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Record W4414245348 · doi:10.1016/j.surg.2025.109657

Harnessing the power of nature in surgery: A systematic scoping review of nature prescribing and measures of benefit

2025· article· en· W4414245348 on OpenAlexafffund
Mimi Thi Nguyen, Emily Liu, Ahmer Karimuddin, Amandeep Ghuman, Annalijn Conklin

Bibliographic record

VenueSurgery · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsCentre for Advancing Health OutcomesSt. Paul's HospitalProvidence Health CareUniversity of British Columbia
FundersMichael Smith Health Research BC
KeywordsCardiorespiratory fitnessPower (physics)MEDLINESystematic reviewEvidence-based medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Natural environments can reduce stress and benefit overall health and nature prescriptions may be a useful adjunct for postoperative care in surgical patients. We sought to identify characteristics and health measures of nature prescriptions in surgery. METHODS: We undertook a scoping review of 5 bibliometric databases (to February 2024) and citations of peer-reviewed original studies examining nature prescription interventions in patients undergoing major surgical procedures requiring anesthesia and hospital admission. Standardized data extraction and narrative synthesis were performed. RESULTS: The search found 2,175 deduplicated eligible records and 20 full-texts for screening. Ten studies were included and covered auditory (n = 3), visual (n = 3), experiential (n = 3), or mixed interventions (n = 1), with small sample sizes (median, 106; interquartile range, 252). About 50% focused on cardiothoracic surgical patients. Interventions varied from viewing plants/trees, listening to bird/water/forest sounds or being physically immersed. Nearly all included studies reported patient-reported outcome measures (eg, anxiety, pain or mood) that significantly improved across all intervention types. Cardiovascular (eg, heart rate, blood pressure) and respiratory (eg, respiratory rate, vital capacity) outcomes were frequently measured, with greater improvements observed in the nature-based intervention groups compared with controls. Few included studies assess other clinical measures (eg, mortality, length of stay, complications) and only 2 evaluated medications to show reductions in the amount of analgesic consumption after being exposed to nature interventions. CONCLUSION: Nature prescribing in surgery appears diverse and shows promise for improving postoperative recovery and well-being through reduced anxiety, pain, cardiorespiratory stress, medication use, and improved mood. Medical and research attention to include nature-based therapy in surgery seems warranted.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.035
metaresearch head score (Gemma)0.157
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.035
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.157
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.011
Bibliometrics0.0100.012
Science and technology studies0.0010.003
Scholarly communication0.0050.005
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.024
GPT teacher head0.275
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractno

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