Is It the Walk or the Park? Exploring Associations Between Exposure to Nature in General and Through Physical Activity and Positive Mental Health in Young Adults in Canada
Bibliographic record
Abstract
BACKGROUND: This study aimed to assess the relationship between exposure to nature in the context of (1) general life and (2) physical activity (PA) and positive mental health in young adults. METHODS: A total of 357 young adults (Mage = 21.9 y old) from the MATCH study reported their exposure to nature in 2 different contexts and positive mental health twice at 12-month intervals. Exposure to nature was categorized into 4 groups based on their self-reported exposure to nature (low or high) in general life and in the context of PA. Multivariable linear regression models assessed the relationship between nature exposure and positive mental health scores, controlling for gender, age, PA level, financial well-being, and positive mental health at baseline. RESULTS: Relative to the low general/low PA nature exposure group, the high general/high PA nature exposure group (β^ [95% CI] 3.61 [1.12 to 6.10]) reported better positive mental health scores, but the high general/low PA nature exposure group (β^ [95% CI], 1.71 [-1.78 to 4.60]) and low general/high PA nature exposure group (β^ [95% CI] 1.69 [-0.79 to 4.17]) were not different, after adjusting for all covariates, including positive mental health at baseline. CONCLUSION: The current study suggests that higher exposure to nature in both the context of PA and general life is associated with better mental health. It underscores the importance of encouraging exposure to nature in different contexts during early adulthood to foster and protect mental health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".