

AI-Assisted Fatigue and Stamina Control for Performance Sports on IMU-Generated Multivariate Times Series Datasets

BACKGROUND

Optimal sports performance requires a balance between intensive training and adequate rest. IMUs provide objective, quantifiable data to analyze performance dynamics, despite the challenges in quantifying athlete training loads. The ability of AI to analyze complex datasets brings innovation to the monitoring and optimization of athlete training cycles. Traditional techniques rely on subjective assessments to prevent overtraining, which can lead to injury and underperformance. IMUs provide objective, quantitative data on athletes' physical status during action. AI and machine learning can turn these data into useful insights, enabling data-driven athlete performance management. With IMU-generated multivariate time series data, this paper uses AI to construct a robust model for predicting fatigue and stamina.

MATERIALS AND METHODS

IMUs linked to 19 athletes recorded triaxial acceleration, angular velocity, and magnetic orientation throughout repeated sessions. Standardized training included steady-pace runs and fatigue-inducing techniques. The raw time series data were used to train a supervised ML model based on frequency and time-domain characteristics. The performances of Random Forest, Gradient Boosting Machines, and LSTM networks were compared. A feedback loop adjusted the model in real time based on prediction error and bias estimation.

RESULTS

The AI model demonstrated high predictive accuracy for fatigue, showing significant correlations between predicted fatigue levels and observed declines in performance. Stamina predictions enabled individualized training adjustments that were in sync with athletes' physiological thresholds. Bias correction mechanisms proved effective in minimizing systematic prediction errors. Moreover, real-time adaptations of the model led to enhanced training periodization strategies, reducing the risk of overtraining and improving overall athletic performance.

CONCLUSIONS

In sports performance analytics, the AI-assisted model using IMU multivariate time series data is effective. Training can be tailored and constantly altered because the model accurately predicts fatigue and stamina. AI models can effectively forecast the beginning of weariness before any physical symptoms appear. This allows for timely interventions to prevent overtraining and potential accidents. The model shows an exceptional ability to customize training programs according to the physiological reactions of each athlete and enhance the overall training effectiveness. In addition, the study demonstrated the model's efficacy in real-time monitoring performance, improving the decision-making abilities of both coaches and athletes. The approach enables ongoing and thorough data analysis, supporting strategic planning for training and competition, resulting in optimized performance outcomes. These findings highlight the revolutionary capability of AI in sports science, offering a future where data-driven methods greatly enhance athlete training and performance management.