Investigating the association between physical activity and the built environment among individuals with schizophrenia
Bibliographic record
Abstract
Background: Despite the known benefits of physical activity (PA) for persons with schizophrenia, most of the population is not meeting PA recommendations. One strategy that may influence the PA of persons with schizophrenia is approaches that provide environmental opportunities and supports to assist individuals in becoming more active. Currently, there is limited knowledge on the role of the environment in the PA behaviour of this population. The purpose of this study was to examine the relationship between perceptions of the built environment and PA among individuals with schizophrenia. Methods: A total of 112 participants (45 female) with schizophrenia (Mage = 41.2±12 years) completed the Physical Activity Neighbourhood Environment Survey (PANES) and wore an accelerometer over a 7-day period. Pearson correlations were used to explore associations between daily minutes of moderate-to-vigorous PA (MVPA) and steps counts, environmental perceptions (residential density, land use mix, transit access, pedestrian and bicycling infrastructure, recreation facilities, street connectivity, traffic, crime and pedestrian safety, and aesthetics) and demographics (age, BMI, gender). Only those variables demonstrating a significant correlation with PA were included in the linear regression. Results: Aesthetics and age were the only variables significantly related to MVPA (R2 = 0.09; β = 0.21, p < 0.05 and β = -0.27, p > 0.01, respectively) and steps counts (R2 = 0.11; β = 0.28, p 0.05, respectively). Conclusion: These findings suggest that an aesthetically appealing environment may have a small influence on daily MVPA behaviour among individuals with schizophrenia, irrespective of age.Acknowledgments: This study is supported by Canadian Institutes of Health Research (operating grant).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".