Effects of Mental Fatigue on Trunk and Knee Kinetics and Kinematics During Unanticipated Stop-Jump in Amateur Soccer Players

Abstract

Background:

Physical fatigue in soccer has been considered a risk factor for anterior cruciate ligament (ACL) injury, while mental fatigue could lead to decision-making errors and induce injuries. However, there is a lack of research on the combined effects of mental fatigue and decision making on lower limb biomechanics.

Hypotheses:

(1) Mental fatigue leads to a decrease in trunk flexion angle and knee flexion angle when touching the ground, as well as an increase in knee valgus moment and horizontal backward ground-reaction force (GRF) under unexpected conditions, which may lead to an increase in knee joint load. (2) The combined effects of mental fatigue and decision making lead to increased knee extension moment and valgus moment, leading to characteristics that may increase the risk of injury.

Study Design:

Descriptive laboratory study.

Methods:

Twenty male amateur soccer players were recruited as participants. Mental fatigue was induced through a 45-minute Stroop task, where the color of the screen changed randomly using a self-made infrared induction synchronous trigger to create different anticipated state scenes. A 12-lens infrared spot 3-dimensional (3D) motion capture system and 3D force plates were used to collect kinematic and dynamic data from the trunk and knee joints.

Results:

Mental fatigue and expected state demonstrated significant interaction effects on knee flexion angle and peak horizontal posterior GRF. At the initial contact, knee flexion angle (P = .002) and trunk flexion angle (P = .04) were significantly decreased post-mental fatigue compared with pre–mental fatigue. In the unanticipated condition, knee valgus moment was significantly increased (P = .014). At the first peak of horizontal posterior GRF, compared with pre–mental fatigue, the trunk flexion angle (P = .04) and knee flexion angle (P = .017) were significantly decreased, and the peak horizontal posterior GRF (P = .03) and knee valgus moment were significantly increased postfatigue (P = .03).

Conclusion:

Soccer players demonstrated a more upright landing posture post–mental fatigue, and unanticipated conditions negatively affected trunk and knee movement patterns, potentially increasing the risk of ACL injury. The interaction of mental fatigue with unexpected factors did not appear to amplify the risk of ACL injury.

Clinical Relevance:

This study elucidates the effect of mental fatigue and decision making on the ACL. These risk factors may be incorporated into ACL prevention strategies.

Keywords

ACL mental fatigue anticipated soccer stop-jump

Anterior cruciate ligament (ACL) injury in soccer is considered one of the most severe and complex types, accounting for 14.2% of all soccer injuries worldwide.^4,14 ACL injury has an extremely serious direct effect on soccer players, which can interrupt training in the short term and prevent them from returning to the field due to ACL injury complications in the long term. Moreover, it imposes a substantial economic burden on individuals and society. Therefore, understanding the risk factors associated with ACL injury and implementing preventive measures has become a key focus in current research.

Fatigue is a prevalent neuromuscular factor linked to ACL injury risk.^6,8 Prolonged engagement in soccer activities not only induces physical fatigue but also mental fatigue, which refers to a psychobiological state resulting from prolonged demanding cognitive tasks characterized by subjective fatigue and lack of energy, the difficulty of signal integration in the central nervous system and the increase of cognitive burden.^29,33 Studies have demonstrated that mental fatigue caused by sustained cognitive activities among soccer players can lead to motor control impairments,⁴¹ decision-making errors, and even injuries.⁴² Gaffney¹⁶ demonstrated that mental fatigue during depth-jump in female soccer players leads to increased hip adduction and knee adduction angles, and that these kinematic changes are some of the factors that contribute to dynamic knee valgus and may increase the risk of noncontact ACL injury. Kong et al²⁶ investigated the heightened risk of musculoskeletal injuries, such as lateral ankle sprain and ACL injury, in patients with functional ankle instability who unexpectedly performed side-cut maneuvers after experiencing mental fatigue. Therefore, it is crucial to pay attention to the changes in movement characteristics caused by mental fatigue during competition and training.

