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### INTRODUCTION

In present research study data related to those who receive CBT treatment is analysed by using varied tools. Main aim of the study is to identify whether changes that are observed due to CBT in patient behaviour remain same one month and 6 months after competition of CBT or better results are seen after 6 months of receipt of CBT. Focus is also on identifying whether socio economic factors and gender lead to intake of more alcohol and drug. Excessive consumption of these two may also lead to development of habit of gambling among individuals. Hypothesis was that CBT results vary after receiving treatment in first and sixth month. Hypothesis was that socio economic and gender factor promote intake of drug and alcohol. Relevant techniques are applied to test this hypothesis. In this way, entire research is carried out.

### Methods

Various statistical methods are utilized for analyzing business data, and in this study, techniques like regression and independent sample t-tests are applied. Regression is a crucial tool for determining the relationship between dependent and independent variables, illustrating how much an independent variable influences the dependent one—whether significantly or moderately (Little & Rubin, 2019). Independent sample t-tests are employed when multiple independent variables are involved, testing them against a specific categorical variable. By applying the most appropriate methods, data analysis can be significantly improved. Need help with statistical analysis? Let us do your math homework for precise results!

## Gender and gambling disorder after diagnosis

H0: There is no significant difference between male and female in respect to level of gambling disorder found among them after diagnosis.

H1: There is significant difference between male and female in respect to level of gambling disorder found among them after diagnosis.

 Group Statistics gender N Mean Std. Deviation Std. Error Mean dsm5Diag6m Female 590 1.49 .500 .021 Male 906 1.60 .490 .016
 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper dsm5Diag6m Equal variances assumed 25.625 .000 -4.188 1494 .000 -.109 .026 -.161 -.058 Equal variances not assumed -4.169 1238.991 .000 -.109 .026 -.161 -.058

Interpretation

Independent sample T test is used to identify whether there is significant difference between variables namely gender and level of gambling disorder after diagnosis. From the above table it can be observed that value of statistic for male is (M = 1.49, SD = 0.5) and same for female is (M = 1.60, SD = 0.49). Value of level of significance is 0.00

## PGSI follow up and PGSI after 6 months

H0: There is no significant impact of results obtained after diagnosis program on the follow up results obtained after 6 months from diagnosis date.

H1: There is significant impact of results obtained after diagnosis program on the follow up results obtained after 6 months from diagnosis date.

 Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 pgsi0mb . Enter a. Dependent Variable: pgsi6m b. All requested variables entered.
 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .049a .002 .002 3.29882 a. Predictors: (Constant), pgsi0m
 ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 39.325 1 39.325 3.614 .057b Residual 16258.028 1494 10.882 Total 16297.352 1495 a. Dependent Variable: pgsi6m b. Predictors: (Constant), pgsi0m
 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 9.868 .269 36.698 .000 pgsi0m .145 .077 .049 1.901 .057 a. Dependent Variable: pgsi6m

Interpretation

Regression is the another most important technique that is used to find out relationship between variables (Crowder, 2017). There is significant impact of independent variable on the dependent variable. It can be observed that value of level of significance in the above table is 0.05=0.05 which means that results that are obtained just after follow up does not determine results that will be observed just after 6 months of follow up. It is possible that just after follow up improvements can be observed in individual but after 6 months individual can be observed gambling addicted. Value of R is 0.043 which means that both variables are not correlated to each other. Value of R square is 0.02 which means that 2% in the dependent variable is explained by the independent variable. Null hypothesis accepted and it can be said that results that are obtained just after treatment can not determine results that will be seen just after 6 months.

## Socio economic status and GD after follow up

H0: There is no significant impact of socio economic status on the gambling disorder (GD) status observed after follow up.

H1: There is significant impact of socio economic status on the gambling disorder (GD) status observed after follow up.

 Variables Entered/Removed Model Variables Entered Variables Removed Method 1 sesb . Enter a. Dependent Variable: pgsi6m b. All requested variables entered.
 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .239a .057 .057 3.20706 a. Predictors: (Constant), ses
 ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 931.240 1 931.240 90.542 .000b Residual 15366.112 1494 10.285 Total 16297.352 1495 a. Dependent Variable: pgsi6m b. Predictors: (Constant), ses
 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 12.080 .200 60.521 .000 ses -.945 .099 -.239 -9.515 .000 a. Dependent Variable: pgsi6m

Interpretation

Value of level of significance is 0.00

## Gender and alcohol

H0: There is no significant difference between male and female in respect to use of alcohol.

H1: There is significant difference between male and female in respect to use of alcohol.

 Group Statistics gender N Mean Std. Deviation Std. Error Mean alcohol Female 614 1.53 .500 .020 Male 1099 2.00 .052 .002
 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper alcohol Equal variances assumed 47784.931 .000 -30.864 1711 .000 -.470 .015 -.499 -.440 Equal variances not assumed -23.218 620.486 .000 -.470 .020 -.509 -.430

Interpretation

In this case gender and alcohol are the two variables that are taken in to account for analysis purpose. Value of statistic for male is (M = 1.53, SD= 0.50) and same for female is (M = 2, SD= 0.052). Value of level of significance is 0.00

## Socio economic status and alcohol

H0: There is no significant difference between socio economic status and alcohol consumption.

