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Comparative Test Evaluation: Methods and Challenges.

Journal of gambling studies·2018
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Test Performance Variation Between Settings and Populations.

Blase Gambino1

  • 1American Academy of Health Care Providers in the Addictive Disorders, 10 Ellet Street, Boston, MA, 02122-2940, USA. blasegambino@comcast.net.

Journal of Gambling Studies
|November 10, 2017
PubMed
Summary

This study explains how test performance for detecting disordered gambling varies across different groups and settings. It introduces "spectrum effects" to understand these variations and improve test evaluation.

Keywords:
Confidence intervalsPopulationsSettingsTest performanceTest uncertainty

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Area of Science:

  • Psychology
  • Psychometrics
  • Addiction Research

Background:

  • The evaluation of new diagnostic tools for disordered gambling is crucial.
  • Previous research has highlighted variations in test performance.
  • Understanding these variations is key to accurate assessment.

Purpose of the Study:

  • To describe and explain variations in disordered gambling test performance across settings and populations.
  • To introduce and define the concept of 'spectrum effects' in test performance.
  • To illustrate expected variations with examples and discuss implications for test evaluation.

Main Methods:

  • Descriptive analysis of observed variations in test performance.
  • Theoretical explanation of variations using the concept of spectrum effects.
  • Illustrative examples of expected variations in different populations and settings.

Main Results:

  • Observed variations in test performance are common across diverse settings and populations.
  • Spectrum effects provide a framework for understanding these performance variations.
  • Examples demonstrate how population and setting characteristics influence test outcomes.

Conclusions:

  • Test performance for disordered gambling is influenced by 'spectrum effects'.
  • Acknowledging and understanding these effects is essential for accurate test evaluation.
  • Future evaluations must consider population and setting-specific factors.