IMUs Can Estimate Hip and Knee Range of Motion during Walking Tasks but Are Not Sensitive to Changes in Load or Grade.

The ability to estimate lower-extremity mechanics in real-world scenarios may untether biomechanics research from a laboratory environment. This is particularly important for military populations where outdoor ruck marches over variable terrain and the addition of external load are cited as leading causes of musculoskeletal injury As such, this study aimed to examine (1) the validity of a minimal IMU sensor system for quantifying lower-extremity kinematics during treadmill walking and running compared with optical motion capture (OMC) and (2) the sensitivity of this IMU system to kinematic changes induced by load, grade, or a combination of the two. The IMU system was able to estimate hip and knee range of motion (ROM) with moderate accuracy during walking but not running. However, SPM analyses revealed IMU and OMC kinematic waveforms were significantly different at most gait phases. The IMU system was capable of detecting kinematic differences in knee kinematic waveforms that occur with added load but was not sensitive to changes in grade that influence lower-extremity kinematics when measured with OMC. While IMUs may be able to identify hip and knee ROM during gait, they are not suitable for replicating lab-level kinematic waveforms.

Sensor location influences the associations between IMU and motion capture measurements of impact landing in healthy male and female runners at multiple running speeds.

This study investigated the relationships between inertial measurement unit (IMU) acceleration at multiple body locations and 3D motion capture impact landing measures in runners. Thirty healthy runners ran on an instrumented treadmill at five running speeds (9-17 km/h) during 3D motion capture. Axial and resultant acceleration were collected from IMUs at the distal and proximal tibia, distal femur and sacrum. Relationships between peak acceleration from each IMU location and patellofemoral joint (PFJ) peak force and loading rate, impact peak and instantaneous vertical loading rate (IVLR) were investigated using linear mixed models. Acceleration was positively related to IVLR at all lower limb locations (p < 0.01). Models predicted a 1.9-3.2 g peak acceleration change at the tibia and distal femur, corresponding with a 10% IVLR change. Impact peak was positively related to acceleration at the distal femur only (p < 0.01). PFJ peak force was positively related to acceleration at the distal (p = 0.03) and proximal tibia (p = 0.03). PFJ loading rate was positively related to the tibia and femur acceleration in males only (p < 0.01). These findings suggest multiple IMU lower limb locations are viable for measuring peak acceleration during running as a meaningful indicator of IVLR.

Optimizing Wearable Device and Testing Parameters to Monitor Running-Stride Long-Range Correlations for Fatigue Management in Field Settings.

PURPOSE: There are important methodological considerations for translating wearable-based gait-monitoring data to field settings. This study investigated different devices' sampling rates, signal lengths, and testing frequencies for athlete monitoring using dynamical systems variables. METHODS: Secondary analysis of previous wearables data (N = 10 runners) from a 5-week intensive training intervention investigated impacts of sampling rate (100-2000 Hz) and signal length (100-300 strides) on detection of gait changes caused by intensive training. Primary analysis of data from 13 separate runners during 1 week of field-based testing determined day-to-day stability of outcomes using single-session data and mean data from 2 sessions. Stride-interval long-range correlation coefficient α from detrended fluctuation analysis was the gait outcome variable. RESULTS: Stride-interval α reduced at 100- and 200- versus 300- to 2000-Hz sampling rates (mean difference: -.02 to -.08; P ≤ .045) and at 100- compared to 200- to 300-stride signal lengths (mean difference: -.05 to -.07; P < .010). Effects of intensive training were detected at 100, 200, and 400 to 2000 Hz (P ≤ .043) but not 300 Hz (P = .069). Within-athlete α variability was lower using 2-session mean versus single-session data (smallest detectable change: .13 and .22, respectively). CONCLUSIONS: Detecting altered gait following intensive training was possible using 200 to 300 strides and a 100-Hz sampling rate, although 100 and 200 Hz underestimated α compared to higher rates. Using 2-session mean data lowers smallest detectable change values by nearly half compared to single-session data. Coaches, runners, and researchers can use these findings to integrate wearable-device gait monitoring into practice using dynamic systems variables.

