IDEAS home Printed from https://ideas.repec.org/a/cup/inorps/v9y2016i03p604-611_00.html
   My bibliography  Save this article

Theoretical Applications of the MODE Model to Law Enforcement Training and Interventions

Author

Listed:
  • Zabel, Keith L.
  • Zabel, Kevin L.
  • Olson, Michael A.
  • Carlson, Jessica H.

Abstract

As discussed in the focal article, numerous research studies have supported the existence of automatic or implicit racial bias (Ruggs et al., 2016). In this commentary, we argue that examining implicit bias through the perspective of the motivation and opportunity as determinants (MODE) model (see Fazio & Olson, 2014, for a review) offers a framework for industrial–organizational (I-O) psychologists to design and implement strategies that reduce the number of violent interactions between police and communities. The MODE model has been applied to areas such as interpersonal relationships (McNulty, Olson, Meltzer, & Shaffer, 2013), effective treatment of mental disorders (Vasey, Harbaugh, Buffington, Jones, & Fazio, 2012), and crafting of media messages (Ewoldsen, Rhodes, & Fazio, 2015), as well as racial prejudice (Olson & Fazio, 2004). Below, we elaborate on how the I-O-related strategies and interventions described in the focal article can be captured by the components of the MODE model and highlight which interventions may be most efficacious in reducing discriminatory police officer behavior.

Suggested Citation

  • Zabel, Keith L. & Zabel, Kevin L. & Olson, Michael A. & Carlson, Jessica H., 2016. "Theoretical Applications of the MODE Model to Law Enforcement Training and Interventions," Industrial and Organizational Psychology, Cambridge University Press, vol. 9(3), pages 604-611, September.
    • Handle: RePEc:cup:inorps:v:9:y:2016:i:03:p:604-611_00
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1754942616000614/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    More about this item

    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:cup:inorps:v:9:y:2016:i:03:p:604-611_00. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/iop .

    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.