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Neurobehavioural evaluation of rehabilitation programs for dangerous drivers

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F18%3A00100858" target="_blank" >RIV/00216224:14740/18:00100858 - isvavai.cz</a>

  • Alternative codes found

    RIV/44994575:_____/17:N0000072

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-60441-1_27" target="_blank" >http://dx.doi.org/10.1007/978-3-319-60441-1_27</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-60441-1_27" target="_blank" >10.1007/978-3-319-60441-1_27</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Neurobehavioural evaluation of rehabilitation programs for dangerous drivers

  • Original language description

    Study aim to advance understanding of empathy in different driver samples, and to identify ways of modifying such social behaviour in dangerous drivers. This is achieved by evaluating empathy – related driver – rehabilitation programs with a novel neurobehavioral technique. Statistics show that almost 85% of road – traffic accidents in the Czech Republic are caused by the drivers themselves, and approximately 63% of these accidents are due to dangerous driving behaviour (e. g. Speeding, aggressive driving). Developing an effective rehabilitation requires an objective method of evaluation. Our rehabilitation program for dangerous drivers consists of empathy induction. Many studies have revealed associations between reduced empathic awareness and various forms of antisocial behavior. Further research also shows that empathic skills can be enhanced during group therapy. Empathy and anti – social behaviour are associated with specific patterns of brain function and structure. Present study focuses on way, how to evaluate the drivers ‘rehabilitation program. We used for this evaluation MRI data combining functional (e.g. partial least squares) and effective connectivity analyses (e.g. dynamic causal modelling) with measures of structural covariance. Combining these multidimensional network level analyses of neuroimaging data with measures of trait empathy and behavioral performance on socio – emotional tasks allow us better comprehensive into brain relationships. © Springer International Publishing AG 2018.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    30103 - Neurosciences (including psychophysiology)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Advances in Intelligent Systems and Computing

  • ISBN

    9783319604404

  • ISSN

    2194-5357

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    275-281

  • Publisher name

    Springer Verlag

  • Place of publication

    Los Angeles

  • Event location

    Los Angeles

  • Event date

    Jan 1, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000448241200027