In Section 2 we commence a review of the different instruments for measuring problem gambling prevalence and the adaptations of various screens to measuring youth problem gambling (ToR: 1). Section 3 follows and extends on this discussion to review selected prevalence studies on youth problem gambling (ToR: 2), from a range of countries employing different screens and/or research methods. In both sections we have selected a major representative study using the screen under discussion and provided a boxed summary to highlight characteristics of the study and the screen.
2.1 Testing for Problem Gambling
The most widely used and quoted tests for problem gambling are the South Oaks Gambling Screen developed by Lesieur and Blume (1987) which emphasises the financial implications arising from excessive gambling and DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, 4th edition) which has a ‘greater emphasis on psychological aspects of problems such as preoccupation, development of tolerance, irritability, and gambling as an escape.’ (Productivity. Commission p. 6.17).
While the two screens referred to above are the most widely used, there are many other screens in use for measuring the prevalence of problem gambling. Shaffer et al (1997) in the meta-analysis of problem gambling prevalence studies, states that:
‘We can be confident that the various instruments used in the disordered gambling field measure essentially the same underlying construct. Further, since there is no ‘gold standard’ for the identification of disordered gambling, we cannot determine the absolute accuracy with which any of these instruments identifies the underlying construct of pathological gambling’ (p 52).
However, it is not at all certain from the literature ‘that we can be confident’.
While SOGS was designed on the basis of DSM criteria and uses similar terms to clarify status of the gambler (i.e., pathological, compulsive) Orford (2003) maintains that, disagreements about the terms and definitions used ‘extends to the very conceptualisation of the gambling problem or difficulty which some people experience’ (p. 53). Under the original DSM, pathological gambling was an ‘impulse control’ disorder later to be replaced in the revised version, by items measuring preoccupation or dependence. That is to say, the underlying conceptualisation of the gambling problem changed and is reflected in the revised version of items.
SOGS on the other hand, as noted above, emphasised financial and guilt aspects. A score of 5+ indicated ‘probable pathological gambling’.
Due to the growing concern with adolescent gambling behaviour three screens - SOGSRA, DSM-IV-J and MAGS - have been specifically adapted or developed for adolescent gambling studies. Derevensky (2000) concludes:
‘Each instrument is reported to have its advantages and disadvantages with considerable overlap between measures. Similar to adult instruments the notion of deception (lying), stealing money to support gambling, preoccupations, and chasing losses are common among instruments used for adolescents’, p. 231.
In choosing a gambling screen the strengths and weaknesses of each much be weighed against each other. The conclusion is that ultimately there is no ‘precise test’ of problem gambling principally because problem gambling is a continuum and where you define the cut-off or threshold will be influenced by what the researcher is seeking to measure. Shaffer (1997) compared instruments and the rates derived from different instruments in studies where two or more screens were used. The ratio of estimates within a single study ‘ranged from 1.02 (quite similar) to 2.83 (quite different) … [suggesting] that the SOGS produces significantly higher estimates of pathological gambling than versions of the DSM criteria’, (p. 57).
Thus, the idea of the gambling continuum (rather than the clinical diagnostic pathology approach) has given rise to a multiplicity of categories such as non-gamblers, nonproblem gambling, ‘those at risk’, ‘low risk gamblers’, non-regular and regular gamblers, moderate and severe problem gamblers, pathological gamblers, Level 0, 1, 2 and 3 gamblers, etcetera. This arises from the fact that researchers are seeking to measure different prevalence rates. Where the threshold lies between these categories and across the various studies is unclear. What appears to have evolved over time, in the development of new instruments to measure prevalence is that continuum scales have been grafted onto the medical model. Degrees of problem gambling (the continuum approach) are now being estimated using derivations of a medical model that was originally designed to measure pathological gambling.
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2.2 A Biopsychosocial Theory of Gambling: A Comprehensive Model3
In recent years, there seems to have been a move towards a multifaceted explanation of problem gambling known as the biopsychosocial model (e.g., Griffiths 1999, Blaszczynski 2000, Griffiths & Delfabbro 2001, Sharpe 2002).
