Study of the measurement and predictive validity of the Functional Movement Screen

Little associations exist between the three commonly used functional screening tests in collegiate athletes

Although an abundant number of studies have investigated the predictability of the commonly used functional screening tests and despite their popularity and applicability, the relationships between these tests have rarely been studied and have not been well established. This study aimed to examine the potential association between the Functional Movement Screen (FMS), Y Balance Test (YBT), and Landing Error Scoring System (LESS). Six hundred twenty-seven Iranian collegiate athletes (347 males, age = 22.63 ± 4.07, weight = 75.98 ± 13.79, height = 181.99 ± 10.15, BMI = 22.84 ± 3.16; and 280 females, age = 22.22 ± 3.37, weight = 60.63 ± 9.58, height = 166.55 ± 6.49, BMI = 21.81 ± 2.84) participated in this study. Following a 5-min warm-up, each participant underwent a standardized screening battery including the FMS, YBT, and LESS, and the scores were recorded and live coded for the statistical analysis, except for the LESS. The LESS tests were video recorded and scored by one expert examiner using an open-source 2D video analysis software (Kinovea- version 0.9.5), afterwards. The Spearman correlation was utilized as a measure for the correlation, and the Mann‒Whitney U test with a significance level of 0.05 was used to check the differences between male and female athletes. The statistical analysis was performed with RStudio 2023.03.0 using R 4.3.1. A small correlation (0.364) was observed between the FMS composite score and the YBT in male athletes. All other pairwise correlations were negligible among male and female athletes, ranging from - 0.096 to 0.294. Reducing the FMS to the component scores targeting the lower extremities did not alter the correlation to the other screening scores. The median FMS composite score in female athletes was significantly higher than that in males (p < 0.001). Negligible correlations exist between the FMS, LESS, and YBT; they do not measure the same values and therefore are irreplaceable with one another. A combination of these tests as a standardized screening battery may potentially better identify injury-predisposed athletes than the application of each test as a stand-alone screening test. Females outperformed males in the FMS test significantly, so sex must be considered a key variable in the FMS studies. Males had slightly higher LESS scores (median difference = 0.5) than females, but this difference is not clinically meaningful. Future research should continue to explore the relationships between various functional screening tests and identify the most effective combinations for comprehensive assessment in different populations and sports disciplines.

An international survey mapping practice and barriers for upper-limb assessments in movement analysis

BACKGROUND

Upper-limb movement analysis could improve our understanding of function, pathological mechanisms and inform rehabilitation and surgical decision-making. Despite the potential benefits, the use of clinical upper-limb motion analysis is not well established and it is not clear what the barriers to clinical motion analysis are.

RESEARCH QUESTION

What is current practice for assessment of the upper-limb and what are the barriers currently limiting upper-limb motion analysis being routinely used in clinical practice?

METHODS

A web-based questionnaire was used to collect responses through international professional movement analysis society coordinators over an 18 month-period.

RESULTS

A total of 55 responses were received and 75% of laboratories performed some form of upper-limb assessment. In total 44% of laboratories performed upper-limb assessments for clinical purposes and only 33% did 3D-movement analysis. The most commonly seen patient groups were those with neurological injury e.g. cerebral palsy (adults and children) and normal controls for comparative purposes. Barriers to upper-limb motion analysis were the availability of standard reference tasks, protocols, software, funding and clinical need. Practice was variable with no universally identified approaches to upper-limb movement analysis. Differences in practice were also identified between laboratories accredited by the Clinical Movement Analysis Society of the UK and Ireland and other international professional societies and affiliate laboratories.

SIGNIFICANCE

These findings may be used to inform the development of practice standards and progress the use of clinical motion analysis in the upper-limb. This study provides a summary and describes current practice, potentially providing access to peer support and experience for laboratories with an identified clinical need looking to conduct upper-limb assessment. A national picture (UK and Ireland) for practice regarding upper-limb assessment in this sub-population is presented. We have laid out further work which is needed to establish standards of practice or consensus initiatives for enhancing clinical upper-limb motion analysis.

Evaluation of the Functional Movement Screen (FMS) in Identifying Active Females Who are Prone to Injury. A Systematic Review

Background

The validity of the Functional Movement Screen (FMS) in identifying active females who are predisposed to injury has not been specifically reviewed. This study aims to synthesize the literature on the ability of the FMS to identify at-risk active females.

