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Record W2069506962 · doi:10.3109/09593985.2014.908443

Does verbal encouragement actually improve performance in the 6-minute walk test?

2014· article· en· W2069506962 on OpenAlexaff
Patrícia Érika de Melo Marinho, Maria Cristina Falcão Raposo, Elizabeth Dean, Ricardo Oliveira Guerra, Armèle Dornelas de Andrade

Bibliographic record

VenuePhysiotherapy Theory and Practice · 2014
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineCOPDVital capacityPhysical therapyPulmonary diseasePhysical medicine and rehabilitationInternal medicineLung functionLung

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate the performance in the 6-minute walk test (6 MWT) of elderly patients with chronic obstructive pulmonary disease (COPD) by comparing to a group of healthy elderly patients, performed with and without verbal encouragement. This cross-sectional study compared 40 patients with COPD (forced expiratory volume in the first second (FEV1%) = 53.7 ± 23.8%; forced vital capacity (FVC%) = 65.5 ± 20.8%; and the FEV1/FVC ratio = 55.4 ± 12.4) and 40 healthy elderly patients (control). The 6 MWT's were performed with and without verbal encouragement according to the American Thoracic Society (ATS), monitoring the distance walked (6 MWD), the duration of walking (TW) and the perceived effort index (PEI) through the Borg scale between the groups. No differences were observed in patients with COPD when the tests were performed with and without verbal encouragement for the 6 MWD, TW and PEI, the same occurring in the control group for the 6 MWD, TW and PEI, respectively. The use of verbal encouragement was not sufficient to promote improvement in the performance of the 6 MWT (6 MWD, TW and PEI) of patients with COPD and healthy elderly patients.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.315
Teacher spread0.305 · 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 designOther design
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

Citations15
Published2014
Admission routes1
Has abstractyes

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