Prescription exercise at Queen's: A prospective program evaluation of physical activity effects among university students with depression and anxiety
Bibliographic record
Abstract
Participation in physical activity (PA) may lead to positive improvements in mental health status. Prescription Exercise at Queen's (PE-Q) is an eight-week PA program that offers students with mild to moderate depression and/or anxiety with the option to supplement their treatment with exercise. The program includes personal training sessions, self-selected PA, and a peer-delivered 'Brief Action Planning' self-management component. The purpose of this study was to evaluate the impact of the PE-Q program on participants' mental health symptoms and PA behaviour and social cognitions (based on the Health Action Process Approach). Twenty-one participants completed pre-, mid- and post-program online questionnaires. Separate repeated measures ANOVAs and post-hoc t-tests evaluated changes in participants' mental health symptoms, PA behaviour and social cognitions. Significant decreases in participants' depression symptoms and anxiety symptoms were reported from pre- to mid-program (ds ? 0.98; ps < 0.05), which were maintained from mid- to post-program. Significant increases in participants' PA planning and action control were reported from pre-to mid-program (ds ? 1.04; ps < 0.05), which were also maintained from mid- to post-program. In general, students provided high ratings for program instructiveness, usefulness, credibility, and personal importance (all Ms ? 5.57 out of 7). While these findings contribute to existing literature on holistic treatment programs for students with mental illnesses, further testing with a control group and an adequately-powered sample is warranted.Acknowledgments: Funding for the PE-Q program 2017-2018 was provided by a Special Projects Grant from Michael Condra in the Department of Psychology at Queen's University. Initial startup funding for the PE-Q program was provided by the First Year Experience Fund (Queen's University) and jack.org. Ms. Flood is supported by a SSHRC Canadian Graduate Scholarship - Master's.
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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 | 0.002 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".