Winning and losing in online gambling: Effects on within-session chasing

Within-session chasing of losses and wins in an online eCasino

Chasing refers to the escalation of betting behaviour. It is conventionally seen when losing but can also be seen after wins. Diagnostic and screening items for gambling problems describe chasing as returning 'another day' to gamble. However, gamblers may also chase within sessions, and this is particularly relevant in online gambling. This study focused on two expressions of within-session chasing: (1) increasing the bet amount, or (2) a reduced probability of quitting the session, as a function of prior losses or wins. These expressions were examined across five online gambling products: slot machines, probability games, blackjack, video poker, and roulette. Our results showed that gamblers bet more and played longer sessions after immediate losses, but they bet less and played shorter sessions when losing cumulatively. The reversed pattern in the cumulative model may be due to financial constraints. For wins, gamblers bet more after both immediate and cumulative wins, but they also played shorter sessions. Chasing patterns were qualitatively similar by game type-with limited evidence for our hypothesis that chasing would be greatest for slot machines as an established high-risk category. Overall, chasing is multi-faceted, varying across the behavioural expressions, by the immediate or cumulative timeframe of prior outcomes, and by game type.

Getting even: chasing behavior, decision-making, and craving in habitual gamblers

BACKGROUND

Dysfunctional decision-making and intense craving represent pivotal aspects across all addictive behaviors, notably evident in gambling addiction where these factors significantly shape chasing behavior-continuing gambling to recoup losses-indicative of problematic gambling. This study explores the correlation between chasing behavior, craving, affective decision-making, decision-making styles, and gambling severity among habitual Italian gamblers.

METHODS

One hundred and sixty-six participants from diverse gambling venues completed assessments including the South Oaks Gambling Screen (SOGS), the Iowa Gambling Task (IGT), the General Decision-Making Style (GDMS), the Gambling Craving Scale (GACS), and a computerized task to measure chasing behavior. Participants were randomly assigned to Control and Loss chasing conditions.

RESULTS

Regression analyses revealed craving as a predictor of chasing behavior. Interestingly, individuals with a dependent decision-making style exhibited lower tendencies to chase. While IGT performance correlates with chasing frequency, it is not associated with the decision to continue or cease gambling. Intriguingly, gambling severity (SOGS total score) did not feature in the final models of both regression analyses.

DISCUSSION

These findings emphasize the significant role of craving in driving chasing behavior. Additionally, this study introduces, for the first time, the idea that a dependent decision-making style could potentially serve as a safeguard against chasing proneness.

CONCLUSIONS

The study suggests a fundamental dichotomy between chasers and nonchasers among gamblers, irrespective of gambling severity. This distinction could be instrumental in tailoring more effective intervention strategies for gambling disorder treatment.

Between-session chasing of losses and wins in an online eCasino

Background and aims

This study characterized chasing behaviour as the time to return to an online gambling website after a losing or a winning visit.

Methods

We analyzed a naturalistic dataset from an eCasino (PlayNow.com, the provincial platform for British Columbia, Canada), comprising 1,909,681 sessions from 15,544 individuals. Analyses distinguished sessions on slot machines, blackjack, roulette, video poker, probability games, or mixed-category sessions.

Results

Overall, gamblers on most games returned more slowly as a function of the prior loss, and more quickly as a function of the prior win. Loss chasing intensities in blackjack, probability, video poker, and mixed sessions did not differ significantly from slot machines, but roulette was associated with shorter intervals to return (b = -0.13, p < 0.001). Similarly, win chasing did not vary across slot machines, blackjack, probability games, and video poker, but roulette (b = -0.08, p < 0.001) and mixed (b = -0.02, p = 0.009) sessions were associated with shorter intervals.

Discussion and conclusions

The average behavioural patterns provide limited evidence for loss chasing but clearly indicate win chasing. Although slot machines are commonly considered a high-risk product, roulette in our analyses was associated with the greatest chasing intensities.

Behavioural Tracking and Profiling Studies Involving Objective Data Derived from Online Operators: A Review of the Evidence

Studies involving the analysis of objective data from online operators attempt to address common concerns about biases in self-report research. This paper surveys the progress in this area of research over the last 15 years. The findings highlight many areas of achievement, including: the development of a set of behavioural markers that reliably differentiate variations in gambler risk. Online gamblers can be grouped into clusters based on the intensity and frequency of gambling; behavioural variability; or, signs of over-commitment (e.g., deposit frequency or expenditure patterns). Behavioural indicators have also been successfully used to predict proxies of harm such as self-exclusion or account closures. However, relatively few studies have combined objective data with self-report data to achieve independent validation of the risk-status of gamblers. Evidence also supports the potential value of short-term responsible gambling interventions involving the use of voluntary and mandatory limits, messages and behavioural feedback. Less work has, on the other hand, addressed the comparative risk of different online gambling products. The findings suggest the need for further validation of findings against independent measures of gambling risk; consistent definitions of indicators; a greater focus on the differentiation of product risk; and, on the long-term impact of RG interventions.

Am I Winning or Losing? Probing the Appraisal of Partial Wins via Response Vigor

Attempts to obtain rewards are not always successful. Despite investing much time, effort, or money, sometimes individuals may not obtain any reward. Other times they may obtain some reward, but the obtained reward may be smaller than their initial investment, such as partial wins in gambling. It remains unclear how such ambiguous outcomes are appraised. To address this question, we systematically varied the payoffs for different outcomes in a computerized scratch card task across three experiments. To test outcome appraisal, we used response vigor as a novel proxy. In the scratch card task, participants turned three cards one by one. Depending on the turned cards, they either received an amount that was higher than the wager (win), an amount lower than the wager (partial win), or nothing (loss). Overall, participants responded to partial wins more slowly than losses, but more quickly than wins. Partial wins were therefore appraised to be better than losses, but worse than wins. Importantly, further analyses showed that outcome appraisal was not based on the net win or loss amount. Instead, participants primarily used the configuration of turned cards as a cue for the relative rank of an outcome within a specific game. Outcome appraisals thus utilize simple heuristic rules, rely on salient information (such as outcome-related cues in gambling), and are specific to a local context. Together, these factors may contribute to the misperception of partial wins as real wins in gambling. Future work may examine how outcome appraisal may be modulated by the salience of certain information, and investigate the appraisal process in contexts beyond gambling.

