Gambling, Gaming and Technology Use
Putting It Into Practice
The IGS should not be used in place of a visit, call, consultation or advice of a physician or other qualified health care provider. You should never disregard medical advice or delay in seeking it because of results suggested by the IGS. You acknowledge that the IGS does not make clinical, medical or other decisions and is not a substitute for competent, properly trained and knowledgeable staff who bring professional judgment and analysis to the information presented by the IGS. Most of the demographic information collected is optional not required.
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No personal information is collected. As part of the interview the participants were asked to verbally describe the situations in which they gambled problematically. In the current paper the data from these three studies has been combined in order to use confirmatory factor analysis to confirm the factorial validity of the CAMH-IGS. The reason for combining the data is that confirmatory factor analysis requires a large sample size.
The IGS total score is linked to overall level of situational risk; a person who responds to more situations in general has a more severe gambling problem.
Thus the overall IGS score should be correlated with measures of gambling problem severity. Various external measures were used to validate the differences between the subscales.
In this study, to validate the different subscales we included external variables that were conceptually related to some specific subscales convergent and not related to other specific subscales divergent. In addition measures of impulsivity, erroneous beliefs, and beliefs about skill were included to test the validity of UT, WC, and CS respectively.
The data for this paper was collected in three different but related studies see below. The total sample size was This sample size is sufficient for the type of analysis that is conducted in this paper given the sample size, the number of items and the commonalities between items see MacCallum et al. In all three studies, the participants were recruited using newspaper ads, advertisements at our treatment centre new clients only , and snowball techniques wherein each participant was asked to refer other problem gamblers to the study.
Although all three studies used the same methods, sample 1 emphasized recruitment through the treatment centre more and sample 3 emphasized newspaper ads more. The participants contacted the research team using a 1— number.
Sample one Turner and Toneatto , Unpublished raw data; Turner et al. People who called the 1— number were invited to CAMH for an interview and questionnaire. Participants were asked about their own gambling and the gambling habits of other people in their families mother, father, sister, brother. A package containing the questionnaires and a self-addressed envelope was mailed out to participants who had contacted us through the 1— number.
Some participants received up to 4 different questionnaire packages over a span of several months. Sample three Turner et al.
People who called the 1— number were invited to the CAMH for an interview, questionnaire, and blood test. The participants completed a large battery of questionnaires, some experimental procedures, and had a blood sample taken to measure genetic risk. By design, there was considerable overlap in the questionnaires used in these three studies, and their data was combined together; however, some variables were only present in one or two studies.
During recruitment it was ensured that none of the participants were included in more than one study. Each project was reviewed and approved by the CAMH ethics review board and the authors complied with American Psychological Association ethical standards in the treatment of human participants.
These three studies used a correlational design. Purposive sampling was utilised for sample selection. Based on past recruitment efforts, this strategy has been shown to be an efficient and inexpensive means of recruiting both non-problem social gamblers and probable pathological gamblers Turner et al. People called the advertised toll free number and left their phone numbers on voice mail. For samples 1 and 3, participants were invited into the office to complete the questionnaires.
The researcher sat in an adjoining room and was available for questions. The researcher was available by telephone to answer any questions. After the session ended or the questionnaire package was returned , all participants were provided with information about problem gambling and treatment services. The debriefing form stated clearly that the information was provided to all participants regardless of whether they had a problem in order to raise awareness about problem gambling and the availability of treatment services.
Numerous studies have shown that the SOGS-R is a valid and reliable instrument for assessing problem and pathological gambling e. These two scales were included in all three studies. In order to test hypothesis 4c UT related to impulsiveness samples 2 and 3 included an assessment of impulsiveness Barrat The Gambling Cognitions Questionnaire, Toneatto was included in samples 1 and 2 as a measure of erroneous beliefs and cognitive distortions.
The questions cover topics such as beliefs about luck, the belief that persistence e. Previous research has shown that this scale is a reliable and valid measure of erroneous beliefs Turner and Liu Two subscales are of particular relevance to the current study: The TCI maintains strong theoretical and empirical links to psychobiological models of behaviour Kose , but is designed for clinical use.
It consists of 7 major subscales, which have been shown to be reliable and valid Cloninger et al. Two TCI subscales were of interest in 1 harm avoidance which is related to anxiety and depression hypothesis 4a , and novelty seeking which is related to impulsiveness hypothesis 4c. A confirmatory factor analysis involves fitting a theoretical model to the data. All models were estimated using the generalized least squares estimation. The confirmatory factor analysis reported below used Spearman correlations.
