Road to Serenity: Individual Variations in the Efficacy of Unobtrusive Respiratory Guidance for Driving Stress Regulation
<|reference_start|>Road to Serenity: Individual Variations in the Efficacy of Unobtrusive Respiratory Guidance for Driving Stress Regulation: Stress impacts driving-related cognitive functions like attention and decision-making, and may arise in automated vehicles due to non-driving tasks. Unobtrusive relaxation techniques are needed to regulate stress without distracting from driving. Tactile wearables have shown efficacy in stress regulation through respiratory guidance, but individual variations may affect their efficacy. This study assessed slow-breathing tactile guidance under different stress levels on 85 participants. Physiological, behavioral and subjective data were collected. The influence of individual variations (e.g., driving habits and behavior, personality) using logistic regression analysis was explored. Participants could follow the guidance and adjust breathing while driving, but subjective efficacy depended on individual variations linked to different efficiency in using the technique, in relation with its attentional cost. An influence of factors linked to the evaluation of context criticality was also found. The results suggest that considering individual and contextual variations is crucial in designing and using such techniques in demanding driving contexts. In this line some design recommendations and insights for further studies are provided.<|reference_end|>
@article{bequet2024road,
    title={Road to Serenity: Individual Variations in the Efficacy of Unobtrusive
  Respiratory Guidance for Driving Stress Regulation},
    author={A.J. Bequet, C. Jallais, J. Quick, D. Ndiaye, A.R. Hidalgo-Munoz},
    journal={A.J. Bequet, C. Jallais, J. Quick, D. Ndiaye, A.R. Hidalgo-Munoz,
  Road to serenity: Individual variations in the efficacy of unobtrusive
  respiratory guidance for driving stress regulation, Applied Ergonomics,
  Volume 120, 2024, 104334},
    year={2024},
    doi={10.1016/j.apergo.2024.104334},
    archivePrefix={arXiv},
    eprint={2406.09777},
    primaryClass={cs.HC}
}