The impact of emissions from an essential oil diffuser on cognitive performance
Bibliographic record
Abstract
Essential oil products are increasingly used in indoor environments and have been found to negatively contribute to indoor air quality. Moreover, the chemicals and fragrances emitted by those products may affect the central nervous system and cognitive function. This study uses a double-blind between-subject design to investigate the cognitive impact of exposure to the emissions from essential oil used in an ultrasonic diffuser. In a simulated office environment where other environmental parameters were maintained constant, 34 female and 25 male university students were randomly allocated into four essential oil exposure scenarios. The first two scenarios contrast lemon oil to pure deionized water, while the latter two focus on different levels of particulate matter differentiated by HEPA filters with non-scented grapeseed oil as the source. Cognitive function was assessed using a computer-based battery consisting of five objective tests that involve reasoning, response inhabitation, memory, risk-taking, and decision-making. Results show that exposure to essential oil emissions caused shortened reaction time at the cost of significantly worse response inhabitation control and memory sensitivity, indicating potentially more impulsive decision-making. The cognitive responses caused by scented lemon oil and non-scented grapeseed oil were similar, as was the perception of odor pleasantness and intensity.
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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 | 0.001 |
| 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) | 0.001 | 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".