Evaluation of the Outcomes and Influencing Factors of Non-Custodial Educational Programmes for Drug Abusers

Evaluation of the Outcomes and Influencing Factors of Non-Custodial Educational Programmes for Drug Abusers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Evaluation of the Outcomes and Influencing Factors of Non-Custodial Educational Programmes for Drug Abusers Kyung-ae Nam, In-Sun Oh, Sun-Kyeong Park This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4748630/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study evaluated the effectiveness of deferred prosecution (DP) and probation, defined as non-custodial education programmes (NCEPs), for drug abusers in South Korea. We analysed participants’ questionnaire responses in the DP ( N = 203) and probation ( N = 254) groups over a two-year period (January 2022–December 2023). The Wilcoxon signed-rank test was used to compare pre-and post-programme questionnaires on knowledge of drug addiction and the Hanil Drug Insight Scale (HDIS) for participants in DP and probation. Using multivariate logistic analysis, we examined the factors influencing effectiveness, including previous treatment experience, Meaning of Life Questionnaire (MLQ) scores, and mental health status. NCEP effectiveness was assessed based on the participants’ reported intentions for future treatment at the end of the NCEP. DP participants and probationers showed significant increases in their knowledge of drug addiction and HDIS scores ( p < 0.001). Results showed that treatment experience (odds ratio [OR] 3.73, 95% confidence interval [CI] 1.30–10.71), poor mental health (OR 2.45, 95% CI 1.01–5.95), and good MLQ (OR 2.90, 95% CI 1.50–5.63) were significantly associated with improved NCEP effectiveness. This study provides the first evidence of the beneficial outcomes of the NCEP and identifies the factors influencing its effectiveness. Health sciences/Health care/Drug regulation Health sciences/Health care/Health policy Health sciences/Health care/Public health Drug abuser non-custodial education programme deferred prosecution probation logistic regression analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The war on drugs in the United States between 1986 and 1994 led to widespread incarceration of both drug abusers and traffickers 1 . This surge in incarceration has overwhelmed the criminal justice system, with the number of individuals charged with drug offences in federal courts increasing by 147% from 11,854 in 1984 to 29,306 in 1999 2 . Consequently, the stigma faced by low-level drug offenders has driven a rise in poverty and worsened both racial and gender discrimination 3 – 5 . Moreover, high rates of incarceration have intensified public health issues such as AIDS and hepatitis 5 – 7 . In response, various non-custodial programmes have been developed and increasingly adopted as alternative strategies to address drug addiction 8 , showing promise in improving recidivism rates, reducing substance use, and enhancing psychosocial outcomes 9 . Non-custodial programmes have diverse structures and applications in various countries. Australia, the United States, the United Kingdom, Taiwan, and Japan have implemented such approaches as diversion programmes, deferred prosecution (DP), and probation for drug offenders 9 – 13 . These initiatives effectively prevent criminal offenses 9 – 12 , enhance the health of drug users 9 , 13 , and lower social costs 10 , 14 . Specifically, non-custodial programmes for individuals with substance use disorders (SUDs) employ a variety of measures, including inpatient and outpatient treatment, opioid substitution therapy (OST) 15 , counseling 16 , and educational interventions 9 , 17 . For example, hospital treatment effectively reduces recidivism and drug use, 12 , 13 while providing OST upon release from prison reduces mortality and is cost-effective 15 . Mandatory hospital treatment in particular has been shown to improve stabilisation in patients with amphetamine-type stimulant use disorder 18 . The positive outcomes of non-custodial programmes have been demonstrated to reduce recidivism and maintain sustained abstinence by enhancing the motivation for subsequent SUD treatment 19 – 21 . These non-custodial programmes can be implemented individually or in combination and often include additional educational support for drug addicts 17 . In South Korea, drug-related crimes surged by 99.4% from 2012 (9,225 cases) to 2022 (18,395 cases), which is 4.3 times the growth rate of the global average 22 , 23 . In response, the Korean government declared a war on drugs in 2023, adopting a non-custodial approach for drug abusers while imposing severe penalties on traffickers 24 . South Korea has a Non-Custodial Education Programme (NCEP) that targets individuals under deferred prosecution and probation. The Narcotics Control Act mandates these community-based NCEPs to serve drug addicts 25 , 26 . Figure 1 illustrates South Korea’s NCEP procedures, including DP and probation with educational programmes (Fig. 1 ) 23 . The NCEP is a programme that takes place within three months of arrest and is intended to provide motivation for subsequent SUD treatment 27 . The provision of various community-based NCEPs has been significantly associated with positive physical and mental health outcomes in drug abusers 28 . NCEPs aim to ease the load on the criminal justice system and boost community engagement for effective societal reintegration, benefiting both society and individual health 29 , 30 . Globally, the escalating supply and use of methamphetamine, a stimulant, has heightened dependency and presents a critical public health challenge 31 . While pharmacological treatments for methamphetamine addiction lack efficacy 32 , the NCEP could serve as a crucial alternative treatment, underscoring the urgent need to verify its effectiveness in addressing these cases. In South Korea, approximately 70% of drug addicts use stimulants, mainly methamphetamine 23 , 33 . In addition, the NCEP is important because it could serve as a contingency when there is a shortage of psychiatrists available for treating drug addiction, as in the United States and South Korea 34 – 36 . Despite these challenges, there is a paucity of research on the outcomes of the NCEP. Analysing the outcomes and success factors of recent NCEP participants is crucial for understanding its impact. Therefore, we aimed to examine the positive changes in NCEP participants, identify factors that increase SUD treatment intentions, and suggest avenues for improvement. In addition, we examined factors that increase the effectiveness of the NECP through logistic regression analysis. Methods Programme Overview Study participants were individuals referred by the Incheon City Prosecutor’s Office to educational programmes provided by the Korea Association against Drug Abuse (KAADA) 27 between January 2022 and December 2023. We included participants who satisfied the following criteria: 1) aged 18 years or older; 2) a drug offender who had purchased, possessed, or administered drugs; 3) individuals with SUD susceptible to relapse necessitating continuous counselling or intervention for treatment and rehabilitation; and 4) those who had completed the NCEP. The operators and instructors who provided the NCEP received formal training as rehabilitation professionals. These professionals include recovering drug addicts, pharmacists, psychiatrists, social workers, and mental health counsellors who provide standardised education and counselling 27 . The DP programme consisted of 28 hours of face-to-face education. The pre-questionnaires were administered during the first period on the first day of education, and the post-questionnaires after class on the last day. The survey was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Catholic University of Korea (IRB No. 1040395-202312-901). All participants provided written informed consent before participating in the study. The consent form outlined the study’s purpose, procedures, potential risks, and benefits. Participants were informed that their participation was voluntary and that they could withdraw from the study at any time without any consequences. Incheon KAADA anonymized and de-identified all personal information before it was provided to the researchers, ensuring the confidentiality of personal data. Content of programme questionnaires We divided the programme questionnaires into two categories: the first section surveyed the characteristics of the participants before the programme, and the second section surveyed pre- and post-programme questionnaires to assess the programme outcomes. In the first part, the following information was gathered: 1) Age group: under 30; 30–39; 40 and older; 2) sex; 3) duration of drug use (less than 2 years; more than 2 years); 4) educational status (completed compulsory education, not completed); 5) annual income (less than $ 23,230; $ 23,230 or more) 37 ; 6) Previous treatment experience (treatment-naïve; treatment-experienced); 7) main type of drug used (stimulants, mainly methamphetamine, cannabis, and others, including opioids); 8) employment status (unemployed; employed) 9) marital status (unmarried; married) 10) social/family support as measured by the Medical Outcomes Study Social Support Survey (MOS-SSS; 0 − 25 points: 0 to 19, poor; 20 or more, good) 38 ; 11) mental health (0–18 points: good, 4 or less; poor, more than 4) 39 ; 12) depression measured by Patient Health Questionnaire (PHQ)-9 (0–27 points: not depressed, 4 or less; depressed, 5 or more) 40 ; 13) Meaning of Life Questionnaire (MLQ; 0 − 70 points: poor, 46 or less; good, 47 or more) 41 ; 14) Drug Abuse Screening Test-10 (DAST-10; 0 − 10 points: no addiction, 1 or less; addiction, 2 or more) 42 . The second set of questionnaires for examining educational outcomes included 1) Knowledge of Drug Addiction Scale (0–10 points: higher scores indicate better knowledge of drug addiction) 39 ; 2) Hanil Drug Insight Scale (HDIS) (− 20 to 20 points: higher scores corresponds to greater insight) 43 ; 3) recognise the significance of drug cessation (0–9 points; higher scores indicate greater recognition of the importance of quitting); 4) confidence of discontinuing drugs (0–9 points: higher scores indicate greater confidence in the ability to cease using drugs); and 5) four questions about rehabilitation plans (Q1. I intend to continue receiving treatment for SUD at the hospital; Q2. I intend to participate in a narcotic-anonymous (NA) group 44 ; Q3. I intend to use the KAADA Rehabilitation Center; Q4. If I relapse with narcotics, I will voluntarily seek counselling and treatment at a specialised facility, such as a hospital or KAADA rehabilitation centre) These questionnaires evaluated changes in the participants’ knowledge, attitudes, and intentions concerning drug rehabilitation following the educational programme. We defined NCEP as effective if there was a desire for follow-up after SUB treatment 28 . The effectiveness of the NCEP depends on positive responses to subsequent SUD treatment intentions 19 – 21 . We thus asked the participants about their follow-up SUD treatment intentions, either positive or negative, after completing the NCEPs. Statistical analysis We analysed the data collected from the respondents using descriptive statistics. Categorical variables are presented as frequencies and percentages, while continuous variables are summarised as mean and standard deviation (SD). Chi-squared tests were used to examine the differences in the participants’ pre-survey characteristics between the DP and probation education programmes. We also compared items from the pre- and post-education questionnaires to examine the programme outcomes. For continuous variables, we used paired t -tests for normally distributed data, and paired Wilcoxon signed-rank tests for data that did not meet the normality assumption. McNemar’s test was used to analyse the binary responses (positive or negative) to the