Is the affective response to exercise related to motivations and future physical activity behaviour in schizophrenia
Bibliographic record
Abstract
Physical activity (PA) provides numerous health benefits, which may help manage physical comorbidity among people with schizophrenia. However, cognitive impairments are additional concerns for persons with schizophrenia that may reduce the usefulness of cognitive determinants commonly used in behaviour change models to predict and modify PA behaviour. In order to better understand non-cognitive (i.e. hedonic) motivations to engage in PA in this population, it is relevant to examine whether affective responses to PA are a determinant of PA behaviour. Therefore, the purpose of this study was to determine whether change in pleasure, as measured by the Feeling Scale at the midpoint of a 10-minute bout of moderate intensity treadmill exercise, is related to task self-efficacy, affective outcome expectancies, and intentions to engage in PA measured 1 week prior to the exercise session as well as PA measured by accelerometry 2 weeks after the exercise session. Twenty-eight participants completed the study. Differences in self-reported pleasure from baseline to the midpoint in the 10-minute exercise session were correlated with task self-efficacy, affective attitudes and intentions, as well as average daily minutes of moderate-to-vigorous PA (MVPA). Pleasure during exercise correlated significantly with task self-efficacy (r=.40, p=.035) and intentions (r=.38, p=.045), but not with affective outcome expectancies (r=.05, p=.80) nor MVPA (r=.32, p=.11). Overall, findings support the hypothesis that the affective response to exercise relates to key motivational constructs and future physical activity. Interventions to manipulate affect during exercise require development and evaluation. Acknowledgments: This study was supported by a CIHR Operating Grant and an Ontario Graduate Scholarship
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".