H0: There is significant difference between socio economic status and alcohol consumption.

 Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 sesb . Enter a. Dependent Variable: alcohol b. All requested variables entered.
 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .000a .000 -.001 .377 a. Predictors: (Constant), ses
 ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression .000 1 .000 .000 .998b Residual 242.884 1711 .142 Total 242.884 1712 a. Dependent Variable: alcohol b. Predictors: (Constant), ses
 Coefficients Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 1.829 .022 83.254 .000 ses 2.416E-005 .011 .000 .002 .998 a. Dependent Variable: alcohol

Interpretation

In above table it can be seen that value of level of significance is 0.998>0.05 which means that there is no significant difference between variables. It can be said that with change in socio economic status no change comes in alcohol consumption. Value of R is 0 and same of R square is 0 which reflect that there is no correlation of socio economic status with alcohol consumption and socio-economic status does not play any role in determining alcohol consumption. Null hypothesis accepted.

## Gender and drug

H0: There is no significant impact of gender groups on drug consumption.

H1: There is significant impact of gender groups on drug consumption.

 Group Statistics gender N Mean Std. Deviation Std. Error Mean drugs Female 614 1.53 .499 .020 Male 1099 1.65 .476 .014
 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper drugs Equal variances assumed 56.324 .000 -4.973 1711 .000 -.121 .024 -.169 -.074 Equal variances not assumed -4.907 1218.819 .000 -.121 .025 -.170 -.073

Interpretation

In above case value of level of significance is 0.00M = 1.53, SD = 0.499) for female and in case of male value of statistic is (M = 1.65, SD = 0.476). Thus, it can be said that there is difference in the mean score across both groups. Alternative hypothesis accepted.

## Socio economic status and drug

 Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 sesb . Enter a. Dependent Variable: drugs b. All requested variables entered.
 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .002a .000 -.001 .488 a. Predictors: (Constant), ses
 ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression .002 1 .002 .009 .926b Residual 407.943 1711 .238 Total 407.945 1712 a. Dependent Variable: drugs b. Predictors: (Constant), ses
 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 1.611 .028 56.595 .000 ses -.001 .014 -.002 -.093 .926 a. Dependent Variable: drugs

Interpretation

Value of level of significance is 0.926,0.05 which means that there is no significant difference between variables. It can be said that with change in socio economic status drug consumption does not get affected. Value of R is 0.02 and R square is 0.00 which also indicate that there is no connection or correlation between both variables. Null hypothesis accepted.

## Discussion

On the basis of above discussion, it is concluded that gambling disorder is observed at quite different level across male and female. Means that after receiving treatment under CBT or cognitive behaviour therapy male and female observe changes differently (Naqvi and et.al., 2015). Interesting fact is that if any individual gets changes in terms of gambling addiction after treatment during follow up time period then that change remain persistent. If any individual's addiction level remains same after receiving treatment during follow up process then in that case it will not get reduced even after 6 months time period. Thus, whatever results obtained during follow up period reflect effectiveness of the CBT treatment for the individual. Interesting fact is that socio economic status of the patient is play crucial role in determining GD status of individual. Means that there may be chances that one belongs to the high-class society then in that case it may remain addicted to gambling even after receiving CBT treatment (Garland and et.al., 2016). Hence, it can be said that availability of sufficient amount of money become motivating factor for one to participate in gambling. Socio economic factor may be one of the reason behind the situation where individual addiction to gambling does not change even after receiving CBT. In terms of consumption of alcohol, it is observed that there is significant difference between male and female.

Overconsumption of the alcohol many times is considered main reason behind one’s involvement in playing gambling games and it may also be main reason behind no change in patient frequency of playing gambling games even after receiving CBT treatment. Frequency of drug consumption is also different across male and female. However, socio economic status does have any relationship with drug consumption (Killeen, Back and Brady, 2015). This reflect that like dislike matter and sort of lifestyle individual wants to live. Even one has low income it may prefer drug intake. Thus, it can be said that gender category has significant relationship with drug and alcohol consumption and both these may be main reason due to which significant change does not come in one habit to play gambling game even after receiving CBT.

## CONCLUSION

On the basis of above discussion, it is concluded that there is significant importance of the CBT approach to assist one in changing its habit of gambling. If in case of patient it is observed that changes come in its behaviour after receiving CBT then same will persist. If no change comes in the patient behaviour even after receiving CBT during one month then in that case same situation probably will remain in future time period. Socio economic factors does not play any role in alcohol and drug consumption. It is the gender factor where significant difference is observed in the consumption of drug and alcohol. In case of male consumption of both are high and due to this reason during CBT program special emphasis must be laid down on the male so that chances of not getting better results after CBT treatment can be minimized.

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