Notably, noncontact ACL injuries in soccer players have been associated with increased neurocognitive load resulting from decision-making factors.²² Research has demonstrated that during the first half of a game, soccer players are able to adjust their movements and predict goals based on immediate sensory feedback. However, toward the end of games or during the second half when mental fatigue sets in for soccer players, quick decisions regarding sudden ball movements need to be made. Such unexpected interferences can disrupt players’ original movement patterns and potentially lead to injuries.²¹ Numerous scholars have investigated the biomechanical characteristics of knee joints when athletes perform unplanned stop-jump or side-cut under different anticipated conditions. Findings suggest that compared with anticipated movements, unexpected movements may impose greater ACL loads on lower limb biomechanics displayed by athletes.⁹ Therefore, the combination of decreased motor control ability and decreased decision-making ability caused by mental fatigue may contribute to poor performance and injury in soccer.³⁰ However, there is currently no research investigating the effect of mental fatigue and decision making on lower limb biomechanics. Thus, it is crucial to clarify how mental fatigue and decision making affect trunk posture and lower limb joint movements during high-risk dynamic exercises to better understand the causal relationship between noncontact ACL injuries.

In summary, this study aims to develop an effective method for inducing mental fatigue in soccer players while simulating high-risk ACL injury actions under unexpected decision-making scenarios. Furthermore, it seeks to analyze the biomechanical characteristics of knee joint movements among soccer players. This will provide a deeper understanding of the mechanism behind noncontact ACL injuries and enable us to propose targeted prevention strategies. On the basis of previous research and our objectives, we hypothesize that (1) after experiencing mental fatigue, soccer players have reduced trunk flexion angle and knee flexion angle when touching the ground and adopt a more upright posture when landing. Under anticipated conditions, the knee valgus moment and horizontal backward ground-reaction force (GRF) have increased, potentially leading to an increased risk of injury; and that (2) the dual task of mental fatigue and decision making may increase the extension moment and valgus moment of the knee joint, which may increase the risk of injury.

Methods

Participants

Twenty male university students with >2 years of soccer training experience were recruited for this study. Their lower limb health status was assessed through interviews and recorded before participation. All participants had not undergone any knee-related surgical treatments before the experiment and had no history of lower limb injuries or chronic knee pain in the past 6 months. Additionally, they did not have any sleep disorders, color blindness, or heart disease. Participants were instructed to maintain a regular sleep pattern (≥8 hours) and diet; to refrain from strenuous exercise; and to avoid caffeine, nicotine, and alcohol in the 24 hours before the experiment. Utilizing G*Power Version 3.1.9.2, we conducted a power analysis to ascertain the minimal sample size necessary for a 2-factor within-participants analysis of variance (ANOVA) employing a 2 × 2 repeated-measures design (effect size, 0.3; alpha level, .05; power, 0.80), which indicated that a participant cohort of 17 individuals would be required to achieve the desired statistical power. Before participating in the tests, all participants received detailed explanations about the experimental procedures and requirements and signed informed consent forms approved by the institution’s academic ethics review board. Basic participant information is provided in Table 1.

Table 1

Basic Information of the Participants ^a

N	Age, y	Height, cm	Body Mass, kg	Training, y
20	21.5 ± 1.3	178.5 ± 2.9	68.3 ± 8.5	3.5 ± 1.1

Data are presented as mean ± SD.

Experimental Process

Participants were instructed to provide their basic information and indicate their dominant leg (kicking leg). Subsequently, participants were asked to change into the laboratory-provided body-tight clothing and sports shoes and familiarize themselves with all test procedures. Then they completed the visual analog scale for evaluating fatigue severity (VAS-F) to assess mental fatigue, physical fatigue, and energy levels. The anticipated and unanticipated experimental tests were then conducted. The 45-minute Stroop task was performed. Upon completion of the task, the participants filled out the VAS-F scale once again. They repeated the anticipated and unanticipated experimental tests.

