The Impact of Mental Fatigue on Drop Landing Injury Risk and Lower Limb Asymmetry in Elite Collegiate American Football Players

The Impact of Mental Fatigue on Drop Landing Injury Risk and Lower Limb Asymmetry in Elite Collegiate American Football Players | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Impact of Mental Fatigue on Drop Landing Injury Risk and Lower Limb Asymmetry in Elite Collegiate American Football Players Zilong Wang, Jie Lu, Huizi Cui, Lingyue Meng, Jiawei Zheng, Wensheng Miao, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9061980/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract This study investigated the impact of mental fatigue (MF) on lower limb biomechanics and bilateral asymmetry during drop landings in elite collegiate American football players to assess injury risk implications. Twelve elite male players performed bilateral drop landings before and after a 45-minute Stroop task. Data were analyzed using a 2×2 repeated-measures ANOVA. Irrespective of MF, the dominant limb exhibited significantly smaller hip flexion, larger peak vertical ground reaction force (vGRF), and longer time to vGRF peak compared to the non-dominant limb. Following MF, knee flexion range of motion (RoM) and peak vGRF increased bilaterally, and the non-dominant limb specifically demonstrated greater knee varus/valgus RoM compared to baseline. While the symmetry index (SI) indicated baseline asymmetry, MF exerted no significant effect on global SI. We conclude that MF impairs landing mechanics through limb-specific constraints rather than systemic symmetry collapse. Because compensatory strategies preserve global SI, standard indices may mask underlying injury risks under cognitive load. Consequently, athletic screening should prioritize the sensorimotor resilience of the non-dominant limb. Health sciences/Health care Biological sciences/Neuroscience Biological sciences/Physiology Mental Fatigue American Football Players Drop landing Injury Risk Symmetry Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1 Introduction In the intensely competitive landscape of contemporary elite sports, American football stands out as a discipline demanding both high levels of physical confrontation and complex tactical execution 1 . Athletic performance in this domain relies not only on physical attributes such as explosive power and agility 2 , but is also profoundly influenced by cognitive capacities essential for rapid tactical decision-making and environmental anticipation 3 . During competitive scenarios, players are required to continuously process dynamic information under high-pressure conditions, such as recognizing defensive formations and selecting passing lanes, potentially leading to cumulative cognitive load 4 . This sustained cognitive demand may compete for finite neural resources, thereby interfering with sensorimotor integration efficiency and subsequently impacting reaction speed, decision accuracy, and tactical execution 5 . Concurrently, the intensity and complexity of the sport expose athletes to a substantial risk of musculoskeletal injury, which may be further exacerbated by cognitive load. Consequently, a comprehensive understanding of how cognitive load impacts athletic performance and injury risk is paramount for optimizing training and competitive strategies. Mental fatigue (MF), a subjective state of fatigue induced by sustained cognitive activity, is characterized by diminished attention, delayed decision-making, and heightened perception of effort 6 . Neurocognitive research indicates that mental fatigue competes for prefrontal cortical resources with motor processes, thereby disrupting sensorimotor integration efficiency 7 . This decrement in central processing capacity has been shown to delay muscle activation and alter landing strategies, subsequently elevating the risk of non-contact ACL injuries, particularly in unpredictable environments. Notably, beyond the cognitive demands inherent to competition, modern American football players also contend with multitasking challenges in daily life. The pervasive use of technology and accelerated lifestyles subject individuals to persistent multitasking and cognitive resource allocation demands. Factors such as frequent smartphone use, sleep deprivation, and concurrent task management can precipitate MF, a state characterized by limited short-term recovery capacity 8 . In prior research, various standardized MF induction protocols, including the Stroop task, n-back task, Go/No-Go task, and Flanker task, have been employed to simulate complex cognitive environments, facilitating the investigation of MF's impact on motor control 9 . MF has been demonstrated to impair decision-making and technical skill execution in team invasion sports like soccer and basketball 10 . While skill requirements differ, significant similarities exist in the demands placed on athletes in these sports and American football, particularly regarding high-intensity intermittent exercise characteristics and the imperative for sustained environmental and teammate awareness. This suggests American football players may likewise be susceptible to the detrimental effects of MF. However, the specific impact of MF on the biomechanics of high-impact drop landings and associated injury risk in this population remains inadequately elucidated. The drop landing represents a frequent technical action in American football, occurring during scenarios such as stabilizing after catching a pass or decelerating rapidly following a break. Instability in joint alignment at IC and aberrant impact loading during the landing absorption phase are directly associated with non-contact injuries, including ACL rupture and ankle sprains 11 . In practical sporting contexts, this relationship is complicated by cognitive load, particularly concerning sensorimotor integration within motor control strategies 12 . Athletes must execute technical movements under cognitive load, and MF may alter movement strategies by disrupting sensorimotor integration. Lower limb biomechanical asymmetry is a critical indicator for assessing injury risk, particularly during high-impact tasks like landing, where differences exist between the dominant and non-dominant limbs regarding load distribution, muscle activation patterns, and kinetic chain coordination 13 , 14 . From a motor control perspective, the theoretical framework proposed by Sadeghi et al. 15 posits that the dominant limb prioritizes precise movement control, while the non-dominant limb assumes greater responsibility for maintaining overall postural stability. When MF occurs, the additional cognitive load may differentially impair the brain's capacity to regulate the two limbs 16 . Both the movement control function of the dominant limb and the postural stability function of the non-dominant limb could be compromised. This interference could potentially amplify pre-existing bilateral asymmetries, leading to diminished inter-limb coordination during high-impact tasks and consequently exacerbating injury risk. Nevertheless, existing research has yet to elucidate the differential biomechanical response patterns (kinematic and kinetic) of the dominant versus non-dominant limb in American football players performing drop landings under MF. Furthermore, a detailed exploration of the dynamic changes in lower limb functional symmetry under MF conditions is lacking. Addressing this gap, the present study employed the classic Stroop task to induce MF, combined with three-dimensional motion capture and force plate technology, to investigate the impact of MF on lower limb biomechanics in the dominant and non-dominant limbs during bilateral drop landings among elite collegiate American football players. By comparing changes in joint kinematics, kinetics, and asymmetry indices pre- and post-MF, the Interaction Effect between MF and limb dominance was explored, aiming to provide a biomechanical basis for injury risk assessment under fatigue. Based on prior research, the following hypotheses were formulated: 1) MF exerts differential biomechanical effects on the dominant and non-dominant limbs of American football players; 2) MF will increase lower limb asymmetry between the dominant and non-dominant limbs during drop landing. 2 Participants and Methods 2.1 Participants Sample size estimation was performed using G*Power 3.1.9 software. Based on previous research which reported an effect size of 0.59 17 , we adopted a conservative effect size (f) of 0.4 for the current analysis. Consequently, with the power (1-β) set to 0.80 and Type I error rate (α) at 0.05, the calculation yielded a minimum required sample size of 10 participants. Ultimately, twelve male athletes were recruited from the Soochow University American football team [age: 22.2 ± 1.9 years, height: 182.1 ± 3.5 cm, body mass: 82.6 ± 6.8 kg, training experience: 4.1 ± 1.3 years]. All participants were key players from the championship team of the China Collegiate American Football League. Specifically, to ensure the ecological relevance of the cognitive load, the recruited cohort consisted exclusively of skill position players whose on-field roles heavily demand continuous cognitive-tactical processing, such as rapidly reading defensive formations and executing complex routes. Limb dominance (dominant limb vs. non-dominant limb) was determined using the ball-kicking test 18 . All assessments and screenings were conducted by an experienced experimenter. Prior to participation, all participants were fully informed about the testing procedures and provided written informed consent. The study protocol received approval from the Soochow University Ethics Committee (Ethics Approval Number: SUDA20240626H03). Inclusion criteria were as follows: 1) No history of lower limb joint, neuromuscular diseases, or injuries within the preceding six months; 2) Similar morphological characteristics and attainment of an optimal standard of physical fitness; 3) Maintenance of regular training status throughout the study period; 4) Abstention from strenuous exercise and caffeine consumption for 24 hours prior to testing; 5) Abstention from alcohol consumption for at least one week prior to testing; 6) Possession of sound psychological health, without severe psychological disorders or excessive mental stress. 2.2 Experimental Equipment 2.2.1 Vicon Infrared Three-Dimensional Motion Capture System The system comprised eight infrared cameras (Model: MX13, UK), MX Net, MX Control, a PC host, a calibration kit, and standard accessories. Data were captured at a sampling frequency of 200 Hz. The Plug-in Gait Full Body model within the Vicon system was utilized for motion capture and data acquisition. 