Into the wild: a mixed-methods pilot study of the mental health benefits of a nature summer camp for urban children with psychological needs
Bibliographic record
Abstract
Research suggests that nature promotes psychological and behavioral health among children. However, children living in low-income urban communities often have less access to green spaces compared to their counterparts living in high-income neighborhoods, and limited research has investigated the impact of nature on well-being and social connectedness in children experiencing marginalization. To address this gap, this mixed-methods study examined the impact of a one-week immersive nature camp on the well-being and social connectedness of 27 children aged 6-12 years referred to a community hub in Ottawa, Canada, for complex psychosocial difficulties. One week prior to and one week after the camp, caregivers completed a survey inquiring about their child's personal well-being, social contact, loneliness, positive emotional state, and positive outlook. On the first and last days of the camp, children completed the same survey. Children also engaged in an audio-recorded focus group about their experience in the camp to inform the quantitative findings. Quantitative and qualitative responses were analyzed using paired samples t-tests and thematic analysis, respectively. Although not statistically significant, small to medium effect sizes for improved positive emotional state and positive outlook were reported by children (p =.26, d = 0.24; p =.14, d = 0.31) and their caregivers (p =.12, d = 0.37; p =.89, d = 0.03). Qualitative thematic analyses of focus groups revealed nine themes including making friends, acquiring new skills, and connecting with nature. Within the Canadian child health context, exposure to green spaces for children with complex psychological difficulties living in low-income urban communities may be associated with perceived enhancements in social connections and skills. Future research with larger sample sizes is needed.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".