Exercise practices in individuals at clinical high risk of developing psychosis
Bibliographic record
Abstract
AIM: Recent research suggests aerobic exercise has a positive impact on symptoms and cognition in psychosis. Because individuals with psychosis are at risk of weight gain and the resultant metabolic side-effects, developing effective exercise programmes is of interest. Furthermore, this may be a useful intervention for those who are at risk of developing psychosis, that is, those at clinical high risk (CHR). The aim of this initial exploratory project was to examine the role of exercise in participants at CHR for psychosis. METHODS: A comprehensive questionnaire was developed to assess current physical activity involvement; exercise levels in terms of frequency, intensity and duration; and perceived fitness levels. Reported barriers to exercise and reasons for exercising were also considered. Eighty participants, 40 CHR and 40 healthy controls, were assessed with this questionnaire. RESULTS: Overall, both groups were involved in a wide range of physical activity. Healthy controls reported higher levels of participation in indoor/outdoor activities and strength and/or flexibility training. They also exercised more frequently, more intensely and reported higher perceived fitness levels than CHR participants. Levels of exercise were unrelated to clinical symptoms and functioning in CHR participants. CHR youth reported more barriers to exercise and less positive reasons for exercising that were related to self-perception. CONCLUSION: The results suggest that exercise should be investigated further in the CHR population as it may have treatment implications.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".