Methods

Six online databases, including PubMed, Medline, Web of Science, Science Direct, SPORTDiscus and Google Scholar, were searched for the period of April 2006 to September 2021. Out of the 61 potential references, 17 were reviewed in detail with respect to the inclusion criteria; ten were ultimately included. The risk of bias, applicability and level of the studies were then identified using the QUADAS-2 and a checklist for assessing methodological quality. The following data were obtained from the included studies: year of publication, title, study type, participants’ demographic, sample size, FMS cutoff point, injury definition, statistical analyses used, FMS results and study level.

Results

Generally, the quality of eight studies was poor to moderate due to both small sample sizes and short follow-up periods. Except for a study on military members, all studies were carried out on team sports players. The overall bias of the studies was low, but there was an unclear amount of bias for participant selection. Two studies reported no predictive validity for the FMS, while three defended its predictive validity; the rest partially supported the FMS as a valid diagnostic tool. The reliability of the recommended cutoff point was confirmed, though cutoffs higher than 14 were significantly associated with the predictive ability of the FMS.

Conclusion

Although the FMS is reliable for clinical practice, and the current literature shows promise regarding the predictive ability of the FMS among active females, concerns remain regarding its validity in identifying at-risk females. Given the lack of clarity in the literature on the use of the FMS in females, further well-organized studies with larger sample sizes and longer monitoring periods are highly recommended. The sensitivity and specificity of the recommended cutoff of ≤ 14 has considerably decreased , and higher cutoff values should be applied to increase the FMS predictive ability.

Level of evidence The level of evidence was determined to be 2b.

Can Injuries Be Predicted by Functional Movement Screen in Adolescents? The Application of Machine Learning

ABSTRACT

Karuc, J, Mišigoj-Duraković, M, Šarlija, M, Marković, G, Hadžić, V, Trošt-Bobić, T, and Sorić, M. Can injuries be predicted by functional movement screen in adolescents? The application of machine learning. J Strength Cond Res 35(4): 910-919, 2021-This study used machine learning (ML) to predict injuries among adolescents by functional movement testing. This research is a part of the CRO-PALS study conducted in a representative sample of adolescents and analyses for this study are based on nonathletic (n = 364) and athletic (n = 192) subgroups of the cohort (16-17 years). Sex, age, body mass index (BMI), body fatness, moderate-to-vigorous physical activity (MVPA), training hours per week, Functional Movement Screen (FMS), and socioeconomic status were assessed at baseline. A year later, data on injury occurrence were collected. The optimal cut-point of the total FMS score for predicting injury was calculated using receiver operating characteristic curve. These predictors were included in ML analyses with calculated metrics: area under the curve (AUC), sensitivity, specificity, and odds ratio (95% confidence interval [CI]). Receiver operating characteristic curve analyses with associated criterium of total FMS score >12 showed AUC of 0.54 (95% CI: 0.48-0.59) and 0.56 (95% CI: 0.47-0.63), for the nonathletic and athletic youth, respectively. However, in the nonathletic subgroup, ML showed that the Naïve Bayes exhibited highest AUC (0.58), whereas in the athletic group, logistic regression was demonstrated as the model with the best predictive accuracy (AUC: 0.62). In both subgroups, with given predictors: sex, age, BMI, body fat percentage, MVPA, training hours per week, socioeconomic status, and total FMS score, ML can give a more accurate prediction then FMS alone. Results indicate that nonathletic boys who have lower-body fat could be more prone to suffer from injury incidence, whereas among athletic subjects, boys who spend more time training are at a higher risk of being injured. Conclusively, total FMS cut-off scores for each subgroup did not successfully discriminate those who suffered from those who did not suffer from injury, and, therefore, our research does not support FMS as an injury prediction tool.

Implications for the design of a Diagnostic Decision Support System (DDSS) to reduce time and cost to diagnosis in paediatric shoulder instability

Background

Currently the diagnosis of shoulder instability, particularly in children, is difficult and can take time. These diagnostic delays can lead to poorer outcome and long-term complications. A Diagnostic Decision Support System (DDSS) has the potential to reduce time to diagnosis and improve outcomes for patients. The aim of this study was to develop a concept map for a future DDSS in shoulder instability.

