Evaluation of the Clinical and Economic Effects of a Primary Care Anchored, Collaborative, Electronic Health Lifestyle Coaching Program in Denmark: Protocol for a Two-Year Randomized Controlled Trial
Bibliographic record
Abstract
Background Obesity is linked to a number of chronic health conditions, such as type 2 diabetes, heart disease, and cancer, and weight loss interventions are often expensive. Recent systematic reviews concluded that app and web-based interventions can improve lifestyle behaviors and weight loss at a reasonable cost, but long-term sustainability needs to be demonstrated. Objective This study protocol is for a 2-year randomized controlled trial that aims to evaluate the clinical and economic effects of a primary care, anchored, collaborative, electronic health (eHealth) lifestyle coaching program (long-term Lifestyle change InterVention and eHealth Application [LIVA] 2.0) in obese participants with and without type 2 diabetes. The program’s primary outcome is weight loss. Its secondary outcome is the hemoglobin A1c (HbA1c) level, and its tertiary outcomes are retention rate, quality of life (QOL), and cost effectiveness. Analytically, the focus is on associations of participant characteristics with outcomes and sustainability. Methods We conduct a multicenter trial with a 1-year intervention and 1-year retention. LIVA 2.0 is implemented in municipalities within administrative regions in Denmark, specifically eight municipalities located within the Region of Southern Denmark and two municipalities located within the Capital Region of Denmark. The participants are assessed at baseline and at 6-, 12-, and 24-month follow-ups. Individual data from the LIVA 2.0 platform are combined with clinical measurements, questionnaires, and participants’ usage of municipality and health care services. The participants have a BMI ≥30 but ≤45 kg/m2, and 50% of the participants have type 2 diabetes. The participants are randomized in an approximately 60:40 manner, and based on sample size calculations on weight loss and intention-to-treat statistics, 200 participants are randomized to an intervention group and 140 are randomized to a control group. The control group is offered the conventional preventive program of the municipality, and it is compared to the intervention group, which follows the LIVA 2.0 in addition to the conventional preventive program. Results The first baseline assessments have been carried out in March 2018, and the 2-year follow-up will be carried out between March 2020 and April 2021. The hypothesis is that the trial results will demonstrate decreased body weight and that the number of patients who show normalization of their HbA1c levels in the intervention group will be much higher than that in the control group. The participants in the intervention group are also expected to show a greater decrease in their use of glucose-lowering medication and a greater improvement in their QOL when compared with the control group. Operational costs are expected to be lower than standard care, and the intervention is expected to be cost-effective. Conclusions This is the first time that an app and web-based eHealth lifestyle coaching program implemented in Danish municipalities will be clinically and economically evaluated. If the LIVA 2.0 eHealth lifestyle coaching program is proven to be effective, there is great potential for decreasing the rates of obesity, diabetes, and related chronic diseases. Trial Registration ClinicalTrials.gov NCT03788915; https://clinicaltrials.gov/ct2/show/NCT03788915 International Registered Report Identifier (IRRID) DERR1-10.2196/19172
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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 | 0.070 | 0.052 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.011 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.041 | 0.010 |
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".