2.2.2 Kistler Three-Dimensional Force Plates Two Kistler three-dimensional force plates (90cm x 60cm x 10cm, Model: 9281EA, Switzerland) were embedded in the floor at the center of the motion capture volume. Data were acquired at a sampling frequency of 1000 Hz. An analog-to-digital converter synchronized the Kistler force plates with the Vicon motion capture system for simultaneous data collection. 2.3 Research Design and Procedure Prior to each experimental session, participants were provided with standardized tight-fitting shorts and athletic shoes. Following a warm-up period, 27 retroreflective markers (14 mm diameter) were affixed to specific anatomical landmarks on the body surface according to the full-body model protocol. To ensure consistency and accuracy, marker placement was performed exclusively by the same experienced technician. To ensure the efficacy of the warm-up, the experiment was conducted in two phases: First, prior to MF induction, participants performed a 10-minute standardized warm-up, immediately followed by baseline drop landing task testing. Following the MF task, participants performed a standardized 2-minute low-intensity re-warm-up (consisting primarily of dynamic stretching and joint mobilization, with heart rate maintained below 110 bpm). This was designed to prevent physical injury due to muscle cooling while minimizing any potential physiological arousal that might "wash out" the mental fatigue effect. Testing was then conducted immediately. Furthermore, to minimize the potential influence of circadian rhythms on the results, testing times were scheduled between 15:00 and 19:00, a period characterized by relatively stable and high physiological arousal, as suggested by Wang et al. 19 . This scheduling aimed to ensure that subjective fatigue perceptions were primarily attributable to task load. The experimental procedure is shown in Fig. 1 . 2.4 Experimental Protocol 2.4.1 MF Protocol The task design was adapted from Badin et al. 20 and has been validated as an effective MF induction method 21 . The specific procedure was as follows: The Chinese characters for "red", "green", "blue", and "yellow" were presented sequentially in random order on a computer screen. Each character was displayed in one of the four colors (red, green, blue, yellow), with a 50% probability of incongruence between the character's meaning and its displayed color. Participants were instructed to respond via key press based solely on the font color of the character. Each character was displayed for 1000 ms, followed by a 1000 ms blank screen interval before the next character appeared. Participants completed a total of 1350 judgment responses throughout the task. To encourage performance accuracy and speed, participants were instructed to respond as quickly and accurately as possible. An auditory cue was triggered in the event of an incorrect response or a failure to respond within 1500 ms, prompting participants to refocus. The task was administered in a quiet, isolated room using E-Prime 3.0 software. Two researchers supervised the session to ensure protocol adherence and participant engagement. Since the Stroop task may interfere with participant status multidimensionally, the NASA-TLX (National Aeronautics and Space Administration Task Load Index) was used to evaluate MF status (Hart & Staveland, 1988) and accurately capture MF and derived perceptual changes. Participants completed the task while seated, without additional physical load, ensuring fatigue stemmed solely from cognitive demands. To minimize ambiguity in MF perception, clear definitions and standardized instructions were provided during the familiarization session 22 . 2.4.2 Drop Landing Test Protocol The drop landing protocol was adapted from the design previously described by Ren et al. 18 . Participants dropped from a 40-cm box, marked on the floor. Participants were instructed to land with each foot on a separate force plate, keeping their gaze fixed forward to avoid looking down. Each participant performed 5 trials, and 3 valid trials were averaged for analysis. A valid trial was defined as: feet landing completely within the boundaries of the respective force plates and maintaining balance for at least 2 seconds post-landing. 2.5 Data Collection and Analysis Visual3D software (C-Motion Inc., USA) was employed to process the raw coordinate data captured by the Vicon system for kinematic and inverse dynamic analyses. Three-dimensional coordinate data were filtered using a fourth-order low-pass Butterworth filter with a cutoff frequency of 10 Hz. Force plate data were similarly filtered using a 50 Hz cutoff frequency. Lower limb joint angles were calculated using the Cardan sequence (Euler angles). IC was defined as the instant when the vertical ground reaction force (vGRF) exceeded 10 N. The landing absorption phase was defined as the interval from IC until the vGRF reached its first peak 23 . The primary outcome measures were: Joint angles at IC for the hip, knee, and ankle joints in the sagittal and frontal planes (units: degrees (°)). Peak joint angles during the landing absorption phase for the hip, knee, and ankle joints in the sagittal and frontal planes (units: degrees (°)). Joint range of motion (RoM), defined as the difference between the IC angle and the peak angle during the absorption phase (units: degrees (°)). Peak vGRF normalized to body weight (units: BW). Time to peak vGRF (T_vGRF) (units: milliseconds (ms)). Vertical loading rate, calculated as (Peak vGRF - vGRF at IC) / T_vGRF (units: BW/ms). Symmetry index (SI)=[(Value Dominant Limb - Value Non-Dominant Limb) / (0.5 * (Value Dominant Limb + Value Non-Dominant Limb))]×100%. The SI, initially proposed by Robinson et al. 24 , quantifies bilateral differences. An SI=0 indicates perfect symmetry; SI ≤ 10% indicates relatively high symmetry; larger SI values indicate greater asymmetry. This study calculated SI for peak vGRF and loading rate. 2.6 Statistical Analysis Statistical analyses were conducted using SPSS version 27 (IBM Corp., USA). Descriptive statistics are presented as mean ± standard deviation (M ± SD). The normality of data distribution was assessed using the Shapiro-Wilk test. Homogeneity of variances was evaluated using Levene's test. Paired sample t-tests were used to analyze SI for peak vGRF and loading rate before and after MF. Kinematic and kinetic data were analyzed using a 2×2 [MF (Baseline vs. MF) × Limb (Dominant vs. Non-Dominant)] repeated-measures analysis of variance (ANOVA). Mauchly's Test of Sphericity was employed to assess the assumption of sphericity. When this assumption was violated, Greenhouse-Geisser corrections were applied to adjust the F-statistic and degrees of freedom. Post-hoc pairwise comparisons were performed using the least-significant difference (LSD) method. Statistical significance was set at α = 0.05. 3 Results 3.1 MF Intervention Effectiveness In the MF protocol, there was a significant increase in the cognitive demand ( p <0.001) and effort expenditure ( p =0.002) of the participants, thus indicating that the participants met the criteria for MF induction (Figure 2). 3.2 Hip, Knee, and Ankle Joint Angles at IC A significant main effect of limb dominance was observed for hip flexion angle at IC. The dominant limb exhibited significantly smaller hip flexion angles compared to the non-dominant limb ( p= 0.045, F =5.117, η 2 =0.317) (Figure 3). 3.3 Peak Hip, Knee, and Ankle Joint Angles During Landing Absorption Phase A significant main effect of limb dominance was observed for peak knee varus angle during the absorption phase. The dominant limb exhibited significantly smaller peak knee varus angles compared to the non-dominant limb ( p =0.046, F =5.045, η 2 =0.314) (Figure 4). 3.4 RoM During Landing Absorption Phase A significant MF×Limb interaction effect was observed for knee varus/valgus RoM ( p =0.009, F =9.996, η 2 =0.476). Simple effects analysis revealed that the non-dominant limb exhibited significantly greater knee varus/valgus RoM following MF compared to baseline ( p =0.028). Furthermore, under baseline conditions, the dominant limb exhibited significantly greater varus/valgus RoM compared to the non-dominant limb ( p =0.049). A significant main effect of MF was observed for knee flexion RoM. Both limbs exhibited significantly greater knee flexion RoM following MF compared to baseline ( p =0.049, F =4.896, η 2 =0.308) (Figure 5). 3.5 Kinetic Characteristics Significant main effects of both MF and limb dominance were observed for peak vGRF. Peak vGRF was significantly greater following MF compared to baseline ( p =0.006, F =11.415, η 2 =0.509). Furthermore, the dominant limb exhibited significantly larger peak vGRF compared to the non-dominant limb, irrespective of MF condition ( p =0.001, F =11.737, η 2 =0.630). A significant main effect of limb dominance was observed for T_vGRF, with the dominant limb exhibiting significantly longer T_vGRF compared to the non-dominant limb ( p =0.027, F =6.475, η 2 =0.371). Significant bilateral asymmetry was observed for both peak vGRF and loading rate SI, both before and after MF. However, no statistically significant differences were found in SI values between the baseline and MF conditions for either measure ( p > 0.05) (Figure 6). 