When Losing Money and Time Feels Good: The Paradoxical Role of Flow in Gambling
Bibliographic record
Abstract
Despite being well-known for its positive consequences, the psychological state of flow has raised some concerns. In this research, we advanced our understanding of the relationships that flow has in the context of online gambling. Across two studies, in which participants played blackjack and slots, we demonstrated that flow is associated with an increase in the amount of time spent gambling. Flow is also related to an increase in the amount of money spent. We demonstrated that the reason that flow increases the amount of playing time is that its inherently enjoyable nature makes it difficult to stop. We also tested the alternative hypothesis that this relationship occurs because in flow, people lose track of time. Although flow is related to losing track of time, that does not mediate the relationship with playing time. Lastly, we demonstrated that despite losing more money and spending more time while gambling, those who experienced flow had more enjoyable experiences overall, creating a counterintuitive and potentially dangerous situation for gamblers. A secondary goal of this research was to explore ways in which to protect consumers from this paradox. We used warning messages and on-screen interruptions to potentially thwart flow. However, both tactics were ineffective. We discuss the implications for future research and practice.RésuméBien qu’il soit connu pour ses conséquences positives, l’état de fonctionnement psychologique optimal (state of flow) suscite certaines inquiétudes. Dans cette recherche, nous approfondissons notre compréhension des relations propres à cet état qui s’établissent dans le contexte du jeu en ligne. Dans deux études dans lesquelles les participants ont joué au blackjack et à des machines à sous, nous avons démontré que l’état optimal est associé à une augmentation du temps passé à jouer. Cet état psychologique est également lié à une augmentation des dépenses. Nous démontrons la raison pour laquelle l’état optimal augmente le temps de jeu, notamment sa nature intrinsèquement agréable qui rend un arrêt difficile. Nous avons également testé l’autre hypothèse selon laquelle cette relation est due au fait que, dans cet état optimal, les gens perdent le contrôle du temps. Bien que cet état soit lié à la perte de la notion du temps, cela ne modifie pas la relation avec le temps de jeu. Enfin, nous démontrons que malgré la perte d’argent et la perte de temps au jeu, ceux qui vivent une expérience optimale au jeu ont eu des expériences plus agréables dans l’ensemble, créant une situation contre-intuitive et potentiellement nocive pour les joueurs. Un objectif secondaire de cette recherche est d’explorer les moyens de protéger les consommateurs de ce paradoxe. Nous avons utilisé des messages d’avertissement et des interruptions à l’écran pour tenter d’entraver l’état optimal, en vain. Ces deux tactiques se révèlent inefficaces. Nous abordons les répercussions pour la recherche et la pratique futures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".