scholarly journals Intra and inter-rater agreement of the Dynamic Movement Assessment ™ Agreement of the DMA™

2020 ◽  
Vol 26 (4) ◽  
Author(s):  
Priscila dos Santos Bunn ◽  
Hélcio Figueiredo da Costa ◽  
Celso José da Silva Júnior ◽  
Saulo de Almeida Silva ◽  
Ricardo Costa Abrantes Júnior ◽  
...  
Author(s):  
M. McGroarty ◽  
S. Giblin ◽  
D. Meldrum ◽  
F. Wetterling

The aim of the study was to perform a preliminary validation of a low cost markerless motion capture system (CAPTURE) against an industry gold standard (Vicon). Measurements of knee valgus and flexion during the performance of a countermovement jump (CMJ) between CAPTURE and Vicon were compared. After correction algorithms were applied to the raw CAPTURE data acceptable levels of accuracy and precision were achieved. The knee flexion angle measured for three trials using Capture deviated by −3.8° ± 3° (left) and 1.7° ± 2.8° (right) compared to Vicon. The findings suggest that low-cost markerless motion capture has potential to provide an objective method for assessing lower limb jump and landing mechanics in an applied sports setting. Furthermore, the outcome of the study warrants the need for future research to examine more fully the potential implications of the use of low-cost markerless motion capture in the evaluation of dynamic movement for injury prevention.


2019 ◽  
Vol 7 (3_suppl) ◽  
pp. 2325967119S0016
Author(s):  
Jeff W. Barfield ◽  
Gretchen D. Oliver

Background: When using the tuck jump as a dynamic movement assessment, clinicians note movement flaws to determine injury potential and provide further training in attempt to improve movement technique deficits. The Tuck Jump Assessment has been identified as a dynamic assessment for lower extremity injury susceptibility.[3-6] The purpose of the Tuck Jump Assessment is to identify postural neuromuscular imbalances, throughout the dynamic movement, that could potentially result in greater injury susceptibility.[5] With the focus of neuromuscular imbalances on Tuck Jump Assessment performance, as well as the common notion of the body acting as a kinetic chain functions most efficient when there is proximal stability for distal mobility,[1] it was our purpose to determine if the Tuck Jump Assessment can be used as a dynamic movement assessment to ascertain a previous history of upper extremity injury in overhead throwing sports such as baseball and softball. We hypothesized that a more flexed trunk and less elevated upper leg in the peak of the tuck jump would correlate with previous history of upper extremity injury for the overhead athlete. Methods: Seventy-one youth baseball and softball athletes (28 baseball/43 softball; 12.41 ± 2.22 yrs.; 161.98 ± 13.65 cm; 59.17 ± 14.90 kg) were recruited to participate. All participants were in good physical condition and had no injuries within the last six months. A health history form was completed by the participants prior to participation. If a participant indicated that they have had an upper extremity injury in the past year that had kept them from competition, then they were placed in the previous injury group (N = 18). All other participants were placed into the no previous injury group (N = 53). Participants that indicated they had a previous lower extremity injury were excluded from of the study. The University’s Institutional Review Board approved all testing protocols. Informed written consent was obtained from each participant and participant’s parents before testing.[2] Kinematic data were collected at 100 Hz using an electromagnetic tracking system (trakSTARTM, Ascension Technologies, Inc., Burlington, VT, USA) synced with the MotionMonitor® (Innovative Sports Training, Chicago, IL. USA). Participants were instructed to start with their feet shoulder width apart and initiate the jump with a slight downward crouch while holding their arms in front of their chest. As they jumped, they were instructed to pull their knees as high as possible during the jump aiming to reach a position where their thighs were parallel to the ground and to immediately begin the next tuck jump once landing.[5] A trial of 10 tuck jumps was collected. Analysis included jumps 4 through 8 to mitigate the Hawthorne effect. Values for trunk flexion and upper leg elevation were taken from peak leg elevation and averaged and a priori was set at a level of p = 0.05 to determine significance. Results: A logistic regression showed no significance in trunk flexion or upper leg elevation being able to determine upper extremity injury (&[Chi] &[sup]2 (&[sub]1, N = 71) = 3.55, p = .315). The model explained 7.2% of the variance in upper extremity injury and correctly classified 73.2% of all cases. Conclusion/Significance: While a direct link was not found between the Tuck Jump Assessment and upper extremity injury, further investigation into injury precursors should be performed. During our Tuck Jump Assessment, we only examined trunk flexion and upper leg elevation, which are two variables that make up the proximal control factor indicated by Lininger and colleagues. [3] In their exploratory factor analysis, it was concluded that three factors defined as fatigue, distal landing pattern, and proximal control should be examined to get the most benefit of the Tuck Jump Assessment in injury assessments.[3] Our results agree with their conclusion, that a simplified unidimensional construct of the Tuck Jump Assessment may not be the best way to use this dynamic movement assessment to identify previous upper extremity injury. In conclusion, examining only trunk flexion and upper leg elevation during the Tuck Jump Assessment is not enough for clinicians to recognize previous upper extremity injury. Even though the body behaves as a kinetic chain, simplifying the dynamic movement assessment while not specifying the type of upper extremity injury is not favorable for the clinician to identify previous injury. References Chu SK et al. PM R. 2016;8(3 Suppl): S69-77. Harris D et al. Int J Sports Med. 2017;38:1126-1131. Lininger MR et al. J Strength Cond Res. 2017;31(3):653-659. Myer GD et al. Strength and Conditioning Journal. 2011;33(3):21-35. Myer GD et al. Athl Ther Today. 2008;13(5):39-44. Myer GD et al. Am J Sports Med. 2010;38(19):2025-2033.


