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Record W4389086802 · doi:10.4085/1062-6050-0403.23

Instrumented Static and Reactive Balance in Collegiate Athletes: Normative Values and Minimal Detectable Change

2023· article· en· W4389086802 on OpenAlexaff
Tessa L. Petersell, David L. Quammen, Regan Crofts, Amanda Morris, Nora F. Fino, Cameron B. Jensen, Adam Hollien, Ryan Pelo, Brody J. Roemmich, Leland E. Dibble, Peter C. Fino

Bibliographic record

VenueJournal of Athletic Training · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsAthletic Edge Sports Medicine
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesNational Institute of Child Health and Human DevelopmentNational Institutes of Health
KeywordsIntraclass correlationContext (archaeology)NormativeBalance (ability)AthletesPhysical therapyPhysical medicine and rehabilitationPsychologyMedicineStatisticsMathematicsReproducibility

Abstract

fetched live from OpenAlex

CONTEXT: Wearable sensors are increasingly popular in concussion research because of their objective quantification of subtle balance deficits. However, normative data and minimal detectable change (MDC) values are necessary to serve as references for diagnostic use and tracking longitudinal recovery. OBJECTIVE: To identify normative and MDC values for instrumented static- and reactive-balance tests, an instrumented static mediolateral (ML) root mean square (RMS) sway standing balance assessment and the instrumented, modified push and release (I-mP&R), respectively. DESIGN: Cross-sectional study. SETTING: Clinical setting. PATIENTS OR OTHER PARTICIPANTS: Normative static ML RMS sway and I-mP&R data were collected on 377 (n = 184 female) healthy National Collegiate Athletic Association Division I athletes at the beginning of their competitive seasons. Test-retest data were collected in 36 healthy control athletes based on standard recovery timelines after concussion. MAIN OUTCOME MEASURE(S): Descriptive statistics, intraclass correlation coefficients (ICCs), and MDC values were calculated for primary outcomes of ML RMS sway in a static double-limb stance on firm ground and a foam block, and time to stability and latency from the I-mP&R in single- and dual-task conditions. RESULTS: Normative outcomes across static ML RMS sway and I-mP&R were sensitive to sex and type of footwear. Mediolateral RMS sway demonstrated moderate reliability in the firm condition (ICC = 0.73; MDC = 2.7 cm/s2) but poor reliability in the foam condition (ICC = 0.43; MDC = 11.1 cm/s2). Single- and dual-task times to stability from the I-mP&R exhibited good reliability (ICC = 0.84 and 0.80, respectively; MDC = 0.25 and 0.29 seconds, respectively). Latency from the I-mP&R had poor to moderate reliability (ICC = 0.38 and 0.55; MDC = 107 and 105 milliseconds). CONCLUSIONS: Sex-matched references should be used for instrumented static- and reactive-balance assessments. Footwear may explain variability in static ML RMS sway and time to stability of the I-mP&R. Moderate-to-good reliability suggests time to stability from the I-mP&R and ML RMS static sway on firm ground can be used for longitudinal assessments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.128
GPT teacher head0.351
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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