Minimizing the evidence-practice gap – a prospective cohort study incorporating balance training into pulmonary rehabilitation for individuals with chronic obstructive pulmonary disease
Bibliographic record
Abstract
BACKGROUND: We have recently demonstrated the efficacy of balance training in addition to Pulmonary Rehabilitation (PR) at improving measures of balance associated with an increased risk of falls in individuals with Chronic Obstructive Pulmonary Disease (COPD). Few knowledge translation (KT) projects have been conducted in rehabilitation settings. The goal of this study was to translate lessons learnt from efficacy studies of balance training into a sustainable clinical service. METHODS: Health care professionals (HCPs) responsible for delivering PR were given an hour of instruction on the principles and practical application of balance training and the researchers offered advice regarding; prescription, progression and practical demonstrations during the first week. Balance training was incorporated three times a week into conventional PR programs. Following the program, HCPs participated in a focus group exploring their experiences of delivering balance training alongside PR. Service users completed satisfaction surveys as well as standardized measures of balance control. At six month follow-up, the sustainability of balance training was explored. RESULTS: HCPs considered the training to be effective at improving balance and the support provided by the researchers was viewed as helpful. HCPs identified a number of strategies to facilitate balance training within PR, including; training twice a week, incorporating an interval training program for everyone enrolled in PR, providing visual aids to training and promoting independence by; providing a set program, considering the environment and initiating a home-based exercise program early. Nineteen service users completed the balance training [ten male mean (SD) age 73 (6) y]. Sixteen patients (84%) enjoyed balance training and reported that it helped them with everyday activities and 18 (95%) indicated their wish to continue with it. Scores on balance measures improved following PR that included balance training (all p < 0.05). At six month follow-up balance training is being routinely assessed and delivered as part of standardised PR. CONCLUSIONS: Implementing balance training into PR programs, with support and training for HCPs, is feasible, effective and sustainable. TRAIL REGISTRATION: Clinical Trials ID: NCT02080442 (05/03/2014).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".