Griffiths (1999) stated, ‘Gambling behaviour is a biopsychosocial process and must therefore be explained in biopsychosocial terms using the best theoretical strands of contemporary psychology, biology and sociology …. It is probable that sociological, psychological, and biological processes are involved in an interactive and complex fashion in its aetiology’, (p. 444). Griffiths quite rightly notes that no single, simple explanation will ever be sufficient on its own to explain all cases of gambling.
Sharpe (2002) states that ‘Evidence now exists that biological, psychological, and social factors are all relevant to the development of problematic levels of gambling’, (p. 1). She argues that behavioural, arousal or cognitive theories on their own cannot fully explain the acquisition of gambling behaviour, the development of problematic levels of gambling, and the maintenance of these behaviours to the point where people jeopardise biopsychosocial model of pathological gambling.
Blaszczynski (2000), while examining pathways into pathological gambling, concludes that problem gambling is ‘the end result of a complex interaction of genetic, biological, psychological and environmental factors’, (p. 7). He identified three different pathways into gambling and argued that each type contains different implications for management strategies and treatment interventions.
- The ‘normal’ problem gamblers (A group with no pre-existing psychopathology. May lose transient control over their gambling behaviour, but their disordered gambling can remit spontaneously or with minimal intervention):
This group may need minimal interventions, counselling and support services. Self-help and self-control educational materials as well as self-help groups such as Gamblers Anonymous can be effective. They may resume controlled gambling after intervention.
- The psychologically vulnerable group of gamblers (Gamblers who try to deal with their emotional distress or life’s pressures by ‘escaping’ through gambling):
Blaszczynski (1998) advises that, for this group, ‘Abstinence is perhaps the best goal of treatment’ (p 37). In addition, these gamblers can benefit from psycho-therapeutic interventions to resolve internal conflict and deal with anxiety. This could include stress management, problem-solving skills, and strategies to enhance self-esteem.
- Group with biologically based impulses: The impulsive gamblers (Defined by the presence of neurological or neurochemical dysfunction, reflecting features such as impulsivity and attention deficit):
This group require intensive cognitive behavioural interventions aimed at impulse control. Medication can be considered, with a view to reducing impulsivity through its calming effects. Blaszczynski et al., (2001) advised that genetic vulnerability is unlikely to be amenable to harm minimisation strategies. This group may therefore be better off abstaining from gambling while receiving treatment.
While this classification has been contested, and perhaps denotes adult pathways, rather than adolescent pathways, there is broad agreement with the explanation or biopsychological model as advanced by Blaszczynski. This represents a marked shift away from the more limited diagnostic/medical models as reflected in DSM criteria. It also stresses the importance of screening tools that are relevant to the social context in which they are applied.
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2.3 South Oaks Gambling Screen (SOGS)
SOGS is a 20-item questionnaire originally developed for use in clinical settings that was designed to evaluate the presence of pathological gambling. It is essentially based on the medical model employing diagnostic criteria to assess pathological gambling. It derived from the various DSM screening instruments, although it emphasises other aspects such as financial impacts of gambling (e.g., borrowing money). The items include questions about returning another day to win back money lost, gambling more than intended, feeling guilty about gambling, being criticised by others over gambling, having difficulty stopping gambling, and losing time from work because of it. In its original form it used a dichotomous yes/no approach although recent variations of the instrument employ a graded response scale or numbered Likert scales. The respondent is able to indicate a ‘degree of relevance’ such as often, rarely, never, sometimes, etcetera.
Lesieur and Blume (1987) based SOGS on DSM-III criteria and 1,616 subjects were involved in its development, from a number of sources but over half were patients with diagnoses of substance abuse and pathological gambling. They found SOGS to be valid, reliable screening instrument for the fast screening of alcoholic, drug-dependent, and other patients for pathological gambling. A refinement of SOGS is the SOGS-R instrument, initially developed to differentiate between inactive and active gamblers. Svensen (undated) comments that ‘in order to limit the prevalence of problem gambling to those most likely to be currently experiencing problems, instruments such as SOGS-R were devised that question people about their gambling behaviours in the immediate past, generally the past six months in Australian studies,’( p. 7) although twelve months is the usual time found in almost all studies in other countries.