Mental Fatigue Induction Protocols

The Stroop task required sustained attention and response inhibition; hence, it has been demonstrated as an effective method for inducing mental fatigue over extended durations.^27,34 The 45-minute Stroop task was conducted using E-Prime (Version 3.0; Psychological Software Tools), and 4 different Chinese characters (red, yellow, blue, green) were randomly presented on a computer screen using 1 of 4 colors. Participants had to select keys corresponding to word color regardless of Chinese character meaning. Each word remained on-screen for 1000 ms followed by a blank screen lasting another 1000 ms before displaying the next word stimulus. A total of 1320 trials were performed during the 45-minute Stroop mission. Participants were instructed to complete each trial as quickly and accurately as possible, while any incorrect or timed-out responses (>1500 ms) triggered an auditory beep alerting them to respond faster with greater accuracy (Figure 1).

Figure 1.

Stroop task test diagram.

Anticipated/Unanticipated Task

This study examined the stop-jump and side-cut maneuvers.^11,24 As can be visualized in Figure 2, participants were instructed to initiate their sprint from a distance of 5 to 10 m away from the force plate. This stipulation was crucial to ensure ample space for an effective starting position. The infrared induction synchronization trigger was placed 2 m past the starting gate. The participants were required to maintain a minimal run-up speed of 3.5 ± 0.2 m/s²⁵. In anticipated conditions, participants adhered to directives to execute stop-jump maneuvers and side-cutting movements of approximately 45° in both the left and the right directions. Under unanticipated conditions, when participants accelerated from the starting gate, an infrared induction synchronous trigger (HG-J18-T20N1; OMCH) was used along with sensor connections to transmit induced infrared light signals to a computer screen where 3 randomly generated colors appeared immediately. Participants determined their action based on these colors: red indicated performance of a left 45° side-cut, green indicated execution of a right 45° side-cut, and yellow signified the performance of scram jump actions (Figures 2 and 3). The data analysis was focused on 3 effective actions under different anticipated conditions.

Figure 2.

Test-site schematic diagram.

Figure 3.

Experimental test diagram. (A) Anticipated left side-cut; (B) Anticipated stop-jump; (C) Anticipated right side-cut; (D) Unanticipated left side-cut; (E) Unanticipated stop-jump; (F) Unanticipated right side-cut.

Experimental process: the participant passed through the infrared induction synchronous trigger 2 m behind the starting gate, then 1 of the 3 colors of red, yellow, and green appeared randomly on the computer screen and the participant made corresponding actions according to the color. Laboratory equipment included an infrared induction synchronous trigger, a 12-lens infrared spot 3D motion capture system (Mars2H; Nokov), 3D force plates (FP4060; Bertec), and a Witty-Manual gate (Microgate).

Data Collection and Processing

All participants were required to wear the uniform provided by the laboratory, and the same operator pasted 29 reflective markers on each participant according to the Helen Hayes model⁴⁰ (Figure 4). The kinematic data were obtained by using the 12-lens infrared spot 3D motion capture system synchronized at the sampling frequency of 200 Hz. The two 3D force plates were simultaneously used to collect the GRF and related indicators with a sampling frequency of 1000 Hz. The approach speed was measured using the Witty-Manual gate during the test.

Figure 4.

Infrared reflective marker ball paste scheme. L, left; R, right; V, vertical.

Cortex (Motion Analysis Inc) software was used to process kinematics and dynamics data, and Butterworth low-pass filtering with a truncated frequency of 13 Hz was used to smooth the 3D coordinates of all landmarks. A multirigid body model of human link was established, and the 3D angle of the trunk and knee joint was calculated using the Euler angle method. The first rotation was around the x-axis to obtain the flexion and extension angle, the second rotation was around the y-axis to obtain the varus and valgus angle, and the third rotation was around the z-axis to obtain the internal and external rotation angle. Among the motion parameters defined by the three rotational axes, the following demonstrated positive (+) values: trunk flexion, and knee flexion, varus, and internal rotation. In addition, the measured raw dynamic data was low-pass filtered at 50 Hz, and then the 3D torque of the knee joint was calculated by an inverse dynamic method. The GRF peak data obtained in each direction were standardized through body weight, and the unit was recorded as BW. The knee torque was normalized as a multiple of the product of height (BH) and body mass (BW), and the unit was recorded as BW × BH. Some studies have pointed out that the moment of landing and the first peak of horizontal posterior GRF were considered to be the high-risk moment for ACL injury.^10,31 The initial contact was defined as landing when the vertical GRF component was >20 N and leaving the ground when it was >20 N.¹³ Combined with previous studies, the indicators included in this study were the kinematics and dynamics data of the trunk and knee joints at the time of initial contact and the first peak of horizontal posterior GRF.

