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Cryptocurrency Trading, Day Trading, and Gambling Behavior: Examining the Moderating Effects of Financially Focused Self-Concept and Gambling Motives.

Eric R LouderbackSeth P McCullockDebi A LaPlante
Published in: Journal of gambling studies (2024)
Cryptocurrency and day trading have grown in popularity over the past decade following the creation of the first cryptocurrency, Bitcoin, in 2009. These activities share important features with gambling, including risking money on an uncertain outcome, a chance of monetary rewards, and the potential to experience harm (e.g., financial or relationship problems). However, little is known about cryptocurrency and day trading engagement in the adult population, including associations with gambling behavior, harm, and psychological factors that might moderate these relationships. We analyzed cross-sectional data for n = 822 adults from an online panel in the U.S. to examine: (1) the extent to which cryptocurrency trading, day trading, and gambling are associated, (2) relationships between cryptocurrency trading, day trading, and higher risk gambling behavior, and (3) whether financially focused self-concept and four types of gambling motives moderate these relationships. We found moderate to strong positive intercorrelations between cryptocurrency and day trading, and gambling behavior, including engagement and risk. We identified significant moderating effects of financially focused self-concept, and coping motives for gambling, on the relationship between cryptocurrency trading and gambling frequency, and between day trading and gambling frequency. For the models predicting higher risk gambling status, the only significant moderators were financially focused self-concept for the day trading model, and the enhancement motive for the cryptocurrency and day trading models. Our results have important implications for understanding interrelationships between gambling-adjacent activities and more traditional gambling forms, as well as the moderating roles of key psychosocial concepts in these relationships.
Keyphrases
  • cross sectional
  • social support
  • healthcare
  • mental health
  • depressive symptoms
  • social media
  • high intensity
  • risk assessment
  • physical activity
  • climate change
  • deep learning