Prevention of musculoskeletal injuries (MSKI) is a principal concern of employers, commanders, and healthcare professionals in civilian and military settings. MSKI are a leading cause of both morbidity and mortality in active populations, placing a considerable burden on those affected and society at large. With military personnel, MSKI have the added consequence of directly impacting force readiness and, in turn, national defense. MSKI can result from a single, acute macrotraumatic overload event/exposure (e.g., noncontact anterior cruciate ligament (ACL) tear or ankle sprain), a chronic repetitive exposure or overuse that leads to subtle microtrauma (e.g., shin splints or stress fractures), or a combination of an acute-on-chronic presentation (153). Both traumatic overload- and overuse-related injuries can predispose individuals to posttraumatic degenerative osteoarthritis — the most common and costly disability in the U.S. Military and other active populations (133). Accordingly a significant amount of effort has been dedicated to the primary prevention of MSKI in order to reduce the related morbidity and consequent degradation of performance and attending health care costs.
A significant challenge to preventing both traumatic overload- and overuse-related MSKI is the multifactorial nature of these injuries (3,68,75,77,143). Risk factors are categorized traditionally as extrinsic or intrinsic. Established extrinsic risk factors, arguably the most common contributors to injury, include training errors (doing too much, too soon, and/or too fast); training, playing, or occupational surfaces; and the external environment (e.g., heat stress) (3,68,75,77,143). However in many military, occupational, and sports setting, the extrinsic risk factors are nonmodifiable (e.g., unstable ground surfaces found in remote areas in which soldiers must patrol). Intrinsic risk factors include individual characteristics such as female sex, high percent body fat, history of prior injury, skeletal malalignment (e.g., foot structure), and deficits or imbalances in strength, flexibility, and/or neuromuscular control (32,50,122,147). Currently interest in the ability to predict MSKI risk has increased, and attention has focused on the civilian and military medical communities to identify movement patterns that may predispose individuals to dangerous loading patterns and high joint forces. These suboptimal patterns of movement, although perhaps considered intrinsic factors, in fact may be modifiable and potentially mitigate future risk of injury.
Many individuals have one or more movement impairments (dysfunctions) that may render them susceptible to MSKI (72,110,127). Addressing identified movement impairments could result in improved dynamic balance, trunk stability, and functional movement quality while potentially minimizing risk of incurring MSKI (32,61,71,122,160). In addition to inherent movement impairments, excessive or repeated overload and overuse associated with specific occupations or athletic endeavors can induce a level of neuromuscular and structural fatigue that may alter movement control and joint stability (18,59). Accordingly evaluating sport- or activity-specific repetitive movement patterns and minimizing injury risk through preventive or corrective neuromuscular training of movement impairments should be incorporated and emphasized in the selective occupational, military, and athletic populations. The goal is to promote better biomechanics and improve the overall functional fitness of civilian athletes, warfighters, first responders, and others working in physically demanding occupations. Such a process, in turn, likely would be effective in reducing MSKI costs and improving operational and performance readiness.
This consensus statement details the outcome of a strategic summit convened between members of the Department of Defense (DoD) and leading civilian experts to assess the current state of the science with regard to the emerging role and utility of assessing impaired or dysfunctional movements in the populations where physical performance is critical. More specifically, the goal was to identify factors and screening methods that together could predict and prevent MSKI risk. The overall outcome was to clarify what we know, what we do not know, and where we should go from here.
In an effort to develop a more unified approach for addressing and combating MSKI, the Consortium for Health and Military Performance convened a summit and expert panel at the Uniformed Services University in Bethesda, MD, on September 10 and 11, 2012. Participants included scientists and physicians from the DoD, representatives from the American College of Sports Medicine, the National Academy of Sports Medicine, the National Strength and Conditioning Association, and other subject matter experts from various research institutions. The group was charged with four specific tasks:
- Review the epidemiology and burden of MSKI in military and civilian athletic communities;
- Define functional fitness for populations with high physical demands and identify MSKI risk related to impaired movement patterns;
- Describe and assess current functional movement assessment tools used to assess athletes in military and civilian sports medicine communities;
- Identify knowledge gaps related to MSKI risk assessment and prediction and implementation challenges in evaluating functional movement in at-risk populations.
The expert panel also was charged to address the utility of functional movement assessment following injury rehabilitation to determine return-to-duty/play/work (RTD/P/W) to optimize physical readiness of civilian athletes, warfighters, first responders, and others working in physically demanding occupations. Finally needed research would be highlighted and consensus would be provided on effective strategies for improving functional movement assessment and mitigating MSKI risk.
Summit Findings and Discussion
Task #1: Review the Epidemiology and Burden of MSKI in Military and Civilian Athletic Communities
MSKI in the military
MSKI is a primary source of disability in the U.S. Military (86,141). Physical training and sport-related activities account for up to 90% of all MSKI (69,74,76). In 2007, MSKI resulted in approximately 2.4 million medical visits to military medical treatment facilities and accounted for $548 million dollars in direct patient care costs (46). The prevalence of injuries requiring an outpatient visit in the U.S. Army entry-level training is about 25% for men and 55% for women (53,69,134). Lower extremity injuries, both traumatic overload and overuse related, account for over 4.8 million of the 11 million annual limited duty days related to injury (5). Notably 80% of MSKI are considered overuse in nature (3,5,135). In addition, sport-related activities account for 13.1% of unintentional injury hospitalizations in active duty U.S. Armed Forces (67). Although battle-related injuries are a medical priority to preserve life, limb, and/or eye sight, the majority of MSKI in the deployed setting are non-battle related and account for the highest percentage of primary care and physical therapy visits in the deployed environment (24,144,151,158). Importantly 34% of deployed troops experience noncombat MSKI, which cause significant morbidity during deployment (19,67). Nonbattle injuries in a combat setting are estimated to be 87% of all deployment-related injuries and are 6 times more frequent than battle-related injuries (52).
An indirect measure of the impact of MSKI on combat readiness can be ascertained through evaluating the causes of medical evacuations from theater. During Operation Iraqi Freedom and Operation Enduring Freedom, approximately 14% of all medical evacuations were for combat injuries and 24% were for noncombat MSKI (19,67). Lower extremity injuries accounted for more than 40% of all medical evacuations (66), with low back pain being the number one complaint among service members returning from Iraq/Afghanistan (19,67). The detrimental impact of MSKI on combat readiness cannot be overstated, as the typical service member evacuated from theater is younger than 29 years and requires extensive subsequent orthopedic care (52).
MSKI in civilians
As within the military, MSKI attributable to occupational demands, sports, recreational activities, and exercise participation present a significant public health concern among the civilian sector. The National Center for Injury Prevention and Control estimated that more than 10,000 Americans seek medical treatment each day for sports, recreational activities, and exercise-related injuries (36), with lower extremity injuries making up 50% to 80% of these injuries (3,69,154).
In sports, 66% of all sport-related injuries are lower extremity, and nearly 75% to 80% of these injures are not a result of contact with another competitor or participant (1,25,90,105,106). Given that dysfunctional movements are associated highly with noncontact, lower extremity injury risk factors and mechanisms, it has been suggested that improving movement control and quality can prevent 65% to 85% of sport-related lower extremity injuries (62,78,136,157). Specific to competitive collegiate athletes, overuse and acute injuries continue to be problematic, with an overall injury rate of 63.1 per 10,000 athletic exposures, and very little research has been conducted to clarify best practices in prevention and rehabilitation (166).
Task #2: Defining Functional Fitness and Identifying MSKI Risk Related to Impaired Movement Patterns
Historically most training and conditioning programs for physically demanding occupations and recreation pursuits have focused on selected basic components of fitness (e.g., cardiovascular fitness, agility, muscular strength and endurance, power, and speed) and physical potential to define athleticism and purportedly predict performance success (118). However focusing solely on measures of athleticism during training and conditioning can lead to a “performance paradox,” whereby an individual can demonstrate extreme levels of athleticism but still display significant movement dysfunctions that may (or may not) increase his or her risk for injury. Therefore underlying functional fitness depends more on movement efficiency and control than on just the expression of specific athletic or military skills, as the former is the foundational constructs of observed functional movement and performance (Fig. 1). The theoretical construct is that movement efficiency and control are built on key-contributing determinants of stability (strength, neuromuscular control, and endurance) and functional mobility of the kinetic chain. Muscle imbalances, inadequate core stability, and altered kinematics due to fatigue and/or muscle strength imbalances can readily lead to dysfunctional neuromuscular control, impaired movement patterns, and increased risk for MSKI.
