Effectiveness of an eHealth self-management tool for older adults with multimorbidity (KeepWell): protocol for a hybrid effectiveness–implementation randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: In response to the burden of chronic disease among older adults, different chronic disease self-management tools have been created to optimise disease management. However, these seldom consider all aspects of disease management are not usually developed specifically for seniors or created for sustained use and are primarily focused on a single disease. We created an eHealth self-management application called 'KeepWell' that supports seniors with complex care needs in their homes. It incorporates the care for two or more chronic conditions from among the most prevalent high-burden chronic diseases. METHODS AND ANALYSIS: We will evaluate the effectiveness, cost and uptake of KeepWell in a 6-month, pragmatic, hybrid effectiveness-implementation randomised controlled trial. Older adults age ≥65 years with one or more chronic conditions who are English speaking are able to consent and have access to a computer or tablet device, internet and an email address will be eligible. All consenting participants will be randomly assigned to KeepWell or control. The allocation sequence will be determined using a random number generator.Primary outcome is perceived self-efficacy at 6 months. Secondary outcomes include quality of life, health background/status, lifestyle (nutrition, physical activity, caffeine, alcohol, smoking and bladder health), social engagement and connections, eHealth literacy; all collected via a Health Risk Questionnaire embedded within KeepWell (intervention) or a survey platform (control). Implementation outcomes will include reach, effectiveness, adoption, fidelity, implementation cost and sustainability. ETHICS AND DISSEMINATION: Ethics approval has been received from the North York General Hospital Research and Ethics Board. The study is funded by the Canadian Institutes of Health Research and the Ontario Ministry of Health. We will work with our team to develop a dissemination strategy which will include publications, presentations, plain language summaries and an end-of-grant meeting. TRIAL REGISTRATION NUMBER: NCT04437238.
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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 | 0.056 | 0.051 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.098 | 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".