Notwithstanding, since its inception SOGS has been used as a general screening tool. Furthermore, Orford et al (2003) surveyed 7,680 households on their gambling behaviour to test the psychometric properties of SOGS and DSM-IV. SOGS was found to have a reasonably high internal reliability.
Ladouceur et al (2000) recruited 60 adult participants to study their understanding of telephone adapted SOGS items.4 Participants who scored 5 or more were asked to attend a structured interview in order to measure their understanding of items. In a series of stages items were explained and SOGS given a second time. No respondent understood all of the items. On average participants did not understand 25.8 per cent of the items (27.2 per cent of the non-problem gamblers and 22.2 per cent of the ‘probably’ pathological gamblers). Significantly, some 23.4 per cent of respondents that were classified as problem gamblers were, when items were later clarified, subsequently categorised as non-problem gamblers illustrating the problem of ‘false positives’. None of the non-problem gamblers increased their score enough to be classified as ‘probably’ pathological gamblers.
Battersby et al (2002) reviewed SOGS with reference to Australian use, describing SOGS as a self-rated screening instrument, based on DSM-III and DSM-IIIR criteria. The authors maintain that establishment of the optimal cut-off point of 5+ to indicate possible pathological gambling appears to have been chosen by ‘trial and error to provide the least number of false positives and false negatives’, (p. 260). They indicate that the problem gambler identified by SOGS in telephone surveys of the general population in the USA is quite different to that defined in the original clinical trials, including Gamblers Anonymous. They suggest that SOGS may not be appropriate in non-clinical populations. More importantly, as with Dickerson (1996) and others, the authors argue that there is no general support for the concept of pathological gambling. ‘It has not been clearly specified and may not exist’, (p. 263).
Battersby et al (2002), among others, argue against SOGS being utilised in an Australian context, due to the unique Australian experience. As Dickenson et al (1997) notes
‘The Australian social context not only is typified by a community acceptance of, and participation in, gaming and wagering, but also by broad based preventative and harm minimisation strategies to address problem gambling’. (page 28)
It is claimed that the cut-off point of 5+ for SOGS commonly used in Australia leads to high prevalence rates and that this may simply reflect the gambling culture in Australia, compared to the United States and other countries. There have been numerous instances where the cut-off score has been increased from 5+ even up to a score of 10+. The most notable example of this is the national Productivity Commission study, wherein they argue that ‘SOGS 10+ group have a very similar pattern of SOGS responses to those gamblers who seek help from specialist problem gambling agencies’. (6.26). The Commission however, went further to assess measures of harm and stated that there is a strong basis for seeing ‘SOGS 5+ as a reasonable measure of problem gambling [ and that] it is apparent that SOGS 10+ group fails to identify the bulk of people who are experiencing significant problems with their gambling.’ (6.30) Svensen (undated) asserts that ‘instead of concluding that Australia had a high prevalence of problem gambling. some Australian researchers argued that Australians should be measured differently to other human beings,’(page 11) and that this axiomatically leads to continual adjustments to the cut-off score used to measure ‘problem gambling’ behaviour and the rate of prevalence reported by various studies.
Svensen refers to a ‘national study in 1991-92 that found current prevalence rates of 6.6 per cent when a 5+ cut-off was used. (page 12). What is clear is that the purpose of the study must be clearly enunciated. If for example, the researchers desires to measure ‘severe problem gambling’ then a score of 10+ would be justified. If the purpose is to decide on a possible range of interventions then a score of 5+ may be more appropriate. For those gamblers requiring specific counselling and intervention, a score of 10+ would be more appropriate then a lower score.