Statistical Analysis

All data variables were presented in the form of mean ± SD, with the mean value ± 3 SD as the criterion for the exclusion of outliers. SPSS 23.0 (SPSS Inc) software was used to verify whether the normal distribution was obeyed by the Shapiro-Wilk test. If the normal distribution was not followed, the nonparametric Wilcoxon test was used. A 2-factor ANOVA with a 2 × 2 repeated design was used to examine the differences between the degree of mental fatigue (pre– and post–) and different anticipated states (anticipated and unanticipated) on the kinematic and dynamic parameters of the trunk and knee joint. If there was a significant interaction between the factors, simple effect analysis was used to compare whether there was a significant difference between pre– and post–mental fatigue and anticipated and unanticipated states. The level of significant difference was P < .05.

Results

Mental Fatigue Induced

Through the analysis of the VAS-F scale, the subjective evaluation index of mental fatigue, it was found that the energy index of 20 participants pre– and post–mental fatigue was 37.13 ± 5.38 mm versus 21.27 ± 11.30 mm. The fatigue index score was 26.13 ± 15.03 mm versus 65.20 ± 30.29 mm. After the Stroop task, fatigue scores increased significantly (P < .001) and energy scores decreased significantly (P < .001) in all participants (Figure 5).

Figure 5.

Changes in the visual analog scale for evaluating fatigue severity pre– and post–mental fatigue. * indicates a significant difference between the two, P < .05.

There was no significant difference between the 3-minute correct rate before and after the Stroop task (98.08% ± 2.16% vs 98.59% ± 1.52%; P = .31). The reaction time at 3 minutes after the Stroop task was significantly longer than that at 3 minutes before the task (702.68 ± 81.71 ms vs 667.15 ± 87.73 ms; P = .025) (Figure 6). This is consistent with the successful results of mental fatigue induction conducted by previous scholars¹⁷, indicating that a 45-minute Stroop task can successfully induce mental fatigue.

Figure 6.

Changes in cognitive performance. (A) Correctness rate results; (B) Reaction time results. In both figures, the dashed lines denote the changes in indices for each participant pre- and post-mental fatigue, while the solid lines represent the changes in the mean values across all participants pre- and post-mental fatigue. * indicates a significant difference between the two, P < .05.

Initial Contact Moment

The results showed that the state pre– and post–mental fatigue and different tasks (anticipated/unanticipated) had a significant interaction on knee flexion angle (F_(1,38) = 4.141; P = .049; η² = 0.098). Simple effect analysis showed that knee flexion angle (32.10° vs 35.79°; P = .002) decreased significantly post–mental fatigue compared with previously when performing anticipated tasks. Regardless of the anticipated or unanticipated state, the trunk forward angle post–mental fatigue was significantly reduced compared with pre–mental fatigue (F_(1,38) = 4.399; P = .04; η² = 0.104) (Table 2). Whether fatigue or not, the trunk forward angle (F_(1,38) = 4.618; P = .04; η² = 0.108), knee flexion moment (F_(1,38) = 5.465; P = .025; η² = 0.132), and knee valgus moment (F_(1,38) = 6.594; P = .01; η² = 0.148) increased significantly under unanticipated conditions, showing a trend of knee varus moment under anticipated conditions and knee valgus moment under unanticipated conditions. The horizontal posterior GRF under unanticipated conditions post–mental fatigue (F_(1,38) = 4.270; P = .046; η² = 0.101) decreased significantly (Figure 7).