Inadequate core stability and muscle imbalances
Although numerous definitions of core stability can be found in the literature, Kibler et al. described core stability as “the ability to control the position and motion of the trunk over the pelvis and leg to allow optimum production, transfer and control of force and motion to the terminal segment in integrated kinetic chain activities” (70). A stable core may help mitigate compressive, torsional, and translational forces on the articular joints during energy transfer (40). However inadequate control of the core during performance of functional activities may result in inefficient and dysfunctional movement patterns (81,139,163,164) and potentially an increased risk of MSKI. Factors related to core stability, such as lumbopelvic strength and endurance, have been identified as predictors of an individual’s risk of developing recurrent low back pain and lower extremity injuries (39,40,57,81,159). In addition, hip muscle strength (hip external rotation (HER) and abduction (ABD)) has been associated with lower extremity overuse injuries in runners sustaining knee pain (17,26,38,81,108,125). Notably research has indicated sex differences in these muscular fitness measurements, with women demonstrating less hip ABD and HER strength than men (10,81,164), and these decrements may predispose women to an increased risk of lower extremity injury (64,81). In contrast, some evidence suggests that interventions aimed at improving core stability may decrease the risk of certain injuries in athletes (56,58,157) and high-risk workers (124).
Muscle imbalances have been identified also as predictors of MSKI (7,38,73,107,115). Bilateral strength differences in knee flexion and hip extension and ABD have been associated with a variety of lower extremity injuries in athletes (38,73,115). Side-to-side strength asymmetries may increase the risk of injury for both limbs, as overdependence on the stronger limb may subject it to higher joint forces, while the weaker limb may lack the strength to withstand the forces associated with performing functional activities (103). Atypical agonist-to-antagonist strength ratios, such as low knee flexion to extension, hip abduction to adduction, and ankle dorsiflexion to plantarflexion, have been documented in athletes experiencing lower extremity injuries (7,73,89,115). Likewise a low trunk extension-to-flexion ratio has been identified as a risk factor for low back pain (80). Moreover abnormal ratios between antagonistic muscle groups may compromise muscle balance and overall joint integrity during performance of athletic activities.
Neuromuscular control, kinematics, and fatigue
Neuromuscular control — activation of muscles to control joint motion and maintain joint stability — requires complex interactions among sensory, motor, and central processing components of the motor control system (84). Inefficient neuromuscular control can impose large forces on static restraints (ligaments, bone, and cartilage) of the respective joint(s) and readily lead to failure of these static restraints (63). Kinematic analysis allows neuromuscular control during jumping (13,98,129,130), vertical drops, step downs (31), and side stepping to be examined (60). Impaired neuromuscular control has been associated with muscular imbalances (82), fatigue (8,94), foot type (12,91,161), and asymmetry in movement (131,168,169). In addition, the finding that women and girls exhibit differences in lower extremity kinematics and neuromuscular control as compared with men and boys may help explain why woman and girl athletes are at a higher risk for certain lower extremity injuries (37,65,79,95). Ineffective neuromuscular control has been documented with noncontact ACL injuries as well as lower extremity overuse injuries, such as tibial stress fractures (99–101,128,168), patellofemoral pain syndrome (26,162), and iliotibial band syndrome (51,109). Also decreased neuromuscular control of the lumbopelvic complex may predict development of recurrent low back pain and lower extremity injuries (39,40,57,81,159).
Neuromuscular control is also necessary for maintenance of balance, and deficits in static and dynamic balance are predictive of MSKI (127,150,156). Balance deficits have been documented in those with a history of lower extremity injury, such as ankle sprains, chronic ankle instability, ACL deficiency, and anterior knee pain (2,4,47,48,55). Importantly sound balance characteristics provide a foundation for the advanced, specialized, and skilled movements required for performance in physical activity and sports.
Neuromuscular control is affected markedly by relevant muscle fatigue. Numerous epidemiological studies in civilian athletics have demonstrated that selected muscle fatigue creates an environment wherein certain MSKI are to occur more likely (42,85,102). The mechanism by which muscle fatigue increases the risk of injury is multifactorial, but a clear contributing factor is how muscle fatigue alters related components of neuromuscular control required for joint stability. For example, muscle fatigue affects electromyographic characteristics of the joint musculature necessary for dynamic joint stability (43), alters proprioception (43,149), increases joint laxity (165), and changes landing kinematics (8,14,96). Accordingly although reliable, valid, and field-expedient screening tools capable of identifying individual balance profiles and movement dysfunctions are needed, these tools should be employed during both nonfatiguing and fatiguing conditions. This approach would provide greater insight and utility in developing targeted injury prevention protocols for reducing MSKI risk.
Task #3: Functional Movement Assessment Tools
Effective functional movement assessment screening tools should involve multiple body segments and be associated with practical functional fitness (92,93). More specifically, assessments for impaired movement patterns aimed at preventing MSKI should be based on the following (88):
- Pathokinesiologic model of assessment, with a focus on identifying specific movement impairments (e.g., knee valgus collapse, toe out, lumbar lordosis, etc.) known to be associated with specific MSKI risk(s);
- Targeted preventive training programs linked to and aimed at fixing those specific movement impairments.
Because MSKI risk is individual specific and multifactorial, a personalized approach to identify and address modifiable individual risk factors likely is to be more effective than a generalized program. Many types of screening tools have been used successfully in research and clinical practice, and others continue to be developed. In general, any practical, effective tool for determining an individual’s movement profile must 1) easily assess relevant, demand-specific impaired movements; 2) provide outcome measures that are reliable and reproducible; 3) rapidly, accurately, and validly identify the greatest primary MSKI risk factors for the particular movements of the sport/task (recognizing that injury risk is multifactorial and difficult to fully and precisely predict); 4) be sensitive and specific; and 5) provide sufficient information regarding movement deficiencies and muscle/range of motion imbalances to adequately guide intervention strategies (118).
Multifactorial screening tools to predict MSKI risk have been somewhat successful (11,83,87,104,110). Although some disagreement exists in the literature (45), one multivariate model was able to identify female athletes at increased risk of ACL injury (sensitivity/Sn: 84%, specificity/Sp: 67%) (104). In Marine Corps Officer Candidate Training, a multivariate model suggested that individuals with slow 3-mi run times and a low score on the Functional Movement Screen (FMS) were 4.2 times more likely to experience an MSKI than those with fast run times and a high FMS score (87). Lehr et al. (83) found that athletes identified as high risk, based on FMS and Y-Balance Test (YBT) scores, demographics, and prior history of MSKI, had a relative risk of 3.4 for an injury in the upcoming season. One commonality across these studies was the inclusion of screening tools to identify modifiable risk factors.
The following subsections provide a general overview of selected well-known screening tests that have shown some success and utility in identifying modifiable risk factors associated with increased MSKI risk. These screening tests also could play a role in developing prevention programs to mitigate those risks. This brief overview is not exhaustive but does provide a synopsis of three common, readily available and field-expedient screening tools found to predict injury risk — Star Excursion Balance Test (SEBT)/YBT, the Landing Error Scoring System (LESS), and the FMS.
SEBT and YBT
The SEBT assesses functional movement during a dynamic balance activity by challenging the entire lower extremity and core stability during selective movements. Deficits in functional reach, single limb dynamic balance, and altered kinematics have been documented in those with a history of lower extremity injury such as ankle sprains, chronic ankle instability, and anterior knee pain (2,4,47,48). The YBT, which measures three components of the SEBT, has excellent intrarater (Intraclass Correlation Coefficient [ICC] = 0.85 to 0.89) and interrater (ICC = 0.99) reliability (126,127). The YBT challenges single-limb balance while simultaneously having the nonstance limb move in an anterior, posterolateral, and posteromedial direction (see Inset 1).
