Duration and economic value of a walking‐in‐nature therapy programme: Implications for conservation
Bibliographic record
Abstract
Abstract Nature exposure, such as visiting protected areas, provides mental health benefits that reduce healthcare costs and improve productivity, with global values in the trillions. Countries are bringing nature‐based programs into mainstream mental healthcare via nature therapies. This study quantifies the scale, duration and economic value of mental health benefits from a long‐established nature therapy programme and implications for conservation. Using a Before‐After‐Control‐Impact design, we evaluated a 12‐week nature walking programme with social mechanisms for therapeutic adherence. Mental health was assessed using the Personal Well‐being Index (PWI), a measure of subjective well‐being, with participants and controls from the same subpopulation. Measurements occurred at programme start, end and 12 weeks post‐intervention. Economic benefits were calculated using the financial value of quality‐adjusted life‐years. The nature‐based therapy programme improved the mental well‐being of participants during the programme and for at least 3 months afterwards. While controls showed well‐being improvements when they reported having physically exercised (despite not being instructed to), programme participants exhibited an additional PWI increase of 5.1%. Training in nature was a critical component, leading to the highest increase in mental health benefits, and doubling of their duration (up to 12 months). Mean total economic benefit per participant who followed the programme design in full was c.AU$4000. Total economic contribution via mental health, adjusted for socio‐economic and demographic factors, participation patterns, post‐programme fade‐out and the national number of participants each year, is therefore c.AU$20 million per annum. Mental health benefits of nature visits fade once people stop visiting parks. To maximise their contribution to political and economic support for protected areas, therefore, the focus for future research and practice should be on social mechanisms to promote lifelong park visit habits. Read the free Plain Language Summary for this article on the Journal blog.
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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 | 0.000 | 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".