Association of clinically-measured and dynamic ankle dorsiflexion assessed by markerless motion capture during the drop-jump task on landing biomechanics and risk of ankle injury in military personnel undergoing 10 weeks of physical training.

OBJECTIVES: Determine the influence of clinically-measured maximum dorsiflexion, dynamic peak dorsiflexion and percent of clinically-measured maximum dorsiflexion used during a drop-jump task on landing biomechanics and risk of ankle injury in military personnel. DESIGN: Prospective cohort study. METHODS: 672 participants (122 women) enrolled. The weightbearing lunge test assessed clinically-measured maximum dorsiflexion averaged across limbs (degrees). Markerless motion capture and force plates collected lower extremity kinematic and kinetic data during a drop-jump task. Percent of clinically-measured maximum dorsiflexion used during landing was calculated as dynamic peak dorsiflexion divided by clinically-measured value, multiplied by 100 (%). De-identified injury data was derived from military physical therapists. Simple linear regression analysis determined the association between dorsiflexion measures and landing biomechanics. Simple binary logistic regression analyses identified predictors of ankle injuries. Statistical significance was set at α = 0.05. RESULTS: Eighteen participants sustained a traumatic ankle injury from a landing. All measures of dorsiflexion were associated with movement patterns that countered the stiff-legged landing strategy with dynamic measures showing a higher predictive value. Protective factors against ankle injury included height (odds ratio: 0.818, p = 0.006) and weight (odds ratio: 0.824, p = 0.023) for women. Relative braking impulse was a risk factor for men (odds ratio: 1.890, p = 0.001). CONCLUSIONS: Greater clinically-measured and dynamic measures of dorsiflexion were associated with movement patterns that countered the stiff-legged landing strategy but neither measure of dorsiflexion predicted ankle injury risk. Resultant biomechanics and anthropometrics influenced ankle injury risk to warrant recognition for injury prevention initiatives.

Cumulative patellofemoral force and stress are lower during faster running compared to slower running in recreational runners.

Management strategies for patellofemoral pain often involve modifying running distance or speed. However, the optimal modification strategy to manage patellofemoral joint (PFJ) force and stress accumulated during running warrants further investigation. This study investigated the effect of running speed on peak and cumulative PFJ force and stress in recreational runners. Twenty recreational runners ran on an instrumented treadmill at four speeds (2.5-4.2 m/s). A musculoskeletal model derived peak and cumulative (per 1 km of continuous running) PFJ force and stress for each speed. Cumulative PFJ force and stress decreased with faster speeds (9.3-33.6% reduction for 3.1-4.2 m/s vs. 2.5 m/s). Peak PFJ force and stress significantly increased with faster speeds (9.3-35.6% increase for 3.1-4.2 m/s vs. 2.5 m/s). The largest cumulative PFJ kinetics reductions occurred when speeds increased from 2.5 to 3.1 m/s (13.7-14.2%). Running at faster speeds increases the magnitude of peak PFJ kinetics but conversely results in less accumulated force over a set distance. Selecting moderate running speeds (~3.1 m/s) with reduced training duration or an interval-based approach may be more effective for managing cumulative PFJ kinetics compared to running at slow speeds.

Cue utilisation is partially related to performance on an urban operations course but not experience.

INTRODUCTION: Decision making in use of force relies on accurate cue identification to inform appropriate response. This research was designed to test the relationship between cue utilisation and performance prior to, and following participation in an urban operations course (UOC). METHODS: A total of 37 participants were assessed on cue utilisation measures, course outcome and between group changes following course participation. RESULTS: A significant main effect was evident for Cue utilisation and administration, (p = 0.005), but not training group, (p = 0.54), nor between groups and point of administration, (p = 0.410). No main effect was evident between groups and training outcome, (p = 0.11). However, there was a main effect for point of administration, (p = 0.02) and training outcome and point of administration (p = 0.02). CONCLUSION: Although cue utilisation is an essential component of perception-action tasks, cues may be more specific to the relevant training environment with limited transfer to the operational context.

Predictive utility of commercial grade technologies for assessing musculoskeletal injury risk in US Marine Corps Officer candidates.