four questions on the rehabilitation plans. Statistical significance was set at p < 0.05. significant. We evaluated the effectiveness of the NCEP using a logistic regression model that included all factor variables from the first part of the pre-questionnaires. In our logistic regression analysis, variables were selected based on a cut-off criterion (0.5) derived from the Wald test results, and collinearity diagnostics were examined to exclude correlated variables 45 , 46 . To comprehensively understand the individual effects of the covariates and their overall interactions, we conducted sequential univariate and multivariate logistic regression analyses, and calculated the odds ratios (ORs) and 95% confidence intervals (CIs) for the covariates selected to assess the effectiveness of the NCEP. In the multivariate logistic regression, we handled missing data using multiple imputation (MI) through chained equations to predict missing values, including the duration of drug use, main type of drug used, income, and age group 47 . In addition, to enhance the robustness of our estimates, we conducted nonparametric bootstrapping resampling with the replacement of an entire observation 48 . Subgroup logistic regression analysis was also conducted to examine the covariates affecting the effectiveness of the NCEP by drug type and sex. All data were analysed using SAS 9.0 statistical software and SPSS 28 statistical software. Results Programme Participant Characteristics A total of 337 participants were enrolled in the DP education programme and 401 were enrolled in the probation education programme. Of these, 301 and 308 participants completed the programmes, and 233 and 307 completed the questionnaires, respectively. A final sample of 203 and 254 participants in DP and probation, respectively, were matched on the pre- and post-questionnaires (Fig. 2 ). Table 1 summarises the general characteristics of the survey respondents among the NCEP participants. As stated, there were 203 participants in the DP group (44.4%), and 254 in the probation group (55.6%). The majority were male ( n = 313, 68.5%), had completed compulsory education ( n = 384, 84.8%), were employed ( n = 349, 76.4%), were unmarried ( n = 357, 78.8%), had a good MOS-SSS ( n = 244, 53.5%), and had a similar age distribution ( 40 years, 38.0%). We also examined the characteristics of the participants in the DP and probation education programmes. Differences between the two groups were observed in age ( p = 0.020), previous treatment experience ( p = 0.009), type of drug used ( p < 0.001), and DAST-10 score ( p < 0.001). In terms of age, those under 30 years were DP (37.3%) but on probation (29.8%), whereas those over 40 years were DP (30.8%) but on probation (43.7%). DP had more treatment-naïve participants than did probation (80.4% in DP; 69.6% in probation). Regarding the type of drug used, stimulants were more commonly used in the probation group (58.8%) than DP (39.9%), whereas cannabis was more commonly used in DP (30.8%) than probation (24.5%). Finally, the number of participants who tested positive on the DAST-10 was higher in the probation group (85.0%) than in the DP group (71.4%). Although not statistically significant, the proportion of female participants in the DP education programme, 72 (35.5%), was higher than in the probation education programme, 72 (28.3%). Table 1 General characteristics of participants in a non-custodial education program for drug offenders Characteristics N (%) Deferred Prosecution (N = 203) Probation (N = 254) P- Value Sex, N (%) Male 313(68.5) 131 (64.5) 182 (71.7) 0.103 Female 144(31.5) 72 (35.5) 72 (28.3) Age, N (%) < 30 years 150(33.1) 75 (37.3) 75(29.8) 0.020 30–39 years 131(28.9) 64 (31.8) 67 (26.6) ≥ 40 years 172(38.0) 62 (30.8) 110 (43.7) Duration of drug use, N (%) <2 years 271(63.5) 123(65.8) 148(61.7) 0.382 ≥ 2 years 156(36.5) 64(34.2) 92(38.3) Education, N (%) Incomplete compulsory education 69(15.2) 31 (15.4) 38 (15.1) 0.735 Complete compulsory education 384(84.8) 170(84.6) 214 (84.9) Annual income, N (%) < $ 23,230 219(51.8) 91(48.9) 128 (54.0) 0.299 ≥ $ 23,230 204(48.2) 95(51.1) 109 (46.0) Previous treatment experience, N (%) Treatment-naive 334(74.4) 160 (80.4) 174 (69.6) 0.009 Treatment-experienced 115(25.60 39 (19.6) 76 (30.4) Type of the used drug, N (%) Stimulants 201(51.8) 57 (39.9) 144 (58.8) < 0.001 Cannabis 104(26.8) 44 (30.8) 60 (24.5) Others 83(21.4) 42 (29.4) 41 (16.7) Employment, N (%) Unemployed 98(21.4) 45(22.4) 53(21.5) 0.830 Employed 349(76.4) 156(77.6) 193(78.5) Marital status, N (%) Unmarried 357(78.8) 160(79.6) 197(78.2) 0.712 Married 96(21.2) 41(20.4) 55(21.8) Social support measured by MOS-SSS, N (%) Poor (0–19 score) 212(46.5) 91(45.0) 121(47.6) 0.582 Good ( ≥ 20 score) 244(53.5) 111(55.0) 133(52.4) Mental health, N (%) Good (0–4 score) 238(52.5) 110(55.0) 128(50.6) 0.351 Poor ( ≥ 5 scores) 215(47.5) 90(45.0) 125(49.4) Depression measured by PHQ-9, N (%) No (0 ~ 4 score) 272(59.8) 119(59.2) 153(60.2) 0.824 Yes ( ≥ 5 scores) 183(40.2) 82(40.8) 101(39.8) MLQ, N (%) Bad (0–46 score) 184(40.8) 85(42.5) 99(39.4) 0.512 Good ( ≥ 47 score) 267(59.2) 115(57.5) 152(60.6) Drug Abuse Screening Test-10, N (%) Negative (0–1 score) 96(21.0) 58(28.6) 38(15.0) < 0.001 Positive ( ≥ 2 score) 361(79.0) 145(71.4) 216(85.0) MOS-SSS; Medical outcomes study social support survey, PHQ, Patient Health Questionnaire; MLQ, Meaning in Life Questionnaire; Analysis is chi-square test. Pre- and Post-Education Outcome Analysis Table 2 shows the pre- and post-education scales for NCEP participants. For DP participants, there were significant increases in the scores on the Knowledge of Drug Addiction Scale (from 5.21 to 7.61, p < 0.001), HDIS (from 1.00 to 3.53, p < 0.001), and Recognise the Significance of Drug Cessation (from 7.56 to 8.01, p = 0.018). In contrast, while probationers showed significant increases on the Knowledge of Drug Addiction Scale (from 5.11 to 7.04, p < 0.001) and the HDIS (from 2.51 to 5.24, p < 0.001), Recognise the Significance of Drug Cessation ( p = 0.180) did not show a statistically significant increase. Neither DP ( p = 0.447) nor probation ( p = 0.280) resulted in a statistically significant increase in confidence in discontinuing drugs. Table 2 A comparison of outcomes before and after education programs Characteristics Pre-education Post-education P -value Deferred prosecution education program Knowledge of drug addiction 5.21 ± 2.71 7.61 ± 2.13 < 0.001 Hanil Drug Insight Scale 1.00 ± 7.53 3.53 ± 7.80 < 0.001 Recognize the significance of drug cessation 7.56 ± 2.59 8.01 ± 2.13 0.018 The confidence of discontinuing drugs 8.27 ± 1.62 8.15 ± 1.70 0.447 Probation education program Knowledge of drug addiction 5.04 ± 2.73 7.04 ± 2.37 < 0.001 Hanil Drug Insight Scale 2.51 ± 7.71 5.24 ± 8.64 < 0.001 Recognize the significance of drug cessation 7.96 ± 2.29 8.14 ± 1.87 0.180 The confidence of discontinuing drugs 8.04 ± 1.86 8.16 ± 1.52 0.280 We performed a paired t-test to analyze outcomes before and after education programs for variables with a normal distribution only in the confidence of discontinuing drugs, and a Wilcoxon signed-rank for the other three variables. Data are expressed as mean ± standard deviation for variables. Figure 3 shows the results of McNemar’s test for the four questions about plans for addiction rehabilitation before and after the education programme. In the DP education programme, there was a significant increase in positive responses to Q2 about joining an NA group (from 30 [15.1%] to 47 [23.6%], p = 0.002) and Q3 about using the KAADA rehabilitation centre (from 49 [24.7%] to 67 [33.5%], p = 0.009). Similarly, in the probationary education programme, there was a significant increase in positive responses to Q2 about joining an NA group (from 44 [17.6%] to 74 [29.6%], p < 0.001) and Q3 about using KAADA (from 79 [31.7%] to 96 [38.2%], p = 0.041). However, positive responses regarding hospital treatment (Q1) and recurrence (Q4) increased slightly but were not statistically significant in the DP and probation groups. Univariate and Multivariate Logistic Regression Analysis Employment status, marital status, social support, and education were excluded. The variable ‘DAST-10’ was excluded due to collinearity. We conducted a logistic analysis of the factors that increased NCEP effectiveness (Table 3 ). In the univariate logistic regression analysis, the following covariates showed significant results: Compared to those under 30 years of age, participants aged 30–39 years (OR 1.95, 95% CI 1.11–3.45) and those over 40 years (OR 2.53, 95% CI 1.46–4.39) showed higher odds. Duration of drug use exceeding 2 years (OR 2.62, 95% CI 1.49–4.59) and being treatment-experienced (OR 4.86, 95% CI 2.28–10.39) were associated with higher odds. Regarding drug type, compared to stimulants, cannabis users (OR 0.37, 95% CI 0.20–0.67) and users of other drugs (OR 0.47, 95% CI 0.24–0.92) showed lower odds. Additionally, poor mental health (OR 2.98, 95% CI 1.81–4.90) and positive for depression (OR 2.41, 95% CI 1.45–4.00) were significant covariates. In contrast, DP did not show significant differences compared with probation ( p = 0.712), and good MLQ ( p = 0.310) did not show significant differences. Table 3 The success of educational programs using univariate and multivariate logistic regression analysis Variables Univariate model Multivariate model OR (95% CI) OR (95% CI) Type of Education Program Probation [Reference] [Reference] Deferred Prosecution 1.09 (0.69–1.72) 2.45 (1.25–4.82) Sex Female [Reference] [Reference] Male 1.38 (0.86–2.22) 1.89 (0.88–4.08) Age < 30 years [Reference] [Reference] 30–39 years 1.95 (1.11–3.45) 3.00 (1.23–7.31) ≥ 40 years 2.53 (1.46–4.39) 1.84 (0.84–4.01) Duration of drug use <2 years [Reference] [Reference] ≥ 2 years 2.62 (1.49–4.59) 1.77 (0.89–3.55) Annual income < $ 23,230 [Reference] [Reference] ≥ $ 23230 1.10 (0.69–1.76) 1.07 (0.54–2.13) Previous treatment experience Treatment-naive [Reference] [Reference] Treatment-experienced 4.86 (2.28–10.39) 3.73 (1.30-10.71) Type of the used drug Stimulants [Reference] [Reference] Cannabis 0.37 (0.20–0.67) 0.36 (0.17–0.75) Others 0.47 (0.24–0.92) 0.62 (0.26–1.48) Mental health Good (0–4 score) [Reference] [Reference] Poor ( ≥ 5 scores) 2.98 (1.81–4.90) 2.45 (1.01–5.95) Depression measured by PHQ-9 No (0–4 score) [Reference] [Reference] Yes ( ≥ 5 scores) 2.41 (1.45-4.00) 1.92 (0.76–4.85) MLQ Bad (0–46 score) [Reference] [Reference] Good ( ≥ 47 score) 1.27 (0.80–2.01) 2.90 (1.50–5.63) OR, odds ratio; CI, confidence interval; PHQ, Patient Health Questionnaire; MLQ, Meaning in Life Questionaeire In multivariate logistic regression analysis, significant results were found for participation in DP compared to probation (OR 2.45, 95% CI 1.25–4.82, p = 0.01) and for having good MLQ (OR 2.90, 95% CI 1.50–5.63, p = 0.002). Participants aged 30–39 years showed a significant increase in odds compared to those under 30 years of age (OR 3.00, 95% CI 1.23–7.31, p = 0.05). However, age > 40 years ( p = 0.847), positive depression status ( p = 0.166), and drug type compared with stimulants (other drugs; p = 0.938) were not significant despite being significant in the univariate analysis. In both univariate and multivariate analyses, the following covariates remained significant: being treatment-experienced (OR 3.73, 95% CI 1.30–10.71, p = 0.015), using cannabis compared to stimulants (OR 0.36, 95% CI 0.17–0.75, p = 0.022), being aged 30–39 years compared to those under 30 years (OR 3.00, 95% CI 1.23–7.31, p = 0.05), and having poor mental health (OR 2.45, 95% CI 1.01–5.95, p = 0.047). However, age > 40 years (compared to age < 30 years, p = 0.847), positive depression status (compared to no depression status, p = 0.166), and drug type with others (compared to stimulants, p = 0.938) were not significant, despite being significant in the univariate analysis. Sensitivity analyses We performed a sensitivity analysis to confirm the robustness of the multivariate logistic