THE EFFECTS OF LISTENING WHILE DRIVING IN OLDER AND YOUNGER ADULTS
Bibliographic record
Abstract
Abstract Driving collisions are a top cause of accidental death globally and adults aged 65+ are overrepresented. Driving is a highly complex task, requiring sensory processing, motor control, and divided attention. Driving is especially challenging when simultaneously listening to a passenger. Age-related declines in sensory (e.g., hearing) and cognitive abilities (e.g., working memory) may result in increased effort while listening. High listening effort may reduce spare cognitive capacity, thereby limiting the cognitive resources available to support driving. However, there are very few realistic and controlled experiments examining how the demands of listening while driving are managed in older adults. Therefore, the main objective of this study was to examine performance during a driving-while-listening task in older (aged 61-80 years, 15 female) and younger (aged 20-36 years, 12 female) adults with normal hearing/vision, and cognition, using a high-fidelity driving simulator. Participants completed a driving task at two different driving loads (e.g., straight in rural (low) vs. left turn in city (high)), a listening task (Connected Speech Test [CST]) at two different listening loads (+4 signal-to-noise ratio [SNR], 0 SNR), and both tasks together, to examine dual-task costs. Results demonstrated that only older adults showed significantly lower CST accuracy scores in the dual- compared to single-task conditions across both SNRs. Both older and younger adults showed significantly greater SD of lane position in the dual- compared to the single-task conditions, only under high driving load. Findings may inform educational practices, policies, and technological solutions to maintain and support safe driving among older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".