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Record W2806081818 · doi:10.1186/s40634-018-0129-5

Implicit video feedback produces positive changes in landing mechanics

2018· article· en· W2806081818 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Experimental Orthopaedics · 2018
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhysical medicine and rehabilitationBiomechanicsPhysical therapyCued speechRepeated measures designMedicinePsychologyOrthodonticsMathematicsCognitive psychologyStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: Implicit (IF) and explicit (EF) feedback are two motor learning strategies demonstrated to alter movement patterns. There is conflicting evidence on which strategy produces better outcomes. The purpose of this study was to examine the effects of reduced IF and EF video feedback on lower extremity landing mechanics. METHODS: Thirty participants (24 ± 2 years, 1.7 ± 0.1 m, 70 ± 11 kg) were randomly assigned to three groups: IF (n = 10), EF (n = 10), and control (CG) (n = 10). They performed twelve box-drop jumps three times a week on the training sessions for six weeks. Only IF and EF groups received video feedback on the training sessions. IF was cued to focus their attention on the overall jump, while EF was cued to focus on position of their knees. 3D lower extremity biomechanics were tested on testing sessions with no feedback. All sessions were at least 24 h apart from another. Testing sessions included baseline testing (pretest), testing after 3 training sessions with 100% feedback (pst1), testing after 6 training sessions with 33.3% feedback (pst2), testing after 6 training sessions with 16.6% feedback (Pst3), and testing 1 month after with no feedback (retention - ret). ANOVA compared differences between groups and time at initial contact and peak for hip flexion (HF, °) and abduction angle (HA, °), hip abduction moment (HAM, Nm/kgm), knee flexion (KF, °) and abduction angle (KA, °), knee abduction moment (KAM, Nm/kgm) and VGRF (N) (p < 0.05). RESULTS: A significant main effect for group was found between IF and EF groups for HA (IF = - 6.7 ± 4; EF = - 9.4 ± 4.1) and KAM (IF = 0.05 ± 0.2; EF = - 0.07 ± 0.2) at initial contact, and peaks HA (IF = - 3.5 ± 4.5; EF = - 7.9 ± 4.7) and HAM (IF = 1.1 ± 0.6; EF = 0.9 ± 0.4). A significant main effect for time at initial contact for HF (pre = 32.4 ± 3.2; pst2 = 36.9 ± 3.2; pst3 = 37.9 ± 3.7; ret. = 34.1 ± 3.7), HAM (pre = 0.1 ± 0.1; pst1 = 0.04 ± 0.1; pst3 = 0.1 ± 0.01), KA (pre = 0.7 ± 1.1; pst1 = 0.2 ± 1.2; pst3 = 1.7 ± 1), and KAM (pre = 0.003 ± 0.1; pst3 = 0.01 ± 0.1) was found. DISCUSSION/CONCLUSION: We found that implicit feedback produced positive changes in landing mechanics while explicit feedback degraded motor learning. Our results indicate that implicit feedback should be used in programs to lower the ACL injury risk. We suggest that implicit feedback should be frequent in the beginning and not be reduced as much following the acquisition phase.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.027
GPT teacher head0.290
Teacher spread0.263 · 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