2018 ◽  
Vol 25 (3) ◽  
pp. 352-361
Author(s):  
Priscila dos Santos Bunn ◽  
Elirez Bezerra da Silva

ABSTRACT Dynamic Movement AssessmentTM (DMATM) and Functional Movement ScreeningTM (FMSTM) are tools to predict the risk of musculoskeletal injuries in individuals who practice physical activities. This systematic review aimed to evaluate the association of DMATM and FMSTM with the risk of musculoskeletal injuries, in different physical activities, categorizing by analysis. A research without language or time filters was carried out in November 2016 in MEDLINE, Google Scholar, SciELO, SCOPUS, SPORTDiscus, CINAHL and BVS databases using the keywords: “injury prediction”, “injury risk”, “sensitivity”, “specificity”, “functional movement screening”, and “dynamic movement assessment”. Prospective studies that analyzed the association between DMATM and FMSTM with the risk of musculoskeletal injuries in physical activities were included. The data extracted from the studies were: participant’s profile, sample size, injury’s classification criteria, follow-up time, and the results presented, subdivided by the type of statistical analysis. The risk of bias was performed with Newcastle-Ottawa Scale for cohort studies. No study with DMATM was found. A total of 20 FMSTM studies analyzing one or more of the following indicators were included: diagnostic accuracy (PPV, NPV and AUC), odds ratios (OR) or relative risk (RR). FMSTM showed a sensitivity=12 to 99%; specificity=38 to 97%; PPV=25 to 91%; NPV=28 to 85%; AUC=0.42 to 0.68; OR=0.53 to 54.5; and RR=0.16-5.44. The FMSTM has proven to be a predictor of musculoskeletal injuries. However, due to methodological limitations, its indiscriminate usage should be avoided.


2018 ◽  
Vol 02 (04) ◽  
pp. E113-E116
Author(s):  
Jeff Barfield ◽  
Gretchen Oliver

AbstractThe purpose of this study was to determine if tuck jumps can be used as a dynamic movement assessment to ascertain a previous history of upper extremity injury in an overhead throwing sport. Seventy-one youth baseball and softball athletes (28 baseball/43 softball; 12.41±2.22 yrs.; 161.98±13.65 cm; 59.17 ± 14.90 kg) were recruited to participate and were placed in either the previous injury (N=18) or no previous injury (N=53) groups. Kinematic data were collected from jumps 4 through 8 during a trial of 10 tuck jumps performed at 100 Hz using an electromagnetic tracking system (trakSTARTM, Ascension Technologies, Inc., Burlington, VT, USA) synced with the MotionMonitor® (Innovative Sports Training, Chicago, IL, USA). A logistic regression showed no significance in trunk flexion or upper leg elevation in the ability to determine upper extremity injury (χ 2 (1, N=71)=3.55, p=0.315). In conclusion, examining only trunk flexion and upper leg elevation during the tuck jump assessment (TJA) is not enough for clinicians to recognize previous upper extremity injury. Even though the body behaves as a kinetic chain, simplifying the dynamic movement assessment while not specifying the type of upper extremity injury is not favorable for the clinician to identify previous injury.


