Evaluation of a Novel Field Expedient Musculoskeletal Readiness Screening Tool in an Army Basic Training Population

Hearn, Darren; Rhon, Daniel I.; Goss, Donald; Thelen, Mark

doi:10.7205/milmed-d-16-00384

Cited by 10 publications

(6 citation statements)

References 25 publications

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“…MSKIs accounted for 59% of all limited duty days in the US Army, compared to 10% attributed to behavioural health conditions across the first six months of 2019 (Molloy et al, 2020). More than 50% of US soldiers sustained at least one injury (MSKI or non‐MSKI) in 2017; many MSKIs result in lost duty days among US Army trainees and operational soldiers (Hearn, Rhon, Goss, & Thelen, 2017; Teyhen et al, 2018). Similarly, more than half of 660 male soldiers from three British Army infantry battalions sustained at least one injury across one year of pre‐deployment training (Wilkinson et al, 2011) and 52% of Israeli infantry and armour conscripts sustained an injury during their three years of military service (Hollander, Finestone, Yofe, Bader, & Magnezi, 2020).…”

Section: Introductionmentioning

confidence: 99%

Much work remains to reach consensus on musculoskeletal injury risk in military service members: A systematic review with meta‐analysis

Rhon

Molloy

Monnier

et al. 2021

European Journal of Sport Science

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Musculoskeletal injuries are the most common reason military service members cannot perform their military duties. Not only are they costly and associated with long-term disability, often long after completion of military service, but injuries also adversely affect the military readiness of a nation. This can be seen as a threat to national security and part of the impetus behind many efforts to better understand, predict, and mitigate injury risk in the military. A systematic review of the literature published between 1995 and October 31, 2020 was conducted to identify significant risk factors of musculoskeletal injury in military populations across the world. 74 out of 170 eligible studies addressed comprehensive injuries, providing 994 unique risk factors. 46 of these studies provided data that could be included in a meta-analysis, which was possible for 15 predictor variables. Seven predictors were significant in meta-analysis: female sex(RR=1.46;95CI 1.30,1.64), high body mass index(RR=1.36;95CI 1.21,1.53), functional movement screen pain (RR=1.70;95CI 1.55,1.87) or scores ≤ 14(RR=1.42 95CI 1.29,1.56), prior injury (RR=1.54;95CI 1.32,1.80), slower running performance(RR=1.33;95CI 1.18,1.51), and poorer pushup performance(RR=1.15;95CI 1.04,1.27). Low BMI, height, weight, smoking, physical activity scores, and sit-up and jump performance were not significant risk factors in the meta-analysis. Most studies had a high risk of bias. Lack of raw data and large heterogeneity in definitions of predictors and injury outcomes limited comparison across many studies. Highlights. Female sex, high body mass index, pain with functional movement screen or a score of ≤ 14, prior injury, slower running performance and poorer push-up performance were all significant predictors of musculoskeletal injury. . Low body mass index, height, weight, smoking, physical activity scores, and sit-up and jump performance were not significant predictors of musculoskeletal injury. . Many other predictors were present only in single studies, but large heterogeneity in definitions of both outcomes and predictors limited comparison across studies. . Overall, studies assessing risk factors to predict musculoskeletal injuries in the military were at high risk for bias, especially in regards to statistical approaches.

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Section: Introductionmentioning

confidence: 99%

Much work remains to reach consensus on musculoskeletal injury risk in military service members: A systematic review with meta‐analysis

Rhon

Molloy

Monnier

et al. 2021

European Journal of Sport Science

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“…To ensure preventive strategies are cost-effectively offered to those at risk, an effective field-accessible screening tool that identifies modifiable risk factors must be established. MSK injury prediction models that combine demographic and movementbased risk factors have been developed (15)(16)(17) but are limited to prediction of general or lower extremity MSK injuries. Few, if any, studies have investigated whether a movement-based screening tool is predictive of UQI specifically.…”

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confidence: 99%

Predicting Upper Quadrant Musculoskeletal Injuries in the Military: A Cohort Study