analyses. The results of the base-case multivariate logistic analysis were compared with those of the MI and bootstrap analyses, as shown in Fig. 4 . Three covariates—previous treatment experience, mental health, and MLQ—were significant in all the cases. The results for MI cases showed statistically significant results for the following covariates: treatment-experienced (OR 1.93, 95% CI 1.26–2.95, p = 0.002), poor mental health (OR 1.59, 95% CI 1.12–2.28, p = 0.010), good MLQ (OR 1.43, 95% CI 1.09–1.88, p = 0.010), and male gender (OR 1.47, 95% CI 1.06–2.04, p = 0.021). Bootstrap case analysis was performed 5, 25, 100, 500, and 5000 times to observe changes in the regression results across iterations (Supplementary Table 1). Bootstrapped analysis showed consistent and valid results for all variables except annual income and the type of drug as ‘Others’. Subgroup analysis We conducted a subgroup multivariate logistic regression analysis for the covariates related to the type of drug used, as shown in Supplementary Table 2. Multivariate logistic analyses were performed to determine the increase in the NCEP effectiveness in the stimulant and cannabis groups. The good MLQ covariate showed significant results for stimulants (OR 7.78, 95% CI 2.36–25.65, p = 0.001) and cannabis (OR 5.42, 95% CI 1.44–20.40, p = 0.012). The stimulant group showed higher educational effectiveness for participants aged 30–39 years than for those under 30 years (OR 7.50, 95% CI 1.17–48.20, p = 0.039). Meanwhile, the cannabis group showed a higher educational effectiveness for drug use duration of more than two years (OR 6.03, CI 1.46–24.86, p = 0.013) and was positive for depression (OR 16.02, CI 2.06–124.9, p = 0.008). Although not statistically significant, the duration of drug use over two years showed a negative trend in the stimulant group, with an OR of 0.78, whereas the opposite trend was observed for cannabis, with an OR of 6.03. In addition, mental health showed a positive trend in the stimulant group, with an OR of 3.34, whereas the opposite trend was observed for cannabis, with an OR of 0.79. Further subgroup multivariate logistic regression analyses were performed on covariates associated with sex (Supplementary Table 3). The results showed that there were no universally effective covariates for men or women. For males, the covariates DP compared to probation (OR 2.56, 95% CI 1.10–5.97, p = 0.03), aged 30–39 years compared to those under 30 years (OR 3.77, 95% CI 1.22–11.62, p = 0.027), treatment-experienced (OR 6.60, 95% CI 1.36–32.12, p = 0.019), drug type compared to stimulants (cannabis, OR 0.36, 95% CI 0.15–0.83, p = 0.093), and good MLQ (OR 3.12, 95% CI 1.41–6.87, p = 0.005) were effective. In contrast, for women, only poor mental health (OR 6.88, 95% CI 1.61–29.41, p = 0.009) was an effective covariate. Although not statistically significant, annual income showed a negative trend in the stimulant group, with an OR of 0.78, whereas the opposite trend was observed for cannabis, with an OR of 6.03. Discussion The increasing number of drug offenders in South Korea highlights the need for NCEPs to address drug addiction. This study examined the outcomes of the DP and probation education programmes implemented in South Korea during 2022–2023. The results showed that the NCEPs significantly increased knowledge of drug addiction, HDIS scores, and positive rehabilitation plans for drug abusers. This suggests that short-term NCEP can be effectively extended to community-based SUD treatments, which is beneficial for long-term rehabilitation 28 , 49 . We also found that treatment experience, poor mental health, and a positive MLQ score were associated with a greater effectiveness of the NCEP. Comparing these results with those of earlier studies, we can consider the following points for future implementation. First, linking NCEP participants to hospital SUD treatment is crucial, as treatment experience improves intentions. Second, the finding that poor mental health improves effectiveness is encouraging, as it underscores the need for continued therapeutic interventions to maintain these improvements post-NCEP 20 , 50 . This highlights the positive results of the NCEP as an alternative to incarceration 50 , 51 . Third, positive MLQ reinforcement aligns with previous research and, in a sub-analysis by drug type, was a success factor for both stimulants and cannabis. Therefore, it is recommended that well-being and health-related education associated with the positive reinforcement of the MLQ be improved 41 . In contrast to prior studies linking positive effectiveness with employment, marriage, and new family members, our study found no significant impact of these variables 12 , 19 , 28 , 52 – 54 . Income variables had a greater impact on programme effectiveness than employment status. Our study found no significant differences in the NCEP effects based on marital status or the social/family support index (MOS-SSS). The marriage rate among the participants was 21.2 percent, significantly lower than the 2020 adult average of 44.1 percent reported by Statistics Korea 55 . With Korea’s fertility rate projected to be the lowest at 0.78 in 2022 67 and the unmarried fertility rate remaining around 2% (compared to the OECD average of 40%), the participants’ fertility rate is also expected to be significantly low 55 , 56 . Therefore, in many countries where birth rates are decreasing and non-marital relationships are increasing 57 , approaches to addressing the issue of drug addiction should evolve from previous methods. This implies that, in some cases, family therapy interventions should be restricted, especially for individuals who are unmarried or lack significant social support, and should instead focus on individual counselling, welfare, and health education 16 . In addition, the drug classification used in this study was pharmacotherapeutic 53 , 58 , which is slightly different from the legal classification 25 . For example, the ‘other’ category includes sedatives and propofol in addition to opioids. As in previous research, probationers were more likely to use stimulants, especially methamphetamine, were older, and scored more positively on the DAST-10 than the DP group 49 , 59 , 60 . They also had higher rates of NA participation and prior treatment experience 49 , 59 . Additionally, our subgroup analysis showed opposite trends in duration of drug use and mental health for the cannabis and stimulant groups, highlighting their different health-related harms 61 . The cannabis group’s positive subsequent SUD treatment intentions with depression constitutes evidence that individuals with depression are more likely to use cannabis 62 , 63 . The effectiveness in men followed a trend similar to those reported in previous studies 52 – 54 . Only poor mental health was a key factor for women, emphasising the importance of mental health services 64 . The global economic burden of illicit drug use, including healthcare, criminal justice costs, and productivity losses, can reach several hundred billion dollars annually 22 . Improving cost-effectiveness is crucial to drug policy 65 , 66 . As sustained investment in NCEPs is essential to mitigate social and economic costs and ensure long-term benefits, this necessitates a cost-per-person study 67 . To prepare for future cost-effectiveness studies of NCEP, we used micro-costing techniques to determine per-participant costs in this study 68 . The budget of Incheon KAADA ( $ 382,194) consisted of national funds (42.9%), Incheon City funds (34.4%), and contributions from the pharmacist organisation (22.7%; Supplement Fig. 1 ). The DP education programme has a cost per participant of $ 307, whereas the probation education programme costs $ 391 (Supplement Table 4). This is cheaper than Seattle’s LEAD programme at $ 899 per person per month. In the United States, costs focus on housing and food, whereas in Korea, only education is emphasised. We examined the positive outcomes and identified the key factors that influenced the effectiveness of NCEP. However, this study had several limitations. Careful consideration must be given to the transferability of the NCEP findings. Japan, Taiwan, and South Korea are high-income countries in which methamphetamine is the prevalent illicit drug 33 , 60 . Although their legal systems are similar 69 , their non-custodial programmes differ. Instead of incarceration, Taiwan has achieved positive results through judicial diversion for Schedule I drug offenses 13 . Japan relies on strict laws and mandatory treatment 12 , while Korea relies on NCEPs. However, this study was conducted on participants from Incheon, a particular region of Korea, and there may be issues of representativeness. Incheon, the third-largest city in South Korea, referred 9% of national drug offenders to the NCEP. The participants did not differ from the national drug offender data in terms of age, sex, or education level 23 . Conclusion The NCEP implemented in South Korea has been shown to improve drug addiction knowledge and HDIS, and positively influences future rehabilitation plans of drug abusers. Factors contributing to the increased effectiveness of the NCEP were treatment experience, poor mental health, and a good MLQ. While the impact of factors such as marriage, childbirth, and employment were lower than reported in other studies, personal well-being and health education emerged as stronger influencers. Our study provides recent evidence of the positive outcomes, effectiveness factors, and costs of the NCEP programme. These findings should be considered for future rehabilitation policies and programme improvements. Declarations Competing interests The authors declare no competing interests. Author Contribution Kyung-ae Nam contributed to the conceptualisation, data collection, methodology, and drafting of the manuscript. In-Sun Oh contributed to the data analysis and critical review. Sun-Kyeong Park contributed to the supervision, conceptualisation, data curation, drafting, review, and editing of the manuscript. Acknowledgement We would like to thank those who participated in the questionnaire, as well as the Supreme Prosecutors’ Office, for their advice. Additionally, we extend our gratitude to the Incheon officials who are working to solve the problem of drug addiction. Data Availability The data that support the findings of this study are available from the Korea Association Against Drug Abuse in Incheon, but restrictions apply to the availability of these data, which were used under license for the current study and are not publicly available. 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Galanter, M., White, W. L. & Hunter, B. Narcotics Anonymous members in recovery from methamphetamine use disorder. Am J Addict 32 , 54-59, doi:10.1111/ajad.13362 (2023). Bursac, Z., Gauss, C. H., Williams, D. K. & Hosmer, D. W. Purposeful selection of variables in logistic regression. Source code for biology and medicine 3 , 1-8 (2008). Midi, H., Sarkar, S. K. & Rana, S. Collinearity diagnostics of binary logistic regression model. Journal of interdisciplinary mathematics 13 , 253-267 (2010). Austin, P. C. & van Buuren, S. The effect of high prevalence of missing data on estimation of the coefficients of a logistic regression model when using multiple imputation. BMC Medical Research Methodology 22 , 196, doi:10.1186/s12874-022-01671-0 (2022). Castelli, J. M. et al. Effectiveness of mRNA-1273, BNT162b2, and BBIBP-CorV vaccines against infection and mortality in children in Argentina, during predominance of delta and omicron covid-19 variants: test negative, case-control study. BMJ 379 , e073070, doi:10.1136/bmj-2022-073070 (2022). Yeong-sil Jeon, Y.