Related Experiment Video
Updated: Aug 8, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Published on: September 19, 2012
Weighing the Harm: Direct Elicitation of Gambling Harm Severity Through Expert Evaluation of Narrative Accounts
Matthew Browne1, Vijay Rawat1, Catherine Tulloch2
1Experimental Gambling Research Laboratory, School of Health, Medical and Applied Sciences, CQUniversity, Bundaberg, Australia.
Abstract:
This study examined whether direct expert elicitation of gambling harm severity, applied to blinded first-hand narrative accounts, produces ordered and consistent estimates with respect to quantitative self-reports. As such, this represented independent convergent validation evidence of the Gambling Harms Scales (GHS) instruments for people who gamble and affected others (AOs). Six experts with significant research or clinical expertise in the gambling field evaluated 60 transcripts from people who gamble and AOs experiencing varying levels of gambling-related harm (no-harm, low-harm, moderate-harm, and high-harm). Each transcript was evaluated using four protocols (visual analogue scale, rank ordering, time trade-off, and standard gamble). Narratives from participants with higher levels of harm (as assessed by the GHS) were associated with significantly higher expert-elicited health disutility. Disutility increased monotonically with GHS harm bands, and this pattern was consistent across all four elicitation protocols and all six expert raters. Pooled disutility estimates were 0.084 for low-harm, 0.187 for moderate-harm, and 0.221 for high-harm. Harm severity elicited by interviews and expert assessment was consistent with harm severity as assessed by the brief GHS measures. Expert evaluation of blinded narrative accounts provides independent external evidence supporting the GHS suite of instruments as measures of gambling-related harm.
Related Concept Videos
Self-Presentation: Self-Monitoring and Self-Handicapping
Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
The Availability Heuristic
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Diagnostic and Statistical Manual of Mental Disorders (DSM)