2017 ◽  
Vol 20 ◽  
pp. S29
Author(s):  
Priscila Bunn ◽  
Thiago Lopes ◽  
Bruno Terra ◽  
Daniel Alves ◽  
Allan Rodrigues ◽  
...  

2010 ◽  
Vol 17 (2) ◽  
pp. 36-49 ◽  
Author(s):  
Julia Kastner ◽  
Franz Petermann

Zusammenfassung. Der aktuelle Forschungsstand deutet darauf hin, dass entwicklungsbedingte Koordinationsstörungen häufig mit psychischen und sozialen Verhaltensauffälligkeiten sowie kognitiven Defiziten verknüpft sind; insbesondere der Kontakt zur Gleichaltrigengruppe scheint problematisch. Die vorliegende Studie überprüft, ob betroffene Kinder spezifische kognitive Defizite sowie verschiedene Verhaltensprobleme aufweisen. Es besteht die Hypothese, dass psychische Auffälligkeiten sowie Probleme im sozialen Bereich nicht nur unmittelbare Folgen der motorischen Ungeschicklichkeit darstellen, sondern dass bestimmte kognitive Defizite an der Entstehung dieser negativen Begleiterscheinungen beteiligt sind. In der Studie wurden 35 koordinationsgestörte Kinder im Alter von sechs bis elf Jahren mit einer alters- und geschlechtsgematchten Kontrollgruppe (n = 35) anhand ihrer kognitiven Leistungen, ihres Sozialverhaltens sowie bestimmter psychischer Verhaltensauffälligkeiten mittels t-Tests verglichen. Zur Absicherung der Diagnose einer entwicklungsbedingten Koordinationsstörung wurde der Motoriktest Movement Assessment Battery for Children (M-ABC-2) eingesetzt. Die Überprüfung der kognitiven Leistungen erfolgte mittels des Hamburg-Wechsler-Intelligenztest für Kinder – IV (HAWIK-IV). Psychische und soziale Verhaltensabweichungen wurden mithilfe des Elternfragebogens der Intelligence and Developmental Scales (IDS) und der Lehrereinschätzliste (LSL) erfasst. Anhand von Mediatoranalysen wird überprüft, ob ein indirekter Zusammenhang zwischen motorischer Leistung und verschiedenen Verhaltensauffälligkeiten besteht, der durch bestimmte kognitive Defizite vermittelt wird. Die Kinder weisen im Vergleich zur Kontrollgruppe ein erhöhtes Maß an psychischen Auffälligkeiten, Einschränkungen im Sozialverhalten sowie signifikante Intelligenzunterschiede auf. Das Wahrnehmungsgebundene Logische Denken (HAWIK-IV) vermittelt den Zusammenhang zwischen der motorischen Gesamtleistung sowie den LSL-Skalen Einfühlungsvermögen und Kooperation. Die Ergebnisse weisen darauf hin, dass verschiedene Wahrnehmungsdefizite den Umgang mit der Gleichaltrigengruppe erschweren.


2006 ◽  
Vol 11 (1) ◽  
pp. 12-24 ◽  
Author(s):  
Alexander von Eye

At the level of manifest categorical variables, a large number of coefficients and models for the examination of rater agreement has been proposed and used. The most popular of these is Cohen's κ. In this article, a new coefficient, κ s , is proposed as an alternative measure of rater agreement. Both κ and κ s allow researchers to determine whether agreement in groups of two or more raters is significantly beyond chance. Stouffer's z is used to test the null hypothesis that κ s = 0. The coefficient κ s allows one, in addition to evaluating rater agreement in a fashion parallel to κ, to (1) examine subsets of cells in agreement tables, (2) examine cells that indicate disagreement, (3) consider alternative chance models, (4) take covariates into account, and (5) compare independent samples. Results from a simulation study are reported, which suggest that (a) the four measures of rater agreement, Cohen's κ, Brennan and Prediger's κ n , raw agreement, and κ s are sensitive to the same data characteristics when evaluating rater agreement and (b) both the z-statistic for Cohen's κ and Stouffer's z for κ s are unimodally and symmetrically distributed, but slightly heavy-tailed. Examples use data from verbal processing and applicant selection.


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