-g. K., false. Advancements in drug control strategies: emphasizing the rehabilitation and treatment systems. (2019). Paramjit Singh, J. S., Azlinda, A., Shankar, D., Mohd Syaiful Nizam, A. H. & Farah Wahida, S. Enhancing Drug Users’ Mental Health by Decriminalizing Drug Use: Insights from In-Depth Interviews with Drug Rehabilitation Officers and Relapsed Drug Users. Journal of Korean Academy of psychiatric and Mental Health Nursing 33 , 27-39, doi:10.12934/jkpmhn.2024.33.1.27 (2024). Virtanen, S. et al. Effectiveness of substance use disorder treatment as an alternative to imprisonment. BMC Psychiatry 24 , 260, doi:10.1186/s12888-024-05734-y (2024). Wu, L. J., Altshuler, S. J., Short, R. A. & Roll, J. M. Predicting drug court outcome among amphetamine-using participants. J Subst Abuse Treat 42 , 373-382, doi:10.1016/j.jsat.2011.09.008 (2012). Kim, J., Leban, L. & Lee, Y. Cross-Level Theoretical Predictions of Marijuana, Methamphetamine, and Opium Use. Deviant Behavior 38 , 810-823, doi:10.1080/01639625.2016.1197696 (2016). Kim, C. M. et al. A Study on Relapse Predictors in Korean Alcohol-Dependent Patients-A 24 Weeks Follow up Study. Korean Journal of Biological Psychiatry 14 , 249-255 (2007). StatisticKorea. in Statistic Korea (2020). Seo, S. H. Low fertility trend in the Republic of Korea and the problems of its family and demographic policy implementation. Population and Economics 3 , 29-35, doi:10.3897/popecon.3.e37938 (2019). Lutz, W. Fertility rates and future population trends: will Europe's birth rate recover or continue to decline? International journal of andrology 29 , 25-33 (2006). Kim, J. Evidence-Based Treatments of Drug Addiction. Korean Journal of Clinical Psychology 39 , 186-201, doi:https://doi.org/10.15842/kjcp.2020.39.2.008 (2020). Hazama, K. & Katsuta, S. Factors to Reduce Drug-Related Recidivism Among Paroled Methamphetamine Users in Japan: 10-Year Data Analysis. Int J Offender Ther Comp Criminol , 306624x231172651, doi:10.1177/0306624x231172651 (2023). Kwon, N. J. & Han, E. A commentary on the effects of methamphetamine and the status of methamphetamine abuse among youths in South Korea, Japan, and China. Forensic Sci Int 286 , 81-85, doi:10.1016/j.forsciint.2018.02.022 (2018). Degenhardt, L. & Hall, W. Extent of illicit drug use and dependence, and their contribution to the global burden of disease. The Lancet 379 , 55-70 (2012). Gorfinkel, L. R., Stohl, M. & Hasin, D. Association of Depression With Past-Month Cannabis Use Among US Adults Aged 20 to 59 Years, 2005 to 2016. JAMA Netw Open 3 , e2013802, doi:10.1001/jamanetworkopen.2020.13802 (2020). Moore, T. H. et al. Cannabis use and risk of psychotic or affective mental health outcomes: a systematic review. The Lancet 370 , 319-328 (2007). Grella, C. E. & Joshi, V. Gender differences in drug treatment careers among clients in the national Drug Abuse Treatment Outcome Study. Am J Drug Alcohol Abuse 25 , 385-406, doi:10.1081/ada-100101868 (1999). Cartwright, W. S. & Solano, P. L. The economics of public health: financing drug abuse treatment services. Health Policy 66 , 247-260, doi:10.1016/s0168-8510(03)00066-6 (2003). Cartwright, W. S. Economic costs of drug abuse: financial, cost of illness, and services. J Subst Abuse Treat 34 , 224-233, doi:10.1016/j.jsat.2007.04.003 (2008). Anglin, M. D., Nosyk, B., Jaffe, A., Urada, D. & Evans, E. Offender diversion Into substance use disorder treatment: the economic impact of California’s Proposition 36. American journal of public health 103 , 1096-1102 (2013). Frick, K. D. Microcosting quantity data collection methods. Med Care 47 , S76-81, doi:10.1097/MLR.0b013e31819bc064 (2009). Feng, L. Y., Wada, K., Chung, H., Han, E. & Li, J. H. Comparison of legislative management for new psychoactive substances control among Taiwan, South Korea, and Japan. Kaohsiung J Med Sci 36 , 135-142, doi:10.1002/kjm2.12140 (2020). Additional Declarations No competing interests reported. Supplementary Files Supplement.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4748630","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":341349670,"identity":"b0de265d-a92a-4d8d-aa5e-6b28c2e1e1ee","order_by":0,"name":"Kyung-ae Nam","email":"","orcid":"","institution":"The Catholic University of Korea","correspondingAuthor":false,"prefix":"","firstName":"Kyung-ae","middleName":"","lastName":"Nam","suffix":""},{"id":341349671,"identity":"caed1b9f-7973-4735-8983-196785c72d6c","order_by":1,"name":"In-Sun Oh","email":"","orcid":"","institution":"Lady Davis Institute, Jewish General Hospital","correspondingAuthor":false,"prefix":"","firstName":"In-Sun","middleName":"","lastName":"Oh","suffix":""},{"id":341349672,"identity":"8526e559-6865-4157-bafe-375bf39fec97","order_by":2,"name":"Sun-Kyeong Park","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYDACHjCZIAck2BgYCiTAXMYGIrQYMzAwA7UYkKAlsQGihYGwFvmeA2wPfu5JS+9vP3/swQcDC3kG9sMPGGfuwa3F4GwDu2HPs5zcGWeS2Q1nGEgYNvCkGTBueIZHCz8DmwTPgYrcDQzJbNI8BhIJDAw5DIwPDuBxWD8Dm+SfAxXpBvyPoVr43+DXwnC2AajyQE6CgQTMFgmgLRvwaDE4c7DdWOZAmuGMG4/NJEF+aZN4ZnBwBj6H9SQfe/jmQLI8f3/iM4kPFXXy/PzJDx/24HMYA2MbKh8YOwx4NUDVjIJRMApGwSjAAwBu6ElacYfVaQAAAABJRU5ErkJggg==","orcid":"","institution":"The Catholic University of Korea","correspondingAuthor":true,"prefix":"","firstName":"Sun-Kyeong","middleName":"","lastName":"Park","suffix":""}],"badges":[],"createdAt":"2024-07-16 09:33:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4748630/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4748630/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63289157,"identity":"51f82712-e2eb-4060-bcc2-fa6747b715a6","added_by":"auto","created_at":"2024-08-26 14:02:37","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49654,"visible":true,"origin":"","legend":"\u003cp\u003eDeferred prosecution and probation education program referral process\u003c/p\u003e\n\u003cp\u003e(Reorganization of the 2022 Supreme Prosecutors' Office drug crime report retrieved from https://www.spo.go.kr/site/spo/ex/board/View.do)\u003c/p\u003e\n\u003cp\u003e(The dotted line is for cases requested by the Ministry of Justice)\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4748630/v1/1444f9626b6a71cc2ce82f0e.jpg"},{"id":63290213,"identity":"e21373e8-2a19-415c-bd56-a1281c3acb33","added_by":"auto","created_at":"2024-08-26 14:10:37","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50775,"visible":true,"origin":"","legend":"\u003cp\u003eDeferred prosecution and probation education survey research participant selection process\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4748630/v1/633b6f8b845cfe8291cb5ff5.jpg"},{"id":63289158,"identity":"d102d889-1c78-4084-af9a-2ad0841b6bbe","added_by":"auto","created_at":"2024-08-26 14:02:37","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":67855,"visible":true,"origin":"","legend":"\u003cp\u003epre-and post-education outcomes of participants in the deferred prosecution and probation education program\u003c/p\u003e\n\u003cp\u003e* McNemar test. p\u0026lt;0.05 is considered statistically significant.\u003c/p\u003e\n\u003cp\u003eQ1. I intend to continue receiving treatment for substance use disorder at the hospital.\u003c/p\u003e\n\u003cp\u003eQ2. I intend to participate in narcotics anonymous group\u003c/p\u003e\n\u003cp\u003eQ3. I intend to utilize the Korea Association Against Drug Abuse rehabilitation center.\u003c/p\u003e\n\u003cp\u003eQ4. If I relapse with narcotics, I will voluntarily seek counseling and treatment at a specialized facility, such as a hospital or the Korea Association Against Drug Abuse rehabilitation center.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4748630/v1/f86c6f093ef4d5abf5ccda9a.jpg"},{"id":63289161,"identity":"4ee4e9ed-7d01-432d-926e-df445227d4f2","added_by":"auto","created_at":"2024-08-26 14:02:37","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":58815,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLogistic analysis of factors affecting positive educational effectiveness.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4748630/v1/748c052f2539a1b16670fda2.jpg"},{"id":78719990,"identity":"ff5b7a7a-5502-4ae2-956a-704f7c84ca57","added_by":"auto","created_at":"2025-03-18 04:16:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1385256,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4748630/v1/771c831a-2033-43b0-aff6-2502ab87823a.pdf"},{"id":63289160,"identity":"3e641c14-6f84-4181-8c85-9019ae31c6ad","added_by":"auto","created_at":"2024-08-26 14:02:37","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":173881,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-4748630/v1/18ee5cdbbace0171251c1f6d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of the Outcomes and Influencing Factors of Non-Custodial Educational Programmes for Drug Abusers","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe war on drugs in the United States between 1986 and 1994 led to widespread incarceration of both drug abusers and traffickers\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. This surge in incarceration has overwhelmed the criminal justice system, with the number of individuals charged with drug offences in federal courts increasing by 147% from 11,854 in 1984 to 29,306 in 1999\u003csup\u003e2\u003c/sup\u003e. Consequently, the stigma faced by low-level drug offenders has driven a rise in poverty and worsened both racial and gender discrimination\u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Moreover, high rates of incarceration have intensified public health issues such as AIDS and hepatitis\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In response, various non-custodial programmes have been developed and increasingly adopted as alternative strategies to address drug addiction\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, showing promise in improving recidivism rates, reducing substance use, and enhancing psychosocial outcomes\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNon-custodial programmes have diverse structures and applications in various countries. Australia, the United States, the United Kingdom, Taiwan, and Japan have implemented such approaches as diversion programmes, deferred prosecution (DP), and probation for drug offenders\u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. These initiatives effectively prevent criminal offenses\u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, enhance the health of drug users\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, and lower social costs\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Specifically, non-custodial programmes for individuals with substance use disorders (SUDs) employ a variety of measures, including inpatient and outpatient treatment, opioid substitution therapy (OST)\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, counseling\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, and educational interventions\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. For example, hospital treatment effectively reduces recidivism and drug use,\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e while providing OST upon release from prison reduces mortality and is cost-effective\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Mandatory hospital treatment in particular has been shown to improve stabilisation in patients with amphetamine-type stimulant use disorder\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. The positive outcomes of non-custodial programmes have been demonstrated to reduce recidivism and maintain sustained abstinence by enhancing the motivation for subsequent SUD treatment\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. These non-custodial programmes can be implemented individually or in combination and often include additional educational support for drug addicts\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn South Korea, drug-related crimes surged by 99.4% from 2012 (9,225 cases) to 2022 (18,395 cases), which is 4.3 times the growth rate of the global average\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. In response, the Korean government declared a war on drugs in 2023, adopting a non-custodial approach for drug abusers while imposing severe penalties on traffickers\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. South Korea has a Non-Custodial Education Programme (NCEP) that targets individuals under deferred prosecution and probation. The Narcotics Control Act mandates these community-based NCEPs to serve drug addicts\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates South Korea\u0026rsquo;s NCEP procedures, including DP and probation with educational programmes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The NCEP is a programme that takes place within three months of arrest and is intended to provide motivation for subsequent SUD treatment\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. The provision of various community-based NCEPs has been significantly associated with positive physical and mental health outcomes in drug abusers\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. NCEPs aim to ease the load on the criminal justice system and boost community engagement for effective societal reintegration, benefiting both society and individual health\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGlobally, the escalating supply and use of methamphetamine, a stimulant, has heightened dependency and presents a critical public health challenge\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. While pharmacological treatments for methamphetamine addiction lack efficacy\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, the NCEP could serve as a crucial alternative treatment, underscoring the urgent need to verify its effectiveness in addressing these cases. In South Korea, approximately 70% of drug addicts use stimulants, mainly methamphetamine\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. In addition, the NCEP is important because it could serve as a contingency when there is a shortage of psychiatrists available for treating drug addiction, as in the United States and South Korea\u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Despite these challenges, there is a paucity of research on the outcomes of the NCEP. Analysing the outcomes and success factors of recent NCEP participants is crucial for understanding its impact. Therefore, we aimed to examine the positive changes in NCEP participants, identify factors that increase SUD treatment intentions, and suggest avenues for improvement. In addition, we examined factors that increase the effectiveness of the NECP through logistic regression analysis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eProgramme Overview\u003c/h2\u003e \u003cp\u003eStudy participants were individuals referred by the Incheon City Prosecutor\u0026rsquo;s Office to educational programmes provided by the Korea Association against Drug Abuse (KAADA)\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e between January 2022 and December 2023. We included participants who satisfied the following criteria: 1) aged 18 years or older; 2) a drug offender who had purchased, possessed, or administered drugs; 3) individuals with SUD susceptible to relapse necessitating continuous counselling or intervention for treatment and rehabilitation; and 4) those who had completed the NCEP.\u003c/p\u003e \u003cp\u003eThe operators and instructors who provided the NCEP received formal training as rehabilitation professionals. These professionals include recovering drug addicts, pharmacists, psychiatrists, social workers, and mental health counsellors who provide standardised education and counselling\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. The DP programme consisted of 28 hours of face-to-face education. The pre-questionnaires were administered during the first period on the first day of education, and the post-questionnaires after class on the last day. The survey was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Catholic University of Korea (IRB No. 1040395-202312-901). All participants provided written informed consent before participating in the study. The consent form outlined the study\u0026rsquo;s purpose, procedures, potential risks, and benefits. Participants were informed that their participation was voluntary and that they could withdraw from the study at any time without any consequences. Incheon KAADA anonymized and de-identified all personal information before it was provided to the researchers, ensuring the confidentiality of personal data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eContent of programme questionnaires\u003c/h2\u003e \u003cp\u003eWe divided the programme questionnaires into two categories: the first section surveyed the characteristics of the participants before the programme, and the second section surveyed pre- and post-programme questionnaires to assess the programme outcomes. In the first part, the following information was gathered: 1) Age group: under 30; 30\u0026ndash;39; 40 and older; 2) sex; 3) duration of drug use (less than 2 years; more than 2 years); 4) educational status (completed compulsory education, not completed); 5) annual income (less than \u003cspan\u003e$\u003c/span\u003e23,230; \u003cspan\u003e$\u003c/span\u003e23,230 or more)\u003csup\u003e \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e \u003c/sup\u003e; 6) Previous treatment experience (treatment-na\u0026iuml;ve; treatment-experienced); 7) main type of drug used (stimulants, mainly methamphetamine, cannabis, and others, including opioids); 8) employment status (unemployed; employed) 9) marital status (unmarried; married) 10) social/family support as measured by the Medical Outcomes Study Social Support Survey (MOS-SSS; 0 \u0026minus;\u0026thinsp;25 points: 0 to 19, poor; 20 or more, good)\u003csup\u003e \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e \u003c/sup\u003e; 11) mental health (0\u0026ndash;18 points: good, 4 or less; poor, more than 4)\u003csup\u003e \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e \u003c/sup\u003e; 12) depression measured by Patient Health Questionnaire (PHQ)-9 (0\u0026ndash;27 points: not depressed, 4 or less; depressed, 5 or more)\u003csup\u003e \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e \u003c/sup\u003e; 13) Meaning of Life Questionnaire (MLQ; 0 \u0026minus;\u0026thinsp;70 points: poor, 46 or less; good, 47 or more)\u003csup\u003e \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e \u003c/sup\u003e; 14) Drug Abuse Screening Test-10 (DAST-10; 0 \u0026minus;\u0026thinsp;10 points: no addiction, 1 or less; addiction, 2 or more)\u003csup\u003e \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e \u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe second set of questionnaires for examining educational outcomes included 1) Knowledge of Drug Addiction Scale (0\u0026ndash;10 points: higher scores indicate better knowledge of drug addiction)\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e; 2) Hanil Drug Insight Scale (HDIS) (\u0026minus;\u0026thinsp;20 to 20 points: higher scores corresponds to greater insight)\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e; 3) recognise the significance of drug cessation (0\u0026ndash;9 points; higher scores indicate greater recognition of the importance of quitting); 4) confidence of discontinuing drugs (0\u0026ndash;9 points: higher scores indicate greater confidence in the ability to cease using drugs); and 5) four questions about rehabilitation plans (Q1. I intend to continue receiving treatment for SUD at the hospital; Q2. I intend to participate in a narcotic-anonymous (NA) group\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e; Q3. I intend to use the KAADA Rehabilitation Center; Q4. If I relapse with narcotics, I will voluntarily seek counselling and treatment at a specialised facility, such as a hospital or KAADA rehabilitation centre) These questionnaires evaluated changes in the participants\u0026rsquo; knowledge, attitudes, and intentions concerning drug rehabilitation following the educational programme.\u003c/p\u003e \u003cp\u003eWe defined NCEP as effective if there was a desire for follow-up after SUB treatment\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. The effectiveness of the NCEP depends on positive responses to subsequent SUD treatment intentions\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. We thus asked the participants about their follow-up SUD treatment intentions, either positive or negative, after completing the NCEPs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe analysed the data collected from the respondents using descriptive statistics. Categorical variables are presented as frequencies and percentages, while continuous variables are summarised as mean and standard deviation (SD). Chi-squared tests were used to examine the differences in the participants\u0026rsquo; pre-survey characteristics between the DP and probation education programmes. We also compared items from the pre- and post-education questionnaires to examine the programme outcomes. For continuous variables, we used paired \u003cem\u003et\u003c/em\u003e-tests for normally distributed data, and paired Wilcoxon signed-rank tests for data that did not meet the normality assumption. McNemar\u0026rsquo;s test was used to analyse the binary responses (positive or negative) to the four questions on the rehabilitation plans. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. significant.\u003c/p\u003e \u003cp\u003eWe evaluated the effectiveness of the NCEP using a logistic regression model that included all factor variables from the first part of the pre-questionnaires. In our logistic regression analysis, variables were selected based on a cut-off criterion (0.5) derived from the Wald test results, and collinearity diagnostics were examined to exclude correlated variables\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. To comprehensively understand the individual effects of the covariates and their overall interactions, we conducted sequential univariate and multivariate logistic regression analyses, and calculated the odds ratios (ORs) and 95% confidence intervals (CIs) for the covariates selected to assess the effectiveness of the NCEP. In the multivariate logistic regression, we handled missing data using multiple imputation (MI) through chained equations to predict missing values, including the duration of drug use, main type of drug used, income, and age group\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. In addition, to enhance the robustness of our estimates, we conducted nonparametric bootstrapping resampling with the replacement of an entire observation\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Subgroup logistic regression analysis was also conducted to examine the covariates affecting the effectiveness of the NCEP by drug type and sex. All data were analysed using SAS 9.0 statistical software and SPSS 28 statistical software.