Recently, commercial grade technologies have provided black box algorithms potentially relating to musculoskeletal injury (MSKI) risk and functional movement deficits, in which may add value to a high-performance model. Thus, the purpose of this manuscript was to evaluate composite and component scores from commercial grade technologies associations to MSKI risk in Marine Officer Candidates. 689 candidates (Male candidates = 566, Female candidates = 123) performed counter movement jumps on SPARTA™ force plates and functional movements (squats, jumps, lunges) in DARI™ markerless motion capture at the start of Officer Candidates School (OCS). De-identified MSKI data was acquired from internal OCS reports for those who presented to the Physical Therapy department for MSKI treatment during the 10 weeks of training. Logistic regression analyses were conducted to validate the utility of the composite scores and supervised machine learning algorithms were deployed to create a population specific model on the normalized component variables in SPARTA™ and DARI™. Common MSKI risk factors (cMSKI) such as older age, slower run times, and females were associated with greater MSKI risk. Composite scores were significantly associated with MSKI, although the area under the curve (AUC) demonstrated poor discrimination (AUC = .55-.57). When supervised machine learning algorithms were trained on the normalized component variables and cMSKI variables, the overall training models performed well, but when the training models were tested on the testing data the models classified MSKI "by chance" (testing AUC avg = .55-.57) across all models. Composite scores and component population specific models were poor predictors of MSKI in candidates. While cMSKI, SPARTA™, and DARI™ models performed similarly, this study does not dismiss the use of commercial technologies but questions the utility of a singular screening task to predict MSKI over 10 weeks. Further investigations should evaluate occupation specific screening, serial measurements, and/or load exposure for creating MSKI risk models.

A Minimal Sensor Inertial Measurement Unit System Is Replicable and Capable of Estimating Bilateral Lower-Limb Kinematics in a Stationary Bodyweight Squat and a Countermovement Jump.

This study aimed to validate a 7-sensor inertial measurement unit system against optical motion capture to estimate bilateral lower-limb kinematics. Hip, knee, and ankle sagittal plane peak angles and range of motion (ROM) were compared during bodyweight squats and countermovement jumps in 18 participants. In the bodyweight squats, left peak hip flexion (intraclass correlation coefficient [ICC] = .51), knee extension (ICC = .68) and ankle plantar flexion (ICC = .55), and hip (ICC = .63) and knee (ICC = .52) ROM had moderate agreement, and right knee ROM had good agreement (ICC = .77). Relatively higher agreement was observed in the countermovement jumps compared to the bodyweight squats, moderate to good agreement in right peak knee flexion (ICC = .73), and right (ICC = .75) and left (ICC = .83) knee ROM. Moderate agreement was observed for right ankle plantar flexion (ICC = .63) and ROM (ICC = .51). Moderate agreement (ICC > .50) was observed in all variables in the left limb except hip extension, knee flexion, and dorsiflexion. In general, there was poor agreement for peak flexion angles, and at least moderate agreement for joint ROM. Future work will aim to optimize methodologies to increase usability and confidence in data interpretation by minimizing variance in system-based differences and may also benefit from expanding planes of movement.

Evaluating the intra- and inter-day reliability of output measures for the VALD HumanTrak: dynamic movements and range of motion of the shoulder and hip with body armour.

The HumanTrak captures human movement through markerless motion tracking and can be a crucial tool in military physical screening. Reliability was examined in eighteen healthy participants who completed shoulder and hip ROM, and dynamic tasks in three body armour conditions. Generally, for all conditions, good to excellent reliability was observed in shoulder abduction and flexion, hip abduction and adduction, and dynamic squats knee and hip flexion (ICC ≥ 0.75 excluding outliers). Shoulder adduction and hip flexion demonstrated moderate to excellent reliability (ICC ≥ 0.50). Shoulder and hip extension and the drop jump were unreliable (ICC: 0.10-0.94, 0.15-0.89, and 0.30-0.82, respectively) due to the large distribution of ICC scores. Tasks with ROM values ≥ 100° involving movement towards or perpendicular to the HumanTrak camera tended to have greater reliability than movements moving away from the camera and out of the perpendicular plane regardless if body armour was worn.Practitioner summary: The HumanTrak analyses ROM in a time-efficient manner in a military setting. This study established that shoulder abduction and adduction (no body armour) and shoulder, hip, and knee flexion were the most reliable measurement for all conditions. Further work is required for movements across different planes.Abbreviations: ROM: range of motion; NBA: no body armour; BA: unloaded body armour; BA9: body armour with 9 kg; RGB: red, green, blue; ICC: intra-class correlation; SEM: standard error of measurement; MDC: minimal detectable change: MSE: mean square error; r: pearson correlations; N: sample size.

