Modeling associations between physical recreation engagement and correlates of post-secondary student psychosocial well-being: Exploring differences among students living with and without a mental health condition
Bibliographic record
Abstract
The purpose of the study was to examine on-campus physical recreation engagement as a student-life activity for supporting post-secondary student psychosocial well-being, physical activity (PA) guideline adherence, and academic achievement among post-secondary students. The study aimed to: (1) test a comprehensive model examining associations between engagement in on-campus physical recreation, psychosocial well-being outcomes (campus climate, social support, loneliness, psychological distress), PA guideline adherence, and academic achievement; and (2) explore model differences in the associations among students living with and without a mental health condition. Cross-sectional data from the national spring 2023 Canadian Campus Well-Being Survey were used. The analytical sample included 9575 students ( M age = 23.17 years; 48 % White; 65 % women; 29 % with a mental health condition). Based on findings from structural equation modeling, physical recreation engagement was directly associated with PA guideline adherence, social support, psychological distress, and loneliness. PA guideline adherence, social support, and campus climate were also directly associated with psychological distress, loneliness, and academic achievement. Physical recreation engagement was indirectly associated with more favourable outcomes in academic achievement, psychological distress, and loneliness through higher levels of social support. Physical recreation was indirectly associated with lower levels of psychological distress and loneliness through PA guideline adherence. Exploratory multi-group invariance analyses supported no model differences in the structural associations among students with a mental health condition. Promising targetable processes for supporting student psychosocial well-being through physical recreation engagement are provided. Theoretical and practical implications for informing whole-campus preventive well-being strategies centered on physical recreation among post-secondary students are discussed. • Strategies for improving student well-being through physical recreation are offered. • Well-being benefits were the same among students with a mental health condition. • Student-life engagement among students with a mental health condition is a concern.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".