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eProgramme Participant Characteristics\u003c/h2\u003e \u003cp\u003eA total of 337 participants were enrolled in the DP education programme and 401 were enrolled in the probation education programme. Of these, 301 and 308 participants completed the programmes, and 233 and 307 completed the questionnaires, respectively. A final sample of 203 and 254 participants in DP and probation, respectively, were matched on the pre- and post-questionnaires (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarises the general characteristics of the survey respondents among the NCEP participants. As stated, there were 203 participants in the DP group (44.4%), and 254 in the probation group (55.6%). The majority were male (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;313, 68.5%), had completed compulsory education (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;384, 84.8%), were employed (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;349, 76.4%), were unmarried (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;357, 78.8%), had a good MOS-SSS (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;244, 53.5%), and had a similar age distribution (\u0026lt;\u0026thinsp;30 years, 33.1%; 30-\u0026ndash;39 years, 28.9%; \u0026gt; 40 years, 38.0%). We also examined the characteristics of the participants in the DP and probation education programmes. Differences between the two groups were observed in age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020), previous treatment experience (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009), type of drug used (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001), and DAST-10 score (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001). In terms of age, those under 30 years were DP (37.3%) but on probation (29.8%), whereas those over 40 years were DP (30.8%) but on probation (43.7%). DP had more treatment-na\u0026iuml;ve participants than did probation (80.4% in DP; 69.6% in probation). Regarding the type of drug used, stimulants were more commonly used in the probation group (58.8%) than DP (39.9%), whereas cannabis was more commonly used in DP (30.8%) than probation (24.5%). Finally, the number of participants who tested positive on the DAST-10 was higher in the probation group (85.0%) than in the DP group (71.4%). Although not statistically significant, the proportion of female participants in the DP education programme, 72 (35.5%), was higher than in the probation education programme, 72 (28.3%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral characteristics of participants in a non-custodial education program for drug offenders\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDeferred Prosecution\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;203)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbation\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;254)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e313(68.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131 (64.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e182 (71.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144(31.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72 (35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72 (28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 30 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e150(33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75(29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e131(28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e 40 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e172(38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e110 (43.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of drug use, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e271(63.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123(65.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e148(61.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e 2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e156(36.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64(34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92(38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncomplete\u0026nbsp;compulsory\u0026nbsp;education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69(15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38 (15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete\u0026nbsp;compulsory\u0026nbsp;education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e384(84.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e170(84.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e214 (84.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnual income, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; \u003cspan\u003e$\u003c/span\u003e23,230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e219(51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91(48.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e128 (54.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e \u003cspan\u003e$\u003c/span\u003e23,230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e204(48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95(51.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e109 (46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious treatment experience, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment-naive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e334(74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e160 (80.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e174 (69.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment-experienced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e115(25.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39 (19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76 (30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of the used drug, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStimulants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e201(51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (39.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e144 (58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannabis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e104(26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60 (24.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83(21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42 (29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEmployment, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e98(21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45(22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53(21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.830\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e349(76.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e156(77.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e193(78.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMarital status, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e357(78.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e160(79.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e197(78.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.712\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96(21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41(20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55(21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSocial support measured by MOS-SSS, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePoor (0\u0026ndash;19 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e212(46.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e91(45.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121(47.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.582\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGood (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;20 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e244(53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e111(55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e133(52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental health, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood (0\u0026ndash;4 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e238(52.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110(55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e128(50.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;5 scores)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e215(47.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90(45.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e125(49.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression measured by PHQ-9, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo (0\u0026thinsp;~\u0026thinsp;4 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e272(59.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e119(59.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e153(60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;5 scores)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e183(40.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82(40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e101(39.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLQ, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad (0\u0026ndash;46 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e184(40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85(42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99(39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;47 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e267(59.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e115(57.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e152(60.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug Abuse Screening Test-10, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative (0\u0026ndash;1 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96(21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58(28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38(15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;2 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e361(79.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e145(71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e216(85.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eMOS-SSS; Medical outcomes study social support survey, PHQ, Patient Health Questionnaire; MLQ, Meaning in Life Questionnaire; Analysis is chi-square test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePre- and Post-Education Outcome Analysis\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the pre- and post-education scales for NCEP participants. For DP participants, there were significant increases in the scores on the Knowledge of Drug Addiction Scale (from 5.21 to 7.61, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), HDIS (from 1.00 to 3.53, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and Recognise the Significance of Drug Cessation (from 7.56 to 8.01, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018). In contrast, while probationers showed significant increases on the Knowledge of Drug Addiction Scale (from 5.11 to 7.04, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and the HDIS (from 2.51 to 5.24, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Recognise the Significance of Drug Cessation (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.180) did not show a statistically significant increase. Neither DP (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.447) nor probation (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.280) resulted in a statistically significant increase in confidence in discontinuing drugs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eA comparison of outcomes before and after education programs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-education\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePost-education\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeferred prosecution education program\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKnowledge of drug addiction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.21\u0026thinsp;\u0026plusmn;\u0026thinsp;2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHanil Drug Insight Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.53\u0026thinsp;\u0026plusmn;\u0026thinsp;7.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecognize the significance of drug cessation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.01\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe confidence of discontinuing drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.27\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.15\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eProbation education program\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKnowledge of drug addiction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.04\u0026thinsp;\u0026plusmn;\u0026thinsp;2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.04\u0026thinsp;\u0026plusmn;\u0026thinsp;2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHanil Drug Insight Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.51\u0026thinsp;\u0026plusmn;\u0026thinsp;7.