Single-Subject Analyses Reveal Altered Performance and Muscle Activation during Vertical Jumping

Harry, John R.; Eggleston, Jeffrey D.; Dufek, Janet S.; James, C. Roger

doi:10.3390/biomechanics1010002

Cited by 6 publications

(8 citation statements)

References 31 publications

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“…The model statistic technique is a critical difference method that can be loosely considered a single-subject dependent t -test, whereby the observed difference between the sessions is compared with a probabilistic critical difference (7,9). It was designed in the early 1990s by Bates et al (7) and has been used to demonstrate the value of single-subject comparisons between 2 conditions relative to the group-level equivalent (31). Critical values were generated (7) for selected trial sizes (i.e., the number of trials used to calculate the test session average) and statistical probabilities (i.e., alpha levels; α ), which are provided in Table 1.…”

Section: Overview Of Session Versus Session Analysis Methodsmentioning

confidence: 99%

“…Conventional statistical analyses limit practitioners to the assessment of a group's "average" response or adaptation, and this practice is echoed in the sports science literature (4,17,18,34,50). However, replicated single-subject approaches have been used by some to detect changes, and this approach may provide the most value to sports scientists and practitioners (11,29,31,55), particularly high value for those working with smaller squads of athletes (e.g., basketball, soccer, volleyball, etc). An appropriate foundation of single-subject analyses in athletes is forming (11,29,31), helping to create the impetus needed to move away from group-average assessments, when necessary, without reliance on subjective visual inspection or trend analyses.…”

Section: Introductionmentioning

confidence: 99%

“…However, replicated single-subject approaches have been used by some to detect changes, and this approach may provide the most value to sports scientists and practitioners (11,29,31,55), particularly high value for those working with smaller squads of athletes (e.g., basketball, soccer, volleyball, etc). An appropriate foundation of single-subject analyses in athletes is forming (11,29,31), helping to create the impetus needed to move away from group-average assessments, when necessary, without reliance on subjective visual inspection or trend analyses. Unfortunately, anecdotal evidence indicates that many practitioners currently employing replicated single-subject assessments rely on arbitrary thresholds for change (i.e., 5% or 10% improvement) as an indicator for real change.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Statistical Tests for Sports Science Practitioners: Identifying Performance Gains in Individual Athletes

Harry,

Hurwitz,

Agnew

et al. 2024

Journal of Strength &Amp; Conditioning Research

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Harry, JR, Hurwitz, J, Agnew, C, and Bishop, C. Statistical tests for sports science practitioners: identifying performance gains in individual athletes. J Strength Cond Res 38(5): e264–e272, 2024—There is an ongoing surge of sports science professionals within sports organizations. However, when seeking to determine training-related adaptations, sports scientists have demonstrated continued reliance on group-style statistical analyses that are held to critical assumptions not achievable in smaller-sample team settings. There is justification that these team settings are better suited for replicated single-subject analyses, but there is a dearth of literature to guide sports science professionals seeking methods appropriate for their teams. In this report, we summarize 4 methods' ability to detect performance adaptations at the replicated single-subject level and provide our assessment for the ideal methods. These methods included the model statistic, smallest worthwhile change, coefficient of variation (CV), and standard error of measurement (SEM), which were discussed alongside step-by-step guides for how to conduct each test. To contextualize the methods' use in practice, real countermovement vertical jump (CMJ) test data were used from 4 (2 females and 2 males) athletes who complete 5 biweekly CMJ test sessions. Each athlete was competing in basketball at the NCAA Division 1 level. We concluded that the combined application of the model statistic and CV methods should be preferred when seeking to objectively detect meaningful training adaptations in individual athletes. This combined approach ensures that the differences between the tests are (a) not random and (b) reflect a worthwhile change. Ultimately, the use of simple and effective methods that are not restricted by group-based statistical assumptions can aid practitioners when conducting performance tests to determine athlete adaptations.

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Section: Overview Of Session Versus Session Analysis Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Statistical Tests for Sports Science Practitioners: Identifying Performance Gains in Individual Athletes

Harry,

Hurwitz,

Agnew

et al. 2024

Journal of Strength &Amp; Conditioning Research

Self Cite

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“…As mentioned previously, across the sample, the average and standard deviation for the number of trials included was 19 ± 5 trials, with a range of 9–24 trials. Limitations related to group average analyses, especially with small samples like the one here and in most team sport settings, have been discussed and explored at length elsewhere (2–4,12,21). Accordingly, we sought to determine the relationship between landing performance and the remaining metrics of interest at the group average and individual athlete levels, similar to a recent article exploring relationships during jumping (19).…”

Section: Methodsmentioning

confidence: 99%

Establishing Phase Definitions for Jump and Drop Landings and an Exploratory Assessment of Performance-Related Metrics to Monitor During Testing

