Measurement of Prevalence of Youth Gambling in Australia: Report on Review of Literature 

• Appendix A
• Appendix B

Appendix A

Endorsement and Discrimination Measures of the performance, specifically the validity of the screen, its relationship to some theoretical model and the reliability of the screen are usually discussed under the following headings¹⁴:

Endorsement: refers to the count or frequency of respondents who respond to each question or category in each question.

Discrimination: refers to whether or not an item discriminates between those who score high and those who score low (i.e., you may hypothesise that a question would discriminate on the basis of gender or age).

Construct Validity: that an item in a screen measures what theoretically and conceptually it is supposed to measure. For example, what a psychologists measures by interview should also be closely measured by the screen (a question or a set of question). A further measure is by the use of correlates to measure how well the screen predicts (e.g., excessive gambling associated with smoking).

Content Validity: what does the screen purport to measure and its relationship with the relevant theoretical model. Is the screen measuring pathological gambling (DMV-IV), harm to others or harm to self, etcetera. Screens vary based on theoretical model and cluster of items.

Measures of reliability relate to the stability and internal consistency of the screen:

Stability: is demonstrated if the results of a measurement are identical or similar each time it is conducted (Streiner and Norman: 1991). Measure of agreement of a test and retest.

Internal Consistency: is a measure of the internal correlation of items which demonstrates the extent to which items in a scale measure different aspects of the same attribute. For example, taking each item in a screen and correlating it to the overall scare; if the item correlation to the total score is high this indicates a high degree of internal consistency.

Classification Validity: the usual statistical technique to determine classification of gambling status is to examine the distribution of scores and assign boundaries based on cut-off scores. The distribution of scores will show some evidence of multiple peaks; however, there are clear situations where no evidence for classification can be drawn from the distribution and sensitivity analysis may be used to construct the best judgement.

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Appendix B

14. Based on discussion by Poulin (2002), Rossen (2001), Ladouceur (2000), Oxford et al (2003) and McMillen (2003). The SA Centre for Economic Studies acknowledges that the authors listed here have conducted the most intensive examinations into the construction, validity and reliability of gambling screens.