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The Risk of Gambling Problems in the General Population: A Reconsideration.

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Estimating disordered gambling prevalence using standard surveys may overestimate the issue. Correcting for sample selection bias reveals a higher prevalence (7.7%) and lower comorbidity with other psychiatric disorders.

Keywords:
Bias correctionComorbiditiesDiagnostic stem questionsEconometricsGambling disorderPrevalence studiesSample selection bias

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Area of Science:

  • Psychiatry
  • Behavioral Economics
  • Epidemiology

Background:

  • Population prevalence of disordered gambling is typically estimated using general population surveys.
  • These surveys often employ "trigger" questions that may introduce sample selection bias.
  • This bias can affect the accuracy of prevalence and comorbidity estimates for psychiatric disorders.

Purpose of the Study:

  • To re-evaluate the population prevalence of disordered gambling by correcting for sample selection bias.
  • To investigate the impact of this bias on comorbidity estimates with other psychiatric disorders.
  • To propose methods for mitigating behavioral biases in future mental health surveys.

Main Methods:

  • Utilized advanced econometric techniques to model and correct for sample selection bias.
  • Analyzed data from general population surveys on gambling behavior and attitudes.
  • Compared corrected prevalence and comorbidity estimates with previously reported figures.

Main Results:

  • Corrected prevalence of problem or pathological gambling in the United States is estimated at 7.7%, significantly higher than the commonly cited 1.3%.
  • Comorbidities with other psychiatric disorders appear to be substantially lower than previously understood, especially when considering marginal associations.
  • The identified behavioral biases are potentially applicable to surveys of various psychiatric disorders.

Conclusions:

  • Standard survey methods for estimating disordered gambling prevalence are susceptible to significant sample selection bias.
  • Econometric correction for this bias yields substantially different estimates for prevalence and comorbidity.
  • Future mental health surveys require methodological adjustments to mitigate these behavioral biases and improve accuracy.