A Remotely Delivered GLP-1RA–Supported Specialist Weight Management Program in Adults Living With Obesity: Retrospective Service Evaluation
Bibliographic record
Abstract
BACKGROUND: Limited access to specialist weight management services restricts the implementation of novel pharmacotherapies for obesity such as glucagon-like peptide-1 receptor agonists (GLP-1RAs) in the UK National Health Service (NHS). Second Nature, a commercial digital health company, offers a remotely delivered program combining a GLP-1RA medication (semaglutide) with digital behavioral support, potentially providing a scalable solution. However, evidence for long-term effectiveness in this real-world context is limited. OBJECTIVE: This study aimed to evaluate the 12-month effectiveness, feasibility, acceptability, and potential cost-effectiveness of the remotely delivered, semaglutide-supported weight management program by Second Nature. METHODS: This retrospective service evaluation analyzed data from participants who initiated the program between September and December 2023. The primary outcome was weight change at 12 months among participants with available data (completers). Secondary outcomes included retention, program engagement (measured by views of the Home screen in the app), behavioral changes, side effects, participant experience (qualitative analysis), and a comparative cost analysis against an NHS specialist weight management service. An "active subscription" was defined as maintaining a paid subscription for the full 12-month period. Descriptive statistics and paired 2-tailed t tests evaluated outcomes. RESULTS: ). At 12 months, 39.6% (135/206) maintained an active subscription, while 60.4% (206/341) became inactive. Weight data at 12 months were available for 179 participants (52.5% of the baseline cohort; 100% of active and 19.4% of inactive participants). Among completers who maintained an active subscription, the mean weight loss was 20.0 kg (SD 8.7 kg; P<.001), representing 19.1% of starting weight. Overall, 77.7% (139/179) of completers achieved ≥10% weight loss and 61.5% (110/179) achieved ≥15%. Program engagement declined over time. Side effects also decreased, with 69.6% (81/116) of respondents reporting none by month 12. Most participants completing the 12-month survey reported positive (41/120, 34.2%) or neutral (68/120, 56.7%) experiences. CONCLUSIONS: This evaluation suggests that remotely delivered GLP-1RA-supported weight management can achieve significant weight loss in participants remaining engaged for 12 months. However, the high rate of withdrawal limits generalizability. The program appears feasible, acceptable, and potentially cost-effective for completers. Further research, ideally in public health care settings using intent-to-treat analyses, is needed to confirm clinical outcomes, assess sustained results, and understand factors influencing retention.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".