4 Discussion The impact of MF on motor control stems from its dual disruption of higher-order cognitive functions and decision-making processes. The underlying neural mechanism is closely tied to the excessive depletion of central resources, affecting not only cognitive task execution but also the assessment of effort costs and the decision to continue resource investment 7 , 25 . When MF is induced through sustained cognitive load, such as the Stroop task, metabolic demands increase in the dorsolateral prefrontal cortex, leading to diminished signal transmission efficiency. This, in turn, impairs the central nervous system's capacity to allocate attentional resources effectively towards motor control 25 . Crucially, the neuromodulatory mechanism of MF is strongly linked to limitations in dopaminergic system function. Dopamine, a core neurotransmitter for motivated behavior and motor control 26 , is frequently implicated as a key substrate in MF 9 . Sustained cognitive load induces the accumulation of the neuromodulator adenosine, leading to an increased perception of effort during subsequent physical tasks 27 . Concurrently, adenosine accumulation impedes dopamine release in the anterior cingulate cortex, reducing its signaling efficiency and potentially further diminishing an individual's willingness to invest effort in a task, thereby exacerbating central resource allocation imbalances 28 . The present findings align with this theoretical framework, suggesting that MF may exert differential biomechanical effects on the dominant and non-dominant limbs, manifesting as alterations in knee joint RoM and peak vGRF parameters. Specifically, the non-dominant limb exhibited significantly greater knee varus/valgus RoM following MF compared to baseline. Furthermore, knee flexion RoM was significantly increased bilaterally following MF. These results support Hypothesis 1, confirming that MF exerts differential biomechanical effects on the dominant and non-dominant limbs. However, no significant effects of MF were observed on hip, knee, or ankle joint angles at IC or their peak angles during the absorption phase. This observation may be attributable to the specific drop landing protocol employed and the participants' elite athletic level. In actual game scenarios, American football players often execute landings amidst complex tactical decisions and rapid environmental adaptation. The standardized drop landing task utilized in this study may not have fully replicated these intricate competitive demands, potentially limiting the manifestation of MF's influence on certain joint angle parameters. Additionally, as elite athletes, the participants likely possess robust compensatory capabilities within their motor control systems, enabling them to maintain stability in key joint angles to some extent, thereby preserving performance and mitigating injury risk. This indirectly supports the conclusions of Duru et al. 29 , who reported significantly higher alpha band power in posterior brain regions among elite athletes compared to non-athletes during mental arithmetic tasks, suggesting superior neural efficiency under cognitive load for maintaining stable movement patterns. This neural efficiency appears to extend beyond motor tasks to cognitive domains, indicating a globally optimized brain function mechanism in elite athletes. While MF does not directly induce muscular fatigue, its detrimental effects on cognitive functions and decision-making can indirectly cascade to motor performance 25 . Therefore, the observed increase in knee varus/valgus RoM in the non-dominant limb post-MF may be linked to MF-induced attentional resource misallocation. Faced with the additional cognitive burden imposed by MF, athletes may prioritize attentional resources towards controlling the dominant limb, leading to relatively diminished monitoring of the non-dominant limb. This could result in the non-dominant limb exhibiting greater frontal plane knee motion variability during landing. This interpretation is supported by Tanaka et al. 30 , whose electroencephalography (EEG) study found decreased beta power density at Pz, decreased alpha power density at P3 and O2, and increased theta power density at Cz following an MF task. Furthermore, Tran et al.'s 31 systematic review corroborates that MF is associated with significantly enhanced theta wave activity in frontal, central, and posterior cortical regions, alongside increased alpha wave activity in central and posterior areas. These EEG spectral changes reflect reduced efficiency in attentional resource allocation within fronto-parietal networks, signifying that MF significantly alters central nervous system activity, particularly in regions associated with attention and cognition. In American football, players frequently perform landing and pivoting maneuvers 32 . Excessive knee varus motion during the absorption phase on the non-dominant limb may elevate the risk of injuries to the medial collateral ligament and ACL 33 . Moreover, MF may also prompt athletes to adopt altered global movement strategies to cope with the challenge of cognitive load. The bilateral increase in knee flexion RoM following MF could represent a compensatory strategy to absorb greater impact forces during landing. Larger knee flexion RoM enhances joint energy absorption capacity, reducing the direct transmission of impact forces through the lower limb and potentially lowering injury risk 34 . However, excessive flexion can also generate undue stress on posterior cruciate ligaments and menisci, which is detrimental to joint health 35 . These findings highlight the importance of monitoring athletes' movement control strategies, particularly the stability of the non-dominant limb, under cognitive load during training and competition to optimize performance and prevent injuries. The findings regarding MF's impact on lower limb asymmetry present a degree of complexity. Bilateral asymmetry (SI ≠ 0) was consistently observed for both peak vGRF and loading rate SI, both before and after MF.. However, no statistically significant differences were found in SI values between the baseline and MF conditions. This result contradicts Hypothesis 2, which posited that MF would increase asymmetry between the dominant and non-dominant limbs during drop landing. This discrepancy may indicate that MF's influence on asymmetry manifests in specific biomechanical parameters but does not reach significance in the overall SI indices calculated here. This could be attributed to the elite status of the participants. American football players at this level are required to maintain high levels of alertness and concentration during prolonged periods of training and competition to respond to rapidly changing game environments and process information efficiently 36 This sustained cognitive load makes them prone to MF, and the frequency of games and training further increases their exposure to this state 37 . Over time, this chronic exposure may enhance their tolerance to MF, and their motor nervous systems may have developed relatively stable motor control patterns and compensatory mechanisms. Consequently, even under cognitive load, overall lower limb asymmetry appeared to remain within a controlled range. This speculation aligns with findings from Russell et al. 38 and Martin et al. 39 , suggesting experienced athletes possess a greater capacity to mitigate the effects of MF. This implies that extensive competitive experience may confer efficiency in managing cognitive resources and coping with psychological pressure, enabling superior maintenance of motor performance under high-stress conditions. However, this maintenance of the global SI should not be simply attributed to insufficient task difficulty or statistical limitations of the sample. Instead, it reflects a specific "protective compensatory strategy" adopted by elite athletes to cope with mental fatigue. While performance appeared stable from a macroscopic kinetic SI, the significant increase in knee valgus excursion on the non-dominant limb reveals the biomechanical cost of this stability. This suggests that for elite athletes, the impact of mental fatigue manifests more as movement quality degradation rather than a systemic performance collapse. This finding implies that relying solely on macroscopic metrics like SI may yield "false negative" results during fatigue monitoring, this does not preclude MF from influencing lower limb functional symmetry. Indeed, MF may potentially induce long-term alterations in functional symmetry by modifying joint kinematics and kinetics. For instance, if the state of increased knee varus/valgus RoM in the non-dominant limb persists, it could gradually alter lower limb movement patterns, ultimately affecting overall performance and injury risk. This is consistent with the finding of inherent asymmetry observed in this study: irrespective of MF state, the dominant limb consistently exhibited larger peak vGRF, longer T_vGRF, and smaller hip flexion angles compared to the non-dominant limb. This pattern suggests the dominant limb likely sustains greater impact loading during landing, coupled with relatively reduced hip flexion, typically associated with diminished energy absorption capacity. This difference in shock absorption may be intrinsically linked to the functional division of labor between the limbs during movement, where the dominant limb's reduced absorption capacity likely reflects its primary role in precise movement execution, while postural stabilization tasks are predominantly assigned to the non-dominant limb. This further supports the theoretical perspective articulated by Sadeghi et al. 15 regarding limb specialization. When MF occurs, this division of labor may be disrupted, leading to the observed increase in knee varus/valgus RoM in the non-dominant limb during the absorption phase. This change could stem from differential impairment in the brain's regulatory capacity over the two limbs under cognitive load or relate to individual movement habits and compensatory strategies. Crucially, the hip, knee, and ankle joints function as interconnected components of a kinetic chain. When dysfunction arises in one joint, the body unconsciously modifies movement patterns to achieve the target action, employing compensatory strategies involving adjacent or distal joints 40 . Although no difference in peak vGRF or loading rate SI was detected between baseline and MF states in this cohort, significant local biomechanical asymmetry was present under both conditions. This persistent local kinematic aberration (particularly the instability of the non-dominant knee) under mental fatigue highlights a latent risk factor. While this acute study cannot directly quantify long-term cumulative injury rates, these biomechanical characteristics, if recurrent and uncorrected throughout a season, could potentially serve as a precursor for cumulative strain. Therefore, future research and training practices should prioritize the continuous monitoring and management of non-dominant limb control under fatigued conditions. Several limitations warrant acknowledgment: 1) The sample size was relatively small (n=12 elite collegiate American football players), potentially limiting the generalizability of the findings; 2) The drop landing task employed was relatively simple and standardized, potentially failing to fully replicate the complex cognitive and motor demands encountered during actual competition, which may have constrained the comprehensiveness of the results; 3) Longitudinal tracking of athlete performance and injury occurrence was not conducted; consequently, the long-term effects of MF and its potential contribution to cumulative injury risk require further investigation. 