Related Experiment Video
Updated: May 5, 2026

Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios
Published on: August 4, 2023
Are poker players all the same? Latent class analysis
Magali Dufour1, Natacha Brunelle, Élise Roy
1Faculty of Medicine (Addiction Program), Université de Sherbrooke (Campus Longueuil), 150, Place Charles-Le Moyne (Bureau 200), Longueuil, QC, J4K 0A8, Canada, Magali.Dufour@usherbrooke.ca.
Abstract:
Poker is the gambling game that is currently gaining the most in popularity. However, there is little information on poker players' characteristics and risk factors. Furthermore, the first studies described poker players, often recruited in universities, as an homogeneous group who played in only one of the modes (land based or on the Internet). This study aims to identify, through latent class analyses, poker player subgroups. A convenience sample of 258 adult poker players was recruited across Quebec during special events or through advertising in various media. Participants filled out a series of questionnaires (Canadian Problem Gambling Index, Beck Depression, Beck Anxiety, erroneous belief and alcohol/drug consumption). The latent class analysis suggests that there are three classes of poker players. Class I (recreational poker players) includes those who have the lowest probability of engaging intensively in different game modes. Participants in class II (Internet poker players) all play poker on the Internet. This class includes the highest proportion of players who consider themselves experts or professionals. They make a living in part or in whole from poker. Class III (multiform players) includes participants with the broadest variety of poker patterns. This group is complex: these players are positioned halfway between professional and recreational players. Results indicate that poker players are not an homogeneous group identified simply on the basis of the form of poker played. The specific characteristics associated with each subgroup points to vulnerabilities that could potentially be targeted for preventive interventions.
Related Concept Videos
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...
Theory of Attribution II: Kelley's Covariation Theory
Stereotypes, Prejudice, and Discrimination
The Representativeness Heuristic
Stratified Sampling Method
To choose a stratified sample, divide the population into groups called strata and then take a...
Surveys