Campbell

Parent

Crumback

et al. 2021

Medicine &Amp; Science in Sports &Amp; Exercise

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Purpose: This study aimed to identify characteristics and movement-based tests that predict upper quadrant musculoskeletal injury (UQI) in military personnel over a 12-month follow-up. Methods: A prospective observational cohort study of military members (n = 494; 91.9% male) was conducted. Baseline predictors associated with UQI were gathered through surveys and movement-based tests. Survey data included demographic information, injury history, and biosocial factors. Movement-based tests include the following: Y Balance Tests (YBT), Functional Movement Screen, Selective Functional Movement Assessment lumbar multisegmental mobility, modified-modified Schober, side bridge, ankle mobility, modified Sorensen, and passive lumbar extension. Self-reported UQI was collected through monthly online surveys, and 87% completed the follow-up. Univariate associations were determined between potential predictors and UQI. A forward, stepwise logistic regression model was used to identify the best combination of predictors for UQI. Results: Twenty-seven had UQI. Univariate associations existed with three demographic (smoking, >1 previous UQI, baseline upper quadrant function ≤90%), three pain-related (Selective Functional Movement Assessment rotation, side bridge, hurdle step), and six movement-based variables (YBT upper quarter (UQ) superolateral worst score ≤57.75 cm, YBT-UQ composite worst score ≤81.1%, failed shoulder clearance, Sorenson <72.14 s, in-line lunge total score <15, and in-line lunge asymmetry >1). Smoking, baseline upper quadrant function ≤90%, and YBT-UQ composite score ≤81.1% predicted UQI in the logistic regression while controlling for age and sex. Presenting two or more predictors resulted in good specificity (85.6%; odds ratio, 4.8; 95% confidence interval, 2.2-10.8), and at least one predictor resulted in 81.5% sensitivity (odds ratio, 3.2; 95% confidence interval, 1.2-8.7). Conclusions: A modifiable movement-based test (YBT-UQ), perceived upper limb function, and smoking predicted UQI. A specific (two or more) and sensitive (at least one predictor) model could identify persons at higher risk.

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“…The prevalence of symptoms during basic training ranges from 13.9% to 48.65% (80 days -26 weeks of training) 68,69,71) , with an incidence of 17.4-17.8/ 100 people/ 100 days being reported 71) , as well as 18 injuries/ 100 people/ month 72) . Injuries during basic training are most commonly in the lower limb 68,69,[73][74][75] , and may include muscle strains 68) , plantar fasciitis 68) , medial tibial stress syndrome 69,75) , sprains 68,69,75) , tendinitis 68) , arthritis 68) , and iliotibial band syndrome 69) . Injuries during basic training have been reportedly due to running, swimming, falling, walking, marching, performing sit ups, carrying equipment, unloading weapons, engaging targets, and making beds 71) .…”

Section: Physicalizationmentioning

confidence: 99%

“…Injuries during basic training have been reportedly due to running, swimming, falling, walking, marching, performing sit ups, carrying equipment, unloading weapons, engaging targets, and making beds 71) . One of the risk factors for injury during basic training is poorer fitness 73, 74,[76][77][78] . While it has not been examined, it is hypothesised that musicians who are not preparing for combat roles, may enter basic training with a lower level of physical fitness than other recruits which may result in musicians having a higher risk of injury while training.…”

Section: Physicalizationmentioning

confidence: 99%

Why do we need to investigate non-classical musicians to reduce the burden of musicians’ musculoskeletal symptoms?

Stanhope

Weinstein

2020

INDUSTRIAL HEALTH

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Musculoskeletal symptoms (MSSs) are common among professional musicians; however, most of the research has focused on orchestral/ classical musicians. In some countries orchestral and classical musicians are in the minority; hence targeting research towards these specific subgroups of musicians is unlikely to address the overall burden of musicians' MSSs, unless the research is generalizable to other types of musicians. This multidisciplinary narrative review seeks to answer the question: "why do we need to examine the MSSs of non-classical groups of performing musicians in order to reduce the burden of musicians' MSSs?". There are differences in the education, posture, tasks (e.g. military training for military band musicians, dancing for those in musical theatre), venues and management of MSSs for different types of musicians. Future research should compare classical and non-classical musicians in order to determine which specific subgroups (e.g. military band musicians) have the greatest MSS burden, such that further research into the risk factors of and interventions for MSSs can be targeted towards the subgroups of musicians with the greatest MSS burden. In doing so, we maximise the likelihood of being able to introduce interventions, policies and practice that reduce the burden of musicians' MSSs.

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Evaluation of a Novel Field Expedient Musculoskeletal Readiness Screening Tool in an Army Basic Training Population

Abstract: The MRST shows potential as a tool for identifying service members at higher risk for sustaining a musculoskeletal injury. Further research is needed to assess the validity, reliability, and responsiveness of this novel screening tool.

Cited by 10 publications

References 25 publications

Much work remains to reach consensus on musculoskeletal injury risk in military service members: A systematic review with meta‐analysis

Much work remains to reach consensus on musculoskeletal injury risk in military service members: A systematic review with meta‐analysis

Predicting Upper Quadrant Musculoskeletal Injuries in the Military: A Cohort Study

Why do we need to investigate non-classical musicians to reduce the burden of musicians’ musculoskeletal symptoms?

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