The Problem Gambling Severity Index (PGSI) is considered the “gold standard” for measuring problem gambling. The PGSI provides a single score summed across nine items. The nine items of the PGSI comprise two subdomains: problematic behaviours and adverse consequences. The aim of the present study was to compare evidence of a one-factor structure to evidence of a two-factor structure representing the two subdomains. With a sample of 1,251 bettors, we conducted confirmatory factor analyses and Rasch analyses to assess evidence supporting the one-factor and the two-factor structures. In addition, stochastic search variable selection was conducted with the total PGSI score, PGSI behaviour score, and PGSI adverse consequences score as separate outcomes to examine whether information is lost when collapsing the two subdomains into a single factor. Overall, there was stronger support of a two-factor structure than a one-factor structure. However, the two-factors were highly correlated with one another and shared most predictors except for one. We recommend continued use of the one-factor structure of the PGSI unless one aims to better understand the relationship between problematic behaviours and adverse consequences.

Two experiments determined whether metamemory judgments invoking covert retrieval practice for a list of unrelated paired associate words led to the facilitation of learning a subsequent list. Three types of relation between successive lists were compared: negative transfer (A-B, A-D); a control for item-specific proactive interference (A-B, C-D); and repetition (A-B, A-B). Experiment 1 showed that the benefit of retrieval practice relative to restudying was equivalent for overt and covert retrieval in the negative transfer paradigm (A-B, A-D). Both types of retrieval minimized intrusions of first list responses in the cued recall of the second list. Experiment 2 showed that memory enhancement following covert retrieval was equivalent for new (C-D) and repeated (A-B) lists. The results are consistent with theories of the forward testing effect (FTE) that assume retrieval practice insulates subsequent learning from proactive interference and provides self-assessment feedback that may lead to more efficient encoding in future learning. Challenges in accounting for the impact of a substantial number of moderators of the FTE are reviewed.

In its original development, the Problem Gambling Severity Index (PGSI) compared frequency weighted and dichotomous scoring of items. Although dichotomous scoring yielded a higher correlation with clinical assessments, it also yielded higher estimates of problem gambling prevalence. The aim of the present study was to compare the two scoring methods as potential moderators in the identification of important psychological predictors of problem gambling. Sports (n = 581) and non-sports gamblers (n = 670) completed an online survey containing the PGSI and standardized measures of impulsivity, gambling motivation, and gambling cognitions. Psychometric analyses were run on the weighted and dichotomous scores of PGSI scale. The two types of scoring systems were regressed on cognitive, motivational, and personality factors. Both scoring systems had high internal consistency for weighted and dichotomous scoring, respectively. Important predictors were determined with stochastic search variable selection (SSVS) and dominance analyses. Weighted and dichotomous scoring converged on identifying four important predictors of problem gambling in both sports and non-sports gamblers: positive urgency; amotivation; luck/perseverance; and gambling identity. The results suggest that dichotomous and weighted scoring systems are similar in their psychometric properties and in the identification of important predictors of problem gambling. One practical advantage of dichotomous scoring is the absence of a reliance on the accuracy of judgments of the frequency of gambling behaviors and adverse consequences.

Differences in the psychological characteristics and gambling behaviors of sports bettors and non-sports bettors were examined with a view to identifying predictors of problem gambling severity. A survey was completed by 1,280 participants, 596 of whom had placed bets on a sporting event in the last year. We found that sports bettors are at greater risk of problem gambling due to differences in attitudes towards gambling, personality traits, thinking styles, erroneous cognitions, and gambling motivations. Moreover, our findings suggest that the difference between individuals who bet on sports and those who do not is more quantitative than qualitative. A stratified stochastic search variable selection analysis by type of bettor revealed similar important predictors of problem gambling for both sports bettors and non-sports bettors; however, the association between the predictors and problem gambling was stronger for sports bettors. Overall, the findings of this study suggest that preventative methods and interventions for problem gambling should be targeted as a function of whether individuals bet on sports.