While Dickerson et al (1996) have argued that a score of 5+ would lead to 6 per cent prevalence rate, and that this over-estimates the prevalence of problem gambling in Australia, there is no clear reason why either Dickerson, the Productivity Commission or any other researcher could support a 10+ SOGS score for problem gambling over a 5+ score. It is not a valid procedure to relate a 10+ score with ratings for those who attend gambling counselling and to then argue that (because the two groups are similar) this is an appropriate cut-off threshold because the ‘attendees’ are obviously problem gamblers. One reason is that less than 5 per cent of problem gamblers report for any treatment. We do not know whether they are the most seriously affected or not. Battersby concludes that SOGS is an inappropriate instrument to use in prevalence surveys. Where you pick the cut off score is then reflected in the prevalence rate. Most importantly, Battersby states
‘The SOGS was designed as a screening tool to detect potential ‘cases’ which would then require further clinical assessment. This has been ignored in the reporting of prevalence studies where there is no clinical assessment, yet claims are made as to the prevalence rate of ‘pathological gamblers’ in the population studied’, (p. 267).
Battersby et al (2002), among others, argue against SOGS being utilised in an Australian context, due to the unique Australian experience. As Dickenson et al (1997) notes
‘The Australian social context not only is typified by a community acceptance of, and participation in, gaming and wagering, but also by broad based preventative and harm minimisation strategies to address problem gambling’. (page 28)
It is claimed that the cut-off point of 5+ for SOGS commonly used in Australia leads to high prevalence rates and that this may simply reflect the gambling culture in Australia, compared to the United States and other countries. There have been numerous instances where the cut-off score has been increased from 5+ even up to a score of 10+. The most notable example of this is the national Productivity Commission study, wherein they argue that ‘SOGS 10+ group have a very similar pattern of SOGS responses to those gamblers who seek help from specialist problem gambling agencies’. (6.26). The Commission however, went further to assess measures of harm and stated that there is a strong basis for seeing ‘SOGS 5+ as a reasonable measure of problem gambling [ and that] it is apparent that SOGS 10+ group fails to identify the bulk of people who are experiencing significant problems with their gambling.’ (6.30) Svensen (undated) asserts that ‘instead of concluding that Australia had a high prevalence of problem gambling. some Australian researchers argued that Australians should be measured differently to other human beings,’(page 11) and that this axiomatically leads to continual adjustments to the cut-off score used to measure ‘problem gambling’ behaviour and the rate of prevalence reported by various studies.
Svensen refers to a ‘national study in 1991-92 that found current prevalence rates of 6.6 per cent when a 5+ cut-off was used. (page 12). What is clear is that the purpose of the study must be clearly enunciated. If for example, the researchers desires to measure ‘severe problem gambling’ then a score of 10+ would be justified. If the purpose is to decide on a possible range of interventions then a score of 5+ may be more appropriate. For those gamblers requiring specific counselling and intervention, a score of 10+ would be more appropriate then a lower score.
While Dickerson et al (1996) have argued that a score of 5+ would lead to 6 per cent prevalence rate, and that this over-estimates the prevalence of problem gambling in Australia, there is no clear reason why either Dickerson, the Productivity Commission or any other researcher could support a 10+ SOGS score for problem gambling over a 5+ score. It is not a valid procedure to relate a 10+ score with ratings for those who attend gambling counselling and to then argue that (because the two groups are similar) this is an appropriate cut-off threshold because the ‘attendees’ are obviously problem gamblers. One reason is that less than 5 per cent of problem gamblers report for any treatment. We do not know whether they are the most seriously affected or not. Battersby concludes that SOGS is an inappropriate instrument to use in prevalence surveys. Where you pick the cut off score is then reflected in the prevalence rate. Most importantly, Battersby states
‘The SOGS was designed as a screening tool to detect potential ‘cases’ which would then require further clinical assessment. This has been ignored in the reporting of prevalence studies where there is no clinical assessment, yet claims are made as to the prevalence rate of ‘pathological gamblers’ in the population studied’, (p. 267).
Battersby (2002) suggests an alternative approach is to use the preferred term ‘problem gambling’ and employ a screening instrument such as the Victorian Gambling Screen (VGS) to measure harm to individuals, their family and to the community. The researchers have no evidence that such a screen has been applied to the adolescent population.
