Do Functional Movement Screen (FMS) composite scores predict subsequent injury? A systematic review with meta-analysis

Moran, Robert; Schneiders, Anthony G.; Mason, Jesse; Sullivan, S. John

doi:10.1136/bjsports-2016-096938

Cited by 164 publications

(140 citation statements)

References 85 publications

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“…As time between baseline assessment and injury occurrence increases the likelihood of confounders explaining an increase in injury risk increases. They suggest investigators consider the use of repeat assessments to improve construct validity [37].…”

Section: Discussionmentioning

confidence: 99%

Single leg squat ratings by clinicians are reliable and predict excessive hip internal rotation moment

Barker-Davies

Roberts²,

Bennett

et al. 2018

Gait & Posture

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Section: Discussionmentioning

confidence: 99%

Single leg squat ratings by clinicians are reliable and predict excessive hip internal rotation moment

Barker-Davies

Roberts²,

Bennett

et al. 2018

Gait & Posture

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“…36 Table 1, most participants were enlisted men who had completed at least some college coursework. The average participant had been exposed to approximately 3 types of traumatic events, had substantial combat exposure, and registered FM and balance scores that, according to published studies, 7,8,10,12,14 were within normal ranges. Nearly 4 of 5 participants endorsed a history of physical injury affecting at least 1 area of the body (eg, trunk, lower extremity).…”

Section: Methodsmentioning

confidence: 99%

“…9 Some attention has been given to measures of fundamental movement patterns and dynamic balance as univariate predictors of injury in sport participants and tactical athletes with varied results. 10 In a multivariate paradigm, however, Lehr et al 11 reported that FM characteristics combined algorithmically with injury history and bodily pain to predict injury occurrence in collegiate athletes. Bodden et al 7 showed that fundamental movements improved as a result of an 8-week ''corrective exercise program'' in mixed martial arts athletes, whereas Stanek et al 8 achieved similar results with male firefighters.…”

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confidence: 99%

Trauma Exposure and Functional Movement Characteristics of Male Tactical Athletes

Taylor

Hernández

Sessoms

et al. 2020

Journal of Athletic Training

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Context: Tactical athletes commonly experience high levels of physical stress, which may increase their risk of musculoskeletal injury. It is critical to understand psychological predictors of functional movement (FM), which may help prevent musculoskeletal injury in this population.Objective: To determine the associations of combat and trauma exposure with FM characteristics of male tactical athletes. Secondary objectives were to explore confounding influences of age and physical injury history as well as the mediating role of bodily pain.Design: Cross-sectional study. Setting: Research laboratory. Patients or Other Participants: Eighty-two healthy, male, active-duty US Navy Explosive Ordnance Disposal personnel (age ¼ 34.0 6 6.7 years).Main Outcome Measure(s): Participants completed measures of combat exposure, trauma exposure, physical injury history, and bodily pain. We assessed FM characteristics (ie, Functional Movement Screen [FMS], Y-Balance Test), from which we derived a composite functional status (CFS) measure.Hypotheses were tested using correlational and multiple regression (causal-steps) models.Results: In unadjusted models, trauma exposure was inversely associated with the FMS (P ¼ .005) and CFS (P ¼ .009) scores. In adjusted models, these relationships were robust to the confounding influences of age and physical injury history. Trauma exposure and bodily pain were substantive, independent predictors of FMS and CFS in causal-steps models (all P values , .05), implying additive rather than mediated effects (R 2 adj ¼ 0.18-0.20). Combat exposure did not predict FM characteristics.Conclusions: To our knowledge, this is the first evidence of the influence of trauma exposure on the FM characteristics of male tactical athletes, independent of age, physical injury, and bodily pain. This program of research may help to advance the prevention and treatment of musculoskeletal injuries in the tactical environment.Greater trauma exposure was associated with lower scores for functional movement. The influence of trauma exposure on functional movement was neither confounded by physical injury nor mediated by bodily pain. These findings will inform algorithms that are designed to predict injury risk in military and other tactical athletes. Clinicians and researchers in sports medicine and orthopaedic settings should consider the individual's trauma history when performing preparticipation physical screening and assessment after injury.

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“…Although the sports medicine model of injury prevention and treatment emerged to meet the special needs of competitive athletes, its applicability to problems encountered in the occupational setting has been recognized (Bigos & Davis, ; Lively, ; Larson et al., ). Because traditional methods for management of musculoskeletal injuries do not typically restore neuromuscular control to a level that minimizes risk for re‐injury and progressive dysfunction (Mottram & Comerford, ; Maffulli, Longo, Gougoulias, Loppini, & Denaro, ; Pietrosimone, McLeod, & Lepley, ; Ward et al., ), a variety of “movement efficiency” screening procedures, similar to the ones demonstrated in this study, are increasingly being used to assign scores that are widely believed to relate to both sport and occupational injury risk (Moran, Schneiders, Mason, & Sullivan, ).…”

Section: Developing Injury Risk Models For Occupational Settingsmentioning

confidence: 99%

Who is More Injury‐Prone? Prediction and Assessment of Injury Risk

et al. 2018

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Injuries are the primary determinant of an individual's mobility, which affect not just their workplace productivity in intensive environments such as manufacturing, but also their decision‐making ability and quality of life. Managers typically assign workers to projects or tasks without having knowledge about their functional capabilities or current state of injury risk as injuries remain highly underreported at workplaces for fear of reprisal and other reasons. Therefore, high‐quality research on injury prevention is nearly nonexistent. Procedures that we use in this study for developing a prediction model for identification of college football players at an elevated injury risk could also be used to quantify injury risk in various occupational settings. Using a number of measurements and models, we arrive at an estimate of an individual's injury likelihood. Our measures include ratings of movement efficiency through physical performance tests, acceleration using Internet of Things (IoT) devices, functional role classifications, and recorded exposures to high‐risk conditions. Findings prescribe several approaches and decision rules for prediction of injury risk and suggest that training programs need to consider an individual's injury risk rather than offer a ‘one‐size‐fits‐all’ approach. The analytics models derived from a combination of injury risk screening and surveillance data can be used for making decisions about targeting employee‐centric risk‐reduction interventions, improved matching of tasks to individuals, or deciding job rotation for improved performance, all while enhancing the quality of life of individuals and reducing the escalating costs of work‐related injuries borne by employers. These models can also be developed for smartphones.

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Do Functional Movement Screen (FMS) composite scores predict subsequent injury? A systematic review with meta-analysis

Abstract: PROSPERO registration number CRD42015025575.

Cited by 164 publications

References 85 publications

Single leg squat ratings by clinicians are reliable and predict excessive hip internal rotation moment

Single leg squat ratings by clinicians are reliable and predict excessive hip internal rotation moment

Trauma Exposure and Functional Movement Characteristics of Male Tactical Athletes

Who is More Injury‐Prone? Prediction and Assessment of Injury Risk

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