Table 2

Kinematic Parameters of the Trunk and Knee Joint at Initial Contact ^a

	Before Mental Fatigue		After Mental Fatigue		P
	Anticipated	Unanticipated	Anticipated	Unanticipated	A	M	A*M
Trunk flexion angle, deg	10.10 ± 8.65	14.18 ± 7.47	7.58 ± 7.12	12.80 ± 6.38	.04	.04	.54
Knee flexion angle, deg	35.79 ± 9.42	32.98 ± 7.80	32.10 ± 10.19	32.49 ± 7.26	.65	.012	.049
Knee valgus angle, deg	1.87 ± 4.70	2.08 ± 5.29	1.86 ± 5.15	1.89 ± 5.70	.94	.88	.90
Knee internal rotation angle, deg	8.24 ± 8.86	9.73 ± 9.09	9.45 ± 11.71	11.97 ± 11.25	.51	.15	.66
Knee flexion moment, BW × BH	0.010 ± 0.008	0.015 ± 0.006	0.009 ± 0.007	0.014 ± 0.009	.025	.58	.88
Knee varus/valgus moment, BW × BH	0.002 ± 0.003	−0.001 ± 0.003	0.001 ± 0.004	−0.001 ± 0.004	.014	.36	.68
Knee internal/external rotation moment, BW × BH	−0.002 ± 0.005	0.004 ± 0.004	−0.004 ± 0.008	0.004 ± 0.006	.39	.90	.25
Vertical ground-reaction force, BW	0.050 ± 0.034	0.040 ± 0.024	0.050 ± 0.031	0.050 ± 0.036	.41	.41	.53
Lateral ground-reaction force, BW	−0.003 ± 0.015	−0.003 ± 0.013	−0.008 ± 0.009	−0.002 ± 0.012	.22	.30	.42
Horizontal posterior ground-reaction force, BW	0.038 ± 0.030	0.021 ± 0.013	0.034 ± 0.031	0.023 ± 0.030	.046	.88	.55

Data are presented as mean ± SD. Bold values represent statistical significance (P < .05). A, P value, anticipated vs unanticipated state; A*M, interaction between A and M; BH, body height; BW, body weight; M, P value, pre–mental fatigue vs post–mental fatigue.

Figure 7.

Dynamic parameters of knee joint at the initial contact. BH, body height; BW, body weight; HGRF, horizontal ground-reaction force; LGRF, lateral ground-reaction force; VGRF, vertical ground-reaction force. * indicates a significant difference between pre- and post-mental fatigue, P < .05.

The First Peak of Horizontal Posterior GRF

The results showed that mental fatigue and expected state had significant interaction on the peak of horizontal posterior GRF (F_(1,38) = 5.726; P = .022; η² = 0.131). Simple effect analysis showed that the peak value of horizontal posterior GRF post–mental fatigue was significantly higher than that before mental fatigue in the anticipated state (0.702 BW vs 0.848 BW; P = .03) (Figure 8). The main effect of mental fatigue was significant. Regardless of the anticipated or unanticipated state, the trunk forward angle (F_(1,38) = 4.735; P = .04; η² = 0.111) and knee joint flexion angle decreased significantly post–mental fatigue compared with that pre–mental fatigue (F_(1,38) = 6.223; P = .02; η² = 0.141) (Table 3). Compared with pre–mental fatigue, the torque of knee joint valvaration increased significantly (F_(1,38) = 5.153; P = .03; η² = 0.119).

Figure 8.

Knee joint dynamic parameters at the first peak of horizontal posterior ground-reaction force (HGRF). BH, body height; BW, body weight; LGRF, lateral ground-reaction force; VGRF, vertical ground-reaction force. * indicates a significant difference between pre- and post-mental fatigue, P < .05.

Table 3

Kinematic Parameters of Trunk and Knee Joint at the First Peak of Horizontal Posterior GRF ^a

