Feasibility and implementation of a healthy lifestyles program in a community setting in Ontario, Canada: protocol for a pragmatic mixed methods pilot study
Bibliographic record
Abstract
INTRODUCTION: Rates of chronic conditions, such as diabetes, cardiovascular disease and obesity are increasing in Canada and internationally. There are effective lifestyle interventions that are known to improve chronic conditions. However, there is often a gap in 'how to' make lifestyle changes. Mental health and other determinants of health play a role in the development and progression of chronic conditions. Changing habits takes time and requires the use of multiple techniques, including mental health and behavioural change strategies, based on a person's needs. A new, multidisciplinary, person-centred and evidence-based and practice-based programme has been created to address these needs. This proposal aims to evaluate the feasibility and implementation of this programme and to determine changes in participant-directed and clinical outcomes through a pilot study. METHODS AND ANALYSIS: A pragmatic mixed methods design will be used to study multiple dimensions of the year-long healthy lifestyles programme. The pilot study includes a randomised controlled trial, with 30 participants randomised to either the programme or to a comparator arm, and qualitative components to determine the feasibility of the programme, including recruitment and retention, data missing rates and resources needed to run this programme. Changes in participant-directed and clinical outcomes will be measured. Descriptive statistics, t-tests and repeated measures analysis of variance (ANOVA) for within group comparisons and generalised estimating equations for between group analyses will be used. Qualitative interviews of programme staff and healthcare providers and family focus groups will be used to further enhance the findings and improve the programme. ETHICS AND DISSEMINATION: Approval from the Hamilton Integrated Research Ethics Board (HiREB) has been obtained. Informed consent will be obtained prior to enrolling any participant into the study. Participant IDs will be used during data collection and entry. Peer-reviewed publications and presentations will target researchers, health professionals and stakeholders. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Identifier: NCT03258138.HiREB project number: 3793.
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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 | 0.058 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".