5 Conclusion MF significantly altered knee joint RoM and peak vGRF, with differential effects observed between the dominant and non-dominant limbs. These findings suggest MF may disrupt sensorimotor integration and motor control strategies, thereby modifying lower limb movement patterns. Furthermore, inherent biomechanical asymmetry was evident, with the dominant limb consistently exhibited larger peak vGRF, longer T_vGRF, and smaller hip flexion angles compared to the non-dominant limb, both at baseline and under MF conditions. This reflects a fundamental functional division of labor between the limbs. Although MF did not significantly worsen overall asymmetry as quantified by the SI, its specific impact on key biomechanical parameters and the potential for kinetic chain compensations suggest that MF may contribute to elevated lower limb injury risk in this population over the long term. Future research should further elucidate the mechanisms underlying MF's impact and utilize this knowledge to optimize athlete training programs, enhancing performance while mitigating injury risk. Declarations Acknowledged The author extends gratitude to all participants for their dedication and cooperation throughout this study. Special thanks are also due to the Biomechanics Laboratory at the School of Physical Education, Soochow University, for their technical support during data collection. Funding This study was funded by the National Social Science Fund Project of China (Grant No. 23BTY120). The funder had no role in the study design, data collection, analysis, interpretation of data, or writing of the manuscript. Author contribution All authors have made important contributions to the study. Authors ZLW designed the study. ZLW and JL carried out the experiment and extracted the data. ZLW and HZC involved in the data analysis. LYM and JWZ created figure and tables. WSM, JBL and XDW reviewed and edited the manuscript. All authors agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Competing interest statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Data availability The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics declarations The study protocol was approved by the Ethics Committee of Soochow University (Approval No. SUDA20240626H03). All experimental methods were carried out in accordance with relevant guidelines and regulations, including the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants prior to their participation in the study. References Alonso-Aubin, D., Rebullido, T. R., Faigenbaum, A. D., Cortell-Tormo, J. M. & Chulvi-Medrano, I. Integrative Neuromuscular Training Enhances Physical Fitness in 6- to 14-Year-Old Rugby Players. 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Symmetry and limb Dominantinance in able-bodied gait: a review. Gait posture . 12 (1), 34–45. https://doi.org/10.1016/s0966-6362(00)00070-9 (2000). McWethy, M., Norte, G. E., Bazett-Jones, D. M., Murray, A. M. & Rush, J. L. Cognitive-Motor Dual-Task Performance of the Landing Error Scoring System. J. Athl. Train. 60 (1), 21–28. https://doi.org/10.4085/1062-6050-0558.23 (2025). Mathieu, B., Robineau, J., Piscione, J. & Babault, N. Concurrent Training Programming: The Acute Effects of Sprint Interval Exercise on the Subsequent Strength Training. Sports 10 (5), 75. https://doi.org/10.3390/sports10050075 (2022). Ren, Y., Wang, C., Zhang, L. & Lu, A. The effects of visual cognitive tasks on landing stability and lower extremity injury risk in high-level soccer players. Gait posture . 92 , 230–235. https://doi.org/10.1016/j.gaitpost.2021.11.031 (2021). Wang, Z. et al. The impact of combined physical and mental fatigue on lower limb explosive power and heart rate variability in rugby players. China Sports Sci. Technol. 61 (2), 3–13. https://doi.org/10.16470/j.csst.2024120 (2025). Badin, O. O., Smith, M. R., Conte, D. & Coutts, A. J. Mental Fatigue: Impairment of Technical Performance in Small-Sided Soccer Games. Int. J. Sports Physiol. Perform. 11 (8), 1100–1105. https://doi.org/10.1123/ijspp.2015-0710 (2016). Mangin, T. et al. A plausible link between the time-on-task effect and the sequential task effect. Front. Psychol. 13 , 998393. https://doi.org/10.3389/fpsyg.2022.998393 (2022). Said, S. et al. Validation of the Raw National Aeronautics and Space Administration Task Load Index (NASA-TLX) Questionnaire to Assess Perceived Workload in Patient Monitoring Tasks: Pooled Analysis Study Using Mixed Models. J. Med. Internet. Res. 22 (9), e19472. https://doi.org/10.2196/19472 (2020). Wang, Z. et al. Effects of attentional focus strategies in drop landing biomechanics of individuals with unilateral functional ankle instability. Front. Physiol. 15 , 1444782. https://doi.org/10.3389/fphys.2024.1444782 (2024). Robinson, R. O., Herzog, W. & Nigg, B. M. Use of force platform variables to quantify the effects of chiropractic manipulation on gait symmetry. J. Manip. Physiol. Ther. 10 (4), 172–176. 10.2307/3563186 (1987). Smith, M. R., Chai, R., Nguyen, H. T., Marcora, S. M. & Coutts, A. J. Comparing the Effects of Three Cognitive Tasks on Indicators of Mental Fatigue. J. Psychol. 153 (8), 759–783. https://doi.org/10.1080/00223980.2019.1611530 (2019). Klein, M. O. et al. Dopamine: Functions, Signaling, and Association with Neurological Diseases. Cell. Mol. Neurobiol. 39 (1), 31–59. https://doi.org/10.1007/s10571-018-0632-3 (2019). Pageaux, B. & Lepers, R. The effects of mental fatigue on sport-related performance. Prog. Brain Res. 240 , 291–315. https://doi.org/10.1016/bs.pbr.2018.10.004 (2018). Martin, K. et al. Mental Fatigue Impairs Endurance Performance: A Physiological Explanation. Sports medicine (), 48 (9), 2041–2051. (2018). https://doi.org/10.1007/s40279-018-0946-9 Duru, A. D. & Assem, M. Investigating neural efficiency of elite karate athletes during a mental arithmetic task using EEG. Cogn. Neurodyn. 12 (1), 95–102. https://doi.org/10.1007/s11571-017-9464-y (2018). Tanaka, M. et al. Effect of mental fatigue on the central nervous system: an electroencephalography study. Behav. brain functions: BBF . 8 , 48. https://doi.org/10.1186/1744-9081-8-48 (2012). Tran, Y., Craig, A., Craig, R., Chai, R. & Nguyen, H. The influence of mental fatigue on brain activity: Evidence from a systematic review with meta-analyses. Psychophysiology 57 (5), e13554. https://doi.org/10.1111/psyp.13554 (2020). Widenhoefer, T. L., Miller, T. M., Weigand, M. S., Watkins, E. A. & Almonroeder, T. G. Training rugby athletes with an external attentional focus promotes more automatic adaptions in landing forces. Sports Biomech. 18 (2), 163–173. https://doi.org/10.1080/14763141.2019.1584237 (2019). Wang, H., Fleischli, J. E. & Nigel Zheng, N. Effect of lower limb Dominantinance on knee joint kinematics after anterior cruciate ligament reconstruction. Clin. Biomech. (Bristol, Avon) . 27 (2), 170–175. https://doi.org/10.1016/j.clinbiomech.2011.08.006 (2012). Laughlin, W. A. et al. The effects of single-leg landing technique on ACL loading. J. Biomech. 44 (10), 1845–1851. https://doi.org/10.1016/j.jbiomech.2011.04.010 (2011). Cengiz, B. & Karaoglu, S. Case report of concomitant avulsion fractures of the medial meniscus and posterior cruciate ligament. Medicine 100 (50), e28273. https://doi.org/10.1097/MD.0000000000028273 (2021). MacDonald, L. A. & Minahan, C. L. Indices of cognitive function measured in rugby union players using a computer-based test battery. J. Sports Sci. 34 (17), 1669–1674. https://doi.org/10.1080/02640414.2015.1132003 (2016). Abbott, W. et al. Changes in perceptions of mental fatigue during a season in professional under-23 English Premier League soccer players. Res. Sports Med. 28 (4), 529–539. https://doi.org/10.1080/15438627.2020.1784176 (2020). Russell, S., Jenkins, D., Halson, S. & Kelly, V. Changes in subjective mental and physical fatigue during netball games in elite development athletes. J. Sci. Med. sport . 23 (6), 615–620. https://doi.org/10.1016/j.jsams.2019.12.017 (2020). Martin, K. et al. Superior Inhibitory Control and Resistance to Mental Fatigue in Professional Road Cyclists. PloS one . 11 (7), e0159907. https://doi.org/10.1371/journal.pone.0159907 (2016). Stanley, L. E. et al. Ankle Dorsiflexion displacement is associated with hip and knee kinematics in females following anterior cruciate ligament reconstruction. Res. Sports Med. 27 (1), 21–33. https://doi.org/10.1080/15438627.2018.1502180 (2019). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9061980","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":614078891,"identity":"d28a1bff-9b04-4247-a945-f210c0743c54","order_by":0,"name":"Zilong Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYNCCAhs5Nvbmgw8+GNjYEanFIM2Yn+dYsuGMgrRkYrUcTpw5w8dMmOfDIcYGgoqPnz388gdQy4YbDGbMNgYHmBnYDx/dgFfLmbw0CwmDdOMNtxvSHucY3OFj4ElLu4FPi9mBHDMDAwNr2Q13Dhw3zjF4xswgwWOGX8v5N2YGCQbMjBtuJLZJWxgcZmwgqOVGjvGDAwbOijNnJLNJMxCjxf7GGzPGBkggMxv2GKQlsxHyi2R/jvHHHxWgqOz/+ODHHxs7fvbDx/BqAQI2CVQuAeUgwPyBCEWjYBSMglEwkgEAPrRPp5woZGoAAAAASUVORK5CYII=","orcid":"","institution":"Jimei University","correspondingAuthor":true,"prefix":"","firstName":"Zilong","middleName":"","lastName":"Wang","suffix":""},{"id":614078892,"identity":"73385871-cfff-42d1-b1c4-3b2e3a01b3df","order_by":1,"name":"Jie Lu","email":"","orcid":"","institution":"Jimei University","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Lu","suffix":""},{"id":614078893,"identity":"dc4a58ec-df8d-40e6-bba1-3b7564955a98","order_by":2,"name":"Huizi Cui","email":"","orcid":"","institution":"Jimei University","correspondingAuthor":false,"prefix":"","firstName":"Huizi","middleName":"","lastName":"Cui","suffix":""},{"id":614078894,"identity":"45c28af1-3ad5-4467-b11a-93d422df7efc","order_by":3,"name":"Lingyue Meng","email":"","orcid":"","institution":"Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Lingyue","middleName":"","lastName":"Meng","suffix":""},{"id":614078895,"identity":"b892404b-c79c-4b15-b293-7070b5a01eac","order_by":4,"name":"Jiawei Zheng","email":"","orcid":"","institution":"Wuhan Sports University","correspondingAuthor":false,"prefix":"","firstName":"Jiawei","middleName":"","lastName":"Zheng","suffix":""},{"id":614078896,"identity":"b2791ec5-7129-4e27-89ce-3af2f0d586b6","order_by":5,"name":"Wensheng Miao","email":"","orcid":"","institution":"China Research Center on Aging","correspondingAuthor":false,"prefix":"","firstName":"Wensheng","middleName":"","lastName":"Miao","suffix":""},{"id":614078897,"identity":"15b88fa2-a7b1-410d-943c-92239ade1bf1","order_by":6,"name":"Jinbiao Lin","email":"","orcid":"","institution":"Jimei University","correspondingAuthor":false,"prefix":"","firstName":"Jinbiao","middleName":"","lastName":"Lin","suffix":""},{"id":614078898,"identity":"171caf82-e373-4be2-8731-f1df6a94028b","order_by":7,"name":"Xiangdong Wang","email":"","orcid":"","institution":"Jimei University","correspondingAuthor":false,"prefix":"","firstName":"Xiangdong","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-03-08 04:53:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9061980/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9061980/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105759307,"identity":"ac7d734d-2549-4a48-86f4-480047e372d1","added_by":"auto","created_at":"2026-03-30 17:36:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":426510,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental Flowchart\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9061980/v1/43b94c3b35ba6fda4834270d.png"},{"id":105759308,"identity":"d208ccbd-7776-47c2-87f7-c02e17533768","added_by":"auto","created_at":"2026-03-30 17:36:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":106958,"visible":true,"origin":"","legend":"\u003cp\u003eNASA-TLX Scores Before and After MF Induction.\u003c/p\u003e\n\u003cp\u003eNote: *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, The same applies below.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9061980/v1/4b2b2e25aa3bff77e89eb97e.png"},{"id":105759309,"identity":"9bebb5b3-3071-42c2-9ade-c8e9abdf8cdf","added_by":"auto","created_at":"2026-03-30 17:36:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":105287,"visible":true,"origin":"","legend":"\u003cp\u003eHip, Knee, and Ankle Joint Angles at IC\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9061980/v1/87d1c44635a392408c8c69d1.png"},{"id":105759312,"identity":"4c5c4189-7a4e-4301-b24b-10571870c764","added_by":"auto","created_at":"2026-03-30 17:36:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":104692,"visible":true,"origin":"","legend":"\u003cp\u003ePeak Hip, Knee, and Ankle Joint Angles During the Landing Absorption Phase.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9061980/v1/c3090ef3d926ff1e0a66bc0e.png"},{"id":105759310,"identity":"f682d6e0-55fc-496f-837f-349f076fee83","added_by":"auto","created_at":"2026-03-30 17:36:04","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":114397,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in Hip, Knee, and Ankle Joint RoM During the Landing Absorption Phase.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9061980/v1/7fd51db6e4f3adac1981f14f.png"},{"id":105759311,"identity":"4a053b81-29ef-417d-a22d-820733118b5c","added_by":"auto","created_at":"2026-03-30 17:36:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":71730,"visible":true,"origin":"","legend":"\u003cp\u003eKinetic Characteristics.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9061980/v1/dc0d6c084eb8a55fb5b45f39.png"},{"id":105904278,"identity":"868ae8c8-1ce2-4896-be01-02af990ec872","added_by":"auto","created_at":"2026-04-01 10:07:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1516717,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9061980/v1/6048c267-705f-4e59-9699-c71196e0bc90.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Mental Fatigue on Drop Landing Injury Risk and Lower Limb Asymmetry in Elite Collegiate American Football Players","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eIn the intensely competitive landscape of contemporary elite sports, American football stands out as a discipline demanding both high levels of physical confrontation and complex tactical execution\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Athletic performance in this domain relies not only on physical attributes such as explosive power and agility\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, but is also profoundly influenced by cognitive capacities essential for rapid tactical decision-making and environmental anticipation\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. During competitive scenarios, players are required to continuously process dynamic information under high-pressure conditions, such as recognizing defensive formations and selecting passing lanes, potentially leading to cumulative cognitive load\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. This sustained cognitive demand may compete for finite neural resources, thereby interfering with sensorimotor integration efficiency and subsequently impacting reaction speed, decision accuracy, and tactical execution\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Concurrently, the intensity and complexity of the sport expose athletes to a substantial risk of musculoskeletal injury, which may be further exacerbated by cognitive load. Consequently, a comprehensive understanding of how cognitive load impacts athletic performance and injury risk is paramount for optimizing training and competitive strategies.\u003c/p\u003e \u003cp\u003eMental fatigue (MF), a subjective state of fatigue induced by sustained cognitive activity, is characterized by diminished attention, delayed decision-making, and heightened perception of effort\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Neurocognitive research indicates that mental fatigue competes for prefrontal cortical resources with motor processes, thereby disrupting sensorimotor integration efficiency\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. This decrement in central processing capacity has been shown to delay muscle activation and alter landing strategies, subsequently elevating the risk of non-contact ACL injuries, particularly in unpredictable environments. Notably, beyond the cognitive demands inherent to competition, modern American football players also contend with multitasking challenges in daily life. The pervasive use of technology and accelerated lifestyles subject individuals to persistent multitasking and cognitive resource allocation demands. Factors such as frequent smartphone use, sleep deprivation, and concurrent task management can precipitate MF, a state characterized by limited short-term recovery capacity\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In prior research, various standardized MF induction protocols, including the Stroop task, n-back task, Go/No-Go task, and Flanker task, have been employed to simulate complex cognitive environments, facilitating the investigation of MF's impact on motor control\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. MF has been demonstrated to impair decision-making and technical skill execution in team invasion sports like soccer and basketball\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. While skill requirements differ, significant similarities exist in the demands placed on athletes in these sports and American football, particularly regarding high-intensity intermittent exercise characteristics and the imperative for sustained environmental and teammate awareness. This suggests American football players may likewise be susceptible to the detrimental effects of MF. However, the specific impact of MF on the biomechanics of high-impact drop landings and associated injury risk in this population remains inadequately elucidated.\u003c/p\u003e \u003cp\u003eThe drop landing represents a frequent technical action in American football, occurring during scenarios such as stabilizing after catching a pass or decelerating rapidly following a break. Instability in joint alignment at IC and aberrant impact loading during the landing absorption phase are directly associated with non-contact injuries, including ACL rupture and ankle sprains\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In practical sporting contexts, this relationship is complicated by cognitive load, particularly concerning sensorimotor integration within motor control strategies\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Athletes must execute technical movements under cognitive load, and MF may alter movement strategies by disrupting sensorimotor integration. Lower limb biomechanical asymmetry is a critical indicator for assessing injury risk, particularly during high-impact tasks like landing, where differences exist between the dominant and non-dominant limbs regarding load distribution, muscle activation patterns, and kinetic chain coordination\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. From a motor control perspective, the theoretical framework proposed by Sadeghi et al.\u003csup\u003e15\u003c/sup\u003e posits that the dominant limb prioritizes precise movement control, while the non-dominant limb assumes greater responsibility for maintaining overall postural stability. When MF occurs, the additional cognitive load may differentially impair the brain's capacity to regulate the two limbs\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Both the movement control function of the dominant limb and the postural stability function of the non-dominant limb could be compromised. This interference could potentially amplify pre-existing bilateral asymmetries, leading to diminished inter-limb coordination during high-impact tasks and consequently exacerbating injury risk. Nevertheless, existing research has yet to elucidate the differential biomechanical response patterns (kinematic and kinetic) of the dominant versus non-dominant limb in American football players performing drop landings under MF. Furthermore, a detailed exploration of the dynamic changes in lower limb functional symmetry under MF conditions is lacking.\u003c/p\u003e \u003cp\u003eAddressing this gap, the present study employed the classic Stroop task to induce MF, combined with three-dimensional motion capture and force plate technology, to investigate the impact of MF on lower limb biomechanics in the dominant and non-dominant limbs during bilateral drop landings among elite collegiate American football players. By comparing changes in joint kinematics, kinetics, and asymmetry indices pre- and post-MF, the Interaction Effect between MF and limb dominance was explored, aiming to provide a biomechanical basis for injury risk assessment under fatigue. Based on prior research, the following hypotheses were formulated: 1) MF exerts differential biomechanical effects on the dominant and non-dominant limbs of American football players; 2) MF will increase lower limb asymmetry between the dominant and non-dominant limbs during drop landing.\u003c/p\u003e"},{"header":"2 Participants and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Participants\u003c/h2\u003e \u003cp\u003eSample size estimation was performed using G*Power 3.1.9 software. Based on previous research which reported an effect size of 0.59\u003csup\u003e17\u003c/sup\u003e, we adopted a conservative effect size (f) of 0.4 for the current analysis. Consequently, with the power (1-β) set to 0.80 and Type I error rate (α) at 0.05, the calculation yielded a minimum required sample size of 10 participants. Ultimately, twelve male athletes were recruited from the Soochow University American football team [age: 22.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 years, height: 182.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5 cm, body mass: 82.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8 kg, training experience: 4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 years]. All participants were key players from the championship team of the China Collegiate American Football League. Specifically, to ensure the ecological relevance of the cognitive load, the recruited cohort consisted exclusively of skill position players whose on-field roles heavily demand continuous cognitive-tactical processing, such as rapidly reading defensive formations and executing complex routes. Limb dominance (dominant limb vs. non-dominant limb) was determined using the ball-kicking test\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. All assessments and screenings were conducted by an experienced experimenter. Prior to participation, all participants were fully informed about the testing procedures and provided written informed consent. The study protocol received approval from the Soochow University Ethics Committee (Ethics Approval Number: SUDA20240626H03).\u003c/p\u003e \u003cp\u003eInclusion criteria were as follows: 1) No history of lower limb joint, neuromuscular diseases, or injuries within the preceding six months; 2) Similar morphological characteristics and attainment of an optimal standard of physical fitness; 3) Maintenance of regular training status throughout the study period; 4) Abstention from strenuous exercise and caffeine consumption for 24 hours prior to testing; 5) Abstention from alcohol consumption for at least one week prior to testing; 6) Possession of sound psychological health, without severe psychological disorders or excessive mental stress.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Experimental Equipment\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Vicon Infrared Three-Dimensional Motion Capture System\u003c/h2\u003e \u003cp\u003eThe system comprised eight infrared cameras (Model: MX13, UK), MX Net, MX Control, a PC host, a calibration kit, and standard accessories. Data were captured at a sampling frequency of 200 Hz. The Plug-in Gait Full Body model within the Vicon system was utilized for motion capture and data acquisition.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Kistler Three-Dimensional Force Plates\u003c/h2\u003e \u003cp\u003eTwo Kistler three-dimensional force plates (90cm x 60cm x 10cm, Model: 9281EA, Switzerland) were embedded in the floor at the center of the motion capture volume. Data were acquired at a sampling frequency of 1000 Hz. An analog-to-digital converter synchronized the Kistler force plates with the Vicon motion capture system for simultaneous data collection.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Research Design and Procedure\u003c/h2\u003e \u003cp\u003ePrior to each experimental session, participants were provided with standardized tight-fitting shorts and athletic shoes. Following a warm-up period, 27 retroreflective markers (14 mm diameter) were affixed to specific anatomical landmarks on the body surface according to the full-body model protocol. To ensure consistency and accuracy, marker placement was performed exclusively by the same experienced technician.\u003c/p\u003e \u003cp\u003eTo ensure the efficacy of the warm-up, the experiment was conducted in two phases: First, prior to MF induction, participants performed a 10-minute standardized warm-up, immediately followed by baseline drop landing task testing. Following the MF task, participants performed a standardized 2-minute low-intensity re-warm-up (consisting primarily of dynamic stretching and joint mobilization, with heart rate maintained below 110 bpm). This was designed to prevent physical injury due to muscle cooling while minimizing any potential physiological arousal that might \"wash out\" the mental fatigue effect. Testing was then conducted immediately. Furthermore, to minimize the potential influence of circadian rhythms on the results, testing times were scheduled between 15:00 and 19:00, a period characterized by relatively stable and high physiological arousal, as suggested by Wang et al.\u003csup\u003e19\u003c/sup\u003e. This scheduling aimed to ensure that subjective fatigue perceptions were primarily attributable to task load. The experimental procedure is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Experimental Protocol\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1 MF Protocol\u003c/h2\u003e \u003cp\u003eThe task design was adapted from Badin et al.\u003csup\u003e20\u003c/sup\u003e and has been validated as an effective MF induction method\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The specific procedure was as follows: The Chinese characters for \"red\", \"green\", \"blue\", and \"yellow\" were presented sequentially in random order on a computer screen. Each character was displayed in one of the four colors (red, green, blue, yellow), with a 50% probability of incongruence between the character's meaning and its displayed color. Participants were instructed to respond via key press based solely on the font color of the character. Each character was displayed for 1000 ms, followed by a 1000 ms blank screen interval before the next character appeared. Participants completed a total of 1350 judgment responses throughout the task. To encourage performance accuracy and speed, participants were instructed to respond as quickly and accurately as possible. An auditory cue was triggered in the event of an incorrect response or a failure to respond within 1500 ms, prompting participants to refocus. The task was administered in a quiet, isolated room using E-Prime 3.0 software. Two researchers supervised the session to ensure protocol adherence and participant engagement. Since the Stroop task may interfere with participant status multidimensionally, the NASA-TLX (National Aeronautics and Space Administration Task Load Index) was used to evaluate MF status (Hart \u0026amp; Staveland, 1988) and accurately capture MF and derived perceptual changes. Participants completed the task while seated, without additional physical load, ensuring fatigue stemmed solely from cognitive demands. To minimize ambiguity in MF perception, clear definitions and standardized instructions were provided during the familiarization session\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2 Drop Landing Test Protocol\u003c/h2\u003e \u003cp\u003eThe drop landing protocol was adapted from the design previously described by Ren et al.\u003csup\u003e18\u003c/sup\u003e. Participants dropped from a 40-cm box, marked on the floor. Participants were instructed to land with each foot on a separate force plate, keeping their gaze fixed forward to avoid looking down. Each participant performed 5 trials, and 3 valid trials were averaged for analysis. A valid trial was defined as: feet landing completely within the boundaries of the respective force plates and maintaining balance for at least 2 seconds post-landing.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data Collection and Analysis\u003c/h2\u003e \u003cp\u003eVisual3D software (C-Motion Inc., USA) was employed to process the raw coordinate data captured by the Vicon system for kinematic and inverse dynamic analyses. Three-dimensional coordinate data were filtered using a fourth-order low-pass Butterworth filter with a cutoff frequency of 10 Hz. Force plate data were similarly filtered using a 50 Hz cutoff frequency. Lower limb joint angles were calculated using the Cardan sequence (Euler angles). IC was defined as the instant when the vertical ground reaction force (vGRF) exceeded 10 N. The landing absorption phase was defined as the interval from IC until the vGRF reached its first peak\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe primary outcome measures were:\u003c/p\u003e\n\u003col class=\"decimal_type\"\u003e\n \u003cli\u003eJoint angles at IC for the hip, knee, and ankle joints in the sagittal and frontal planes (units: degrees (\u0026deg;)).\u003c/li\u003e\n \u003cli\u003ePeak joint angles during the landing absorption phase for the hip, knee, and ankle joints in the sagittal and frontal planes (units: degrees (\u0026deg;)).\u003c/li\u003e\n \u003cli\u003eJoint range of motion (RoM), defined as the difference between the IC angle and the peak angle during the absorption phase (units: degrees (\u0026deg;)).\u003c/li\u003e\n \u003cli\u003ePeak vGRF normalized to body weight (units: BW).\u003c/li\u003e\n \u003cli\u003eTime to peak vGRF (T_vGRF) (units: milliseconds (ms)).\u003c/li\u003e\n \u003cli\u003eVertical loading rate, calculated as (Peak vGRF - vGRF at IC) / T_vGRF (units: BW/ms).\u003c/li\u003e\n \u003cli\u003eSymmetry index (SI)=[(Value Dominant Limb - Value Non-Dominant Limb) / (0.5 * (Value Dominant Limb + Value Non-Dominant Limb))]\u0026times;100%. The SI, initially proposed by Robinson et al.\u003csup\u003e24\u003c/sup\u003e, quantifies bilateral differences. An SI=0 indicates perfect symmetry; SI \u0026le; 10% indicates relatively high symmetry; larger SI values indicate greater asymmetry. This study calculated SI for peak vGRF and loading rate.\u003c/li\u003e\n\u003c/ol\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical Analysis\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eStatistical analyses were conducted using SPSS version 27 (IBM Corp., USA). Descriptive statistics are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). The normality of data distribution was assessed using the Shapiro-Wilk test. Homogeneity of variances was evaluated using Levene's test. Paired sample t-tests were used to analyze SI for peak vGRF and loading rate before and after MF. Kinematic and kinetic data were analyzed using a 2\u0026times;2 [MF (Baseline vs. MF) \u0026times; Limb (Dominant vs. Non-Dominant)] repeated-measures analysis of variance (ANOVA). Mauchly's Test of Sphericity was employed to assess the assumption of sphericity. When this assumption was violated, Greenhouse-Geisser corrections were applied to adjust the F-statistic and degrees of freedom. Post-hoc pairwise comparisons were performed using the least-significant difference (LSD) method. Statistical significance was set at α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 MF Intervention Effectiveness\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the MF protocol, there was a significant increase in the cognitive demand (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001) and effort expenditure (\u003cem\u003ep\u003c/em\u003e=0.002) of the participants, thus indicating that the participants met the criteria for MF induction (Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Hip, Knee, and Ankle Joint Angles at IC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA significant main effect of limb dominance was observed for hip flexion angle at IC. The dominant limb exhibited significantly smaller hip flexion angles compared to the non-dominant limb (\u003cem\u003ep=\u003c/em\u003e0.045, \u003cem\u003eF\u003c/em\u003e=5.117,\u0026nbsp;\u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=0.317) (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Peak Hip, Knee, and Ankle Joint Angles During Landing Absorption Phase\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA significant main effect of limb dominance was observed