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Profiling Online Poker Players: Are Executive Functions Correlated with Poker Ability and Problem Gambling?
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0003-0403-338X
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2018 (English)In: Journal of Gambling Studies, ISSN 1050-5350, E-ISSN 1573-3602Article in journal (Refereed) Epub ahead of print
Abstract [en]

Poker playing and responsible gambling both entail the use of the executive functions (EF), which are higher-level cognitive abilities. This study investigated if online poker players of different ability showed different performances in their EF and if so, which functions were the most discriminating for their playing ability. Furthermore, it assessed if the EF performance was correlated to the quality of gambling, according to self-reported questionnaires (PGSI, SOGS, GRCS). Three poker experts evaluated anonymized poker hand history files and, then, a trained professional administered an extensive neuropsychological test battery. Data analysis determined which variables of the tests correlated with poker ability and gambling quality scores. The highest correlations between EF test results and poker ability and between EF test results and gambling quality assessment showed that mostly different clusters of executive functions characterize the profile of the strong(er) poker player and those ones of the problem gamblers (PGSI and SOGS) and the one of the cognitions related to gambling (GRCS). Taking into consideration only the variables overlapping between PGSI and SOGS, we found some key predictive factors for a more risky and harmful online poker playing: a lower performance in the emotional intelligence competences (Emotional Quotient inventory Short) and, in particular, those grouped in the Intrapersonal scale (emotional self-awareness, assertiveness, self-regard, independence and self-actualization).

Place, publisher, year, edition, pages
2018.
Keyword [en]
Executive functions, GRCS, Online poker, PGSI, Problem gambling, SOGS
National Category
Other Computer and Information Science
Research subject
Complex Systems – Microdata Analysis
Identifiers
URN: urn:nbn:se:du-26938DOI: 10.1007/s10899-017-9741-zPubMedID: 29330827OAI: oai:DiVA.org:du-26938DiVA: diva2:1174299
Available from: 2018-01-15 Created: 2018-01-15 Last updated: 2018-01-15Bibliographically approved

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Westin, Jerker

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf