Using behavior-analytic implicit tests to assess sexual interests among normal and sex-offender populations.

Bryan Roche, Anthony O'Reilly, Amanda Gavin, Maria R Ruiz, Gabriela Arancibia
Author Information
  1. Bryan Roche: Department of Psychology, National University of Ireland, Maynooth, Ireland.
  2. Anthony O'Reilly: Department of Psychology, National University of Ireland, Maynooth, Ireland.
  3. Amanda Gavin: School of Social Science and Law, Teesside University, Middlesbrough, UK.
  4. Maria R Ruiz: Department of Psychology, Rollins College Florida, FL, USA.
  5. Gabriela Arancibia: Department of Psychology, National University of Ireland, Maynooth, Ireland.

Abstract

BACKGROUND: The development of implicit tests for measuring biases and behavioral predispositions is a recent development within psychology. While such tests are usually researched within a social-cognitive paradigm, behavioral researchers have also begun to view these tests as potential tests of conditioning histories, including in the sexual domain.
OBJECTIVE: The objective of this paper is to illustrate the utility of a behavioral approach to implicit testing and means by which implicit tests can be built to the standards of behavioral psychologists.
DESIGN: Research findings illustrating the short history of implicit testing within the experimental analysis of behavior are reviewed. Relevant parallel and overlapping research findings from the field of social cognition and on the Implicit Association Test are also outlined.
RESULTS: New preliminary data obtained with both normal and sex offender populations are described in order to illustrate how behavior-analytically conceived implicit tests may have potential as investigative tools for assessing histories of sexual arousal conditioning and derived stimulus associations.
CONCLUSION: It is concluded that popular implicit tests are likely sensitive to conditioned and derived stimulus associations in the history of the test-taker rather than 'unconscious cognitions', per se.

Keywords

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Word Cloud

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