AUTHOR: Lesieur and Blume (1987)
COUNTRY: USA
METHODOLOGY: Originally conducted in psychiatric hospital for alcoholism and drug dependency and treatment of pathological gambling. Survey and interview; supported by information from family/others who were also interviewed. Tested on GA group, students, 1,616 subjects involved in development.
SCREEN/MODEL:: SOGS pathological gamblers 5+
STRENGTHS: Is the most widely used screen and has a high internal reliability. Able to be used by non-professional in non-clinical setting.
WEAKNESSES: On average over 25 per cent respondents did not understand over a quarter of items and its true sensitivity in the general population is unknown.
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2.4 South Oaks Gambling Screen-Revised for Adolescents (SOGS-RA)
SOGS-RA is a revised version of SOGS developed in order to more accurately assess adolescent gambling problems. It is a 16-item scale (although only 12 items are scored) that assesses gambling behaviours and gambling related problems during the past 12 months. The South Oaks Gambling Screen (and its variations) is one of the most frequently used instruments to assess problem gambling both in adults and in youth, and to provide general population estimates (Wiebe et al, 2000). Rossen (2001) claims that SOGS-RA ‘remains the most widely utilised adolescent gambling screen, particularly in surveys throughout America and Canada’, (p. 4).
SOGS-RA scaled items assess negative behaviours and feelings as a result of gambling involvement. The items include lying about gambling, gambling more than planned, conflict with family and friends and borrowing/stealing to gamble in the last twelve months.
Using this screen, there are three levels of severity: no problem gambling, at-risk gambling and problem gambling. No problem gambling is a SOGS-RA score of zero to one. At-risk gambling is a SOGS-RA total score 2-3. Finally, problem gambling is defined as a SOGS-RA score of four or more. These scores represent the narrow definition of gambling severity as developed by Winters (1995). A broader definition has also been developed (see Poulin, 2000) to account for gambling patterns. Specifically, the broader definition combines gambling frequency and the SOGS-RA score. Under the broader definition problem gambling (as the highest level) consists of SOGS-RA score of 2 or more combined with weekly gambling or ‘daily gambling regardless of the SOGSRA score’.
Winters et al (1993) developed SOGS-RA for use with older adolescents (ages 15 to 18). In the original study both a telephone interview and in-school survey were utilised. They found no significant differences between the two samples with respect to demographics, disclosure rates for questions pertaining to gambling behaviour and to other problem behaviours. Their study results demonstrated that the scale had moderate internal consistency, reliability and was significantly related to alternate measures of problem severity for male subjects. Because the rate and severity of gambling among females is very low, the psychometric properties could not be determined for females.
In assessing SOGS-RA, Wiebe et al (2000) suggests that items do not appear to equally contribute to the total score. If some items are better indicators of problem gambling, it is possible that these items should be more heavily weighed. The researchers concluded that there may be important differences in what items are endorsed by problem gamblers compared to non-problem gamblers.
Ladouceur et al (2000) conducted an analysis of SOGS-RA using children in the age range 9 to 12 years and discovered, that on average, children did not understand 26.7 per cent of the items. In a second study of 587 high school students only 30.8 per cent of the students understood all of the items correctly after being invited to complete the SOGSRA. Following clarification of misunderstood items the SOGS-RA scores decreased for this group by 29.4 per cent again highlighting the problem of ‘false positives’. Clearly, clarification procedures can have a marked impact on the validity of the screen.
Ladouceur et al (2000) then examined how well SOGS-RA items were understood by a group of adolescents in grade 9 to grade 11. Only 30.8 per cent of the 126 students understood all of the items correctly. On average, the participants did not understand 11.7 per cent of the time. No significant differences were found for grades. With respect to changes in scores for the SOGS-RA following a clarification of misunderstood items, the SOGS-RA scores decreased by 29.4 per cent. Furthermore, when the items of the instrument were clearly understood, the number of problem or probably pathological gambling is 41.8 per cent less than the initial figure revealed. One reason for this could be that the interviewers could have created the impression that the respondents should adopt a more conservative approach to answering the questionnaire items.
