IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i15p5266-d387782.html
   My bibliography  Save this article

P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis

Author

Listed:
  • Chao Fang

    (Department of Pharmacology, Fourth Military Medical University, Xi’an 710032, China
    Indicates equal contribution to authorship as the first author.)

  • Yamei Zhang

    (College of Architecture and Urban Planning, Qingdao University of Technology, Qingdao 266033, China
    School of Civil Engineering, Qingdao University of Technology, Qingdao 266033, China
    Indicates equal contribution to authorship as the first author.)

  • Mingyi Zhang

    (School of Civil Engineering, Qingdao University of Technology, Qingdao 266033, China)

  • Qun Fang

    (School of Physical Education, Qingdao University, Qingdao 266071, China)

Abstract

Detecting signs for an increased level of risk during driving are critical for the effective prevention of road traffic accidents. The current study searched for literature through major databases such as PubMed, EBSCO, IEEE, and ScienceDirect. A total of 14 articles that measured P300 components in relation to driving tasks were included for a systematic review and meta-analysis. The risk factors investigated in the reviewed articles were summarized in five categories, including reduced attention, distraction, alcohol, challenging situations on the road, and negative emotion. A meta-analysis was conducted at both behavioral and neural levels. Behavioral performance was measured by the reaction time and driving performance, while the neural response was measured by P300 amplitude and latency. A significant increase in reaction time was identified when drivers were exposed to the risk factors. In addition, the significant effects of a reduced P300 amplitude and prolonged P300 latency indicated a reduced capacity for cognitive information processing. There was a tendency of driving performance decrement in relation to the risk factors, however, the effect was non-significant due to considerable variations and heterogeneity across the included studies. The results led to the conclusion that the P300 amplitude and latency are reliable indicators and predictors of the increased risk in driving. Future applications of the P300-based brain–computer interface (BCI) system may make considerable contributions toward preventing road traffic accidents.

Suggested Citation

  • Chao Fang & Yamei Zhang & Mingyi Zhang & Qun Fang, 2020. "P300 Measures and Drive-Related Risks: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 17(15), pages 1-14, July.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:15:p:5266-:d:387782
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/15/5266/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/15/5266/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shuling Li & Tingru Zhang & Ben D. Sawyer & Wei Zhang & Peter A. Hancock, 2019. "Angry Drivers Take Risky Decisions: Evidence from Neurophysiological Assessment," IJERPH, MDPI, vol. 16(10), pages 1-14, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Milanko Damjanović & Spasoje Mićić & Boško Matović & Dragan Jovanović & Aleksandar Bulajić, 2022. "Differences in Driving Anger among Professional Drivers: A Cross-Cultural Study," IJERPH, MDPI, vol. 19(7), pages 1-18, March.

    More about this item

    Keywords

    road safety; drive-related risks; P300; driving performance;
    All these keywords.

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:15:p:5266-:d:387782. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.