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.24\u0026thinsp;\u0026plusmn;\u0026thinsp;8.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecognize the significance of drug cessation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.96\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe confidence of discontinuing drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.16\u0026thinsp;\u0026plusmn;\u0026thinsp;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eWe performed a paired t-test to analyze outcomes before and after education programs for variables with a normal distribution only in the confidence of discontinuing drugs, and a Wilcoxon signed-rank for the other three variables. Data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation for variables.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the results of McNemar\u0026rsquo;s test for the four questions about plans for addiction rehabilitation before and after the education programme. In the DP education programme, there was a significant increase in positive responses to Q2 about joining an NA group (from 30 [15.1%] to 47 [23.6%], \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.002) and Q3 about using the KAADA rehabilitation centre (from 49 [24.7%] to 67 [33.5%], \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.009). Similarly, in the probationary education programme, there was a significant increase in positive responses to Q2 about joining an NA group (from 44 [17.6%] to 74 [29.6%], \u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001) and Q3 about using KAADA (from 79 [31.7%] to 96 [38.2%], \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.041). However, positive responses regarding hospital treatment (Q1) and recurrence (Q4) increased slightly but were not statistically significant in the DP and probation groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate and Multivariate Logistic Regression Analysis\u003c/h2\u003e \u003cp\u003eEmployment status, marital status, social support, and education were excluded. The variable \u0026lsquo;DAST-10\u0026rsquo; was excluded due to collinearity. We conducted a logistic analysis of the factors that increased NCEP effectiveness (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In the univariate logistic regression analysis, the following covariates showed significant results: Compared to those under 30 years of age, participants aged 30\u0026ndash;39 years (OR 1.95, 95% CI 1.11\u0026ndash;3.45) and those over 40 years (OR 2.53, 95% CI 1.46\u0026ndash;4.39) showed higher odds. Duration of drug use exceeding 2 years (OR 2.62, 95% CI 1.49\u0026ndash;4.59) and being treatment-experienced (OR 4.86, 95% CI 2.28\u0026ndash;10.39) were associated with higher odds. Regarding drug type, compared to stimulants, cannabis users (OR 0.37, 95% CI 0.20\u0026ndash;0.67) and users of other drugs (OR 0.47, 95% CI 0.24\u0026ndash;0.92) showed lower odds. Additionally, poor mental health (OR 2.98, 95% CI 1.81\u0026ndash;4.90) and positive for depression (OR 2.41, 95% CI 1.45\u0026ndash;4.00) were significant covariates. In contrast, DP did not show significant differences compared with probation (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.712), and good MLQ (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.310) did not show significant differences.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe success of educational programs using univariate and multivariate logistic regression analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnivariate model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMultivariate model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of Education Program\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProbation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeferred Prosecution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09 (0.69\u0026ndash;1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.45 (1.25\u0026ndash;4.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.38 (0.86\u0026ndash;2.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.89 (0.88\u0026ndash;4.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 30 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.95 (1.11\u0026ndash;3.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.00 (1.23\u0026ndash;7.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e 40 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.53 (1.46\u0026ndash;4.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.84 (0.84\u0026ndash;4.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of drug use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e 2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.62 (1.49\u0026ndash;4.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.77 (0.89\u0026ndash;3.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnual income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; \u003cspan\u003e$\u003c/span\u003e23,230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u003cspan\u003e$\u003c/span\u003e23230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10 (0.69\u0026ndash;1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07 (0.54\u0026ndash;2.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious treatment experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment-naive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment-experienced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.86 (2.28\u0026ndash;10.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.73 (1.30-10.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of the used drug\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStimulants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannabis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.37 (0.20\u0026ndash;0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.36 (0.17\u0026ndash;0.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.47 (0.24\u0026ndash;0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62 (0.26\u0026ndash;1.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMental health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood (0\u0026ndash;4 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;5 scores)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.98 (1.81\u0026ndash;4.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.45 (1.01\u0026ndash;5.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression measured by PHQ-9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo (0\u0026ndash;4 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;5 scores)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.41 (1.45-4.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.92 (0.76\u0026ndash;4.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad (0\u0026ndash;46 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[Reference]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;47 score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.27 (0.80\u0026ndash;2.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.90 (1.50\u0026ndash;5.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eOR, odds ratio; CI, confidence interval; PHQ, Patient Health Questionnaire; MLQ, Meaning in Life Questionaeire\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn multivariate logistic regression analysis, significant results were found for participation in DP compared to probation (OR 2.45, 95% CI 1.25\u0026ndash;4.82, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.01) and for having good MLQ (OR 2.90, 95% CI 1.50\u0026ndash;5.63, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.002). Participants aged 30\u0026ndash;39 years showed a significant increase in odds compared to those under 30 years of age (OR 3.00, 95% CI 1.23\u0026ndash;7.31, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.05). However, age\u0026thinsp;\u0026gt;\u0026thinsp;40 years (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.847), positive depression status (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.166), and drug type compared with stimulants (other drugs; \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.938) were not significant despite being significant in the univariate analysis.\u003c/p\u003e \u003cp\u003eIn both univariate and multivariate analyses, the following covariates remained significant: being treatment-experienced (OR 3.73, 95% CI 1.30\u0026ndash;10.71, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.015), using cannabis compared to stimulants (OR 0.36, 95% CI 0.17\u0026ndash;0.75, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.022), being aged 30\u0026ndash;39 years compared to those under 30 years (OR 3.00, 95% CI 1.23\u0026ndash;7.31, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.05), and having poor mental health (OR 2.45, 95% CI 1.01\u0026ndash;5.95, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.047). However, age\u0026thinsp;\u0026gt;\u0026thinsp;40 years (compared to age\u0026thinsp;\u0026lt;\u0026thinsp;30 years, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.847), positive depression status (compared to no depression status, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.166), and drug type with others (compared to stimulants, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.938) were not significant, despite being significant in the univariate analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analyses\u003c/h2\u003e \u003cp\u003eWe performed a sensitivity analysis to confirm the robustness of the multivariate logistic analyses. The results of the base-case multivariate logistic analysis were compared with those of the MI and bootstrap analyses, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Three covariates\u0026mdash;previous treatment experience, mental health, and MLQ\u0026mdash;were significant in all the cases. The results for MI cases showed statistically significant results for the following covariates: treatment-experienced (OR 1.93, 95% CI 1.26\u0026ndash;2.95, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.002), poor mental health (OR 1.59, 95% CI 1.12\u0026ndash;2.28, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.010), good MLQ (OR 1.43, 95% CI 1.09\u0026ndash;1.88, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.010), and male gender (OR 1.47, 95% CI 1.06\u0026ndash;2.04, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.021). Bootstrap case analysis was performed 5, 25, 100, 500, and 5000 times to observe changes in the regression results across iterations (Supplementary Table\u0026nbsp;1). Bootstrapped analysis showed consistent and valid results for all variables except annual income and the type of drug as \u0026lsquo;Others\u0026rsquo;.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003cp\u003eWe conducted a subgroup multivariate logistic regression analysis for the covariates related to the type of drug used, as shown in Supplementary Table\u0026nbsp;2. Multivariate logistic analyses were performed to determine the increase in the NCEP effectiveness in the stimulant and cannabis groups. The good MLQ covariate showed significant results for stimulants (OR 7.78, 95% CI 2.36\u0026ndash;25.65, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.001) and cannabis (OR 5.42, 95% CI 1.44\u0026ndash;20.40, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.012). The stimulant group showed higher educational effectiveness for participants aged 30\u0026ndash;39 years than for those under 30 years (OR 7.50, 95% CI 1.17\u0026ndash;48.20, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.039). Meanwhile, the cannabis group showed a higher educational effectiveness for drug use duration of more than two years (OR 6.03, CI 1.46\u0026ndash;24.86, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.013) and was positive for depression (OR 16.02, CI 2.06\u0026ndash;124.9, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.008). Although not statistically significant, the duration of drug use over two years showed a negative trend in the stimulant group, with an OR of 0.78, whereas the opposite trend was observed for cannabis, with an OR of 6.03. In addition, mental health showed a positive trend in the stimulant group, with an OR of 3.34, whereas the opposite trend was observed for cannabis, with an OR of 0.79.