Initial evidence suggests that high school athletes with anterior reach asymmetries greater than 4 cm between limbs and female high school athletes with total excursion in all three directions less than 94% of their limb length were 2.5 and 6.5 times, respectively, more likely to sustain a future lower extremity injury than those who performed better (112,127). Interestingly, differences in balance have been attributed to differences in fatigue and neuromuscular control of the muscles of the lumbopelvic region (47–49,148) and foot structure (22). Thus deficits in static and dynamic balance are to be likely important predictors of MSKI (6).
The LESS is a clinical assessment tool developed to provide a standardized instrument for identifying high-risk movement patterns (“errors”) during a jump-landing maneuver, such as seen in basketball (9,121,140). The LESS score is a numerical count of landing technique “errors” based on readily observable human movement items. A high LESS score indicates poor technique in landing from a jump, whereas a low LESS score indicates appropriate jump-landing technique. Seventeen items are scored in the LESS (see Inset 2).
The LESS correlates well with a three-dimensional motion analysis of jump landings and has demonstrated good inter- and intrarater reliability (121). Specifically Padua et al. (121) found good interrater reliability (ICC = 0.84) and precision (SEM = 0.71) of the original LESS (when scored from video replay). In addition, the LESS can successfully evaluate changes in landing technique in response to an injury prevention program (28).
Although a clinician can score the LESS quickly, two video cameras and video analysis are required. The utility of the LESS could be enhanced if it were modified to allow real-time analysis in a clinical setting. To enhance the utility of the LESS, a modified scoring and testing criteria have been developed to score an individual’s jump-landing movement patterns in real time (LESS-RT) during the performance of four separate jump-landing trials. The LESS-RT appears to have comparable interrater reliability (ICC range = 0.72 to 0.81) and precision (SEM range = 0.69 to 0.79) (119). The average overall LESS score obtained using the LESS-RT (5.6 ± 1.4) is similar to the original LESS in the cadet population (4.9 ± 1.6). However the LESS-RT has not been correlated with biomechanical data or injury outcomes.
The FMS assesses seven fundamental patterns: active straight leg raise, shoulder mobility, trunk stability push-up, rotary stability quadruped, deep squat, hurdle step, and in-line lunge (see Inset 3) (16,72,110,138). One of the original goals of the FMS was to develop a test to assess movements requiring a combination of muscle strength, flexibility, range of motion, coordination, balance, and proprioception (20).
In a retrospective study involving National Football League (NFL) players, an FMS composite score less than or equal to 14 was associated with a significantly greater risk of injury during a competitive season (72). Analyses indicated that players with an FMS score less than or equal to 14 were approximately 11.0 times more likely to be injured during the season, and players with any asymmetry were 3.0 times more likely to be injured during the season (P < 0.05). Others have demonstrated that a composite score less than or equal to 14 on the FMS could predict an increased risk for future MSKI (traumatic or overuse) in Marine Officer Candidates (110), but the Sn of 0.45 and Sp of 0.71 for overuse injuries were low. The FMS also predicted a serious injury (any injury severe enough to remove the participant from the training program) with an Sn of 0.12 and an Sp of 0.94 (110). The FMS composite score also was predictive of injury for woman athletes (16). However the low Sn limits the utility of the FMS.
Task #4: Identifying Knowledge Gaps and Implementation Challenges
Although the evidence supporting the utility of injury prediction screening tools is encouraging, considerable additional research is needed. The primary areas of concern pertain to predicting the outcomes of interest and to the return on investment of these tools, and especially the implementation challenges and barriers in a military setting. For example, do the intervention programs generated by the functional assessment reduce rates of injury? To what extent and how do the costs of such programs compare with costs of injuries? Addressing these concerns and a myriad of other scientific and clinical gaps is not trivial.
Preventing injury through functional movement assessment and correction
The substantial cost and disability associated with MSKI have led to a wide variety of exercise regimens focused on incorporating injury prevention activities within a training program. These training programs have been designed based on the link between impaired movement patterns and biomechanical deficiencies and their contribution to common MSKI. Components of these training regimens often include dynamic warm-ups, neuromuscular training, and functional movement activities (15,44,97). Many of the group-based injury prevention programs focusing on these concepts have reported success (27,155,167). However these programs tend to concentrate on a single isolated potential injury (e.g., ankle sprains or noncontact ACL injuries) and often include individuals that do not respond to the intervention indicated by improved biomechanics and movement (62).
As discussed above, one of the first requirements of an effective injury prevention program is having reliable, valid, and field-expedient tools to sufficiently predict injury risk. A second requirement is that these tools readily identify modifiable risk factors that have known effective treatments to reduce injury risk. Researchers are starting to address these requirements. For example, Owens et al. (117) found that a military movement training program was effective in improving jump-landing mechanics as measured by the LESS, but reductions in injury were not determined. Also Kiesel et al. (71) found that training programs focused on enhancing functional movement improved FMS scores during the off season for athletes in the NFL, but again, whether these functional improvements actually reduced injury rates and/or time lost to training was not determined. Ultimately future research must demonstrate the impact of such purported risk mitigation strategies on reducing overall injury rates. Accordingly until more research has proven that identification of modifiable risk factors and the associated risk mitigation programs are successful, it is hard to recommend widespread and general use of these intervention strategies in a military setting.
Improving functional movement assessments
In addition to being able to identify modifiable risk factors, population-based screening tools for MSKI prediction must be sufficiently sensitive and specific, as well as field expedient and cost effective. Although most of the tests reviewed have acceptable levels of reliability and Sp, one current limitation is low Sn. For example, in Marines, the FMS has a reported Sn of 0.45 for all MSKI and an Sn of only 0.12 for serious MSKI (110). Therefore the FMS currently has a high false-negative rate. Ideally screening tools would require high Sn values prior to recommending their use for population-based screening. However based on the multifactorial nature of MSKI (3,68,75,77,143), screening tools that focus on a particular MSKI risk factor (e.g., neuromuscular control, balance, etc.) may be limited by high Sp and low Sn values, as the screening tool does not account for other MSKI risk factors, such as history of MSKI, fatigue, terrain, environment exposures, and other biopsychosocial factors associated with increased injury risk.
Researchers should seek to improve the Sn levels of injury prediction screening tools by addressing the multifactorial nature of MSKI. Inclusion of MSKI history, activity and physical fitness levels, dietary intake, sleep and fatigue measures, smoking history, environmental exposures, and biopsychosocial factors could enhance the predictive validity of these tools. In some populations, when the cost of injury is very high, adopting a functional movement assessment with high Sn would be critical in mitigating the costs associated with MSKI. In contrast, if the cost of prevention is high, then a high Sp would effectively put an emphasis on those more prone to injury versus implementing widespread (and costly) prevention to many who would not necessarily benefit — i.e., lessen their injury risk. If the functional movement assessment could be administered in an efficient and cost-effective manner, utilization of current field expedient tools may be beneficial as the first step in decreasing the burden of MSKI in the military setting. Given on the predictive nature of prior MSKI on incurring a future related injury (132,152), researchers could focus on secondary and tertiary prevention of MSKI by assessing functional movement in those with a prior injury history. Assessing movement in preidentified high-risk individuals may yield higher screening Sn. Moreover specific movements could be included as part of an annual musculoskeletal physical examination for persons at high risk for MSKI.
Challenges/solutions for implementing effective programs to address dysfunctional movement
Widespread population-based screening is time consuming and costly. Accordingly only a recognized sufficient burden — anticipated/expected major readiness, operational and cost-related consequences — would justify the time and expense. Effective treatments for the functional movement dysfunctions or deficits identified must be available, must be cost effective (benefits outweigh costs), and favorably must alter the individual movement dysfunction or deficit to reduce related MSKI risk. The functional movement assessments outlined in this review were developed for high school, collegiate, and professional athletes. Accordingly the time requirements to screen a high school basketball team, for example, are typically acceptable based on the low number of athletes per team and the risk of MSKI. However the time required to screen those in the military is much greater. Therefore additional research is needed to find the most parsimonious set of MSKI predictors while exploring time as a realistic constraint.
