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Record W3018230470 · doi:10.3138/ptc-2019-0111

Clinician-Led Balance Training in Pulmonary Rehabilitation

2020· article· en· W3018230470 on OpenAlexaffvenue
Sachi O’Hoski, Samantha Harrison, Stacey J. Butler, Roger Goldstein, Dina Brooks

Bibliographic record

VenuePhysiotherapy Canada · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity of TorontoMcMaster UniversityWest Park Healthcare Centre
Fundersnot available
KeywordsBalance (ability)MedicinePhysical therapyPulmonary rehabilitationRehabilitationOperationalizationBalance trainingConfidence intervalPhysical medicine and rehabilitationInternal medicine

Abstract

fetched live from OpenAlex

Purpose: Guidelines for pulmonary rehabilitation (PR) include balance training but lack specific parameters. After a knowledge translation project at our site, clinicians modified the physiotherapy programme to facilitate the sustainability of balance training as part of PR. The purpose of this study was to explore whether the modified programme resulted in improved balance and balance confidence. A secondary aim was to provide information on the way in which balance training was operationalized as part of PR for clinicians wanting to incorporate it into an existing PR programme. Method: We conducted a retrospective study of patients with chronic obstructive pulmonary disease, enrolled in a 4- to 6-week inpatient PR programme over a 1-year period. Balance training was provided biweekly with a staff-to-patient ratio of 2:11. Participants completed the brief Balance Evaluation Systems Test (brief-BESTest) and Activities-Specific Balance Confidence (ABC) scale at the beginning and end of PR. Results: The 85 participants had a mean age of 69.5 (SD 9.0) years. After completing an average of 7.6 balance sessions (min-max 2–13), participants showed improvements in brief-BESTest (mean difference 3.2 [95% CI: 2.5, 3.9] points) and ABC (mean difference 7.8 [95% CI: 4.1, 11.5] percent). Conclusions: A staff-to-patient ratio of 2:11 and a training frequency of twice per week for 4–6 weeks improved balance. This result will inform how we incorporate balance training into existing PR programmes.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.314
Teacher spread0.295 · 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

Citations5
Published2020
Admission routes2
Has abstractyes

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