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Evaluating the Effects of Music on Dyspnea During Exercise in Individuals with Chronic Obstructive Pulmonary Disease: A Pilot Study

2003· article· en· W2157090960 on OpenAlexaff
Dina Brooks, Souraya Sidani, Jane E. Graydon, Sandra McBride, Leslie Hall, Krisztina Weinacht

Bibliographic record

VenueRehabilitation Nursing · 2003
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsToronto Metropolitan UniversityToronto East General HospitalUniversity of Toronto
Fundersnot available
KeywordsPhysical therapyAnxietyCrossover studyMedicinePulmonary diseaseCOPDPsychological interventionActive listeningIntervention (counseling)PsychologyInternal medicinePsychiatryPsychotherapistPlacebo

Abstract

fetched live from OpenAlex

In this study, we examined the effects of music on the dyspnea and anxiety experienced by people with chronic obstructive pulmonary disease (COPD) when they are walking. A crossover design was used. Patients walked for 10 minutes without music and for 10 minutes while listening to music. The order of the interventions was determined by chance. The levels of perceived dyspnea (modified Borg scale) and anxiety (State-Trait Anxiety Inventory-State) were measured at baseline (before a 6-minute walk), at pretest (after that walk and before the 10-minute walks), and after the walks. Thirty subjects with a mean age of 70 +/- 7 years participated in the study. There were no differences in dyspnea or anxiety levels between the walks with music and with no music (p > 0.05). Despite some positive trends, this study did not provide conclusive evidence to support the efficacy of listening to music during exercise; further research is needed to support this intervention.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.374
Teacher spread0.338 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations27
Published2003
Admission routes1
Has abstractyes

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