Dataset Information

GamTest: Psychometric Evaluation and the Role of Emotions in an Online Self-Test for Gambling Behavior.

ABSTRACT: Recent increases in the number of online gambling sites have made gambling more available, which may contribute to an increase in gambling problems. At the same time, online gambling provides opportunities to introduce measures intended to prevent problem gambling. GamTest is an online test of gambling behavior that provides information that can be used to give players individualized feedback and recommendations for action. The aim of this study is to explore the dimensionality of GamTest and validate it against the Problem Gambling Severity Index (PGSI) and the gambler's own perceived problems. A recent psychometric approach, exploratory structural equation modeling (ESEM) is used. Well-defined constructs are identified in a two-step procedure fitting a traditional exploratory factor analysis model as well as a so-called bifactor model. Using data collected at four Nordic gambling sites in the autumn of 2009 (n = 10,402), the GamTest ESEM analyses indicate high correspondence with the players' own understanding of their problems and with the PGSI, a validated measure of problem gambling. We conclude that GamTest captures five dimensions of problematic gambling (i.e., overconsumption of money and time, and monetary, social and emotional negative consequences) with high reliability, and that the bifactor approach, composed of a general factor and specific residual factors, reproduces all these factors except one, the negative consequences emotional factor, which contributes to the dominant part of the general factor. The results underscore the importance of tailoring feedback and support to online gamblers with a particular focus on how to handle emotions in relation to their gambling behavior.

SUBMITTER: Jonsson J

PROVIDER: S-EPMC5445150 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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GamTest: Psychometric Evaluation and the Role of Emotions in an Online Self-Test for Gambling Behavior.

Jonsson Jakob J Munck Ingrid I Volberg Rachel R Carlbring Per P

Journal of gambling studies 20170601 2

Recent increases in the number of online gambling sites have made gambling more available, which may contribute to an increase in gambling problems. At the same time, online gambling provides opportunities to introduce measures intended to prevent problem gambling. GamTest is an online test of gambling behavior that provides information that can be used to give players individualized feedback and recommendations for action. The aim of this study is to explore the dimensionality of GamTest and va ...[more]

PMID: 28265831

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Project description:BackgroundMost people who experience a potentially traumatic event (PTE) recover on their own. A small group of individuals develops psychological complaints, but this is often not detected in time or guidance to care is suboptimal. To identify these individuals and encourage them to seek help, a web-based self-help test called Mobile Insight in Risk, Resilience, and Online Referral (MIRROR) was developed. MIRROR takes an innovative approach since it integrates both negative and positive outcomes of PTEs and time since the event and provides direct feedback to the user.ObjectiveThe goal of this study was to assess MIRROR's use, examine its psychometric properties (factor structure, internal consistency, and convergent and divergent validity), and evaluate how well it classifies respondents into different outcome categories compared with reference measures.MethodsMIRROR was embedded in the website of Victim Support Netherlands so visitors could use it. We compared MIRROR's outcomes to reference measures of PTSD symptoms (PTSD Checklist for DSM-5), depression, anxiety, stress (Depression Anxiety Stress Scale-21), psychological resilience (Resilience Evaluation Scale), and positive mental health (Mental Health Continuum Short Form).ResultsIn 6 months, 1112 respondents completed MIRROR, of whom 663 also completed the reference measures. Results showed good internal consistency (interitem correlations range .24 to .55, corrected item-total correlations range .30 to .54, and Cronbach alpha coefficient range .62 to .68), and convergent and divergent validity (Pearson correlations range -.259 to .665). Exploratory and confirmatory factor analyses (EFA+CFA) yielded a 2-factor model with good model fit (CFA model fit indices: χ219=107.8, P<.001, CFI=.965, TLI=.948, RMSEA=.065), conceptual meaning, and parsimony. MIRROR correctly classified respondents into different outcome categories compared with the reference measures.ConclusionsMIRROR is a valid and reliable self-help test to identify negative (PTSD complaints) and positive outcomes (psychosocial functioning and resilience) of PTEs. MIRROR is an easily accessible online tool that can help people who have experienced a PTE to timely identify psychological complaints and find appropriate support, a tool that might be highly needed in times like the coronavirus pandemic.