Harry,

Simms,

Hite

2023

Journal of Strength and Conditioning Research

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Harry, JR, Simms, A, and Hite, M. Establishing phase definitions for jump and drop landings and an exploratory assessment of performance-related metrics to monitor during testing. J Strength Cond Res XX(X): 000–000, 2023—Landing is a common task performed in research, physical training, and competitive sporting scenarios. However, few have attempted to explore landing mechanics beyond its hypothesized link to injury potential, which ignores the key performance qualities that contribute to performance, or how quickly a landing can be completed. This is because a lack of (a) established landing phases from which important performance and injury risk metrics can be extracted and (b) metrics known to have a correlation with performance. As such, this article had 2 purposes. The first purpose was to use force platform data to identify easily extractable and understandable landing phases that contain metrics linked to both task performance and overuse injury potential. The second purpose was to explore performance-related metrics to monitor during testing. Both purposes were pursued using force platform data for the landing portion of 270 jump-landing trials performed by a sample of 14 NCAA Division 1 men's basketball players (1.98 ± 0.07 m; 94.73 ± 8.01 kg). The proposed phases can separate both jump-landing and drop-landing tasks into loading, attenuation, and control phases that consider the way vertical ground reaction force (GRF) is purposefully manipulated by the athlete, which current phase definitions fail to consider. For the second purpose, Pearson’s correlation coefficients, the corresponding statistical probabilities (α = 0.05), and a standardized strength interpretation scale for correlation coefficients (0 < trivial ≤ 0.1 < small ≤ 0.3 < moderate ≤ 0.5 < large ≤ 0.7 < very large) were used for both the group average (i.e., all individual averages pooled together) and individual data (i.e., each individual's trials pooled together). Results revealed that landing time, attenuation phase time, average vertical GRF during landing, average vertical GRF during the attenuation phase, average vertical GRF during the control phase, vertical GRF attenuation rate, and the amortization GRF (i.e., GRF at zero velocity) significantly correlated with landing performance, defined as the ratio of landing height and landing time (R ≥ ± 0.58; p < 0.05), such that favorable changes in those metrics were associated with better performance. This work provides practitioners with 2 abilities. First, practitioners currently assess jump capacity using jump-landing tests (e.g., countermovement jump) with an analysis strategy that makes use of landing data. Second, this work provides preliminary data to guide others when initially exploring landing test results before identifying metrics chosen for their own analysis.

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“…Visual inspection of several individual learning curves was long used but can at best provide only the first coarse indications for individual learning behavior without meeting the basic forensic requirements of uniqueness and persistence. In addition, longitudinal studies are primarily based on discrete results such as jump height [ 326 ], balance scores [ 327 ], or hitting performances [ 328 ]. Biomechanically based longitudinal studies on movement data are frequently either limited to time-discrete movement characteristics [ 212 ] or to describing average time-courses with a standard deviation [ 329 , 330 ].…”

Section: Perspectivementioning

confidence: 99%

Always Pay Attention to Which Model of Motor Learning You Are Using

Schöllhorn

Rizzi

Slapšinskaitė-Dackevičienė

et al. 2022

IJERPH

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This critical review considers the epistemological and historical background of the theoretical construct of motor learning for a more differentiated understanding. More than simply reflecting critically on the models that are used to solve problems—whether they are applied in therapy, physical education, or training practice—this review seeks to respond constructively to the recent discussion caused by the replication crisis in life sciences. To this end, an in-depth review of contemporary motor learning approaches is provided, with a pragmatism-oriented clarification of the researcher’s intentions on fundamentals (what?), subjects (for whom?), time intervals (when?), and purpose (for what?). The complexity in which the processes of movement acquisition, learning, and refinement take place removes their predictable and linear character and therefore, from an applied point of view, invites a great deal of caution when trying to make generalization claims. Particularly when we attempt to understand and study these phenomena in unpredictable and dynamic contexts, it is recommended that scientists and practitioners seek to better understand the central role that the individual and their situatedness plays in the system. In this way, we will be closer to making a meaningful and authentic contribution to the advancement of knowledge, and not merely for the sake of renaming inventions.

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Single-Subject Analyses Reveal Altered Performance and Muscle Activation during Vertical Jumping

Cited by 6 publications

References 31 publications

Statistical Tests for Sports Science Practitioners: Identifying Performance Gains in Individual Athletes

Statistical Tests for Sports Science Practitioners: Identifying Performance Gains in Individual Athletes

Establishing Phase Definitions for Jump and Drop Landings and an Exploratory Assessment of Performance-Related Metrics to Monitor During Testing

Always Pay Attention to Which Model of Motor Learning You Are Using

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