Prescribing Nature for Human Health: An Examination of Public Interest, Barriers, and Enablers Related to Nature Prescription Programming in Canada
Bibliographic record
Abstract
• Adoption of nature prescription programming to address health challenges through increased contact with nature is unprecedented globally and especially in Canada. • Very limited studies focus on public awareness of, interest in, and the barriers and enablers to participation in nature prescription programs. • We find that while public awareness of such programmes is very low, interest is very high if a trusted healthcare professional suggested that nature contact would be good for an individual's health. • Several barriers to the participation in nature prescription programs exist and are particularly acute for Newcomers to Canada, the BIPOC community, young people, individuals who self-identify, and individuals with children. • To harness the full potential of nature prescriptions, enablers such as health insurance coverage, free access to parks, and free transportation should be used to enhance evidence-based and inclusive programming. Nature prescriptions are emerging as a promising preventive healthcare strategy. Despite their proliferation in recent years, limited research exists on public awareness, interest, and the factors that may influence the success of such programs. For the first time in the Canadian context, we examine public awareness of nature prescription programs and explore the barriers and enablers that may impact their uptake. Using a cross-sectional, online survey of 3,593 respondents, we reveal that over 75% of participants would be more likely to visit natural areas if recommended by a healthcare professional. However, more than 92% of respondents reported being unaware of nature prescription programs. We also reveal several structural, intrapersonal, and interpersonal barriers to accessing nature, which are particularly pronounced for certain subpopulations, including Newcomers, BIPOC, young adults, individuals who self-identify, and individuals with children. We identify the key enablers that could reduce such barriers, including health insurance coverage, free park access, and subsidized transportation. Finally, we discuss the ways in which strategically employing these enablers could help reduce disparities in access to nature and enhance the overall effectiveness of nature prescription programs as they expand in Canada and indeed globally. Effectively leveraging the high levels of public trust and expertise that exist within both the healthcare and conservation sectors in the co-design of programs, as well as more effective policy uptake by health insurance providers, will be essential to advancing this promising frontier in preventative health care and nature conservation.
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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) | 0.000 | 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".