The reduction of directed attention fatigue through exposure to visual nature stimuli: Exploring a natural therapy for fatigue
Bibliographic record
Abstract
This study compares the restorative effects on directed attention functioning following exposure to natural landscape images versus scrambled/distorted landscape images. Attention restoration theory (ART) provides an analysis of the stimuli and environment required for restoration of cognitive fatigue. According to ART, nature employs attention through a bottom-up process in which intrinsically fascinating stimuli from the natural environment itself modestly dominate attention. This allows the mechanisms responsible for top-down processing, which is necessary for directed attention, to recover and replenish. Unlike natural environments, urban environments employ attention through bottom-up stimulation, which forces one to overcome the stimulation using directed attention, thus not allowing for the recovery of directed attention mechanisms. This study looks into whether solely visual stimulation of natural environments is adequate for the restoration of directed attention mechanisms as measured with the “Attention Test” application. The mean completion time on the Attention Test game was significantly lower in the nature image group (M = 54.33) when compared to the scrambled image group (M = 62.04), thus validating the visual aspect of ART.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".