Measures of Lower Body Strength Associated With Injuries in Australian Special Forces Selection Candidates.

The diverse and grueling nature of activities undertaken during Special Forces selection makes it difficult to develop physical training to improve performance and reduce injury risk. It is generally accepted that increased strength is protective against injury, but it is unclear if this is evident in a Special Forces selection environment. This study investigated the effect of the rigors of a Special Forces selection course has on performance of the isometric mid-thigh pull, countermovement jump, squat jump, drop landing, elastic utilization ratio (EUR), and injury occurrence. Throughout the course, 26% of participants sustained a preventable lower limb injury, with 65% of these occurring at the knee. The uninjured had higher values of absolute strength as measured by isometric mid-thigh pull peak absolute force (3399 [371] N, 3146 [307] N; P = .022) and lower EUR (0.94 [0.08], 1.01 [0.09]; P = .025) compared to the injured. Preventable knee injury was significantly correlated with isometric mid-thigh pull (r = -.245, P = .031) and EUR (r = .227, P = .044). The selection course altered EUR for uninjured individuals only (P = .004). Findings indicate that individuals with higher strength levels may be at a lower risk of injury than their weaker counterparts.

Not All Physical Performance Tests Are Related to Early Season Match Running Performance in Professional Rugby League.

ABSTRACT: Glassbrook, DJ, Fuller, JT, Wade, JA, and Doyle, TLA. Not all physical performance tests are related to early season match running performance in professional rugby league. J Strength Cond Res 36(7): 1944-1950, 2022-This study aimed to determine which physical tests correlate with early season running performance. Sixteen professional rugby league players performed the 30-15 intermittent fitness test (IFT), 1.2-km time trial, 1 repetition maximum (RM) barbell back squat, isometric midthigh pull (IMTP), countermovement jump (CMJ), barbell squat jump (SJ), and ballistic bench press throw (BBP). Bivariate Pearson's correlations and linear regression were used to compare physical tests with peak match running intensities recorded by a portable Global Positioning System and represented by peak match velocity and acceleration, as well as peak 1-, 4-, 6-, and 8-minute instantaneous acceleration/deceleration periods of play. Significant (p < 0.05) negative correlations (r = -0.55 to -0.60) were observed between the IFT and relative 1-, 4-, 6-, and 8-minute peaks, and between the relative 1RM back squat and relative 1-, 4-, 6-, and 8-minute peaks. Significant positive correlations (r = 0.52-0.84) were observed between the following physical tests and match performance pairs: IFT and peak acceleration; relative 1RM back squat and peak acceleration; SJ peak power (relative and absolute) and peak acceleration; CMJ peak force (relative and absolute) and peak acceleration; CMJ peak power (relative and absolute) and peak acceleration and 1-, 4-, 6-, and 8-minute peaks; and relative BBP peak power and peak velocity and peak acceleration. The results of this study highlight that not all generic tests of physical qualities are related to peak match running performance and only those with significant correlations are likely to be able to indicate how players may perform during match-play.

Changes in acceleration load as measured by inertial measurement units manifest in the upper body after an extended running task.

The purpose of this study was to investigate the behaviour of physiological load measures as well as ground reaction forces (GRF) and acceleration load during a prolonged running task that simulated the running demands of an intermittent team sport. Nineteen males completed a maximal aerobic fitness test and an extended running protocol across two sessions. Participants wore a portable metabolic system, and four inertial measurement units (IMU), one on each foot, the lower back and upper back. GRF were measured via an instrumented treadmill. Change in metabolic, IMU and GRF variables across five blocks during the running protocol were assessed using a one-way repeated measures ANOVA. The running protocol elicited large increases in heart rate and oxygen consumption over time. No statistically significant changes in any peak impact accelerations were observed. Resultant acceleration area under the curve (AUC) increased at the lower and upper back locations but was unchanged at the foot. GRF active peak but not impact peak increased during the prolonged run. The results of this study indicate that the effect of an extended running task on IMU measures of external mechanical load is manifested in the upper body, and is effectively measured by AUC.