AUTHOR: Poulin (1998)
COUNTRY: 4 Atlantic Provinces, Canada
METHODOLOGY: Survey, 13,549 students in junior and high school, self reported questionnaire included in survey of students and substance abuse.
SCREEN/MODEL: SOGS-RA: problem gambling 4+
STRENGTHS: Reliability and construct validity, internally consistent, discriminated between status of gambling activity.
WEAKNESSES: Criterion validity (i.e., measure traditionally or consensually accepted in the field) has not been demonstrated so uncertainty as to whether definitions and cut-off scores applied to adults can be applied to youth. Cut-off scores could be gender specific.
Another criticism of the SOGS-RA is its lack of questions addressing preoccupation with gambling (Rossen, 2001). Derevensky and Gupta (2000) argue that preoccupation is a necessary element of any gambling screen for the following reasons: it is a criteria central to all addictions, as defined by the DSM-IV; and, their clinical experience has consistently demonstrated it to be relevant to adolescent populations.
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2.5 The Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV)
The basis of this model used extensively throughout the United States and several other countries is the ‘medical model’ where problem or pathological gambling is understood as a psychiatric disorder. The model seeks to understand problem gambling as the result of ‘individual pathology’ (i.e. meeting certain criteria) and then these criteria are used to measure prevalence of problem gambling. Supporters of this approach include Gamblers Anonymous, psychiatrists and most obviously, the gambling industry itself. This model tends to ignore the manner in which the broader economic, familial, social and cultural environment may influence attitudes and propensity to gamble and the intensity of gambling behaviour.
The DSM-IV model has been questioned particularly by Australian researchers including Blaszczynski, Dickerson, Woolley, McMillen and Delfabbro and others who embrace a more multiple faceted explanation of problem gambling which may arise as the result of social, psychological, economic, environmental and behavioural factors. Australian researchers appear to share a common view that ‘problem gambling’ is a multi-faceted in origin although individual researchers may emphasise one aspect over another.
Rossen (2001) argues that despite general consensus that gambling behaviour lies on a continuum, diagnostic tools endorse the assumptions from an underlying disease model. Screens are mostly made up of items that require yes/no answers. The exception to this is DSM-IV-MR-J (see discussion 2.6).
It is important to note that although adaptations of the DSM-IV has been used to measure the numbers of problem gamblers in adolescents, DSM-IV itself is not a screening tool, and has not been designed as such, but is a set of clinical criteria. It shares many features of the SOGS, but has a greater emphasis on the psychological aspects of problem gambling, such as preoccupation, development of tolerance, irritability, and gambling as an escape (Productivity Commission, 1999). It measures the concept of pathological gambling.
2.6 The Diagnostic Statistical Manual-IV-Multiple-Response-Adapted for Juveniles (DSM-IV-MR-J)
The DSM-IV-MR-J was developed by Fisher (2000) for adolescents who have gambled in the last year and was a variation on Diagnostic Statistical Manual-IV Adapted for Juveniles (DSM-IV-J). DSM-IV-J was based on the adult diagnostic criteria for pathological gambling as defined by the American Psychological Association. It was adapted to measure past year gambling among 11 to 16 year olds via a questionnaire administered in a classroom setting (Fisher, 2000). The questionnaire consisted of 12 items with yes/no response. Fisher (2000) found that four positive responses were enough to categorise respondents as ‘probable pathological gamblers’.
DSM-IV-MR-J addresses the appropriateness of yes/no responses in non-clinical situations. As many prevalence studies do not have the opportunity for further probing, most of the questions in the revised instrument have been given four response options: ‘never,’ ‘once or twice,’ ‘sometimes’ or ‘often’. These revisions also lead to there being nine items. The screening test’s readability was computed using the Flesch-Kincaid Grade Level Test that provides a score based on the average number of syllables per word and the average number of words per sentence. The score indicates a gradeequivalent level. The test has a score of 4.8 and is therefore at a high fourth grade reading level.
