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Record W4414245832 · doi:10.3390/jal5030035

The Impact of Nature-Based Interventions on Physical, Psychosocial, and Physiological Functioning for Physical Chronic Diseases: A Systematic Review

2025· review· en· W4414245832 on OpenAlexafffund
Émilie Fortin, Marie-Ève Langelier, Guillaume Léonard, Rubens Alexandre da Silva

Bibliographic record

VenueJournal of Ageing and Longevity · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanUniversité de SherbrookeUniversité du Québec à Chicoutimi
FundersUniversité du Québec à Chicoutimi
KeywordsCINAHLQuality of life (healthcare)Psychological interventionIntervention (counseling)Physical activitySystematic reviewDisease

Abstract

fetched live from OpenAlex

Background: Although nature exposure is recognized for its beneficial effects on psychological, cognitive, and physiological health, its impact on physical function has been underexplored. The main aim of this paper is to cover this gap. Methods: A systematic search of Cochrane, CINAHL Plus, and PubMed databases (2012–2023) was conducted using terms related to nature and physical function. Results: Eight intervention studies (total n = 209, age 25–91) met the inclusion criteria. NBIs, such as horticultural therapy and forest therapy, demonstrated generally positive effects across physical, psychosocial, and physiological outcomes, though effect size and quality varied. Study quality ranged from low to high. Conclusions: NBIs appear to promote multi-dimensional functioning in people living with physical chronic disease and offer promising complementary strategies to traditional rehabilitation.

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)0.005
metaresearch head score (Gemma)0.019
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 score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.039
GPT teacher head0.402
Teacher spread0.363 · 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 abstractyes

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