Development of a Novel Intervention (Mindful Steps) to Promote Long-Term Walking Behavior in Chronic Cardiopulmonary Disease: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Despite current rehabilitation programs, long-term engagement in physical activity remains a significant challenge for patients with chronic obstructive pulmonary disease (COPD) and heart failure (HF). Novel strategies to promote physical activity in these populations are greatly needed. Emerging literature on the benefits of both mind-body interventions and web-based interventions provide the rationale for the development of the Mindful Steps intervention for increasing walking behavior. OBJECTIVE: This study aims to develop a novel multimodal mind-body exercise intervention through adaptation of an existing web-based physical activity intervention and incorporation of mind-body exercise, and to pilot test the delivery of the new intervention, Mindful Steps, in a randomized controlled feasibility trial in older adults with COPD and/or HF. METHODS: In phase 1, guided by a theoretical conceptual model and review of the literature on facilitators and barriers of physical activity in COPD and HF, we convened an expert panel of researchers, mind-body practitioners, and clinicians to inform development of the novel, multimodal intervention. In phase 2, we are conducting a pilot randomized controlled feasibility trial of the Mindful Steps intervention that includes in-person mind-body exercise classes, an educational website, online mind-body videos, and a pedometer with step-count feedback and goals to increase walking behavior in patients with COPD and/or HF. Outcomes include feasibility measures as well as patient-centered measures. RESULTS: The study is currently ongoing. Phase 1 intervention development was completed in March 2019, and phase 2 data collection began in April 2019. CONCLUSIONS: Through the integration of components from a web-based physical activity intervention and mind-body exercise, we created a novel, multimodal program to impact long-term physical activity engagement for individuals with COPD and HF. This developmental work and pilot study will provide valuable information needed to design a future clinical trial assessing efficacy of this multimodal approach. TRIAL REGISTRATION: ClinicalTrials.gov NCT03003780; https://clinicaltrials.gov/ct2/show/NCT03003780. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/27826.
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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 | 0.053 | 0.047 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.008 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.078 | 0.017 |
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".