Fisher (2000) explored psychometric data on respondents who were fruit machine players. She found that internal consistency reliability was acceptable for a scale of this size.5 Survey results also demonstrated that there were no weak items as all of the items discriminated extremely effectively between the problem gamblers and non-problem gamblers. More males were problem gamblers than females and therefore more likely to endorse items. Interestingly, Year 8 respondents (12-13 years) were more likely to endorse all the items than the Year 10 respondent (14-15 years). However, there was no significant difference between the age groups in the proportions categorised as problem gamblers. Furthermore, highly significant mean score differences between regular and non-regular fruit machine gamblers on DSM-IV-MR-J provide evidence of construct validity for the scale. However, this revised screen has not been fully validated.
The strengths of DSM-IV-MR-J is that it has been found that internal consistency reliability is reasonable, all items are discriminatory, construct validity is reliable, it is also a variation of an existing screen and it has a very low reading age. The weaknesses are that it has not fully validated and has not been used extensively or in large scale samples.
No Studies cited SCREEN/MODEL: DSM-IV-MR-J; provides for greater range of options in responding than simple yes/no.
STRENGTHS: Readable, reliable, internally consistent and good discrimination ability, construct validity high so overall some support for use with adolescent group 12-18 years.
WEAKNESSES: No evidence of screen being used in large scale study. The researchers unsure about screen’s sensitivity to gender.
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2.7 SOGS-RA, DSM-IV-J and GA20
Derevensky and Gupta (2000) examined the gambling behaviour of 980 adolescents who were administered three screening measures used with adolescents: SOGS-RA, DSM-IVJ, and the GA 20 questions. All participants were attending junior college and were given a questionnaire during regular class time assessing their past and present gambling history. The questionnaire included the DSM-IV-J, SOGS-RA, and GA20 with instruments presented in random order. They found that DSM-IV-J was found to be the most conservative measure defining 3.4 per cent of the population as problem/pathological gamblers while the SOGS-RA identified 5.3 per cent and the GA Questions identified 6 per cent of youth as experiencing serious gambling problems. It is interesting to note that SOGS-RA found that largest number of males (11 per cent) and the GA20 the largest number of females (3.5 per cent) as probable pathological gamblers. Of particular interest is the finding that scores for female populations exhibit greater variance according to the utilised screen than those for male populations. The researchers also note the variation across the three screens from the same sample: 3.4 per cent up to 6 per cent. Therefore, prevalence rates are partially a product of the screening tool used.
2.8 Gamblers Anonymous Twenty Questions (GA-20)
Ursua and Uribelarrea (1998) tested the Spanish version of the GA 20. The results of 127 problem gamblers presenting for treatment of two self-help associations of Madrid were compared to 142 participants who were social gamblers. The social gamblers were paired with the pathological gamblers for the variables of age and sex. GA20 was found to strongly correlate with SOGS. GA20 had high discriminatory validity; hence the questionnaire differentiates between problem gamblers and social gamblers. Ursua and Uribelarrea concluded that GA20 is a good screening instrument, with high reliability and validity, has a coherent unidimensional structure, had high discriminative power and diagnostic efficacy.
The authors claim that the discrimination power of the GA20 is a major strength, and that the GA20 identifies the largest number of pathological gambling adolescents when compared with the SOGS-RA and DSM-IV-J. They go further to state that GA 20 ‘is as good as the best clinical and diagnostic instruments proposed at present’ (page 11). They also conclude that GA20 seemed to produce less false positives6 than SOGS. Neighbors et al (2002) also reported that as part of their study on 560 undergraduate college students GA20 was moderately correlated with SOGS (correlated 0.55).
AUTHOR: Ursua, M. and Uribelarrea (1998).
COUNTRY: Spain.
METHODOLOGY: Comparison of problem gamblers (R=127) in treatment with N=142 social gamblers.
SCREEN/MODEL: GA twenty questions.
