Improving Health Behaviours and Clinical Factors in Individuals at Risk for Developing Noncommunicable Diseases: The ACCELERATION Program
Bibliographic record
Abstract
Background. Noncommunicable diseases (NCDs: e.g., heart disease, cancer) account for 71% of global deaths. Behavioural risk factors, like physical inactivity and inadequate nutrition, are crucial targets for effectively preventing such diseases. This cohort study evaluated the efficacy of a 12-week lifestyle behaviour change program, called ACCELERATION, for changing lifestyle behaviours (such as physical activity and diet) in individuals at risk of developing NCDs. ACCELERATION was rooted in evidence-based behaviour change techniques/frameworks (such as goal setting, action planning, and motivational communication). Methods. Individuals at risk for developing NCDs (N = 696) were recruited across four sites in Canada (British Columbia, Nova Scotia, Ontario, Quebec) to participate in the ACCELERATION program. Healthy lifestyle behaviours (e.g., physical activity, fruit and vegetable consumption) and markers of psychological/physical health (e.g., depression, blood pressure, waist circumference) were assessed at baseline, immediately after the intervention, and 6-months post-intervention.Results. By the end of the intervention, participants had increased their weekly levels of moderate-to-vigorous physical activity by 76.4 minutes (95% CI: 58.8 to 93.9), and their daily consumption of fruits and vegetables by 0.5 cups (95% CI: 0.3 to 0.6). Participants also showed significant improvements in psychological function (lower depression, better sleep) and physical health (e.g., reduced blood cholesterol, body mass index, waist circumference). Positive changes were generally maintained by 6 months post-intervention. Interpretation. Our findings support the efficacy of the ACCELERATION program for improving healthy lifestyle behaviour change. Other programs may find it beneficial to incorporate similar behaviour change principles (e.g., motivational communication). Trial registration: NCT02264366
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".