Effects of in-car CO2 concentration on driving: a preliminary study with taxi drivers
Kan Shimazaki; Yo Ishigaki; Kazunori Hayashi; Koji Fujita · 2025 · Environmental and Occupational Health Practice
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Objectives: To evaluate the effects of carbon dioxide (CO2) concentrations in automobiles on driving performance. Methods: A driving simulator experiment was conducted with eight taxi drivers. The experiment was conducted under low CO2 concentration (<500 ppm) and high CO2 concentration (5,000 ppm) conditions. To evaluate driving performance and cognitive function, three measures were employed: a two-back task, an LED response task, and a driving assessment. The driving assessment used scoring criteria from the driving license proficiency test. Results: Poisson regression analysis showed that
Abstract by Kan Shimazaki; Yo Ishigaki; Kazunori Hayashi; Koji Fujita, Environmental and Occupational Health Practice (2025) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
t-Test at the Probe Level: An Alternative Method to Identify Statistically Significant Genes for Microarray Data
Negative / Null Result ReportMeteorological Causes of the Secular Variations in Observed Extreme Precipitation Events for the Conterminous United States
Negative / Null Result ReportThe Next Generation of Sepsis Clinical Trial Designs
Negative / Null Result ReportAnalysis of DNA Methylation in Young People: Limited Evidence for an Association Between Victimization Stress and Epigenetic Variation in Blood
Negative / Null Result ReportStudy preregistration: an early example and analysis.
Negative / Null Result ReportInsights Into LSTM Fully Convolutional Networks for Time Series Classification
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: DOAJ · DOI 10.1539/eohp.2025-0001