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Record W563584225

The effect of differing types of music and music preference as a dissociative strategy on exercise performance and perceived exertion

2011· article· en· W563584225 on OpenAlexaff
Hannah A Connon, David Scott

Bibliographic record

VenueJournal of Exercise, Movement, and Sport · 2011
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsDancePsychologyPreferenceMusicalityActive listeningRhythmTask (project management)MusicalPerceived exertionSocial psychologyCognitive psychologyAudiologyCommunicationMedicineHeart rateInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

The purpose of the study was to investigate the effect of different types of music on performance and perceived exertion during a 30 minute self-regulated exercise task. Current theory states that the aspects of music contributing most to inducing potential psychological and physiological benefits are rhythm response, musicality, cultural impact, and extra-musical associations (Terry, 2006). Participants ( N=173 ) completed a 30 minute self-regulated cycling task listening to either dance, motivational, country music or no music. Participants previously rated the types of music on a continuum from 1-10. At five minute intervals performance was measured by calorie expenditure, RPE via the Borg scale, and HR. Results indicated all types of music to induce greater performance than the control group, with dance music being significantly greater than the control group ( F (3, 169) = 3.075, p ? 0.05). Preference of music was not found to significantly influence performance. RPE per calorie was implemented to analyze the psychological aspect; results indicate the control (no music) group underwent the least amount of disassociation and the dance music group the most. Preference was found to significantly affect RPE and a significant negative correlation was also reported. It was concluded that music type and preference should be considered for professionals designing programs for clients. If the objective was to increase performance, dance music should be implemented regardless of individual preference. When the objective is psychological it would be recommended to implement preferred music as the findings here indicate this makes the undesired physiological symptoms of exercise more tolerable.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.040
GPT teacher head0.288
Teacher spread0.248 · 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

Citations4
Published2011
Admission routes1
Has abstractyes

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