Unsupervised Clustering Techniques Identify Movement Strategies in the Countermovement Jump Associated With Musculoskeletal Injury Risk During US Marine Corps Officer Candidates School.

Musculoskeletal injuries (MSKI) are a significant burden on the military healthcare system. Movement strategies, genetics, and fitness level have been identified as potential contributors to MSKI risk. Screening measures associated with MSKI risk are emerging, including novel technologies, such as markerless motion capture (mMoCap) and force plates (FP) and allow for field expedient measures in dynamic military settings. The aim of the current study was to evaluate movement strategies (i.e., describe variables) of the countermovement jump (CMJ) in Marine officer candidates (MOCs) via mMoCap and FP technology by clustering variables to create distinct movement strategies associated with MSKI sustained during Officer Candidates School (OCS). 728 MOCs were tested and 668 MOCs (Male MOCs = 547, Female MOCs = 121) were used for analysis. MOCs performed 3 maximal CMJs in a mMoCap space with FP embedded into the system. De-identified MSKI data was acquired from internal OCS reports for those who presented to the OCS Physical Therapy department for MSKI treatment during the 10 weeks of OCS training. Three distinct clusters were formed with variables relating to CMJ kinetics and kinematics from the mMoCap and FPs. Proportions of MOCs with a lower extremity and torso MSKI across clusters were significantly different (p < 0.001), with the high-risk cluster having the highest proportions (30.5%), followed by moderate-risk cluster (22.5%) and low-risk cluster (13.8%). Kinetics, including braking rate of force development (BRFD), braking net impulse and propulsive net impulse, were higher in low-risk cluster compared to the high-risk cluster (p < 0.001). Lesser degrees of flexion and shorter CMJ phase durations (braking phase and propulsive phase) were observed in low-risk cluster compared to both moderate-risk and high-risk clusters. Male MOCs were distributed equally across clusters while female MOCs were primarily distributed in the high-risk cluster. Movement strategies (i.e., clusters), as quantified by mMoCap and FPs, were successfully described with MOCs MSKI risk proportions between clusters. These results provide actionable thresholds of key performance indicators for practitioners to use for screening measures in classifying greater MSKI risk. These tools may add value in creating modifiable strength and conditioning training programs before or during military training.

Head and Neck Characteristics as Risk Factors For and Protective Factors Against Mild Traumatic Brain Injury in Military and Sporting Populations: A Systematic Review.

BACKGROUND: Investigators have proposed that various physical head and neck characteristics, such as neck strength and head and neck size, are associated with protection from mild traumatic brain injury (mTBI/concussion). OBJECTIVES: To systematically review the literature and investigate potential relationships between physical head and neck characteristics and mTBI risk in athletic and military populations. METHODS: A comprehensive search of seven databases was conducted: MEDLINE, EMBASE, CINAHL, Scopus, SPORTDiscus, Cochrane Library, and Web of Science. Potential studies were systematically screened and reviewed. Studies on military and athletic cohorts were included if they assessed the relationship between physical head-neck characteristics and mTBI risk or proxy risk measures such as head impact kinematics. RESULTS: The systematic search yielded a total of 11,723 original records. From these, 22 studies met our inclusion criteria (10 longitudinal, 12 cross-sectional). Relevant to our PECO (Population, Exposure, Comparator, and Outcomes) question, exposures included mTBI incidence and head impact kinematics (acceleration, velocity, displacement) for impacts during sport play and training and in controlled laboratory conditions. Outcome characteristics included head and neck size (circumference, mass, length, ratios between these measures), neck strength and endurance, and rate of force development of neck muscles. DISCUSSION: We found mixed evidence for head and neck characteristics acting as risk factors for and protective factors against mTBI and increased susceptibility to head impacts. Head-neck strength and size variables were at times associated with protection against mTBI incidence and reduced impact kinematics (14/22 studies found one or more head-neck variable to be associated with protection); however, some studies did not find these relationships (8/22 studies found no significant associations or relationships). Interestingly, two studies found stronger and larger athletes were more at risk of sustaining high impacts during sport. Strength and size metrics may have some predictive power, but impact mitigation seems to be influenced by many other variables, such as behaviour, sex, and impact anticipation. A meta-analysis could not be performed due to heterogeneity in study design and reporting. CONCLUSION: There is mixed evidence in the literature for the protective capacity of head and neck characteristics. We suggest field-based mTBI research in the future should include more dynamic anthropometric metrics, such as neck stiffness and response to perturbation. In addition, laboratory-based mTBI studies should aim to standardise design and reporting to help further uncover these complicated relationships.

