Study protocol for a single-arm pilot trial investigating the feasibility of a multimodal digital technology for managing metabolic syndrome in patients with chronic obstructive pulmonary disease
Bibliographic record
Abstract
Individuals diagnosed with Chronic Obstructive Pulmonary Disease (COPD) are exposed to an increased risk of metabolic syndrome (MetS), which negatively affects their health outcomes and quality of life. Lifestyle interventions have shown promise in managing MetS. This study outlines the protocol for a web-based multimodal self-care program, Digital Metabolic Rehabilitation, for managing MetS in patients with COPD. The Digital Metabolic Rehabilitation is a single-arm pilot trial that integrates the Canadian Health Advanced by Nutrition and Graded Exercise (CHANGE) Program and a web-based wellness platform. The web-based wellness platform employed in this study is My Viva Plan (MVP)®, which integrates a holistic, multicomponent approach to promote wellness. The intervention will primarily focus on lifestyle changes for patients with COPD. Over 6 months, participants will use the web-based wellness platform and engage in weekly online support group sessions. Fifty patients diagnosed with stage I-II COPD and MetS will participate. Blood tests, anthropometrics, body composition, physical function, muscle strength, physical activity, energy metabolism, quality of life and mental health will be assessed at baseline, 3, and 6 months. The Digital Metabolic Rehabilitation program aims to explore whether a multimodal integrative intervention delivered through a web-based wellness platform can be implemented by patients with COPD with MetS. By combining the expertise of the CHANGE Program with the digital delivery format, the intervention seeks to enhance self-monitoring and foster better self-management practices. The protocol outlines a novel and potentially impactful intervention for managing MetS in patients with COPD.
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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 | 0.031 | 0.032 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.095 | 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".