This special session organized by the Centre for Advancing Responsible and Ethical Artificial Intelligence (CARE-AI) consists of two 90-minute parts, focusing on two groups at the frontline of AI Ethics: students and start-up founders. Part 1 is a student-led AI Ethics paper presentation and critique: two students from the Philosophy program will present original work, "Analyzing Distrust in Human Interactions with AI," and "Enactivism and Modelling Human Behaviour in AI," (20 min); each presentation will be followed by a prepared critique from a student in the Collaborative Specialization in AI (10 min) and a 15-minute general discussion with the audience. Part 2 is an AI Ethics start-up showcase: 5 Canadian start-up companies (whose products or services either present an AI Ethics dilemma or propose a solution) will present 5-minute pitches, which will each be followed by 5 minutes of expert commentary and 5 minutes of open discussion.

Background: Bipolar disorder onset peaks over early adulthood and confirmed family history is a robust risk factor. However, penetrance within families varies and most children of bipolar parents will not develop the illness. Individualized risk prediction would be helpful for identifying those young people most at risk and to inform targeted intervention. Using prospectively collected data from the Canadian Flourish High-risk Offspring cohort study available in routine practice, we explored the use of a neural network, known as the Partial Logistic Artificial Neural Network (PLANN) to predict the time to diagnosis of major mood disorders in 1, 3 and 5-year intervals. Results: Overall, for predictive performance, PLANN outperformed the more traditional discrete survival model for 3-year and 5-year predictions. PLANN was better able to discriminate or rank individuals based on their risk of developing a major mood disorder, better able to predict the probability of developing a major mood disorder and better able to identify individuals who would be diagnosed in future time intervals. The average AUC achieved by PLANN for 5-year prediction was 0.74, which indicates good discrimination. Conclusions: This evaluation of PLANN is a useful step in the investigation of using neural networks as tools in the prediction of mood disorders in at-risk individuals and the potential that neural networks have in this field. Future research is needed to replicate these findings in a separate high-risk offspring sample.

Explanatory models of substance and behavioral addictions typically emphasize the contributions of three predictor domains: distorted cognitions related to control; motivations related to rewards and stress-reduction; and, failure to regulate emotions. In the present study, 271 (161 females) patrons at a racetrack-slots facility completed a survey comprising standardized measures of gambling-related cognitions, motivations for gambling, trait impulsivity, and problem gambling severity. The purpose was to explore dominance analysis as a statistical procedure to identify the relative importance of the three domains as predictors of the experience of gambling harms. The first step of the analysis isolated the dominant facet within each of the three multi-dimensional domains. The final step computed relative dominance among those facets. The results indicated that the most dominant predictor was the cognition of an inability to stop gambling. Motivation to avoid life stressors was the second most dominant predictor followed by the tendency to act rashly in the presence of negative emotion (negative urgency). The relative dominance of the predictors of gambling harm may provide a framework for scaffolding interventions directed at mitigating gambling harms.

The purpose of the present study was to introduce stochastic search variable selection (SSVS) as a procedure to identify a subset of important predictors of gambling harm. The target set of predictors were dimensions of trait impulsivity, gambling cognitions, and gambling motivations. Five types of gambling harm (feeling one has a personal problem; social criticism; feeling guilt; health; and, financial) were measured by the Problem Gambling Severity Index. Casino patrons completed the measures. As a first step, we identified the significant predictors that would be included in modelling an aggregate harm score. The most important predictors, the cognition that one is not able to stop gambling, and the motivation to escape or avoid life stressors, were positively associated with overall harm. Two weaker, but statistically significant, predictors were negatively associated with harm: sensation-seeking and illusion of control. Although a perceived inability to stop gambling was the most important predictor of each individual harm, the pattern of predictors varied across harms. For example, sensation-seeking was an important predictor only for the belief that one has a gambling problem, and escape/avoidance motivation was strongly predictive of financial harm. The results suggest that primary interventions designed to mitigate harm should address the belief that the gambler is unable to stop gambling, and motivations related to escape/avoid life stressors. Other interventions would be tailored to the specific harms experience by the gambler.