Growing Up, Naturally: The Mental Health Legacy of Early Nature Affiliation
Bibliographic record
Abstract
Abstract While many studies now demonstrate the emotional and psychological benefits associated with higher levels of nature connectedness, much less is known about how factors such as childhood nature experiences might influence nature connectedness development. In this two-phase mixed-methods study, the relationship between nature connectedness and childhood nature experiences was explored among a sample of Canadian undergraduate university students. The objectives of the study were twofold: (1) To determine associations between quantitative measures of nature connectedness, positive childhood nature experiences, and mental health via an online survey (Phase One) and (2) To compare, qualitatively, the self-reported childhood nature experiences of students who are relatively more nature connected to those who are less nature connected via in-depth interviews (Phase Two). Quantitative findings from the Phase One online survey demonstrate that, in a sample of university students (N = 308 ) , nature connectedness—which was associated significantly with higher levels of emotional and psychological well-being—correlates positively and significantly with students' self-recalled positive childhood nature experiences. Thematic analysis of qualitative findings from in-depth interviews held with students (n = 12 ) in Phase Two shed additional light on this association: Students who measured relatively higher in nature connectedness recalled growing up in the vicinity of accessible, expansive, natural places, and being raised in families that modeled a love for nature and valued shared nature experiences. Overall, findings suggest that positive experiences in natural places growing up may have long-term mental health benefits through fostering a more ecological self. Key Words: Human development—Ecological self—Mental health—Nature connectedness—Mixed methods—Post-secondary students—Biophilia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".