STRENGTHS: High reliability (for internal consistency), high convergent validity and correlation with SOGS rated as very high, discriminating ability also high (i.e., discriminate between problem and social gamblers).
WEAKNESSES: Not discussed.
One possibility arising from the discussion of SOGS-RA and GA20 in regard to their usefulness in identifying youth experiencing gambling problems, would be to use SOGSRA and GA-20 concurrently across the total sample and to compare the results of the two screens.
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2.9 Massachusetts Gambling Screen (MAGS)
The Massachusetts Gambling Screen (MAGS) was originally developed to ‘assess the biological, psychological and social problems associated with excessive gambling in people who may or may not be in treatment.’7 It is a 26 item scale survey screening instrument incorporating DSM-IV criteria designed to predict pathological gambling in the general adolescent population. Initially tested on 856 high school students the general consensus of peer reviews we have cited indicate MAGS to be a reliable, valid and effective (i.e., can identify those at risk of pathological gambling) clinical instrument. The explanation for the more limited use of the MAGS screen for measuring problem gambling is that it relies on a binary response (yes/no) for all but one question (although several other screens do likewise), while the classification of respondents into pathological, in transition or non-pathological gamblers is clearly based within the individual, pathology based paradigm (i.e., the medical/disease/DSM-IV model). This is despite the claim that the screen purports to measure social factors as an explanation for problem gambling.
Derevensky (2000) concludes that MAGS is an effective screening instrument for adolescent pathological gambling, ‘showing a 96 per cent agreement with DSM-IV classification system. The MAGS therefore may be the measure of choice for future research efforts with adolescents although it seems unclear as to the benefits of selecting the MAGS, which is modelled so closely upon the DSM-IV, instead of using the DSM-IV criteria itself’, (p. 247).
2.10 The Canadian Problem Gambling Index
The CPGI was developed because of concerns relating to the use of SOGS and DSM-IV manual diagnostic criteria for pathological gambling to determine prevalence within the general population. Intended for use across the general population, the CPGI includes consideration of broader environmental and social factors.
The Centre for Gambling Research (ANU) describes the composition of the CPGI to include four different sections:
- ‘a detailed measurement of respondents’ involvement in various forms of gambling;
- the assessment of problem gambling;
- an evaluation of correlates of problem gambling (e.g., family history, alcohol or drug use); and
- demographic variables’ (CGR p20).
Scale responses are used to classify or group into the following categorisation:
- 0 = non-problem gambling;
- 1-2 = low risk;
- 3-7 = moderate risk;
- 8+ = problem gambling.
In commenting on validation of the CPGI the researchers note that ‘the validation of the CPGI was to a large degree based on DSM and SOGS as reference standards, even though their underlying model of pathological gambling was rejected. Further evidence for the measurement qualities of the CPGI is desirable.’8 However, users of CPGI in Canada assert that the ‘CPGI is thought to be a more precise measure of problem gambling behaviour among non-clinical populations’. 9 It was tested prior to its use in community based surveys and was found to have well established psychometric properties.
2.11 The Victorian Gambling Screen
Arising from concerns that existing models of problem gambling and their associated gambling screens (SOGS, SOGS-R, DMV-IV, etcetera) focussed too heavily on pathological gambling and thus were considered to not be appropriate for the Australian situation, the Victorian Casino and Gambling Authority commissioned Flinders Technologies to design a new problem gambling screen. The Victorian Gambling Screen (VGS) was designed and has recently been tested in a study conducted by the Centre for Gambling Research (ANU).10
The VGS includes 21 items covering enjoyment derived from gambling (three items), harm to self (fifteen items) and harm to partner (three items), but surprisingly excludes harm to others. These three classifications to account for the 21 questions were developed following focus group discussions with regular and problems gamblers in treatment in Victoria. A pilot validation study was conducted with 239 gambling respondents and we understand, then included detailed interviews with approximately one-third of respondents. To our knowledge the VGS has not been trialled on a much larger sample.
In the next section we consider various studies that have used some of these screens to research adolescent gambling.