Methods

A modified nominal focus group technique, involving three clinical vignettes, was used to elicit physiotherapists decision-making processes.

Results

Twenty-five physiotherapists, (18F:7 M) from four separate clinical sites participated. The themes identified related to ‘Variability in diagnostic processes and lack of standardised practice’ and ‘Knowledge and attitudes towards novel technologies for facilitating assessment and clinical decision making’.

Conclusion

No common structured approach towards assessment and diagnosis was identified. Lack of knowledge, perceived usefulness, access and cost were identified as barriers to adoption of new technology. Based on the information elicited a conceptual design of a future DDSS has been proposed. Work to develop a systematic approach to assessment, classification and diagnosis is now proposed.

Trial Registraty This was not a clinical trial and so no clinical trial registry is needed.

Physical fitness in older adults: Is there a relationship with the modified Functional Movement Screen™?

INTRODUCTION

The modified Functional Movement Screen™ (mFMS) has been used to screen for mobility, stability, motor control, and balance in older adults, yet, its relationship to measures of physical fitness is not fully understood. The purpose of this study was to determine the association between mFMS scores and measures of physical fitness in older adults. A secondary aim was to determine physical fitness differences depending on mFMS Lower Body Motor Control Screen scores.

METHODS

One hundred and eight older adults completed this cross-sectional study. Measurements of physical fitness included: Handgrip Strength (HG), Back-Leg Strength Dynamometer (BLS), 8 foot Up and Go (8UG), Vertical Jump (VJ), Medicine Ball Throw (MBT), Chair Stand (CST), Arm Curl (AC), and 6-Minute Walk test (6 MW). The mFMS consisted of four screens: Shoulder Mobility Screen (SMS), Deep Squat (DS), Active Straight Leg Raise (ASLR), and a Lower Body Motor Control Screen (LB-MCS). Spearman's R correlations determined associations between physical fitness tests and mFMS scores (DS, SMS, ASLR). Independent t-tests or Mann Whitney U tests determined whether individuals who passed the LB-MCS displayed higher physical fitness scores.

RESULTS

The DS was significantly correlated with all fitness measures (p < 0.05). Higher DS scores were associated with better HG (r = 0.31), BLS (r = 0.49), VJ height (r = 0.54), MBT (r = 0.41), CST (r = 0.57), AC (r = 0.30), 6 MW (r = 0.50), and 8UG (r = -0.61) performance. Individuals who passed the LB-MCS displayed superior BLS, 8UG test, and 6 MW test performance (p < 0.05).

DISCUSSION & CONCLUSION

Higher DS scores are associated with higher physical fitness scores. Individuals who passed the LB-MCS displayed better physical fitness scores. Practitioners may desire to use the mFMS to measure physical fitness in older adults.

Factors Influencing the Relationship Between the Functional Movement Screen and Injury Risk in Sporting Populations: A Systematic Review and Meta-analysis

BACKGROUND

Studies investigating the association between the Functional Movement Screen (FMS) and sports injury risk have reported mixed results across a range of athlete populations.

OBJECTIVES

The purpose of this systematic review was to identify whether athlete age, sex, sport type, injury definition and mechanism contribute to the variable findings.

STUDY DESIGN

Systematic review and meta-analysis.

METHODS

A systematic search was conducted in October 2018 using PubMed, EBSCOhost, Scopus, EmBase and Web of Science databases. Studies were included if they were peer reviewed and published in English language, included athletes from any competition level, performed the FMS at baseline to determine risk groups based on FMS composite score, asymmetry or pain, and prospectively observed injury incidence during training and competition. Study eligibility assessment and data extraction was performed by two reviewers. Random effects meta-analyses were used to determine odds ratio (OR), sensitivity and specificity with 95% confidence intervals. Sub-group analyses were based on athlete age, sex, sport type, injury definition, and injury mechanism.

