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Record W2174688387 · doi:10.1093/jmt/thv009

The Effects of Music Salience on the Gait Performance of Young Adults

2015· article· en· W2174688387 on OpenAlexafffund
Natalie de Bruin, C. Kempster, Angelica Doucette, Jon B. Doan, Bin Hu, Lesley A. Brown

Bibliographic record

VenueJournal of Music Therapy · 2015
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of Lethbridge
FundersCanadian Institutes of Health Research
KeywordsCadenceRhythmMetronomeSTRIDEPsychologyGaitBeat (acoustics)Salience (neuroscience)Physical medicine and rehabilitationActive listeningCommunicationCognitive psychologyMedicineAcoustics

Abstract

fetched live from OpenAlex

BACKGROUND: The presence of a rhythmic beat in the form of a metronome tone or beat-accentuated original music can modulate gait performance; however, it has yet to be determined whether gait modulation can be achieved using commercially available music. OBJECTIVE: The current study investigated the effects of commercially available music on the walking of healthy young adults. Specific aims were (a) to determine whether commercially available music can be used to influence gait (i.e., gait velocity, stride length, cadence, stride time variability), (b) to establish the effect of music salience on gait (i.e., gait velocity, stride length, cadence, stride time variability), and (c) to examine whether music tempi differentially effected gait (i.e., gait velocity, stride length, cadence, stride time variability). METHODS: Twenty-five participants walked the length of an unobstructed walkway while listening to music. Music selections differed with respect to the salience or the tempo of the music. The genre of music and artists were self-selected by participants. RESULTS: Listening to music while walking was an enjoyable activity that influenced gait. Specifically, salient music selections increased measures of cadence, velocity, and stride length; in contrast, gait was unaltered by the presence of non-salient music. Music tempo did not differentially affect gait performance (gait velocity, stride length, cadence, stride time variability) in these participants. CONCLUSIONS: Gait performance was differentially influenced by music salience. These results have implications for clinicians considering the use of commercially available music as an alternative to the traditional rhythmic auditory cues used in rehabilitation programs.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.045
GPT teacher head0.311
Teacher spread0.266 · 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

Citations19
Published2015
Admission routes2
Has abstractyes

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