Brief theory-based intervention to increase physical activity levels among obese men with severe mental illness: A feasibility study
Bibliographic record
Abstract
Context: People with severe mental illness (SMI) have a reduced life expectancy notably because of cardiovascular disease and their metabolic consequences, including obesity. Although physical activity (PA) is recommended, people with SMI are insufficiently active and have high levels of sedentary behaviours. So, there is a need to develop interventions to increase PA. The objective of the present study was to evaluate the feasibility of a brief intervention on PA level among adults with obesity and SMI. Methods: Open 6-week brief intervention using a volitional help sheet based on the processes of change from the transtheoretical model and the implementation intention. PA and time spent in sedentary behaviours were evaluated using the International Physical Activity Questionnaire. Results: 12 men (mean age: 33.2±10.1) with obesity (mean BMI: 35.8±7.7 kg/m²) and diagnosis of SMI (75% with schizophrenia) were recruited. In terms of feasibility, the adherence rate was 100% and no drop-out was noted. 80% of participants reported that the project met their expectations and 92% would refer a relative or a peer to the project. Moreover, 77% reported that the project has facilitated another behaviour change (e.g., healthy eating). In terms of impact, a significant improvement were found regarding total PA (d = 0.76), walking behaviour (d = 1.01) and reduction in time spent sitting (d = -0.75). Conclusion: The theory-based brief intervention is feasible and has promising results. However, replication is needed with larger sample size to validate our results.Acknowledgments: AJR is supported by the FRQS
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".