The above table explains the results of confirmatory factor analysis (CFA), which compares the two models (Model D and Model 1) and depicts the goodness of fit. The calculated value of the Chi-square, 63.20 indicates that model 1 is well within the acceptable range, with a p-value of 0.07 indicating a better fit. The computed value of CFI (Comparative Fit Index) and GFI (Goodness of Fit Index) 0.92 for model 1 indicates a good fit. The values of TLI (Tucker Lewis Index) and IFI (Incremental Fit Index), 0.88 and 0.92, also indicate a good fit. The value for RMSEA was, however, 0.04. Hence, the model showed an adequate fit to the data.

Discussion

In the present study, the demographics of the sample having drug addiction are reported in terms of age, substance type, duration of use, and the number of relapses. So, drug addiction was reported in three age cohorts: 33% in late adolescence, 37% in early adulthood, and 30% in middle adulthood. Additionally, results also showed the percentages of choice of drugs. The percentage of cannabis is 32%, a second higher percentage is 21.4% for multiple substance users such as a combination of cannabis with ice or opioids and alcohol, 18% are using ICE (methamphetamine), and 16.4% are using opioids such as heroin, painkillers. Sau, Mukherjee, Manna, and Sanyal (2013) also reported research with percentages such as opiates rate reported as 57% in males, 51% rate of heroin, alcohol 38% rate, rate of heroin, and 22% rate of cannabis. Results were also consistent with old research, such as research conducted by McLellan (2017), which reported that 85% of the individuals who met the criteria of substance use disorder fall in adolescence. Additionally, the report of Drugs and Crime (2018) stated that drug use is higher among 18-25 years of age (Sau et al., 2013). Moreover, they reported the data from 28 states of Europe, along with Norway and Turkey, that the use of amphetamine and ecstasy among individuals under age 35 is two to three times higher than older individuals. Additionally, the lifetime use of cannabis among young individuals aged under 35 is much higher, and these findings are also consistent with the cannabis use in the present study, which was reported as 32%, which indicates that cannabis is most common among addicts. Data from the Plurinational State of Bolivia showed that the recent use of multiple substances is significantly higher among the age group 18-24 than among those in another age group 36-50. According to the European Monitoring Centre for Drugs and Drugs addiction, the concurrent use of more than one substance is characteristic of young individuals as compared to older individuals, and it's more common as recreational and regular drug use. It also involves more established patterns of multiple substance use, which are further linked with patterns such as the increased risk of long-term problems, risk-taking through binge drinking of alcohol, or binge use of stimulants at parties or in group settings (as cited in Drugs & Crime, 2018). The present study also indicated the relapse rate of the patients as 44% of the patients were in their first treatment, and 66% relapsed one time or more than one time. In a research conducted by Sau et al. (2013), 31% of the sample were relapse individuals.

Comorbid illnesses were also reported in the present study. The results indicate that 27.9% are with psychotic disorders, 5.7% are suffering with neurotic disorders, and 66.4% have no mental illness other than substance use disorder. Past literature also showed the rate of comorbid disorders of substance use disorder. The common co-occurrence illnesses were anxiety (44.7%), depression (30.6%), and paranoid delusion (9.8%) (Sau et al., 2013). According to Volkow (2001), drugs have a role in triggering psychosis in those without a history of psychiatric illness. Thought is that the stimulant drugs trigger psychosis, and there is an excess of dopamine concentration in the brain. Additionally, individuals with a history of methamphetamine abuse still have symptoms of psychosis; however, they have a loss of dopamine transporters in the brain.

The psychometrics of the scale, especially the reliability and validity, were not determined before. This was the first attempt at reliability analysis, and the results showed the alpha reliability α = 0.60 of this scale indicates that the reliability of this Urdu version scale is falling in the acceptance range. Which shows the items have internal consistency among items. The authors of the original scale reported the face validity, which was good. When asked about the top three items for recovery, they put abstinence at the top for recovery. For problem drinkers, 65% of them put abstinence as the first thing for recovery, 8% put accommodation and mental health as the second level, 59% of problem drug users also put abstinence as the first level, and 14% said staying away from other users is a second level thing for recovery. Conclusively, 86% of problem drinkers and problem drug users, 49% of concerned others, 36% of specialists, 43% of generalists, and 42% of commissioners put abstinence first (Iveson-Brown & Raistrick, 2016). ARQ also has the ability to discriminate the respondents into three groups, such as well functioning, treatment, and recovery, as validating the outcome of ARQ (Truby, 2020).

The results of confirmatory factor analysis showed acceptable results with a df to chi-square ratio of 63.20, which is well within the acceptable range. The value for RMSEA was, however, 0.04. Hence, the model showed an adequate fit to the data. The results of this study are also evident by the author of ARQ (Iveson-Brown & Raistrick, 2016), where he constructed the scale and ran the Exploratory factor analysis. The component analysis for ARQ found three factors, abstinence, normality, and positivity, which are also confirmed by the confirmatory factor analysis of this research with an acceptable range of chi-square value of 63.20 and RMSEA value of 0.04 with adequate fit of the model.