Is social physique anxiety (SPA) associated with physical activity intentions and behaviour in adults with schizophrenia? A cross-sectional analysis
Bibliographic record
Abstract
Background. Most individuals with schizophrenia spectrum disorders (SSD) are inactive, however the factors influencing physical activity (PA) within this population are understudied. Social physique anxiety (SPA) has been shown to be a significant predictor of PA in healthy populations. Within the SSD population, social anxiety in general has been found to influence PA, but SPA remains unexplored. The purpose of this study is to examine the associations between SPA and PA intentions and PA in individuals with SSD. Methods. As part of a larger 4-week prospective study examining theory-based PA predictors in adults with SSD, participants (N = 111, Mage = 41.09 ± 11.73 years, MBMI = 31.52 ± 8.48 kg/m2, 60% male, 67% diagnosed with schizophrenia) completed a series of instruments at week 4, including the 9-item SPA Scale (Martin et al., 1997), the International Physical Activity Questionnaire (Craig et al., 2003), and wore an accelerometer over a 7-day period. Correlation analyses were conducted to determine the relationships between SPA and (1) intentions to engage in moderate-to-vigorous PA (MVPA) and (2) objective and self-reported MVPA. Results. No significant correlations were found between SPA and either MPVA intentions (r = -.03), or objective (r = -.16) and self-reported (r = -.01) MVPA (all ps > .10). Conclusion. This was the first study to examine the relationship between SPA and PA intentions and behaviour in persons with SSD. Further investigation is needed to understand the role of body image perceptions on the promotion of PA within the SSD population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".