Gambling and virtual reality: unraveling the illusion of near-misses effect

Introduction

Studying gambling behavior is a crucial element in reducing the impact of problem gambling. Nevertheless, most current research is carried out in controlled laboratory settings rather than real-life situations, which raises concerns about how applicable the findings are in the broader context. Virtual reality (VR) has proven to be a valuable tool and has been utilized in various experimental scenarios. A limited number of studies have employed VR to investigate gambling behaviors, and few have explored them in an older adolescent context.

Methods

This study examined the behavioral and physiological effects of gambling behavior, including problem gambling, gaming addiction, and risk-taking decision-making in a sample of 36 high-school students aged between 18 to 20 years using an ad-hoc constructed VR scenario designed to simulate a slot-machine platform.

Results

The behavioral results highlighted that participants reporting more problem gambling were sensitive to near-misses: i.e., they bet more after near-misses than after losses. This result may reflect the false belief that gamblers, after near-misses, are closer to winning. Physiological data showed that participants exhibited heart rate deceleration during the anticipation of the outcome, which has been suggested to represent a marker of feedback anticipation processing and hyposensitivity to losses.

Discussion

Overall, this study provides evidence for a new VR tool to assess gambling behaviors and new insights into gambling-related behavioral and physiological factors. Implications for the treatment of problem gambling are discussed.

Behavioural expressions of loss-chasing in gambling: A systematic scoping review

BANERJEE Nilosmita., CHEN Zhang., CLARK Luke., NOËL Xavier. Behavioural expressions of loss-chasing in gambling: A systematic scoping review NEUROSCI BIOBEHAV REV 152(1) XXX-XXX, 2023. - Loss-chasing, the tendency to continue and/or intensify gambling following losses, is a key clinical symptom in gambling disorder and a central feature endorsed by at-risk problem gamblers. Despite its centrality, loss-chasing has been often operationalised across distinct behavioural expressions. The current systematic scoping review aimed to map the heterogeneous operationalisations of loss-chasing in the literature. The reviewed studies defined loss-chasing either between-sessions (n = 39) or within-sessions (n = 38), as a long-recognised distinction. For both categories, further behavioural expressions could be distinguished. Between-session loss-chasing was captured by endorsing an item 'returning another day/time to recoup losses', or behaviourally as the interval between successive sessions, or as increasing stakes in the next session. Within-session loss-chasing was defined as continuing and/or intensifying gambling either by increased risk-taking, stake size, or speed of play. Additionally, much heterogeneity was observed in the gambling contexts examined, the exact definition of loss, and the potential delineation of win-chasing. Open questions and future directions are discussed. Overall, this paper serves as a first step towards more conceptual clarity of loss-chasing.

Increased volatility in video poker results in more winning players but shorter winning streaks - Evidence from simulations

Objective and Method

Electronic gambling machines are a prominent cause of significant gambling harms globally. We use simulations of a simplified video poker game to show how changes in game volatility, defined primarily by the size of the main prize, affect patterns of wins and losses as well as winning streaks.

Results

We found that in low- and medium volatility games the proportion of winning players quickly drops to zero after about 30 h of play, while in the high volatility game 5% of players are still winning after playing for 100 h. However, the proportion of winning streaks was significantly higher in the low- and medium volatility games compared with high volatility: the simulated players were on a winning streak about 26.3, 25.6 and 18% of the time in the low-, medium- and high volatility games, respectively.

Conclusions

Fast-paced video poker with varying volatility levels but identical return-to-player rates and win frequencies can yield highly different result patterns across individuals. These patterns may be counter-intuitive for players and difficult to realize without simulations and visualizations. We argue that the findings have relevance for responsible gambling communication and for building a better understanding of how cognitive biases influence gambling behaviour.

Modeling urgency in the lab: Exploring the associations between self-reported urgency and behavioral responses to negative outcomes in laboratory gambling

Impulsivity is a multifaceted construct that relates to different behaviors in everyday life and has been associated with many psychopathological disorders and behavioral problems, such as problematic gambling behavior. One questionnaire to measure these several facets on a trait level is the UPPS-P Impulsive Behavior Scale. Specifically, the UPPS-P investigates five distinct facets: (a) negative urgency, (b) lack of premeditation, (c) lack of perseverance, (d) sensation seeking, and (e) positive urgency. Negative urgency at a trait level in particular seems to be associated with the development of psychopathological disorders. To date, there are no established state measures of negative urgency. However, it was recently proposed that speeding after losses might be a suitable measure. Thus, in this study, we explored the possible relationship between a state measure of negative urgency modeled through a behavioral gambling task and a trait measure of negative urgency through the UPPS-P questionnaire. We used correlational and network analyses in an aggregated database of eight samples (total N = 1216) to explore the potential relationships between post-loss speeding on the behavioral gambling task and UPPS-P scores (by combining trait vs. item-based analyses). We found that the degree of speeding after losses (post-loss speeding) did not correlate with the trait measure of impulsivity in general and negative urgency specifically, either at the latent trait level or on an item-based level. This null finding indicates that our state measure of post-loss speeding and negative urgency on a trait level does not seem to capture the same underlying constructs. Implications for personality research are discussed.