	Pre–Mental Fatigue		Post–Mental Fatigue		P
	Anticipated	Unanticipated	Anticipated	Unanticipated	A	M	A*M
Trunk flexion angle, deg	9.99 ± 8.74	12.77 ± 7.30	7.11 ± 7.10	11.54 ± 6.44	.10	.036	.39
Knee flexion angle, deg	42.70 ± 10.10	37.86 ± 8.69	39.02 ± 9.37	36.79 ± 7.08	.19	.017	.18
Knee valgus angle, deg	2.72 ± 4.56	2.52 ± 5.34	2.50 ± 5.34	2.14 ± 6.23	.86	.68	.90
Knee internal rotation angle, deg	9.50 ± 9.46	9.81 ± 8.88	10.06 ± 11.34	11.26 ± 11.25	.81	.39	.70
Knee extension moment, BW × BH	−0.028 ± 0.057	−0.018 ± 0.048	−0.029 ± 0.038	−0.034 ± 0.041	.77	.46	.49
Knee valgus moment, BW × BH	−0.002 ± 0.025	−0.010 ± 0.023	−0.013 ± 0.025	−0.018 ± 0.021	.32	.029	.73
Knee internal rotation moment, BW × BH	0.002 ± 0.005	0.002 ± 0.004	0.003 ± 0.003	0.002 ± 0.007	.79	.38	.68
Vertical ground-reaction force, BW	1.700 ± 0.755	1.951 ± 0.747	1.847 ± 0.743	1.734 ± 0.666	.76	.75	.09
Lateral ground-reaction force, BW	−0.134 ± 0.131	−0.205 ± 0.144	−0.162 ± 0.149	−0.194 ± 0.150	.22	.67	.32
Horizontal posterior ground-reaction force, BW	0.702 ± 0.368	0.896 ± 0.414	0.848 ± 0.397	0.825 ± 0.387	.46	.41	.02

Discussion

Currently, successful induction of mental fatigue during soccer activities is often determined by combining subjective and objective indicators. This study reveals that participants’ subjective VAS-F scale showed significant differences pre– and post–Stroop task, which was consistent with previous studies. Kunrath et al²⁸ conducted a study comparing the induction of mental fatigue in 18 male amateur soccer players through a 30-minute Stroop task. The results revealed that the VAS of mental fatigue (VAS-MF) score before the Stroop task was 22.2 ± 12.3 mm, which increased about 3-fold to 64.0 ± 17.9 mm after the task. Similarly, Smith et al³⁹ performed Stroop tasks on 14 soccer players and observed a significantly higher VAS-MF score of approximately 52.0 ± 11 mm compared with the pretask score of 8 ± 9 mm. Furthermore, our study found a significant increase in reaction time in the last 3 minutes of the Stroop task compared with the first 3 minutes, but no significant change in accuracy, which is consistent with results previously reported by Gantois et al.¹⁷ It was evident from existing studies that subjective and cognitive indicators, which showed significant changes after mental interventions, were considered indicative of the successful induction of mental fatigue among athletes. In line with these findings, our study demonstrated a significant increase in fatigue scores and a decrease in energy scores among all participants, along with a notable rise in reaction time, which further supports the successful induction of mental fatigue using our proposed scheme involving a 45-minute Stroop task.

Indeed, mental fatigue induced by high cognitive load on the soccer field can result in diminished cognitive function. This impairment in cognitive abilities not only reduces physical performance but is also correlated with an elevated risk of ACL injuries.^3,39 Previous studies have shown that increased valgus torque of the knee joint is associated with significant increases in ACL load and ACL injury risk.⁴⁴ Moreover, large horizontal posterior GRFs during stop-jump are considered potential risk factors for ACL injuries.¹¹ Shibata et al³⁶ suggested that in individuals with poor neurocognitive performance, there is an increase in peak angle and moment of knee valgus, as well as an increase in GRF. Herman and Barth¹⁸ observed that exercise involving insufficient cognitive skills often resulted in higher GRF, increased anterior tibial shear force, and elevated abductive torque of the knee joint, leading to excessive ACL load. The study revealed that after mental fatigue, both knee valgus torque and peak GRF significantly increased at the initial peak of GRF compared with pre–mental fatigue levels, which is partially in line with the findings reported by Shibata et al and Herman et al. Additionally, this study revealed no significant change in knee varus angle after mental fatigue compared with before mental fatigue; however, Kong et al²⁶ reported an increase in knee varus angle on the injured side among patients with functional ankle instability after mental fatigue. These discrepancies may be attributed to variations in patient populations and task selection.

