Gambling Addiction Statistics | The Oaks at La Paloma Treatment Center

User Login

Remember me
Calendar It is currently 17.12.2018


Statistics of Gambling Addiction 2016

Congratulate, magnificent idea gambling cowboy transformation for
982 posts В• Page 892 of 16

Gambling addiction ratio 2017

Postby JoJoshakar В» 17.12.2018


Background: The risk of developing a problem gambling behavior is distributed unequally among the population.

For example, individuals who report stressful life events, show impairments of mental health or belong to a socio-economically deprived group are affected more frequently by gambling problems. Methods: Of a total of 10, participants in the representative gambling survey in Austria in , 4, individuals reported gambling during the last 12 months and were allocated to the four gambling groups according to DSM With social gamblers as the reference group, relevant risk factors for the other three groups were identified by means of bi- and multivariate multinomial logistic regression.

Conclusion: Overall, the results of this study suggest, that the number and the influence of the included risk factors differ between gambling problem groups. Apparently, the development of severe gambling problems is to a lesser extent facilitated by specific risk factors than by their cumulative presence. Therefore, future prevention and treatment measures should place a particular focus on individuals who have experienced growing up in a difficult family situation, have poor mental health, suffer from substance-related problems or have a low level of formal education.

In addition to genetic variables as a relevant factor for the development of problem gambling Potenza et al. With the exception of lotteries, gambling is a leisure activity performed more often by men than by women. Notably, men prefer types of gambling which are considered to be of particularly high risk for the development of problem gambling behavior, such as slot machines, casino games or sports betting Hing et al. Therefore, it is not surprising that, compared to women, men are at a higher risk for developing gambling problems Abbott et al.

Age is another important demographic risk factor. Particularly younger age groups are disproportionately affected Subramaniam et al. Furthermore, individuals with a migration background develop a problem gambling behavior more frequently than persons who do not have such a background Volberg et al. In addition to their gambling problems, many pathological gamblers are also affected by depressive or anxiety disorders Barry et al. In a meta-analysis, Dowling et al.

More than half had been diagnosed with depression and about one quarter had an anxiety disorder. These mental health problems can be a cause as well as a consequence of problem gambling Hodgins et al.

However, regardless of causality issues, comorbid mental disorders indicate a higher risk of being affected by gambling problems. Aside from the reported mental health impairments and certain personality traits, substance-related disorders are of great importance Kessler et al. In their meta-analysis Lorains et al. With regard to illegal substances, the respective share was Similar to other addictive disorders, children of parents with a problem gambling behavior are at increased risk of developing gambling problems Williams et al.

A number of studies on substance-related problems showed that having grown up with a single parent increased the risk of developing this sort of problem behavior Blum et al. However, with regard to problem gambling, the effects of being raised by a single parent have been analyzed in only few studies. Ste-Marie found that the share of persons who grew up with single parents increased with the extent of the gambling problems.

The studies by Canale et al. The addictive potential of gambling varies with the different gambling products. While, in comparison, the use of lotteries and scratch cards leads to gambling problems rather rarely, sports betters, individuals who prefer casino games and especially persons who use slot machines are at higher risk of developing a gambling disorder Scalese et al. This is particularly the case if the participation in these gambling forms occurs on a regular basis Williams et al.

The above mentioned findings show that problem gambling is associated with a multitude of variables from various areas. Even though they do not always precede the development of gambling problems, these characteristics indicate a higher risk among affected individuals for also having a gambling problem. The results of the reported studies are predominantly outcomes of bivariate analyses, partly controlled by demographic variables.

However, using these procedures, it cannot be excluded that the associations found are in fact the results of spurious relationships.

The number and the importance of relevant factors of influence therefore might be overestimated. If however risk factors are simultaneously included in a multivariate analysis, the correlations between the variables included in the analysis are subtracted controlled and the effectively relevant factors can be determined.

