Text messaging with or without financial incentives versus a waitlist control for weight loss in men: cost-effectiveness analysis of the Game of Stones randomised controlled trial
Bibliographic record
Abstract
Background: Cost-effective weight loss interventions are needed for people with obesity, particularly men, who are less likely to engage with weight loss programmes. This study aimed to investigate the cost-effectiveness of text messaging plus financial incentives and text messaging alone compared to a waitlist control to help men lose weight. Methods: 585 men with obesity were recruited to Game of Stones (GoS): a 3-arm randomised controlled trial in 3 UK areas. Text messaging alone participants received daily automated behavioural texts for 12-months (3% weight loss). Text messaging with financial incentives participants also received loss-framed financial incentives linked to achieving weight loss targets at 12-months (5% significant weight loss). A control group received no intervention for 12 months (1.3% weight loss) followed by 3 months of texts. We conducted a 24-month within-trial cost-effectiveness analysis and lifetime decision model from a UK NHS perspective. The PRIMEtime model extrapolated the impact of GoS weight-loss data on lifetime obesity related disease incidence, costs, and QALYs. Weight regain assumptions were explored in scenario analyses. Findings: Text messaging with financial incentives costs £243 and text messaging alone costs £110 per participant to deliver. There were no significant differences between 24-month total costs or QALYs across groups. When modelled over lifetime, the mean discounted QALYs per person were 12.48, 12.49, and 12.46 for text messaging with financial incentives, text messaging alone, and waitlist control, respectively. The corresponding mean discounted total costs per person were £15,277, £15,117, and £15,100. The between group results for text messaging with financial incentives versus control were: QALY difference (95% CI): 0.02 (0.007, 0.029); cost difference: £176 (£43; £311); Incremental cost-effectiveness ratio (ICER): £9748 (£7,705, £11,791). For text messaging alone versus control: QALY difference: 0.03 (0.015, 0.037); cost difference: £16.5 (-£117; £152); ICER: £628 (£-5,914, £5384). Interpretation: Text messaging with financial incentives and text messaging alone are cost-effective compared to waitlist control. Both are relatively low-cost interventions that can be scaled to improve weight loss for men. The optimal strategy between them depends on weight regain assumptions after 12 months. Funding: National Institute for Health and Care Research (Ref: NIHR 129703). Trial Registration isrctn.org Identifier: ISRCTN91974895.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".