In addition, the study demonstrated that mental fatigue significantly reduced both trunk forward tilt angle and knee flexion angle during stop-jumps when performed by soccer players, supporting our first hypothesis and showing consistency with previous studies. Higo and Kuruma²⁰ found that mental fatigue decreased trunk forward tilt angle during landing movements, possibly due to impaired movement control caused by mental fatigue, leading to reduced execution accuracy. However, a smaller forward tilt angle of the trunk caused a backward shift in the center of gravity, which is a crucial factor contributing to increased ACL stress.³⁵ Blackburn and Padua⁵ discovered that hip and knee joint flexion angles increased when landing with a flexed trunk compared with an upright position. Studies have confirmed that smaller knee flexion angles significantly elevate ACL load, as decreasing knee flexion angles result in an increased patellar tendon–tibial angle and anterior tibial shear force exerted by the quadriceps muscles, thereby increasing ACL injury risk.^2,11,44 Nevertheless, De Vleeschouwer¹² reported no significant effect on knee kinematic indices induced by mental fatigue, which may be attributed to differences between their experiment involving side-cutting landing jumps movements compared with our study focusing on stop-jump movements where participants would engage a self-protective strategy in the face of the former’s more dangerous movement pattern to better adapt to their movement pattern. In this study, soccer players adopting an upright posture to touch the ground may be due to the fact that mental fatigue limits the activation of the prefrontal cortex during the development of muscle fatigue, which further negatively affects neuromuscular function, including changes in strength, muscle activity, and joint stability.^1,38

Effective neuromuscular control strategies during dynamic landings are typically cultivated under anticipated conditions; hence, an impaired capacity to retrieve, process, and make swift and precise decisions in unfamiliar settings may augment motor coordination errors and the likelihood of subsequent injuries. Generally speaking, smaller knee flexion angles, along with greater knee abduction and eversion moments and increased knee internal rotation are associated with biomechanical risk factors for ACL injury.⁴⁵ This study revealed that, irrespective of pre– and post–mental fatigue, soccer players exhibit a significant increase in trunk forward angle and knee flexion torque when landing unexpectedly after stop-jump. Additionally, there is a notable decrease in horizontal posterior GRF. These findings align with the results reported by Kim et al.²⁵ Previous studies have demonstrated that active trunk flexion during landing leads to an increased knee flexion angle, which may subsequently reduce the GRF.⁵ Based on these findings, it appears that the risk of ACL injury is relatively low in unanticipated situations due to the increase in knee flexion angle accompanying trunk forward inclination. Moreover, coordinated contraction of the hamstring muscle can generate posterior tibial shear force within a specific range of knee flexion (15°-60°), thereby reducing ACL strain.⁵ However, multiple musculoskeletal modeling studies have indicated that sagittal mechanics alone do not exert sufficient forces to cause ACL damage; furthermore, any potential benefits may be counteracted by increased knee valgus angulation as well as hip adduction and pronation.^5,32

Studies have demonstrated that a significant biomechanical risk factor contributing to noncontact ACL injury is the increased knee valgus torque during the landing phase of stop-jump movements.¹⁹ We observed that during the initial contact and the first peak of the horizontal posterior GRF, there was a significantly higher knee valgus torque in the unanticipated condition compared with the anticipated condition. At initial contact, the anticipated condition exhibited a knee varus torque while the unanticipated condition showed a trend toward knee valgus torque, aligning with previous studies’ findings.^21,25 Kahneman’s²³ attentional capacity model has highlighted that limited cognitive resources can lead to distraction during multitasking, resulting in decreased central nervous system control and an elevated risk of injury. Soccer players performing unanticipated tasks experience attentional diversion and disruption of sensory input (eg, visual or vestibular information) required for anticipated task landings, leading to ineffective reduction of knee valgus moment at the appropriate time. In this study, although significantly increased trunk forward angle and knee flexion torque were observed along with a notable decrease in horizontal posterior GRF under unanticipated conditions during stop-jump movements, it is important to note that such scenarios could heighten the risk of noncontact knee injuries due to amplified knee valgus torque, causing greater ACL strain, further supporting hypothesis 1.^15,37

