Evaluation of the Low Carb Program Digital Intervention for the Self-Management of Type 2 Diabetes and Prediabetes in an NHS England General Practice: Single-Arm Prospective Study
Bibliographic record
Abstract
Background Type 2 diabetes mellitus has serious health consequences, including blindness, amputation, and stroke. Researchers and clinicians are increasingly in agreement that type 2 diabetes may be effectively treated with a carbohydrate-reduced diet. Digital apps are increasingly used as an adjunct to traditional health care provisions to support remote self-management of long-term health conditions. Objective Our objective was to evaluate the real-world 12-month outcomes of patients prescribed the Low Carb Program digital health intervention at a primary care National Health Service (NHS) site. The Low Carb Program is a nutritionally focused, 12-session, digitally delivered, educational behavior change intervention for glycemic control and weight loss for adults with prediabetes and type 2 diabetes. The program educates and supports sustainable dietary changes focused on carbohydrate restriction by utilizing behavior change techniques, including goal setting, peer support, and behavioral self-monitoring, as well as personalized downloadable resources, including recipes and meal plans tailored to ethnicity, weekly shopping budget, and dietary preferences. Methods This study evaluated the real-world outcomes of patients recruited to the Low Carb Program at an NHS general practice in Southport, United Kingdom. All of the NHS patients recruited to the program were diagnosed with type 2 diabetes or prediabetes and were given access to the program at no cost. A total of 45 participants, with a mean age of 54.8 years (SD 13.2), were included in the study. Women made up 42% (19/45) of the sample. The mean hemoglobin A1c (HbA1c) of the sample was 56.7 mmol/mol (SD 16.95) and the mean body weight was 89.4 kg (SD 13.8). Results Of the 45 study participants recruited to the program, all of them (100%) activated their accounts and 37 (82%) individuals reported outcomes at 12 months. All 45 (100%) patients completed at least 40% of the lessons and 32 (71%) individuals completed more than nine out of 12 core lessons of the program. Glycemic control and weight loss improved, particularly for participants who completed more than nine core lessons in the program over 12 months. The mean HbA1c went from 58.8 mmol/mol at baseline to 54.0 mmol/mol, representing a mean reduction of 4.78 mmol/mol (SD 4.60; t31=5.87; P<.001). Results showed an average total body weight reduction of 4.17%, with an average weight reduction of 3.85 kg (SD 2.49; t31=9.27; P<.001) at the 12-month follow-up point. Conclusions A digital app prescribed to adults with type 2 diabetes and prediabetes in a primary care setting supporting a transition to a low-carbohydrate diet has been shown to be effective in improving glycemic control and enabling weight loss. Further research to understand more about factors affecting engagement with the app and further positive health implications would be valuable.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".