Spearman correlations are designed for ordinal data and are stable to variations in distribution e. Another option would have been polychoric correlation matrix PM.
However, a PM matrix requires a very large sample size in order to compute an accurate asymptotic weight matrix Jaccard and Wan A PM analysis can produce highly inflated estimates with skewed variables Turner , unless the sample is very large.
No major contradictions of the theoretical model were found. After determining that the model was a rough fit to the data, the program was set to conduct an automatic respecification search in which, after each analysis, the parameter with the largest modification index score is set free and the model is run again. An examination of the modification index and expected changes indicated only small and moderate correlated residuals e.
In summary, there were few changes to the model suggested by this analysis. The ratio of chi-square to degrees of freedom was 1. This is also supported by the non-normed fit index score which was.
The non-normed fit index like other fit indices ranges from 0 to 1 with 1 indicating a very close fit. It has been shown to be less negatively affected by larger sample sizes than other fit indices Marsh et al.
In addition the root mean error of approximation was 0. The goodness of fit score,. Overall these fit indices are within the range of good fitting models Byrne What is important here is that there were no changes that undermined the 10 factor model of the IGS.
The main items on each factor form neat clusters of correlations in a diagonal line down the page. A small number of other loadings are scattered over the matrix indicating the cross loadings. This assessment was further strengthened by an examination of the factor structure of each of the subscales.
The items for each of the 10 subscales were entered into 10 separate factor analyses. In each case only one eigenvalue was greater than 1 and the first eigenvalue accounted for half or more of the covariance between the items suggesting that all of the subscales were unifactorial.
Taken together these results indicate that for each of the 10 subscales the items appear to form stable reliable factors with good internal consistency. Although not intended as a diagnostic measure of pathological gambling, it is clear that a person who gambles problematically should score higher on the CAMH-IGS than someone who does not gamble problematically.
All of the IGS subscales and many of these external variables are related to the severity of problem gambling. In some cases both the correlation r and partial correlation r p are given.
SD self directedness; CO cooperativeness: Hypothesis 4d was that WC would be related to measures of erroneous beliefs. These results are consistent with hypothesis 4d. In addition, the lowest correlations with GCQ positive attitude were for NE, CO and WD which are all negative affect situations thus providing some divergent validation for those scales. However, contrary to hypothesis 4c, the partial correlation of novelty seeking and UT was not significant.
Males scored higher than females. Male and female probable pathological gamblers did not differ on CS. Differences between males vs. Asterisks indicate subscales where male—female differences reached univariate significance. Note that sex was missing in two data files so the sample size was , rather than As a validity check, the subscales scores were compared across the three samples. Consistent with hypothesis 6, the scales produced similar results for the three samples. Not surprisingly, non-problem gamblers scored substantially lower than probable pathological gamblers on all subscales.
Very few non-problem gamblers endorsed any of the items on the WD or CO subscale. It can be used in treatment planning regardless of the theoretical background of the treatment agency.
No major contradictions to the factor structure were found. However, 3 items were found to be non-significant in the confirmatory factor analysis. For each subscale, the alpha was well above the.
The factor analysis of each subscale indicates that a single factor accounts for half or more than half of the co-variance between items for each subscale.
However, it is important to note that gambling heavily in any of these situations may be an indicator of gambling problems. Convergent and divergent validity of the subscales was established by showing that after controlling for SOGS-R and DSM-IV-TR several subscales were more strongly correlated to external variables that they were conceptually related to than to other external variables that they were not conceptually related to.
More information about the article is available on the website of the journal Experimental and Clinical Psychopharmacology. Do you have thoughts or questions about prevention and treatment of gambling disorders? Cognitive-behavioral therapy for pathological gamblers. Journal of Consulting and Clinical Psychology , 74 3 , The Inventory of Gambling Situations in problem and pathological gamblers seeking alcohol and drug abuse treatment.
Experimental and Clinical Psychopharmacology , 18 6 , We are dealing with multi- addictive disorder behaviors. Speaking as a compulsive gambler, there are as many reasons to relapse as there are stars in the sky, if I had to speak for only myself, it would add up to three things: Even after 5 years of sobriety, I keep myself in check, by limiting the amount of money I have available to me, banned all my debit and credit cards from the casino cash machines, I keep myself accountable to my friends and family, by always letting them know where I am, and when I can be expected to return.