Barriers to performing a multifactorial injury screening program include those associated with time and logistics. In 2012, Teyhen et al. (146) reported that automation of data collection was effective in improving efficiency of a comprehensive screening protocol. Specifically hand-held computers were used to collect injury screening data and netbooks to collect survey data; this resulted in saving an average of 37 min per individual, which would represent time savings of 129,500 min (˜2,200 h) for an army brigade size element of 3,500 soldiers. In addition, computerized algorithms that stratified MSKI risk and provided personalized risk mitigation strategies represented an additional 11.5 min per soldier or time savings of 40,250 min (670 h) for this same brigade. Ultimately leveraging technology to enhance injury prevention screening and education would allow for 50 persons to be screened during an hour.
The screening must take place within a sufficient “window of opportunity” so that ample time is available to allow for early detection, correction, and injury prevention. Biomechanics and movement patterns are difficult to change, although those with the greatest movement deficiencies can show the greatest improvement (28). Correction approaches need to be individualized while considering individual factors such as body type. Notably augmenting preventive training and conditioning with visual (video) and verbal feedback and concurrent strength training can readily enhance effectiveness (54,113,114).
Many additional barriers to successfully implementing an injury prediction screening protocol can be identified. Military and athletic programs and their leadership (e.g., commanding officers, coaches) must be willing to designate the time and resources toward functional movement assessment. Most importantly, they must “buy-in” and appreciate both the screening and prevention aspects. Specifically the medical benefits of a MSKI prevention program (e.g., reduced clinic visits, hospitalizations, and health care-related costs) may not be the most effective message to create leadership support. Rather compliance may be improved by focusing on enhancing physical performance (35). Application of the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework to injury prediction and prevention may help optimize program design and enhance behavior change (33–35,137). Institutional endorsement and a solid framework are critical, as altering biomechanics and improving motor control can require prolonged training, compliance, and repeated testing to ensure retention (120,142). Research focusing on how these prevention programs can enhance performance also, while providing a cost savings, may be more effective in ensuring acceptance of these programs by participants and commanders/administrators alike. Because major gaps in implementation design and efficacy can be linked to identifiable issues that can cause prevention programs to fail (29,30,35), future research efforts should address all of these aspects.
RTD/P/W Following Injury Rehabilitation — Using Functional Movement Assessment to Determine Readiness
The optimum “continuum of care” for persons with physically demanding occupations/professions should begin with activity- and/or sport-specific assessment of functional and athletic capacity and underlying injury risk prior to training or occupation/profession onset. Functional movement assessment may be of particular value at this point, as it can identify dysfunctional movement patterns and asymmetry inherent to these groups. Based on the results, individualized strength and conditioning programs, including corrective exercise strategies targeting the identified movement deficiencies and imbalances, can be customized to minimize future injury risk (prehabilitation). Ideally the at-risk individual would be retested periodically, so the effectiveness of the corrective intervention can be evaluated and appropriate revisions, as necessary, made. In addition, performance on initial and all successive preinjury tests can be used as a comparison for identifying any negative alterations in movement pattern quality associated with MSKI. Following injury, clinicians can use the functional movement assessment to help gauge improvement of the pre-/rehabilitation process as it pertains to whole-body movement quality and determine when implementation of more advanced activity/sport and field-specific tests and training is appropriate. This standardized approach of using movement assessments and the same validated preinjury risk criteria may be an effective method to determine readiness to RTD/P/W and prevent subsequent related injuries from occurring in those who return prematurely. This approach also can provide outcome measures of surgical and rehabilitation effectiveness. When considering RTD/P/W criteria, it is important to appreciate that one of the strongest predictors for MSKI is a previous history of injury. For example, young female athletes with a history of ACL injury and subsequent ACL reconstruction are at significantly greater risk (6- to 25-fold) compared with their healthy counterparts (123). Movement dysfunctions exist in those with a history of MSKI (23,111,116,123), and the presence of movement dysfunctions in those with a history of MSKI is also predictive of future injury (123). Thus assessment of movement quality and control may provide vital information for determining an individual’s readiness to RTD/P/W.
New Research and Strategies to Improve Functional Movement Assessment and Mitigate Injury Risk — The Way Ahead
More questions than answers permeate the discussion of functional movement assessment. For example, scant evidence exists for screening tools that assess the impact of speed and load on functional movement, balance, or neuromotor control deficits. The addition of speed and load to a task changes the movement pattern and alters the tissues being stressed, which may increase injury risk and negatively impact performance. Accordingly appropriate speed, load, and repetition are essential components to assess movement competency and predict injury risk and human performance in those in physically demanding occupations/professions (41). Thus new research and practical solutions to validate and effectively improve functional movement assessment implementation and reduce MSKI risk are of paramount importance. A starting point could be a widespread emphasis on functional and fitness screening and stratification for injury risk prior to participating in any physically demanding training, conditioning, or other activity, where injury risk and related cost is high. Moreover appropriate provisions and program modifications to reduce MSKI risk, as well as regular careful monitoring and accurate injury reporting, are essential. To this end, for an effective way ahead, we should:
- Continue to examine and clarify modifiable risk factors for exercise- and sport-related MSKI;
- Compare program effectiveness relative to intervention efficacy;
- Determine whether a combination of questionnaires and one or more functional movement assessments can be a more cost-effective approach to more accurately predicting injury risk;
- Identify (with strength of evidence noted), promote, implement, and continually evaluate and revise as necessary evidence-informed prevention and functional movement deficiency correction strategies;
- Identify (with strength of evidence noted), design, promote, implement, and continually evaluate and revise as necessary outcome-focused prevention and functional movement criteria for RTD/P/W;
- Conduct new research to examine the translational research-to-practice gap, including program implementation and dissemination issues;
- Conduct new research to clarify and update the extent of the problem and remarkable trends in specific areas of and populations with demonstrated improvement or worsening injury risk and health;
- Continue to comprehensively educate and effectively integrate physical therapists, athletic trainers, and certified strength and conditioning specialists in evidence-based functional movement screening, training, and corrective strategies;
- Evaluate cost savings and specific work/athletic-related readiness and performance, MSKI risk, and resilience outcomes relative to screening and optimizing fundamental movement patterns.
The authors are grateful for the contribution of summit participants from academic, government, and commercial organizations: the Consortium for Health and Military Performance, the American College of Sports Medicine, the National Strength and Conditioning Association, and the National Academy of Sports Medicine.
The authors declare no conflicts of interest and do not have any financial disclosures.
The view(s) expressed in this article do not reflect the official policy or position of the U.S. Army Medical Research and Materiel Command, the U.S. Army Medical Command Center and School, the U.S. Army Medical Department, the U.S. Army Office of the Surgeon General, the Department of the Army, Department of the Navy, Department of the Air Force, Department of Defense, Uniformed Services University of the Health Sciences, or the U.S. Government.
1. Agel J, Evans TA, Dick R, et al. Descriptive epidemiology of collegiate men’s soccer injuries: National Collegiate Athletic Association Injury Surveillance System, 1988–1989 through 2002–2003. J. Athl. Train
. 2007; 42: 270–7.
2. Akbari M, Karimi H, Farahini H, Faghihzadeh S. Balance problems after unilateral lateral ankle sprains. J. Rehabil. Res. Dev
. 2006; 43: 819–24.
3. Almeida SA, Williams KM, Shaffer RA, Brodine SK. Epidemiological patterns of musculoskeletal injuries and physical training. Med. Sci. Sports Exerc
. 1999; 31: 1176–82.
4. Aminaka N, Gribble PA. Patellar taping, patellofemoral pain syndrome, lower extremity kinematics, and dynamic postural control. J. Athl. Train
. 2008; 43: 21–8.
5. Army Medical Surveillance Activity (AMSA) [Internet]. U.S. Army Center for Health Promotion and Preventive Medicine. 2005 [cited 2005]. Available from: http://afhsc.army.mil/home
6. Arnold BL, De La Motte S, Linens S, Ross SE. Ankle instability is associated with balance impairments: a meta-analysis. Med. Sci. Sports Exerc
. 2009; 41: 1048–62.
7. Baumhauer JF, Alosa DM, Renstrom AF, et al. A prospective study of ankle injury risk factors. Am. J. Sports Med
. 1995; 23: 564–70.
