Secondary analysis of the Game of Stones trial of text messages with financial incentives for men with obesity
Bibliographic record
Abstract
Abstract Objective To explore whether socio-economic, health and behavioural characteristics moderate effectiveness of a text message intervention with or without financial incentives versus a control group, and to examine differences in exploratory outcomes. Methods Three-group randomized trial including 585 men with obesity comparing daily automated behavioural text messages for 12-months alongside financial incentives; text messages alone; or a waiting list control. Moderator analyses examined percent weight change after 12 months for 9 socio-economic and 11 health factors. Exploratory outcomes included: self-reported physical activity, sedentary behaviour, smoking and alcohol behaviours, engagement in 15 weight management strategies, and weight-management related confidence. Results No moderator effects were found by any factors for either comparison versus control. There were no differences between groups for health behaviours. The texts with incentives group had higher levels of engagement in six strategies including weight goals, food changes and self-weighing, and higher levels of confidence compared to the control group. Conclusion No evidence of differential intervention effectiveness was found across socio-economic, health or wellbeing status. The texts and financial incentives group showed greater engagement in weight management and favourable changes in weight management confidence compared to the control group.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 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".