Mental health and weight loss in men: an exploratory mixed methods study of the Game of Stones trial
Bibliographic record
Abstract
Abstract Objective Weight management interventions can affect mental health. Mental health can affect engagement with weight loss interventions or services. This study explored mental health and wellbeing outcomes, retention and participant experiences of mental health within the Game of Stones trial. Methods Mixed methods process evaluation within a 3-group randomised controlled trial: behavioural text messages with financial incentives, texts alone, and waiting list control, for 585 men with obesity. Secondary outcomes analysed descriptively included: Warwick-Edinburgh Mental Wellbeing Scale, Weight Self-Stigma Questionnaire, EQ-5D-5L, EQ-5D-5L anxiety and depression subscale, Patient Health Questionniare-4, and retention. Three categories of participants were compared: ever diagnosed with a mental health condition (n=146; 25.0%), latent mental health condition (n=142; 24.3%) no mental health condition (n=295; 50.6%). Semi-structured interviews (n=54) were conducted after 12 months and analysed using Framework method. Results A higher proportion of men who self-reported ever having a mental health condition had a disability, multiple long-term conditions, were under financial strain and were single compared to those with those with a latent mental health condition and no mental health condition. Improvements from baseline were shown for weight stigma, wellbeing and PHQ-4 at 12 months for men in intervention groups with a mental health condition and latent mental health condition. EQ-5D-5L Visual Analogue Scale scores improved across all mental health categories and trial groups, but EQ-5D-5L and EQ-5D-5L-AD scores were inconsistent. Retention at 12 months was 76.0% (mental health condition), 70.4% (latent mental health condition) and 72.5% (no mental health condition). The qualitative evidence indicated that stress, anxiety and depression were experienced in different ways by men during the programme. Mental health difficulties were unique to the individual, could be episodic, recurrent, cyclical or ongoing and were a barrier to behaviour change for some but not for others. Conclusion The trial was able to engage and retain men regardless of mental health category. Behavioural text messages with or without incentives helped some men lose weight, but not others. Observed heterogeneity for mental health and wellbeing measures is problematic for weight management trials with men.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".