RESULTS

Twenty-nine studies were included in the FMS composite score meta-analysis. There was a smaller effect for junior (OR = 1.03 [0.67-1.59]; p = 0.881) compared to senior athletes (OR = 1.80 [1.17-2.78]; p = 0.008) and for male (OR = 1.79 [1.08-2.96]; p = 0.024) compared to female (OR = 1.92 [0.43-8.56]; p = 0.392) athletes. FMS composite scores were most likely to be associated with increased injury risk in rugby (OR = 5.92 [1.67-20.92]; p = 0.006), and to a lesser extent American football (OR = 4.41 [0.94-20.61]; p = 0.059) and ice hockey (OR = 3.70 [0.89-15.42]; p = 0.072), compared to other sports. Specificity values were higher than sensitivity values for FMS composite score. Eleven studies were included in the FMS asymmetry meta-analysis with insufficient study numbers to generate sport type subgroups. There was a larger effect for senior (OR = 1.78 [1.16-2.73]; p = 0.008) compared to junior athletes (OR = 1.21 [0.75-1.96]; p = 0.432). Sensitivity values were higher than specificity values for FMS asymmetry. For all FMS outcomes, there were minimal differences across injury definitions and mechanisms. Only four studies provided information about FMS pain and injury risk. There was a smaller effect for senior athletes (OR = 1.28 [0.33-4.96]; p = 0.723) compared to junior athletes (OR = 1.71 [1.16-2.50]; p = 0.006). Specificity values were higher than sensitivity values for FMS pain.

CONCLUSION

Athlete age, sex and sport type explained some of the variable findings of FMS prospective injury-risk studies. FMS composite scores and asymmetry were more useful for estimating injury risk in senior compared to junior athletes. Effect sizes tended to be small except for FMS composite scores in rugby, ice hockey and American football athletes.

PROTOCOL REGISTRATION

CRD42018092916.

Improving predictor selection for injury modelling methods in male footballers

Objectives

This objective of this study was to evaluate whether combining existing methods of elastic net for zero-inflated Poisson and zero-inflated Poisson regression methods could improve real-life applicability of injury prediction models in football.

Methods

Predictor selection and model development was conducted on a pre-existing dataset of 24 male participants from a single English football team's 2015/2016 season.

Results

The elastic net for zero-inflated Poisson penalty method was successful in shrinking the total number of predictors in the presence of high levels of multicollinearity. It was additionally identified that easily measurable data, that is, mass and body fat content, training type, duration and surface, fitness levels, normalised period of 'no-play' and time in competition could contribute to the probability of acquiring a time-loss injury. Furthermore, prolonged series of match-play and increased in-season injury reduced the probability of not sustaining an injury.

Conclusion

For predictor selection, the elastic net for zero-inflated Poisson penalised method in combination with the use of ZIP regression modelling for predicting time-loss injuries have been identified appropriate methods for improving real-life applicability of injury prediction models. These methods are more appropriate for datasets subject to multicollinearity, smaller sample sizes and zero-inflation known to affect the performance of traditional statistical methods. Further validation work is now required.

Functional Movement ScreenTM total score does not present a gestalt measure of movement quality in youth athletes

We aimed to evaluate the internal consistency and factor structure of the Functional Movement Screen (FMS^TM) in youth athletes and quantify differences between individual task score at different stages of maturation. FMS^TM and anthropometric variables were measured in 144 youth athletes (96 female, 48 male). Biological maturation was categorised as before- (<-0.5 years), at- (-0.49-0.50 years) and after- peak height velocity [PHV] (>0.51 years). Internal consistency was poor (Cronbach's alpha; 0.53, ±90% confidence limit 0.10; ordinal alpha 0.6, ±0.09). Principle component analysis extracted two components, representing 47% of the total variance. Tasks loading highest on component 1 required stability, while those loading highest on component 2 favoured mobility. "Likely" decrements in component 1 tasks were observed before-PHV. In-line lunge (effect size ±90% confidence limit; -0.47, ±0.49), hurdle step (-0.38, ±0.49), and trunk stability push-up (-0.51, ±0.45), were lower compared with athletes at-PHV and rotatory stability (-0.44, ±0.37) was lower than those after-PHV. Boys' scored "most likely", higher (0.73, ±0.28) in trunk stability push-up, and girls "likely" higher in shoulder mobility (0.46, ±0.29). In our population, the FMS^TM is not uni-dimensional, thus total score should be avoided. Clear maturation affects were observed in stability tasks.