8. Benjaminse A, Habu A, Sell TC, et al. Fatigue alters lower extremity kinematics during a single-leg stop-jump task. Knee Surg. Sports Traumatol. Arthrosc
. 2008; 16: 400–7.
9. Beutler A, de la Motte S, Marshall S, et al. Muscle strength and qualitative jump–landing differences in male and female military cadets: the JUMP-ACL study. J. Sports Sci. Med
. 2009; 8: 663–71.
10. Bohannon RW. Reference values for extremity muscle strength obtained by hand-held dynamometry from adults aged 20 to 79 years. Arch. Phys. Med. Rehabil
. 1997; 78: 26–32.
11. Boling MC, Padua DA, Marshall SW, et al. A prospective investigation of biomechanical risk factors for patellofemoral pain syndrome: the Joint Undertaking to Monitor and Prevent ACL Injury (JUMP-ACL) cohort. Am. J. Sports Med
. 2009; 37: 2108–16.
12. Butler RJ, Davis IS, Hamill J. Interaction of arch type and footwear on running mechanics. Am. J. Sports Med
. 2006; 34: 1998–2005.
13. Chappell JD, Creighton RA, Giuliani C, et al. Kinematics and electromyography of landing preparation in vertical stop-jump: risks for noncontact anterior cruciate ligament injury. Am. J. Sports Med
. 2007; 35: 235–41.
14. Chappell JD, Herman DC, Knight BS, et al. Effect of fatigue on knee kinetics and kinematics in stop-jump tasks. Am. J. Sports Med
. 2005; 33: 1022–9.
15. Chappell JD, Limpisvasti O. Effect of a neuromuscular training program on the kinetics and kinematics of jumping tasks. Am. J. Sports Med
. 2008; 36: 1081–6.
16. Chorba RS, Chorba DJ, Bouillon LE, et al. Use of a functional movement screening tool to determine injury risk in female collegiate athletes. N. Am. J. Sports Phys. Ther
. 2010; 5: 47–54.
17. Cichanowski HR, Schmitt JS, Johnson RJ, Niemuth PE. Hip strength in collegiate female athletes with patellofemoral pain. Med. Sci. Sports Exerc
. 2007; 39: 1227–32.
18. Clansey AC, Hanlon M, Wallace ES, Lake MJ. Effects of fatigue on running mechanics associated with tibial stress fracture risk. Med. Sci. Sports Exerc
. 2012; 44: 1917–23.
19. Cohen SP, Brown C, Kurihara C, et al. Diagnoses and factors associated with medical evacuation and return to duty for service members participating in Operation Iraqi Freedom or Operation Enduring Freedom: a prospective cohort study. Lancet
. 2010; 375: 301–9.
20. Cook G. Movement: Functional Movement Systems: Screening, Assessment, and Corrective Strategies
. Chichester: Lotus Publishing, 2010.
21. Cook G, Burton L, Hoogenboom B. Pre-participation screening: the use of fundamental movements as an assessment of function — part 1. N. Am. J. Sports Phys. Ther
. 2006; 1: 62–72.
22. Cote KP, Brunet ME, Gansneder BM, Shultz SJ. Effects of pronated and supinated foot postures on static and dynamic postural stability. J. Athl. Train
. 2005; 40: 41–6.
23. Crossley KM, Cowan SM, Bennell KL, McConnell J. Knee flexion during stair ambulation is altered in individuals with patellofemoral pain. J. Orthop. Res
. 2004; 22: 267–74.
24. Darakjy S, Marin RE, Knapik JJ, Jones BH. Injuries and illnesses among armor brigade soldiers during operational training. Mil. Med
. 2006; 171: 1051–6.
25. Dick R, Putukian M, Agel J, et al. Descriptive epidemiology of collegiate women’s soccer injuries: National Collegiate Athletic Association Injury Surveillance System, 1988–1989 through 2002–2003. J. Athl. Train
. 2007; 42: 278–85.
26. Dierks TA, Manal KT, Hamill J, Davis IS. Proximal and distal influences on hip and knee kinematics in runners with patellofemoral pain during a prolonged run. J. Orthop. Sports Phys. Ther
. 2008; 38: 448–56.
27. DiStefano LJ, Blackburn JT, Marshall SW, et al. Effects of an age-specific anterior cruciate ligament injury prevention program on lower extremity biomechanics in children. Am. J. Sports Med
. 2011; 39: 949–57.
28. DiStefano LJ, Padua DA, DiStefano MJ, Marshall SW. Influence of age, sex, technique, and exercise program on movement patterns after an anterior cruciate ligament injury prevention program in youth soccer players. Am. J. Sports Med
. 2009; 37: 495–505.
29. Donaldson A, Finch CF. Applying implementation science to sports injury prevention. Br. J. Sports Med
. 2013; 47: 473–5.
30. Donaldson A, Finch CF. Planning for implementation and translation: seek first to understand the end-users’ perspectives. Br. J. Sports Med
. 2012; 46: 306–7.
31. Earl JE, Monteiro SK, Snyder KR. Differences in lower extremity kinematics between a bilateral drop-vertical jump and a single-leg step-down. J. Orthop. Sports Phys. Ther
. 2007; 37: 245–52.
32. Emery CA. Injury prevention and future research. Med. Sport Sci
. 2005; 48: 179–200.
33. Finch CF. No longer lost in translation: the art and science of sports injury prevention implementation research. Br. J. Sports Med
. 2011; 45: 1253–7.
34. Finch CF, Gabbe BJ, Lloyd DG, et al. Towards a national sports safety strategy: addressing facilitators and barriers towards safety guideline uptake. Inj. Prev
. 2011; 17: 1–10.
35. Finch CF, White P, Twomey D, Ullah S. Implementing an exercise-training programme to prevent lower-limb injuries: considerations for the development of a randomised controlled trial intervention delivery plan. Br. J. Sports Med
. 2011; 45: 791–6.
36. Fleming DW, Binder S, editors. National Center for Injury Prevention and Control. CDC Injury Research Agenda
. Atlanta (GA): Centers for Disease Control and Prevention, 2002.
37. Ford KR, Myer GD, Smith RL, et al. A comparison of dynamic coronal plane excursion between matched male and female athletes when performing single leg landings. Clin. Biomech
. 2006; 21: 33–40.
38. Fredericson M, Cookingham CL, Chaudhari AM, et al. Hip abductor weakness in distance runners with iliotibial band syndrome. Clin. J. Sport Med
. 2000; 10: 169–75.
39. Fredericson M, Misra AK. Epidemiology and aetiology of marathon running injuries. Sports Med
. 2007; 37: 437–9.
40. Fredericson M, Moore T. Muscular balance, core stability, and injury prevention for middle- and long-distance runners. Phys. Med. Rehabil. Clin. N. Am
. 2005; 16: 669–89.
41. Frost D, Andersen J, Lam T, et al. The relationship between general measures of fitness, passive range of motion and whole-body movement quality. Ergonomics
. 2012; 56: 637–49.
42. Gabbett TJ. Incidence, site, and nature of injuries in amateur rugby league over three consecutive seasons. Br. J. Sports Med
. 2000; 34: 98–103.
43. Gehring D, Melnyk M, Gollhofer A. Gender and fatigue have influence on knee joint control strategies during landing. Clin. Biomech
. 2009; 24: 82–7.
44. Gilchrist J, Mandelbaum BR, Melancon H, et al. A randomized controlled trial to prevent noncontact anterior cruciate ligament injury in female collegiate soccer players. Am. J. Sports Med
. 2008; 36: 1476–83.
45. Goetschius J, Smith HC, Vacek PM, et al. Application of a clinic-based algorithm as a tool to identify female athletes at risk for anterior cruciate ligament injury: a prospective cohort study with a nested, matched case-control analysis. Am. J. Sports Med
. 2012; 40: 1978–84.
46. Gregg S. Musculoskeletal Conditions Per M2 Database Analysis for FY 2007 [M2 Database]
. Ft Sam Houston: M2 Database, 2008 [5 June 2008].