Furthermore, the above mentioned studies are based on different definitions of problem gambling. While many studies only include individuals in the affected group who meet the criteria for pathological gambling e. Although the latter procedure is understandable from a methodological perspective, as, particularly in representative surveys, the number of pathological gamblers is often too small for statistical analysis, it is nevertheless questionable when it comes to content.

Thus, Shen et al. Furthermore, the latter group participates significantly more frequently in poker games and sports betting and also takes part in online gambling considerably more often. However, given that both groups differ with regard to these characteristics, one may assume that factors which facilitate gambling problems are of varying importance within these groups.

Aim of the present study is to identify potential risk factors for disordered, problem, and at-risk gambling and to assess their respective relevance. If the analysis shows that the influence of variables varies with the severity of the gambling problem, existing treatment, protection and prevention measures would have to be adapted or new interventions would need to be developed from scratch for each of the individual problem groups.

The analysis is based on data of a general population survey on gambling behavior in Austria in The survey included sociodemographic and biographic data as well as data on gambling behavior, motives for gambling, alcohol use, mental health problems, suicidal thoughts and behavior as well as attitudes toward prevention measures Kalke et al. The basic population of the study consists of 14 to 65 year old inhabitants living in private households in Austria.

This basic population is reduced to a sampling frame of German speaking individuals. Data collection was conducted by means of computer assisted telephone interviews CATI. The telephone numbers were drawn from public telephone directories mobile and landline using random sampling.

The sample was stratified according to the number of inhabitants of each of the Austrian federal states. Prior to the interview, the contacted individuals were asked to report the name of the federal state of their residence, their age and their gender. Only if the contacted person met the criteria of a yet not fully recruited quota, the full interview was carried out. In multiple-person households, the person with the next birthday coming up was interviewed next-birthday-method.

The interviews were conducted between January 9, and June 22, A sample of 32, telephone numbers was drawn using the method described above. A total of 20, individuals had to be contacted in order to reach the targeted number of 10, interviews which equals a response rate of Furthermore, only those 4, individuals who had reported gambling during the last 12 months were included in the following analyses. These missings were imputed with multiple imputation algorithms included in the statistical software MPlus 7.

Despite the use of complex sampling procedures, achieving full representativeness of the sample is generally not possible. Therefore, the distributions in samples of representative surveys always differ slightly from those in the basic population. These differences are corrected post hoc by using weighting factors. This article is based on a secondary analysis of anonymized data from phone interviews for which all respondents gave oral consent before beginning the interview.

They were free to withdraw at any time and without giving any reason. The data cannot be linked to the respondents. As the consultation of an ethics committee is not mandatory in the case of anonymized data collection and analysis, we refrained from requesting an ethics vote.

The variables that should undergo testing were selected primarily on the basis of findings of other international studies which have investigated this issue see above. As representative surveys are quite costly and respondents are only willing to participate in phone interviews for a limited amount of time, only items which could be validly assessed by means of very brief instruments such as Alcohol Use Disorder Identification Test-Consumption Questions AUDIT-C and the Mental Health Interview MHI-5 were included.

Apart from these two instruments, other risk factors included in the analysis were gender, age, highest qualification reached in school, migration background, addiction problems of parents, growing up with a single parent, professional status and participation in high risk gambling forms sports betting, slot machines in and outside of casinos and casino games [i.

The DSM-5 provides nine criteria, which describe the main characteristics of a gambling disorder. These criteria were assessed using an instrument developed by Stinchfield for the DSM-IV which was adapted to DSM-5 by removing the criterion of having committed illegal acts to finance gambling.

Stinchfield appraised the original instrument to be of satisfactory reliability, validity, and classification accuracy. The instrument adapted to DSM-5 includes 18 questions which can be answered with no 0 or yes 1. With the exception of criterion 4 withdrawal symptoms , all criteria are operationalized through two individual questions.

One criterion is met if at least one of the questions is answered with yes. If respondents meet four or more criteria, they are allocated to the group of gambling disorder. Respondents who meet two or three criteria are allocated to the group of problem gamblers.