Negative Consequences of Pressure on Marksmanship May be Offset by Early Training Exposure to Contextually Relevant Threat Training: A Systematic Review and Meta-Analysis.

OBJECTIVE: The purpose of this meta-analytic review is to examine the relationship between increased psychological pressure and Use of Force (UOF) behaviours, identifying current training methodologies and effectiveness of transfer of training interventions in high threat-simulated scenarios. BACKGROUND: Data from UOF performance within Law Enforcement indicates a low transfer of marksmanship training into real-world UOF, resulting in unnecessary damage to property, personal injury and increased risk to loss of life. This meta-analysis examines both the impact of increased pressure and current training interventions. METHOD: A meta-analysis was conducted across a wide range of published research to answer the primary research questions. RESULTS: Increased levels of perceived pressure demonstrated an average decrease in marksmanship accuracy of 14.8%, together with a small increase in incorrect Decision Making (DM) and faster reaction Times (RT). Experience demonstrated a mitigating effect for pressure for marksmanship with a 1.1% increase for every one year of service but no effect on DM or RT. Training interventions utilizing a variety of early contextually relevant exposures to increased pressure improved performance over traditional training on average by 10.6%. CONCLUSION: The outcomes illustrate the negative effect of pressure on marksmanship and UOF behaviours, and that early exposure to contextually relevant pressure may increase the transfer of training to real-world performance. APPLICATION: Occupational experience is an important component in reducing the impact of pressure on UOF performance, and transfer of training may be enhanced through training methodologies that combine early exposure to contextually relevant pressure, that may replicate the benefits of experience.

Senior and Junior Rugby League Players Improve Lower-Body Strength and Power Differently During a Rugby League Season.

ABSTRACT: Wade, JA, Fuller, JT, Devlin, PJ, and Doyle, TLA. Senior and junior rugby league players improve lower-body strength and power differently during a rugby league season. J Strength Cond Res 36(5): 1367-1372, 2022-This investigation evaluated lower-body strength and power changes across a rugby league season in elite junior and senior athletes. Twenty-five senior and 20 junior rugby league players performed an isometric midthigh pull and countermovement jump at 3 time points in a National Rugby League training season (mid-preseason, end-preseason, and in-season). Linear fixed-effects models were used to compare isometric midthigh pull force and countermovement jump power between player experience groups (senior vs. junior) across the season phases (mid-preseason vs. end-preseason vs. and in-season). Cohen's effect sizes (ES) with 95% confidence intervals were calculated for pairwise comparisons. For senior players, absolute and relative strength (ES = 0.38, p < 0.007) and power (ES = 0.64, p < 0.008) increases were observed at end-preseason compared with mid-preseason, but there were no changes in-season (ES = 0.02, p > 0.571). For junior players, strength did not change (ES < 0.01, p > 0.738) and absolute power decreased (ES = 0.29, p < 0.014) at end-preseason compared with mid-preseason; large increases were evident for absolute and relative strength (ES = 1.43, p < 0.001) and power (ES = 0.62, p < 0.001) in-season. This research demonstrates senior and junior rugby league players exhibit unique patterns of improvements in lower-body strength and power across different phases of the season. This highlights the importance for training programs to differ between junior and senior athletes and target different physical qualities for both groups at different times of the season, thus providing guidance for strength and conditioning coaches.