47. Gribble PA, Hertel J, Denegar CR. Chronic ankle instability and fatigue create proximal joint alterations during performance of the Star Excursion Balance Test. Int. J. Sports Med
. 2007; 28: 236–42.
48. Gribble PA, Hertel J, Denegar CR, Buckley WE. The effects of fatigue and chronic ankle instability on dynamic postural control. J. Athl. Train
. 2004; 39: 321–9.
49. Gribble PA, Tucker WS, White PA. Time-of-day influences on static and dynamic postural control. J. Athl. Train
. 2007; 42: 35–41.
50. Hagglund M, Walden M, Ekstrand J. Risk factors for lower extremity muscle injury in professional soccer: the UEFA Injury Study. Am. J. Sports Med
. 2013; 41: 327–35.
51. Hamill J, Miller R, Noehren B, Davis I. A prospective study of iliotibial band strain in runners. Clin. Biomech
. 2008; 23: 1018–25.
52. Harman DR, Hooper TI, Gackstetter GD. Aeromedical evacuations from Operation Iraqi Freedom: a descriptive study. Mil. Med
. 2005; 170: 521–7.
53. Henderson NE, Knapik JJ, Shaffer SW, et al. Injuries and injury risk factors among men and women in U.S. Army Combat Medic Advanced individual training. Mil. Med
. 2000; 165: 647–52.
54. Herman DC, Onate JA, Weinhold PS, et al. The effects of feedback with and without strength training on lower extremity biomechanics. Am. J. Sports Med
. 2009; 37: 1301–8.
55. Herrington L, Hatcher J, Hatcher A, McNicholas M. A comparison of Star Excursion Balance Test reach distances between ACL deficient patients and asymptomatic controls. Knee
. 2009; 16: 149–52.
56. Hewett TE, Lindenfeld TN, Riccobene JV, Noyes FR. The effect of neuromuscular training on the incidence of knee injury in female athletes. A prospective study. Am. J. Sports Med
. 1999; 27: 699–706.
57. Hides JA, Jull GA, Richardson CA. Long-term effects of specific stabilizing exercises for first-episode low back pain. Spine
. 2001; 26: E243–8.
58. Holmich P, Larsen K, Krogsgaard K, Gluud C. Exercise program for prevention of groin pain in football players: a cluster-randomized trial. Scand. J. Med. Sci. Sports
. 2010; 20: 814–21.
59. Hooper DR, Szivak TK, Distefano LJ, et al. Effects of resistance training fatigue on joint biomechanics. J. Strength Cond. Res
. 2013; 27: 146–53.
60. Houck JR, Duncan A, De Haven KE. Comparison of frontal plane trunk kinematics and hip and knee moments during anticipated and unanticipated walking and side step cutting tasks. Gait Posture
. 2006; 24: 314–22.
61. Hrysomallis C. Relationship between balance ability, training and sports injury risk. Sports Med
. 2007; 37: 547–56.
62. Hubscher M, Zech A, Pfeifer K, et al. Neuromuscular training for sports injury prevention: a systematic review. Med. Sci. Sports Exerc
. 2010; 42: 413–21.
63. Huston LJ, Vibert B, Ashton-Miller JA, Wojtys EM. Gender differences in knee angle when landing from a drop-jump. Am. J. Knee Surg
. 2001; 14: 215–20.
64. Ireland ML, Willson JD, Ballantyne BT, Davis IM. Hip strength in females with and without patellofemoral pain. J. Orthop. Sports Phys. Ther
. 2003; 33: 671–6.
65. Jacobs CA, Uhl TL, Mattacola CG, et al. Hip abductor function and lower extremity landing kinematics: sex differences. J. Athl. Train
. 2007; 42: 76–83.
66. Johnson BA, Carmack D, Neary M, et al. Operation Iraqi Freedom: the Landstuhl Regional Medical Center experience. J. Foot Ankle Surg
. 2005; 44: 177–83.
67. Jones BH, Canham-Chervak M, Canada S, et al. Medical surveillance of injuries in the U.S. Military descriptive epidemiology and recommendations for improvement. Am. J. Prev. Med
. 2010; 38: S42–60.
68. Jones BH, Cowan DN, Tomlinson JP, et al. Epidemiology of injuries associated with physical training among young men in the army. Med. Sci. Sports Exerc
. 1993; 25: 197–203.
69. Jones BH, Knapik JJ. Physical training and exercise-related injuries. Surveillance, research and injury prevention in military populations. Sports Med
. 1999; 27: 111–25.
70. Kibler WB, Press J, Sciascia A. The role of core stability in athletic function. Sports Med
. 2006; 36: 189–98.
71. Kiesel K, Plisky P, Butler R. Functional movement test scores improve following a standardized off-season intervention program in professional football players. Scand. J. Med. Sci. Sports
. 2011; 21: 287–92.
72. Kiesel K, Plisky PJ, Voight ML. Can serious injury in professional football be predicted by a preseason functional movement screen? N. Am. J. Sports Phys. Ther
. 2007; 2: 147–58.
73. Knapik JJ, Bauman CL, Jones BH, et al. Preseason strength and flexibility imbalances associated with athletic injuries in female collegiate athletes. Am. J. Sports Med
. 1991; 19: 76–81.
74. Knapik JJ, Bullock SH, Canada S, et al. Influence of an injury reduction program on injury and fitness outcomes among soldiers. Inj. Prev
. 2004; 10: 37–42.
75. Knapik JJ, Canham-Chervak M, Hauret K, et al. Army basic training: injury rates and risk factors. Mil. Med
. 2001; 166: 641–7.
76. Knapik JJ, Jones SB, Darakjy S, et al. Injury rates and injury risk factors among U.S. Army wheel vehicle mechanics. Mil. Med
. 2007; 172: 988–96.
77. Knapik JJ, Sharp MA, Canham-Chervak M, et al. Risk factors for training-related injuries among men and women in basic combat training. Med. Sci. Sports Exerc
. 2001; 33: 946–54.
78. LaBella CR, Huxford MR, Grissom J, et al. Effect of neuromuscular warm-up on injuries in female soccer and basketball athletes in urban public high schools: cluster randomized controlled trial. Arch. Pediatr. Adolesc. Med
. 2011; 165: 1033–40.
79. Landry SC, McKean KA, Hubley-Kozey CL, et al. Neuromuscular and lower limb biomechanical differences exist between male and female elite adolescent soccer players during an unanticipated side-cut maneuver. Am. J. Sports Med
. 2007; 35: 1888–900.
80. Lee JH, Hoshino Y, Nakamura K, et al. Trunk muscle weakness as a risk factor for low back pain. A 5-year prospective study. Spine
. 1999; 24: 54–7.
81. Leetun DT, Ireland ML, Willson JD, et al. Core stability measures as risk factors for lower extremity injury in athletes. Med. Sci. Sports Exerc
. 2004; 36: 926–34.
82. Lehance C, Binet J, Bury T, Croisier JL. Muscular strength, functional performances and injury risk in professional and junior elite soccer players. Scand. J. Med. Sci. Sports
. 2008; 19: 243–51.
83. Lehr ME, Plisky PJ, Butler RJ, et al. Field-expedient screening and injury risk algorithm categories as predictors of noncontact lower extremity injury. Scand. J. Med. Sci. Sports
. 2013; 23: e225–32.
84. Lephart SM, Abt JP, Ferris CM. Neuromuscular contributions to anterior cruciate ligament injuries in females. Curr. Opin. Rheumatol
. 2002; 14: 168–73.
85. Liederbach M, Dilgen FE, Rose DJ. Incidence of anterior cruciate ligament injuries among elite ballet and modern dancers: a 5-year prospective study. Am. J. Sports Med
. 2008; 36: 1779–88.
86. Lincoln AE, Smith GS, Amoroso PJ, Bell NS. The natural history and risk factors of musculoskeletal conditions resulting in disability among US Army personnel. Work
. 2002; 18: 99–113.
87. Lisman P, O’Connor FG, Deuster PA, Knapik JJ. Functional movement screen and aerobic fitness predict injuries in military training. Med. Sci. Sports Exerc
. 2013; 45: 636–43.
88. Ludewig PM, Lawrence RL, Braman JP. What’s in a name? using movement system diagnoses versus pathoanatomic diagnoses. J. Orthop. Sports Phys. Ther
. 2013; 43: 280–3.