Mental fatigue and unexpectedness only exhibit interactive effects on knee flexion angle and the peak of horizontal posterior GRF upon initial contact. Simple effect analysis reveals significant differences in these 2 indicators solely under anticipated conditions, indicating a decrease in knee flexion angle after mental fatigue compared with prefatigue levels, as well as an increase in the peak of horizontal posterior reaction force. In the braking stage, smaller knee joint flexion angle and larger GRF may lead to greater ACL load, thus increasing the risk of injury.⁴⁵ This could be attributed to the fact that position adaptation and adjustment are mainly coordinated through the same central control mechanism of the brain in the anticipated state of movement, which will further lead to increased cognitive load, aggravate brain fatigue, and cause corresponding sports injuries.⁴⁶ This study found that there was no significant difference when the interaction indicator was in an unanticipated state, which is contrary to our hypothesis 2 and also inconsistent with some previous studies. Borotikar et al⁷ believed that the peak value of hip rotation and knee abductor angle increased more significantly at the moment of initial contact when participants performed unanticipated 1-leg landing tasks after completing the fatigue program, indicating that ACL injury was more likely to occur during unanticipated landing tasks after fatigue. This discrepancy may stem from the difference between the 2 fatigue protocols; the physical fatigue program utilized by the former induces neuromuscular fatigue, whereas our research employs a mental fatigue induction protocol. We found that athletes’ motor control ability did not necessarily decline when performing unanticipated situations combined with mental fatigue, which may be due to the fact that performing additional cognitive function tasks may increase brain activity and motivation components, so as to stimulate brain regions responsible for higher-order cognitive functions again, ensuring the maintenance of performance under mental fatigue and thus avoidance of injury.⁴³ However, in real game scenarios, soccer players must make rapid action decisions, often resulting in knee joint load increase. If the athlete is currently in a state of mental fatigue, the risk of injury one faces will correspondingly increase.

Limitations

The present study is subject to several limitations. First, this study employed a self-control design without setting up a control group, which resulted in a deficiency in experimental randomization. It is recommended that future studies incorporate control groups to enhance the comprehensiveness of the experimental design. At present, this study explores the effects of mental fatigue on lower limb biomechanics pre– and post–mental fatigue. However, different levels of mental fatigue have different effects on soccer players’ lower limbs. In future studies, it will be very important to explore the influence of different degrees of mental fatigue (medium, high, and low) on lower limb biomechanics. Moreover, this study only simulated unanticipated states within a laboratory environment; therefore, more realistic scenarios closely resembling actual competition should be created to explore the effect of mental fatigue on lower limb sports biomechanics as well as technical and tactical performance among soccer players.

Conclusion

Under the influence of mental fatigue, we found that trunk inclination angle and knee flexion angle decreased, while valgus torque and GRF increased. In the face of unexpected decisions, the knee joint showed greater valgus torque. These changes are associated with abnormal movement patterns, in which a smaller knee flexion angle and trunk forward inclination may cause the athlete to adopt a more rigid movement pattern when landing, and the body will be subjected to greater GRF, knee valgus moment, and forward shear force of the tibia, resulting in the muscles and ligaments around the knee joint passively absorbing excessive impact energy. This may increase the risk of knee ligament damage. However, we did not observe indicators of significant differences when performing the unexpected task after mental fatigue, which may be due to higher order cognitive function areas of the brain that activate a protective organism strategy when performing the unexpected task. Given that prolonged soccer matches can induce mental fatigue in athletes, implementing interventions aimed at mitigating mental fatigue could potentially mitigate the decline in technical performance and reduce the occurrence of sports injuries during matches.

Footnotes

Final revision submitted January 9, 2025; accepted February 3, 2025.

One or more of the authors has declared the following potential conflict of interest or source of funding: This study was supported by the most recent set of new liberal arts research and reform practice projects (2021050026), Shanxi provincial basic research program (202103021224109), and Shanxi Postgraduate Research Innovation Programme (2023KY267). AOSSM checks author disclosures against the Open Payments Database (OPD). AOSSM has not conducted an independent investigation on the OPD and disclaims any liability or responsibility relating thereto.

Ethical approval for this study was obtained from Taiyuan University of Technology (TYUT-20230705001).

ORCID iDs

Ruizhi Yang

Zeyu Wang

Minpeng Zhao

Xudong Zhu

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