The Effectiveness of Gait Retraining on Running Kinematics, Kinetics, Performance, Pain, and Injury in Distance Runners: A Systematic Review With Meta-analysis.

OBJECTIVE: To evaluate the effectiveness of running gait retraining on kinematics, kinetics, performance, pain, and injury in distance runners. DESIGN: Intervention systematic review with meta-analysis. LITERATURE SEARCH: Seven electronic databases from inception to March 2021. TRIAL SELECTION CRITERIA: Randomized controlled trials that (1) evaluated running gait retraining compared to no intervention, usual training, placebo, or standard care and (2) reported biomechanical, physiological, performance, or clinical outcomes. DATA SYNTHESIS: Random-effects metaanalyses were completed, and the certainty of evidence was judged using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria. We categorized interventions into step rate, non-rearfoot footstrike, impact, ground contact time, and multiparameter subgroups. RESULTS: We included 19 trials (673 participants). Moderate-certainty evidence indicated step rate gait retraining increased step rate (SMD 1.03 [95% confidence interval {CI}: 0.63, 1.44]; number of trials (N): 4; I2: 0%) and reduced average vertical loading rate (SMD -0.57 [95% CI, -1.05 to -0.09], N: 3; I2: 0%). Low-certainty evidence indicated non-rearfoot footstrike retraining increased knee flexion at initial contact (SMD 0.74 [95% CI, 0.11 to 1.37]; N: 2; I2: 0%), but did not alter running economy (SMD 0.21 [95% CI, -1.11 to 1.52]; N: 3; I2: 19%).). Low-certainty evidence indicated multiparameter retraining did not alter running economy (SMD 0.32 [-0.39, 1.02]; N: 3; I2: 19%) or performance (SMD 0.14 [95% CI, -4.87 to 4.58]; N: 2; I2: 18%). Insufficient trials reported on pain outcomes. Two trials demonstrated reduced 1-year injury incidence following gait retraining. CONCLUSIONS: Gait retraining interventions altered step rate and knee kinematics, lowered vertical loading rates, and did not affect running performance. J Orthop Sports Phys Ther 2022;52(4):192-206. Epub 05 Feb 2022. doi:10.2519/jospt.2022.10585.

Time of Season and Game Segment Is Not Related to Likelihood of Lower-Limb Injuries: A Meta-Analysis.

OBJECTIVE: Fatigue due to game play is often cited as a factor in musculoskeletal injuries; however, it is unclear whether or not this view is supported by published research findings. Given the importance researchers and practitioners place on the potential effects of game play with respect to injury, it is important to understand what inferences can be drawn from the collective research in this realm. This meta-analysis will consider the time of season and segment of the game, as it relates anterior cruciate ligament (ACL), groin, and hamstring injury occurrence. DATA SOURCES: Database searches were run in PubMed, MEDLINE, SportDiscus, CINAHL, and Ausport, in addition to the inclusion of articles identified manually. STUDY SELECTION: Search terms were chosen to identify articles related to each of the 3 injuries of interest. There were no date limitations placed on the articles, as such, all published articles listed in the databases up to November 2017 were eligible for selection if they met the search criteria. DATA EXTRACTION: Initial searches yielded 1349 articles, and this was eventually reduced to 15 articles deemed suitable for inclusion in the meta-analysis, which provided 21 data sets. DATA SYNTHESIS: Comparing the first half with the second half of the season, there were no differences in ACL, groin, or hamstring injury occurrences [ACL: odds ratio (OR), 1.27; confidence interval (CI), 0.43-3.78, groin: OR, 1.79; CI, 0.63-5.06, and hamstring: OR, 1.16; CI, 0.88-1.53]. Similarly, there were no differences in injury occurrence between the first and second halves of the game for the ACL or hamstring injuries (ACL: OR, 0.43; CI, 0.47-7.92, hamstring: OR, 0.85; CI, 0.58-1.24). CONCLUSIONS: Findings from this meta-analysis determined that time in season or time in game does not influence risk of the ACL, groin, or hamstring injury. Commonly, many studies did not provide sufficient detail to be included in the meta-analysis. Consequently, it is recommended that future studies report data related to the timing of the injury within the season or game.