89. Magalhaes E, Silva AP, Sacramento SN, et al. Isometric strength ratios of the hip musculature in females with patellofemoral pain: a comparison to painfree controls. J. Strength Cond. Res
. 2012; 7: 2165–70.
90. Marshall SW, Covassin T, Dick R, et al. Descriptive epidemiology of collegiate women’s gymnastics injuries: National Collegiate Athletic Association Injury Surveillance System, 1988–1989 through 2003–2004. J. Athl. Train
. 2007; 42: 234–40.
91. McClay I, Manal K. A comparison of three-dimensional lower extremity kinematics during running between excessive pronators and normals. Clin. Biomech
. 1998; 13: 195–203.
92. McGill S, Frost D, Andersen J, et al. Movement quality and links to measures of fitness in firefighters. Work
93. McGill SM, Andersen JT, Horne AD. Predicting performance and injury resilience from movement quality and fitness scores in a basketball team over 2 years. J. Strength Cond. Res
. 2012; 26: 1731–9.
94. McLean SG, Fellin RE, Suedekum N, et al. Impact of fatigue on gender-based high-risk landing strategies. Med. Sci. Sports Exerc
. 2007; 39: 502–14.
95. McLean SG, Huang X, van den Bogert AJ. Association between lower extremity posture at contact and peak knee valgus moment during sidestepping: implications for ACL injury. Clin. Biomech
. 2005; 20: 863–70.
96. McLean SG, Samorezov JE. Fatigue-induced ACL injury risk stems from a degradation in central control. Med. Sci. Sports Exerc
. 2009; 41: 1661–72.
97. McMillian DJ, Moore JH, Hatler BS, Taylor DC. Dynamic vs. static-stretching warm up: the effect on power and agility performance. J. Strength Cond. Res
. 2006; 20: 492–9.
98. McNair PJ, Prapavessis H, Callender K. Decreasing landing forces: effect of instruction. Br. J. Sports Med
. 2000; 34: 293–6.
99. Milner CE, Davis IS, Hamill J. Free moment as a predictor of tibial stress fracture in distance runners. J. Biomech
. 2006; 39: 2819–25.
100. Milner CE, Ferber R, Pollard CD, et al. Biomechanical factors associated with tibial stress fracture in female runners. Med. Sci. Sports Exerc
. 2006; 38: 323–8.
101. Milner CE, Hamill J, Davis I. Are knee mechanics during early stance related to tibial stress fracture in runners? Clin. Biomech
. 2007; 22: 697–703.
102. Molsa J, Kujala U, Nasman O, et al. Injury profile in ice hockey from the 1970s through the 1990s in Finland. Am. J. Sports Med
. 2000; 28: 322–7.
103. Myer GD, Ford KR, Hewett TE. Rationale and clinical techniques for anterior cruciate ligament injury prevention among female athletes. J. Athl. Train
. 2004; 39: 352–64.
104. Myer GD, Ford KR, Khoury J, et al. Development and validation of a clinic-based prediction tool to identify female athletes at high risk for anterior cruciate ligament injury. Am. J. Sports Med
. 2010; 38: 2025–33.
105. Myklebust G, Maehlum S, Engebretsen L, et al. Registration of cruciate ligament injuries in Norwegian top level team handball. A prospective study covering two seasons. Scand. J. Med. Sci. Sports
. 1997; 7: 289–92.
106. Myklebust G, Maehlum S, Holm I, Bahr R. A prospective cohort study of anterior cruciate ligament injuries in elite Norwegian team handball. Scand. J. Med. Sci. Sports
. 1998; 8: 149–53.
107. Nadler SF, Malanga GA, DePrince M, et al. The relationship between lower extremity injury, low back pain, and hip muscle strength in male and female collegiate athletes. Clin. J. Sport Med
. 2000; 10: 89–97.
108. Niemuth PE, Johnson RJ, Myers MJ, Thieman TJ. Hip muscle weakness and overuse injuries in recreational runners. Clin. J. Sport Med
. 2005; 15: 14–21.
109. Noehren B, Davis I, Hamill J. ASB clinical biomechanics award winner 2006 prospective study of the biomechanical factors associated with iliotibial band syndrome. Clin. Biomech
. 2007; 22: 951–6.
110. O’Connor FG, Deuster PA, Davis J, et al. Functional movement screening: predicting injuries in officer candidates. Med. Sci. Sports Exerc
. 2011; 43: 2224–30.
111. Oberlander KD, Bruggemann GP, Hoher J, Karamanidis K. Altered landing mechanics in ACL-reconstructed patients. Med. Sci. Sports Exerc
. 2013; 45: 506–13.
112. Olmsted LC, Carcia CR, Hertel J, Shultz SJ. Efficacy of the star excursion balance tests in detecting reach deficits in subjects with chronic ankle instability. J. Athl. Train
. 2002; 37: 501–6.
113. Onate JA, Guskiewicz KM, Marshall SW, et al. Instruction of jump–landing technique using videotape feedback: altering lower extremity motion patterns. Am. J. Sports Med
. 2005; 33: 831–42.
114. Onate JA, Guskiewicz KM, Sullivan RJ. Augmented feedback reduces jump landing forces. J. Orthop. Sports Phys. Ther
. 2001; 31: 511–7.
115. Orchard J, Marsden J, Lord S, Garlick D. Preseason hamstring muscle weakness associated with hamstring muscle injury in Australian footballers. Am. J. Sports Med
. 1997; 25: 81–5.
116. Orishimo KF, Kremenic IJ, Mullaney MJ, et al. Adaptations in single-leg hop biomechanics following anterior cruciate ligament reconstruction. Knee Surg. Sports Traumatol. Arthrosc
. 2010; 18: 1587–93.
117. Owens BD, Cameron KL, Duffey ML, et al. Military movement training program improves jump–landing mechanics associated with anterior cruciate ligament injury risk. J. Surg. Orthop. Adv
. 2013; 22: 66–70.
118. Padua DA. Executing a collaborative prospective risk-factor study: findings, successes, and challenges. J. Athl. Train
. 2010; 45: 519–21.
119. Padua DA, Boling MC, Distefano LJ, et al. Reliability of the Landing Error Scoring System-real time, a clinical assessment tool of jump–landing biomechanics. J. Sport. Rehabil
. 2011; 20: 145–56.
120. Padua DA, DiStefano LJ, Marshall SW, et al. Retention of movement pattern changes after a lower extremity injury prevention program is affected by program duration. Am. J. Sports Med
. 2012; 40: 300–6.
121. Padua DA, Marshall SW, Boling MC, et al. The Landing Error Scoring System (LESS) is a valid and reliable clinical assessment tool of jump–landing biomechanics: The JUMP-ACL study. Am. J. Sports Med
. 2009; 37: 1996–2002.
122. Parkkari J, Kujala UM, Kannus P. Is it possible to prevent sports injuries? Review of controlled clinical trials and recommendations for future work. Sports Med
. 2001; 31: 985–95.
123. Paterno MV, Schmitt LC, Ford KR, et al. Biomechanical measures during landing and postural stability predict second anterior cruciate ligament injury after anterior cruciate ligament reconstruction and return to sport. Am. J. Sports Med
. 2010; 38: 1968–78.
124. Peate WF, Bates G, Lunda K, et al. Core strength: a new model for injury prediction and prevention. J. Occup. Med. Toxicol
. 2007; 2: 3.
125. Piva SR, Goodnite EA, Childs JD. Strength around the hip and flexibility of soft tissues in individuals with and without patellofemoral pain syndrome. J. Orthop. Sports Phys. Ther
. 2005; 35: 793–801.
126. Plisky P, Gorman P, Kiesel K, et al. The reliability of an instrumented device for measuring components of the Star Excursion Balance Test. N. Am. J. Sports Phys. Ther
. 2009; 4: 92–9.
127. Plisky PJ, Rauh MJ, Kaminski TW, Underwood FB. Star Excursion Balance Test as a predictor of lower extremity injury in high school basketball players. J. Orthop. Sports Phys. Ther
. 2006; 36: 911–9.