for peak knee varus angle during the absorption phase. The dominant limb exhibited significantly smaller peak knee varus angles compared to the non-dominant limb (\u003cem\u003ep\u003c/em\u003e=0.046, \u003cem\u003eF\u003c/em\u003e=5.045,\u0026nbsp;\u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=0.314) (Figure 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 RoM During Landing Absorption Phase\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA significant MF\u0026times;Limb interaction effect was observed for knee varus/valgus RoM (\u003cem\u003ep\u003c/em\u003e=0.009, \u003cem\u003eF\u003c/em\u003e=9.996,\u0026nbsp;\u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=0.476). Simple effects analysis revealed that the non-dominant limb exhibited significantly greater knee varus/valgus RoM following MF compared to baseline (\u003cem\u003ep\u003c/em\u003e=0.028). Furthermore, under baseline conditions, the dominant limb exhibited significantly greater varus/valgus RoM compared to the non-dominant limb (\u003cem\u003ep\u003c/em\u003e=0.049). A significant main effect of MF was observed for knee flexion RoM. Both limbs exhibited significantly greater knee flexion RoM following MF compared to baseline (\u003cem\u003ep\u003c/em\u003e=0.049, \u003cem\u003eF\u003c/em\u003e=4.896,\u0026nbsp;\u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=0.308) (Figure 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Kinetic Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSignificant main effects of both MF and limb dominance were observed for peak vGRF. Peak vGRF was significantly greater following MF compared to baseline (\u003cem\u003ep\u003c/em\u003e=0.006, \u003cem\u003eF\u003c/em\u003e=11.415,\u0026nbsp;\u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=0.509). Furthermore, the dominant limb exhibited significantly larger peak vGRF compared to the non-dominant limb, irrespective of MF condition (\u003cem\u003ep\u003c/em\u003e=0.001, \u003cem\u003eF\u003c/em\u003e=11.737,\u0026nbsp;\u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=0.630). A significant main effect of limb dominance was observed for T_vGRF, with the dominant limb exhibiting significantly longer T_vGRF compared to the non-dominant limb (\u003cem\u003ep\u003c/em\u003e=0.027, \u003cem\u003eF\u003c/em\u003e=6.475,\u0026nbsp;\u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=0.371).\u003c/p\u003e\n\u003cp\u003eSignificant bilateral asymmetry was observed for both peak vGRF and loading rate SI, both before and after MF. However, no statistically significant differences were found in SI values between the baseline and MF conditions for either measure (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05) (Figure 6).\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe impact of MF on motor control stems from its dual disruption of higher-order cognitive functions and decision-making processes. The underlying neural mechanism is closely tied to the excessive depletion of central resources, affecting not only cognitive task execution but also the assessment of effort costs and the decision to continue resource investment\u003csup\u003e7\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e25\u003c/sup\u003e. \u0026nbsp;When MF is induced through sustained cognitive load, such as the Stroop task, metabolic demands increase in the dorsolateral prefrontal cortex, leading to diminished signal transmission efficiency. This, in turn, impairs the central nervous system\u0026apos;s capacity to allocate attentional resources effectively towards motor control\u003csup\u003e25\u003c/sup\u003e. Crucially, the neuromodulatory mechanism of MF is strongly linked to limitations in dopaminergic system function. Dopamine, a core neurotransmitter for motivated behavior and motor control\u003csup\u003e26\u003c/sup\u003e, is frequently implicated as a key substrate in MF\u003csup\u003e9\u003c/sup\u003e. Sustained cognitive load induces the accumulation of the neuromodulator adenosine, leading to an increased perception of effort during subsequent physical tasks\u003csup\u003e27\u003c/sup\u003e. Concurrently, adenosine accumulation impedes dopamine release in the anterior cingulate cortex, reducing its signaling efficiency and potentially further diminishing an individual\u0026apos;s willingness to invest effort in a task, thereby exacerbating central resource allocation imbalances\u003csup\u003e28\u003c/sup\u003e. The present findings align with this theoretical framework, suggesting that MF may exert differential biomechanical effects on the dominant and non-dominant limbs, manifesting as alterations in knee joint RoM and peak vGRF parameters. Specifically, the non-dominant limb exhibited significantly greater knee varus/valgus RoM following MF compared to baseline. Furthermore, knee flexion RoM was significantly increased bilaterally following MF. These results support Hypothesis 1, confirming that MF exerts differential biomechanical effects on the dominant and non-dominant limbs. However, no significant effects of MF were observed on hip, knee, or ankle joint angles at IC or their peak angles during the absorption phase. This observation may be attributable to the specific drop landing protocol employed and the participants\u0026apos; elite athletic level. In actual game scenarios, American football players often execute landings amidst complex tactical decisions and rapid environmental adaptation. The standardized drop landing task utilized in this study may not have fully replicated these intricate competitive demands, potentially limiting the manifestation of MF\u0026apos;s influence on certain joint angle parameters. Additionally, as elite athletes, the participants likely possess robust compensatory capabilities within their motor control systems, enabling them to maintain stability in key joint angles to some extent, thereby preserving performance and mitigating injury risk. This indirectly supports the conclusions of Duru et al.\u003csup\u003e29\u003c/sup\u003e, who reported significantly higher alpha band power in posterior brain regions among elite athletes compared to non-athletes during mental arithmetic tasks, suggesting superior neural efficiency under cognitive load for maintaining stable movement patterns. This neural efficiency appears to extend beyond motor tasks to cognitive domains, indicating a globally optimized brain function mechanism in elite athletes.\u003c/p\u003e\n\u003cp\u003eWhile MF does not directly induce muscular fatigue, its detrimental effects on cognitive functions and decision-making can indirectly cascade to motor performance\u003csup\u003e25\u003c/sup\u003e. Therefore, the observed increase in knee varus/valgus RoM in the non-dominant limb post-MF may be linked to MF-induced attentional resource misallocation. Faced with the additional cognitive burden imposed by MF, athletes may prioritize attentional resources towards controlling the dominant limb, leading to relatively diminished monitoring of the non-dominant limb. This could result in the non-dominant limb exhibiting greater frontal plane knee motion variability during landing. This interpretation is supported by Tanaka et al.\u003csup\u003e30\u003c/sup\u003e, whose electroencephalography (EEG) study found decreased beta power density at Pz, decreased alpha power density at P3 and O2, and increased theta power density at Cz following an MF task. Furthermore, Tran et al.\u0026apos;s\u003csup\u003e31\u003c/sup\u003e systematic review corroborates that MF is associated with significantly enhanced theta wave activity in frontal, central, and posterior cortical regions, alongside increased alpha wave activity in central and posterior areas. These EEG spectral changes reflect reduced efficiency in attentional resource allocation within fronto-parietal networks, signifying that MF significantly alters central nervous system activity, particularly in regions associated with attention and cognition. In American football, players frequently perform landing and pivoting maneuvers\u003csup\u003e32\u003c/sup\u003e. Excessive knee varus motion during the absorption phase on the non-dominant limb may elevate the risk of injuries to the medial collateral ligament and ACL\u003csup\u003e33\u003c/sup\u003e. Moreover, MF may also prompt athletes to adopt altered global movement strategies to cope with the challenge of cognitive load. The bilateral increase in knee flexion RoM following MF could represent a compensatory strategy to absorb greater impact forces during landing. Larger knee flexion RoM enhances joint energy absorption capacity, reducing the direct transmission of impact forces through the lower limb and potentially lowering injury risk\u003csup\u003e34\u003c/sup\u003e. However, excessive flexion can also generate undue stress on posterior cruciate ligaments and menisci, which is detrimental to joint health\u003csup\u003e35\u003c/sup\u003e. These findings highlight the importance of monitoring athletes\u0026apos; movement control strategies, particularly the stability of the non-dominant limb, under cognitive load during training and competition to optimize performance and prevent injuries.\u003c/p\u003e\n\u003cp\u003eThe findings regarding MF\u0026apos;s impact on lower limb asymmetry present a degree of complexity. Bilateral asymmetry (SI \u0026ne; 0) was consistently observed for both peak vGRF and loading rate SI, both before and after MF.. However, no statistically significant differences were found in SI values between the baseline and MF conditions. This result contradicts Hypothesis 2, which posited that MF would increase asymmetry between the dominant and non-dominant limbs during drop landing. This discrepancy may indicate that MF\u0026apos;s influence on asymmetry manifests in specific biomechanical parameters but does not reach significance in the overall SI indices calculated here. This could be attributed to the elite status of the participants. American football players at this level are required to maintain high levels of alertness and concentration during prolonged periods of training and competition to respond to rapidly changing game environments and process information efficiently\u003csup\u003e36\u003c/sup\u003e This sustained cognitive load makes them prone to MF, and the frequency of games and training further increases their exposure to this state\u003csup\u003e37\u003c/sup\u003e. Over time, this chronic exposure may enhance their tolerance to MF, and their motor nervous systems may have developed relatively stable motor control patterns and compensatory mechanisms. Consequently, even under cognitive load, overall lower limb asymmetry appeared to remain within a controlled range. This speculation aligns with findings from Russell et al.\u003csup\u003e38\u003c/sup\u003e and Martin et al.