Physical activity programming for post-secondary student mental health: Examining the effectiveness of online delivery in response to the COVID-19 pandemic
Bibliographic record
Abstract
In response to the COVID-19 pandemic and lockdown restrictions, telehealth physical activity intervention approaches are increasingly replacing face-to-face modes of delivery. At the University of Toronto, a face-to-face 6-week one-on-one and individualized physical activity program for post-secondary student mental health was adapted to online delivery. The effectiveness of the face-to-face program for student mental health has been demonstrated. Yet, the effectiveness of the online delivery approach is unknown. A pretest-posttest design was implemented to examine the effectiveness of the online program in promoting mental health and social connectedness among students identifying with poor mental health. Program participants (N = 26; M(SD)age = 25.32 (5.03) years; 92.3% female) completed self-report questionnaires to assess pre-post changes in mental health recovery, social connectedness, and depression and anxiety symptoms. Paired sample t-tests demonstrated a significant improvement in mental health recovery (M(SD)pre = 15.91 (4.99); M(SD)post = 18.58 (5.21)) and social connectedness (M(SD)pre = 3.56 (1.54); M(SD)post = 4.32 (1.41)) from pre to post intervention (ps
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".