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Record W4414810729 · doi:10.1080/20445911.2025.2568144

Assessing the objective and subjective impacts of nature for reducing cognitive fatigue

2025· article· en· W4414810729 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Cognitive Psychology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsCognitionWorking memoryMental fatigueSet (abstract data type)ConfoundingEffects of sleep deprivation on cognitive performanceElementary cognitive task

Abstract

fetched live from OpenAlex

Exposure to nature can help recover cognitive fatigue by enhancing working memory, attention control, and cognitive flexibility. However, these effects may be impacted by multiple confounding variables, including engagement level and baseline differences. Additionally, it remains unclear whether changes in objective restoration measures may extend to perceived fatigue as well. This study examined whether nature could reduce cognitive fatigue while controlling for initial fatigue levels and using a set of objective and subjective outcomes. Participants performed working memory and attention control tasks at pretest and posttest. Between these tests, they went through a cognitive fatigue task, followed by exposure to either nature or urban pictures on a computer. Measures of subjective fatigue, performance, and prefrontal cerebral activity were collected. While performance and neurophysiological measures were similar across conditions, nature exposure improved subjective fatigue reports, unlike urban exposure. This finding highlights how subjective and objective experiences of attention restoration may differ.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.411
Teacher spread0.383 · 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