128. Pohl MB, Mullineaux DR, Milner CE, et al. Biomechanical predictors of retrospective tibial stress fractures in runners. J. Biomech
. 2008; 41: 1160–5.
129. Prapavessis H, McNair PJ. Effects of instruction in jumping technique and experience jumping on ground reaction forces. J. Orthop. Sports Phys. Ther
. 1999; 29: 352–6.
130. Prapavessis H, McNair PJ, Anderson K, Hohepa M. Decreasing landing forces in children: the effect of instructions. J. Orthop. Sports Phys. Ther
. 2003; 33: 204–7.
131. Rahnama N, Lees A, Bambaecichi E. Comparison of muscle strength and flexibility between the preferred and non-preferred leg in English soccer players. Ergonomics
. 2005; 48: 1568–75.
132. Rauh MJ, Margherita AJ, Rice SG, et al. High school cross country running injuries: a longitudinal study. Clin. J. Sport Med
. 2000; 10: 110–6.
133. Rivera JC, Wenke JC, Buckwalter JA, et al. Posttraumatic osteoarthritis caused by battlefield injuries: the primary source of disability in warriors. J. Am. Acad. Orthop. Surg
. 2012; 20 (1 suppl): S64–9.
134. Rosendal L, Langberg H, Skov-Jensen A, Kjaer M. Incidence of injury and physical performance adaptations during military training. Clin. J. Sport Med
. 2003; 13: 157–63.
135. Rudzki SJ. Injuries in Australian Army recruits. Part II: Location and cause of injuries seen in recruits. Mil. Med
. 1997; 162: 477–80.
136. Sadoghi P, von Keudell A, Vavken P. Effectiveness of anterior cruciate ligament injury prevention training programs. J. Bone Joint Surg. Am
. 2012; 94: 769–76.
137. Saunders N, Otago L, Romiti M, et al. Coaches’ perspectives on implementing an evidence-informed injury prevention programme in junior community netball. Br. J. Sports Med
. 2010; 44: 1128–32.
138. Schneiders AG, Davidsson A, Horman E, Sullivan SJ. Functional movement screen normative values in a young, active population. Int. J. Sports Phys. Ther
. 2011; 6: 75–82.
139. Shirey M, Hurlbutt M, Johansen N, et al. The influence of core musculature engagement on hip and knee kinematics in women during a single leg squat. Int. J. Sports Phys. Ther
. 2012; 7: 1–12.
140. Smith HC, Johnson RJ, Shultz SJ, et al. A prospective evaluation of the Landing Error Scoring System (LESS) as a screening tool for anterior cruciate ligament injury risk. Am. J. Sports Med
. 2012; 40: 521–6.
141. Songer TJ, LaPorte RE. Disabilities due to injury in the military. Am. J. Prev. Med
. 2000; 18: 33–40.
142. Sugimoto D, Myer GD, Bush HM, et al. Compliance with neuromuscular training and anterior cruciate ligament injury risk reduction in female athletes: a meta-analysis. J. Athl. Train
. 2012; 47: 714–23.
143. Taunton JE, Ryan MB, Clement DB, et al. A retrospective case-control analysis of 2002 running injuries. Br. J. Sports Med
. 2002; 36: 95–101.
144. Teyhen DS. Physical therapy in a peacekeeping operation: Operation Joint Endeavor/Operation Joint Guard. Mil. Med
. 1999; 164: 590–4.
145. Teyhen DS, Shaffer SW, Lorenson CL, et al. The Functional Movement Screen: a reliability study. J. Orthop. Sports Phys. Ther
. 2012; 42: 530–40.
146. Teyhen DS, Shaffer SW, Umlauf JA, et al. Automation to improve efficiency of field expedient injury prediction screening. J. Strength Cond. Res
. 2012; 26 (Suppl. 2): S61–72.
147. Teyhen DS, Stoltenberg BE, Collinsworth KM, et al. Dynamic plantar pressure parameters associated with static arch height index during gait. Clin. Biomech
. 2009; 24: 391–6.
148. Thorpe JL, Ebersole KT. Unilateral balance performance in female collegiate soccer athletes. J. Strength Cond. Res
. 2008; 22: 1429–33.
149. Tripp BL, Yochem EM, Uhl TL. Functional fatigue and upper extremity sensorimotor system acuity in baseball athletes. J. Athl. Train
. 2007; 42: 90–8.
150. Trojian TH, McKeag DB. Single leg balance test to identify risk of ankle sprains. Br. J. Sports Med
. 2006; 40: 610–3.
151. Truax AL, Chandnani VP, Chacko AK, Gonzalez DM. Incidence and methods of diagnosis of musculoskeletal injuries incurred in Operations Desert Shield and Desert Storm. Invest. Radiol
. 1997; 32: 169–73.
152. Tyler TF, McHugh MP, Mirabella MR, et al. Risk factors for noncontact ankle sprains in high school football players: the role of previous ankle sprains and body mass index. Am. J. Sports Med
. 2006; 34: 471–5.
153. United States Department of Labor — Bureau of Labor S. [cited 2013 1-23-13]. Available from: http://www.bls.gov/iif/home.htm
154. van Mechelen W. Running injuries. A review of the epidemiological literature. Sports Med
. 1992; 14: 320–35.
155. Verhagen EA, Bay K. Optimising ankle sprain prevention: a critical review and practical appraisal of the literature. Br. J. Sports Med
. 2010; 44: 1082–8.
156. Vrbanic TS, Ravlic-Gulan J, Gulan G, Matovinovic D. Balance index score as a predictive factor for lower sports results or anterior cruciate ligament knee injuries in Croatian female athletes–preliminary study. Coll. Antropol
. 2007; 31: 253–8.
157. Walden M, Atroshi I, Magnusson H, et al. Prevention of acute knee injuries in adolescent female football players: cluster randomised controlled trial. Br. Med. J
. 2012; 344: e3042.
158. Wasserman GM, Martin BL, Hyams KC, et al. A survey of outpatient visits in a United States Army forward unit during Operation Desert Shield. Mil. Med
. 1997; 162: 374–9.
159. Wilkerson GB, Giles JL, Seibel DK. Prediction of core and lower extremity strains and sprains in collegiate football players: a preliminary study. J. Athl. Train
. 2012; 47: 264–72.
160. Willardson JM. Core stability training: applications to sports conditioning programs. J. Strength Cond. Res
. 2007; 21: 979–85.
161. Williams DS 3rd, Davis IM, Scholz JP, et al. High-arched runners exhibit increased leg stiffness compared to low-arched runners. Gait Posture
. 2004; 19: 263–9.
162. Willson JD, Davis IS. Lower extremity mechanics of females with and without patellofemoral pain across activities with progressively greater task demands. Clin. Biomech
. 2008; 23: 203–11.
163. Willson JD, Dougherty CP, Ireland ML, Davis IM. Core stability and its relationship to lower extremity function and injury. J. Am. Acad. Orthop. Surg
. 2005; 13: 316–25.
164. Willson JD, Ireland ML, Davis I. Core strength and lower extremity alignment during single leg squats. Med. Sci. Sports Exerc
. 2006; 38: 945–52.
165. Wojtys EM, Wylie BB, Huston LJ. The effects of muscle fatigue on neuromuscular function and anterior tibial translation in healthy knees. Am. J. Sports Med
. 1996; 24: 615–21.
166. Yang J, Tibbetts AS, Covassin T, et al. Epidemiology of overuse and acute injuries among competitive collegiate athletes. J. Athl. Train
. 2012; 47: 198–204.
167. Yoo JH, Lim BO, Ha M, et al. A meta-analysis of the effect of neuromuscular training on the prevention of the anterior cruciate ligament injury in female athletes. Knee Surg. Sports Traumatol. Arthrosc
. 2010; 18: 824–30.
168. Zifchock RA, Davis I, Hamill J. Kinetic asymmetry in female runners with and without retrospective tibial stress fractures. J. Biomech
. 2006; 39: 2792–7.
169. Zifchock RA, Davis I, Higginson J, et al. Side-to-side differences in overuse running injury susceptibility: A retrospective study. Hum. Mov. Sci
. 2008; 27: 888–902.