MétaCan
Menu
Back to cohort
Record W2912188587 · doi:10.1089/eco.2018.0061

Mindfulness in Nature Enhances Connectedness and Mood

2019· article· en· W2912188587 on OpenAlex
Elizabeth K. Nisbet, John M. Zelenski, Zsuzsa Grandpierre

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEcopsychology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsCarleton UniversityTrent University
Fundersnot available
KeywordsMindfulnessSocial connectednessMoodPsychologyAffect (linguistics)FeelingPsychotherapistClinical psychologySocial psychologyCommunication

Abstract

fetched live from OpenAlex

Previous research has demonstrated that brief contact with the natural environment can boost feelings of connectedness with nature (nature relatedness) and mood. Less is known about whether mindful awareness of nature improves outdoor experiences, however. We tested the possibility that mindfulness instruction would enhance mood during nature exposure in an urban setting. Participants (n = 100) were randomly assigned to a 20 min guided walk outdoors, outdoors with mindfulness, or indoors. Participants who walked outdoors reported substantially more nature relatedness and better moods than those who walked indoors. Participants who also received mindfulness training reported greater awareness of their surroundings, stronger connectedness with nature, and less negative affect, even compared to outdoor walkers without mindfulness instruction. However, mindfulness did not produce significantly more positive affect outdoors in nearby nature. Results suggest that mindfulness may enhance some beneficial effects of nature exposure.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.006
GPT teacher head0.265
Teacher spread0.259 · 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