\u003csup\u003e39\u003c/sup\u003e, suggesting experienced athletes possess a greater capacity to mitigate the effects of MF. This implies that extensive competitive experience may confer efficiency in managing cognitive resources and coping with psychological pressure, enabling superior maintenance of motor performance under high-stress conditions. However, this maintenance of the global SI should not be simply attributed to insufficient task difficulty or statistical limitations of the sample. Instead, it reflects a specific \u0026quot;protective compensatory strategy\u0026quot; adopted by elite athletes to cope with mental fatigue. While performance appeared stable from a macroscopic kinetic SI, the significant increase in knee valgus excursion on the non-dominant limb reveals the biomechanical cost of this stability. This suggests that for elite athletes, the impact of mental fatigue manifests more as movement quality degradation rather than a systemic performance collapse. This finding implies that relying solely on macroscopic metrics like SI may yield \u0026quot;false negative\u0026quot; results during fatigue monitoring, this does not preclude MF from influencing lower limb functional symmetry. Indeed, MF may potentially induce long-term alterations in functional symmetry by modifying joint kinematics and kinetics. For instance, if the state of increased knee varus/valgus RoM in the non-dominant limb persists, it could gradually alter lower limb movement patterns, ultimately affecting overall performance and injury risk. This is consistent with the finding of inherent asymmetry observed in this study: irrespective of MF state, the dominant limb consistently exhibited larger peak vGRF, longer T_vGRF, and smaller hip flexion angles compared to the non-dominant limb. This pattern suggests the dominant limb likely sustains greater impact loading during landing, coupled with relatively reduced hip flexion, typically associated with diminished energy absorption capacity. This difference in shock absorption may be intrinsically linked to the functional division of labor between the limbs during movement, where the dominant limb\u0026apos;s reduced absorption capacity likely reflects its primary role in precise movement execution, while postural stabilization tasks are predominantly assigned to the non-dominant limb. This further supports the theoretical perspective articulated by Sadeghi et al.\u003csup\u003e15\u003c/sup\u003e regarding limb specialization. When MF occurs, this division of labor may be disrupted, leading to the observed increase in knee varus/valgus RoM in the non-dominant limb during the absorption phase. This change could stem from differential impairment in the brain\u0026apos;s regulatory capacity over the two limbs under cognitive load or relate to individual movement habits and compensatory strategies. Crucially, the hip, knee, and ankle joints function as interconnected components of a kinetic chain. When dysfunction arises in one joint, the body unconsciously modifies movement patterns to achieve the target action, employing compensatory strategies involving adjacent or distal joints\u003csup\u003e40\u003c/sup\u003e. Although no difference in peak vGRF or loading rate SI was detected between baseline and MF states in this cohort, significant local biomechanical asymmetry was present under both conditions. This persistent local kinematic aberration (particularly the instability of the non-dominant knee) under mental fatigue highlights a latent risk factor. While this acute study cannot directly quantify long-term cumulative injury rates, these biomechanical characteristics, if recurrent and uncorrected throughout a season, could potentially serve as a precursor for cumulative strain. Therefore, future research and training practices should prioritize the continuous monitoring and management of non-dominant limb control under fatigued conditions.\u003c/p\u003e\n\u003cp\u003eSeveral limitations warrant acknowledgment: 1) The sample size was relatively small (n=12 elite collegiate American football players), potentially limiting the generalizability of the findings; 2) The drop landing task employed was relatively simple and standardized, potentially failing to fully replicate the complex cognitive and motor demands encountered during actual competition, which may have constrained the comprehensiveness of the results; 3) Longitudinal tracking of athlete performance and injury occurrence was not conducted; consequently, the long-term effects of MF and its potential contribution to cumulative injury risk require further investigation.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eMF significantly altered knee joint RoM and peak vGRF, with differential effects observed between the dominant and non-dominant limbs. These findings suggest MF may disrupt sensorimotor integration and motor control strategies, thereby modifying lower limb movement patterns. Furthermore, inherent biomechanical asymmetry was evident, with the dominant limb consistently exhibited larger peak vGRF, longer T_vGRF, and smaller hip flexion angles compared to the non-dominant limb, both at baseline and under MF conditions. This reflects a fundamental functional division of labor between the limbs. Although MF did not significantly worsen overall asymmetry as quantified by the SI, its specific impact on key biomechanical parameters and the potential for kinetic chain compensations suggest that MF may contribute to elevated lower limb injury risk in this population over the long term. Future research should further elucidate the mechanisms underlying MF's impact and utilize this knowledge to optimize athlete training programs, enhancing performance while mitigating injury risk.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledged\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author extends gratitude to all participants for their dedication and cooperation throughout this study. Special thanks are also due to the Biomechanics Laboratory at the School of Physical Education, Soochow University, for their technical support during data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the National Social Science Fund Project of China (Grant No. 23BTY120). The funder had no role in the study design, data collection, analysis, interpretation of data, or writing of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have made important contributions to the study. Authors ZLW designed the study. ZLW and JL carried out the experiment and extracted the data. ZLW and HZC involved in the data analysis. LYM and JWZ created figure and tables. WSM, JBL and XDW reviewed and edited the manuscript. All authors agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Ethics Committee of Soochow University (Approval No. SUDA20240626H03). All experimental methods were carried out in accordance with relevant guidelines and regulations, including the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants prior to their participation in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlonso-Aubin, D., Rebullido, T. R., Faigenbaum, A. D., Cortell-Tormo, J. M. \u0026amp; Chulvi-Medrano, I. 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Ankle Dorsiflexion displacement is associated with hip and knee kinematics in females following anterior cruciate ligament reconstruction. \u003cem\u003eRes. Sports Med.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e (1), 21\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/15438627.2018.1502180\u003c/span\u003e\u003cspan address=\"10.1080/15438627.2018.1502180\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mental Fatigue, American Football Players, Drop landing, Injury Risk, Symmetry","lastPublishedDoi":"10.21203/rs.3.rs-9061980/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9061980/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigated the impact of mental fatigue (MF) on lower limb biomechanics and bilateral asymmetry during drop landings in elite collegiate American football players to assess injury risk implications. Twelve elite male players performed bilateral drop landings before and after a 45-minute Stroop task. Data were analyzed using a 2\u0026times;2 repeated-measures ANOVA. Irrespective of MF, the dominant limb exhibited significantly smaller hip flexion, larger peak vertical ground reaction force (vGRF), and longer time to vGRF peak compared to the non-dominant limb. Following MF, knee flexion range of motion (RoM) and peak vGRF increased bilaterally, and the non-dominant limb specifically demonstrated greater knee varus/valgus RoM compared to baseline. While the symmetry index (SI) indicated baseline asymmetry, MF exerted no significant effect on global SI. We conclude that MF impairs landing mechanics through limb-specific constraints rather than systemic symmetry collapse. Because compensatory strategies preserve global SI, standard indices may mask underlying injury risks under cognitive load. Consequently, athletic screening should prioritize the sensorimotor resilience of the non-dominant limb.\u003c/p\u003e","manuscriptTitle":"The Impact of Mental Fatigue on Drop Landing Injury Risk and Lower Limb Asymmetry in Elite Collegiate American Football Players","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-30 17:36:00","doi":"10.21203/rs.3.rs-9061980/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-06T05:59:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-06T02:46:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"135836446525131620302631099585394103410","date":"2026-04-02T19:21:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"218677799616609134303038694641296183309","date":"2026-04-02T02:35:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-31T14:37:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"168600149691691571442586642849046660153","date":"2026-03-31T09:09:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-27T07:13:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-17T06:53:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-13T10:27:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-03-12T11:39:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"553ead1b-3a7e-4039-9aee-568d072316e7","owner":[],"postedDate":"March 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":65340935,"name":"Health sciences/Health care"},{"id":65340936,"name":"Biological sciences/Neuroscience"},{"id":65340937,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2026-04-20T07:28:08+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-30 17:36:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9061980","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9061980","identity":"rs-9061980","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}