Project description:BACKGROUND:Individuals who gamble online may be at risk of gambling excessively, but internet gambling also provides a unique opportunity to monitor gambling behavior in real environments which may allow intervention for those who encounter difficulties. OBJECTIVE:The objective of this study was to model the early gambling trajectories of individuals who play online lottery. METHODS:Anonymized gambling-related records of the initial 6 months of 1152 clients of the French national lottery who created their internet gambling accounts between September 2015 and February 2016 were analyzed using a two-step approach that combined growth mixture modeling and latent class analysis. The analysis was based upon behavior indicators of gambling activity (money wagered and number of gambling days) and indicators of gambling problems (breadth of involvement and chasing). Profiles were described based upon the probabilities of following the trajectories that were identified for the four indicators, and upon several covariates (age, gender, deposits, type of play, net losses, voluntary self-exclusion, and Playscan classification-a responsible gambling tool that provides each player with a risk assessment: green for low risk, orange for medium risk and red for high risk). Net losses, voluntary self-exclusion, and Playscan classification were used as external verification of problem gambling. RESULTS:We identified 5 distinct profiles of online lottery gambling. Classes 1 (56.8%), 2 (14.8%) and 3 (13.9%) were characterized by low to medium gambling activity and low values for markers of problem gambling. They displayed low net losses, did not use the voluntary self-exclusion measure, and were classified predominantly with green Playscan tags (range 90%-98%). Class 4 (9.7%) was characterized by medium to high gambling activity, played a higher breadth of game types (range 1-6), and had zero to few chasing episodes. They had high net losses but were classified with green (66%) or orange (25%) Playscan tags and did not use the voluntary self-exclusion measure. Class 5 (4.8%) was characterized by medium to very high gambling activity, played a higher breadth of game types (range 1-17), and had a high number of chasing episodes (range 0-5). They experienced the highest net losses, the highest proportion of orange (32%) and red (39%) tags within the Playscan classification system and represented the only class in which voluntary self-exclusion was present. CONCLUSIONS:Classes 1, 2, 3 may be considered to represent recreational gambling. Class 4 had higher gambling activity and higher breadth of involvement and may be representative of players at risk for future gambling problems. Class 5 stood out in terms of much higher gambling activity and breadth of involvement, and the presence of chasing behavior. Individuals in classes 4 and 5 may benefit from early preventive measures.

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Project description:Background and objectivesThe Internet provides easy access to multiple types of gambling and has led to changes in betting habits. A severe rise in problematic gambling has been predicted among all sectors of the population, and studies are required to assess the emerging phenotypes related to the new structures of gambling activities. This study aimed to explore the existence of latent classes associated with gambling habits among treatment-seeking gamblers due to Online Sports Betting (OSB).MethodInitial sample included n = 4,516 patients consecutively admitted for treatment in a hospital unit specialized in behavioral addictions. Two-step clustering analysis was used within the subsample of n = 323 patients who reported problems related with OSB, within a set of indicators including sociodemographics, psychopathological distress, personality, and severity of the gambling activity.ResultsThe prevalence of OSB as a main type of gambling problem in the study was 7.2% (95% confidence interval: 6.4 to 7.9%). Two latent clusters were identified, with differences in sociodemographics and clinical status. Cluster 1 (n = 247, 76.5%) grouped patients that were more affected due to the OSB behaviors, and it was characterized by non-married patients, lower socioeconomic position index, higher comorbidity with other substance related addictions, younger age, and early onset of the gambling activity, as well as higher debts due to the OSB, higher psychopathological distress, and a more dysfunctional personality profile. Cluster 2 (n = 76, 23.5%) grouped patients that were less affected by OSB, mostly married (or living with a stable partner), with higher social position levels, older age and older onset of the gambling activity, as well as a more functional psychopathological and personality profile.ConclusionThe increasing understanding of latent classes underlying OSB phenotypes is essential in guiding the development of reliable screening tools to identify individuals highly vulnerable to addictive behaviors among Internet gamblers, as well as in planning prevention and treatment initiatives focused on the precise profiles of these patients.

Dataset Information

GamTest: Psychometric Evaluation and the Role of Emotions in an Online Self-Test for Gambling Behavior.

Publications

GamTest: Psychometric Evaluation and the Role of Emotions in an Online Self-Test for Gambling Behavior.

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