The group of at-risk gamblers meets only one of nine possible criteria. The values of the predefined answers range from 0 to 4 points, with 12 points being the maximum total. The cut-off value in German speaking countries has been found to be 5 for men and women Mann et al.

The MHI-5 consists of five questions referring to nervousness, depressiveness with no possibility of solace, downheartedness and sadness, calmness, and happiness within the last 4 weeks. For the items calmness and happiness polarity needs to be reversed recoding. Raw scores of 18 or less indicate problems in the area of mental health Rumpf et al.

Common testing procedures were applied to test differences between the different gambling problem groups. In case of inhomogeneous variances of analyzed items, significance tests were conducted using the Welch-Test Zimmerman, The relevance of the included risk factors for the three problem groups disorder, problem, at-risk in comparison to the reference group social gamblers was initially tested by means of bivariate multinomial logistic regression analyses.

For this procedure all four groups are included simultaneously in the analysis, but only one independent variable is included at a time i. Bivariate analyses may allow for a first appraisal of the relevance of the included factors.

However, this method cannot be used to assess whether the detected effects were possibly influenced by correlations with other potential risk factors. Therefore, in a second step, multivariate multinomial logistic regressions were conducted by simultaneously including all those potential risk factors in the analysis which were considered relevant and provided a sufficient number of cases for each problem gambling group.

By doing so, correlations between different factors can be subtracted out controlled. In order to assess the strength of the association between the included factors, tetrachoric correlations were calculated on the basis of dichotomized items. Of all respondents In order to describe these four groups, a comparison was made regarding a range of variables which are considered as traditional risk factors for problem gambling see introduction.

However, a significantly higher risk for males to be part of a problem group can only be found for disordered gamblers. Furthermore, individuals aged up to 26 bear a higher risk for disordered or problem gambling. Individuals with a migration background, a low level of formal education and the professional status of being a working class member are represented disproportionately strongly within the group of disordered gamblers.

The corresponding odds ratios are only statistically relevant for this group. Potential risk factors for at-risk, problem, and disordered gambling — Results of the univariate logistic Regression.

'I Lost Almost £1 Million to My Gambling Addiction' - Good Morning Britain, time: 5:33
Posts: 152
Joined: 17.12.2018

Re: gambling addiction ratio 2017

Postby Kikus В» 17.12.2018

Almost two thirds of disordered gamblers show at least at-risk use of click here. It is easier than ever to gamble in the privacy of home or on the go with a smart phone. Statistics of Gambling Addiction.

Posts: 139
Joined: 17.12.2018

Re: gambling addiction ratio 2017

Postby Dim В» 17.12.2018

This is particularly the case if the participation in these gambling forms occurs on a regular basis Williams et al. Therefore, the qddiction in samples of representative surveys always differ slightly from those in the basic population. Far fewer risk factors were identified for the group of problem gamblers.

Posts: 327
Joined: 17.12.2018

Re: gambling addiction ratio 2017

Postby Dusho В» 17.12.2018

For this group, the risk of being ratio disordered or problem gambler is increased by factor 5. Health 56— Individuals with a migration background, a low level of formal education and the gambling status of being a working class fatio are represented disproportionately strongly within the group of disordered gamblers. The telephone numbers were drawn gamblinh public telephone directories mobile and landline using random sampling. With the 2017 of lotteries, gambling just click for source a leisure activity performed more often by men than by women.

Posts: 708
Joined: 17.12.2018

Re: gambling addiction ratio 2017

Postby Nelrajas В» 17.12.2018

Therefore, the number of cases included in the analysis is small and correspondingly the confidence intervals of the OR are very wide. Health 56— The cut-off value in German speaking countries has been found to be 5 for men and women Mann et al.

Posts: 344
Joined: 17.12.2018

761 posts В• Page 219 of 693

Return to 2017

Powered by phpBB В© 2001-2020 phpBB Group