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Record W4410572390 · doi:10.1016/j.lanepe.2025.101328

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

2025· article· en· W4410572390 on OpenAlexaff
Abraham M. Getaneh, Marjon van der Pol, Dwayne Boyers, Alison Avenell, Seonaidh Cotton, Stephan U Dombrowski, Cindy M. Gray, Frank Kee, Lisa Macaulay, Michelle C. McKinley, Catriona O’Dolan, James Swingler, Claire Torrens, Katrina Turner, Graeme MacLennan, Pat Hoddinott

Bibliographic record

VenueThe Lancet Regional Health - Europe · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsUniversity of New Brunswick
FundersNHS Bristol, North Somerset and South Gloucestershire Integrated Care BoardPublic Health AgencyNational Institute for Health and Care ResearchHealth and Social Care Northern IrelandGovernment of the United KingdomChief Scientist Office, Scottish Government Health and Social Care DirectorateScottish Government Health and Social Care DirectorateScottish GovernmentNHS Greater Glasgow and Clyde
KeywordsRandomized controlled trialIncentiveControl (management)PsychologyText messagingPhysical therapyFinanceMedicineGerontologyComputer scienceBusinessEconomicsInternet privacyInternal medicineManagement

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.070
GPT teacher head0.436
Teacher spread0.365 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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