\u003c/p\u003e \u003cp\u003eFurther subgroup multivariate logistic regression analyses were performed on covariates associated with sex (Supplementary Table\u0026nbsp;3). The results showed that there were no universally effective covariates for men or women. For males, the covariates DP compared to probation (OR 2.56, 95% CI 1.10\u0026ndash;5.97, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.03), aged 30\u0026ndash;39 years compared to those under 30 years (OR 3.77, 95% CI 1.22\u0026ndash;11.62, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.027), treatment-experienced (OR 6.60, 95% CI 1.36\u0026ndash;32.12, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.019), drug type compared to stimulants (cannabis, OR 0.36, 95% CI 0.15\u0026ndash;0.83, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.093), and good MLQ (OR 3.12, 95% CI 1.41\u0026ndash;6.87, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.005) were effective. In contrast, for women, only poor mental health (OR 6.88, 95% CI 1.61\u0026ndash;29.41, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.009) was an effective covariate. Although not statistically significant, annual income showed a negative trend in the stimulant group, with an OR of 0.78, whereas the opposite trend was observed for cannabis, with an OR of 6.03.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe increasing number of drug offenders in South Korea highlights the need for NCEPs to address drug addiction. This study examined the outcomes of the DP and probation education programmes implemented in South Korea during 2022\u0026ndash;2023. The results showed that the NCEPs significantly increased knowledge of drug addiction, HDIS scores, and positive rehabilitation plans for drug abusers. This suggests that short-term NCEP can be effectively extended to community-based SUD treatments, which is beneficial for long-term rehabilitation\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. We also found that treatment experience, poor mental health, and a positive MLQ score were associated with a greater effectiveness of the NCEP. Comparing these results with those of earlier studies, we can consider the following points for future implementation. First, linking NCEP participants to hospital SUD treatment is crucial, as treatment experience improves intentions. Second, the finding that poor mental health improves effectiveness is encouraging, as it underscores the need for continued therapeutic interventions to maintain these improvements post-NCEP\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. This highlights the positive results of the NCEP as an alternative to incarceration\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Third, positive MLQ reinforcement aligns with previous research and, in a sub-analysis by drug type, was a success factor for both stimulants and cannabis. Therefore, it is recommended that well-being and health-related education associated with the positive reinforcement of the MLQ be improved\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn contrast to prior studies linking positive effectiveness with employment, marriage, and new family members, our study found no significant impact of these variables\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Income variables had a greater impact on programme effectiveness than employment status. Our study found no significant differences in the NCEP effects based on marital status or the social/family support index (MOS-SSS). The marriage rate among the participants was 21.2 percent, significantly lower than the 2020 adult average of 44.1 percent reported by Statistics Korea\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. With Korea\u0026rsquo;s fertility rate projected to be the lowest at 0.78 in 2022\u003csup\u003e67\u003c/sup\u003e and the unmarried fertility rate remaining around 2% (compared to the OECD average of 40%), the participants\u0026rsquo; fertility rate is also expected to be significantly low\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Therefore, in many countries where birth rates are decreasing and non-marital relationships are increasing\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, approaches to addressing the issue of drug addiction should evolve from previous methods. This implies that, in some cases, family therapy interventions should be restricted, especially for individuals who are unmarried or lack significant social support, and should instead focus on individual counselling, welfare, and health education\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In addition, the drug classification used in this study was pharmacotherapeutic\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, which is slightly different from the legal classification\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. For example, the \u0026lsquo;other\u0026rsquo; category includes sedatives and propofol in addition to opioids.\u003c/p\u003e \u003cp\u003eAs in previous research, probationers were more likely to use stimulants, especially methamphetamine, were older, and scored more positively on the DAST-10 than the DP group\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. They also had higher rates of NA participation and prior treatment experience\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. Additionally, our subgroup analysis showed opposite trends in duration of drug use and mental health for the cannabis and stimulant groups, highlighting their different health-related harms\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. The cannabis group\u0026rsquo;s positive subsequent SUD treatment intentions with depression constitutes evidence that individuals with depression are more likely to use cannabis\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e,\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. The effectiveness in men followed a trend similar to those reported in previous studies\u003csup\u003e\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Only poor mental health was a key factor for women, emphasising the importance of mental health services\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe global economic burden of illicit drug use, including healthcare, criminal justice costs, and productivity losses, can reach several hundred billion dollars annually\u003csup\u003e \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e \u003c/sup\u003e. Improving cost-effectiveness is crucial to drug policy\u003csup\u003e \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e \u003c/sup\u003e. As sustained investment in NCEPs is essential to mitigate social and economic costs and ensure long-term benefits, this necessitates a cost-per-person study\u003csup\u003e \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e \u003c/sup\u003e. To prepare for future cost-effectiveness studies of NCEP, we used micro-costing techniques to determine per-participant costs in this study\u003csup\u003e \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e \u003c/sup\u003e. The budget of Incheon KAADA (\u003cspan\u003e$\u003c/span\u003e382,194) consisted of national funds (42.9%), Incheon City funds (34.4%), and contributions from the pharmacist organisation (22.7%; Supplement Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The DP education programme has a cost per participant of \u003cspan\u003e$\u003c/span\u003e307, whereas the probation education programme costs \u003cspan\u003e$\u003c/span\u003e391 (Supplement Table\u0026nbsp;4). This is cheaper than Seattle\u0026rsquo;s LEAD programme at \u003cspan\u003e$\u003c/span\u003e899 per person per month. In the United States, costs focus on housing and food, whereas in Korea, only education is emphasised.\u003c/p\u003e \u003cp\u003eWe examined the positive outcomes and identified the key factors that influenced the effectiveness of NCEP. However, this study had several limitations. Careful consideration must be given to the transferability of the NCEP findings. Japan, Taiwan, and South Korea are high-income countries in which methamphetamine is the prevalent illicit drug\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Although their legal systems are similar\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e, their non-custodial programmes differ. Instead of incarceration, Taiwan has achieved positive results through judicial diversion for Schedule I drug offenses\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Japan relies on strict laws and mandatory treatment\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, while Korea relies on NCEPs. However, this study was conducted on participants from Incheon, a particular region of Korea, and there may be issues of representativeness. Incheon, the third-largest city in South Korea, referred 9% of national drug offenders to the NCEP. The participants did not differ from the national drug offender data in terms of age, sex, or education level\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe NCEP implemented in South Korea has been shown to improve drug addiction knowledge and HDIS, and positively influences future rehabilitation plans of drug abusers. Factors contributing to the increased effectiveness of the NCEP were treatment experience, poor mental health, and a good MLQ. While the impact of factors such as marriage, childbirth, and employment were lower than reported in other studies, personal well-being and health education emerged as stronger influencers. Our study provides recent evidence of the positive outcomes, effectiveness factors, and costs of the NCEP programme. These findings should be considered for future rehabilitation policies and programme improvements.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eKyung-ae Nam contributed to the conceptualisation, data collection, methodology, and drafting of the manuscript. In-Sun Oh contributed to the data analysis and critical review. Sun-Kyeong Park contributed to the supervision, conceptualisation, data curation, drafting, review, and editing of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank those who participated in the questionnaire, as well as the Supreme Prosecutors\u0026rsquo; Office, for their advice. Additionally, we extend our gratitude to the Incheon officials who are working to solve the problem of drug addiction.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the Korea Association Against Drug Abuse in Incheon, but restrictions apply to the availability of these data, which were used under license for the current study and are not publicly available. However, the data are available from the corresponding author or Kyung-ae Nam ([email protected]) upon reasonable request and with the permission of the Korea Association Against Drug Abuse in Incheon.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMackey‐Kallis, S. \u0026amp; Hahn, D. 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Comparison of legislative management for new psychoactive substances control among Taiwan, South Korea, and Japan. \u003cem\u003eKaohsiung J Med Sci\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 135-142, doi:10.1002/kjm2.12140 (2020).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Drug abuser, non-custodial education programme, deferred prosecution, probation, logistic regression analysis","lastPublishedDoi":"10.21203/rs.3.rs-4748630/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4748630/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study evaluated the effectiveness of deferred prosecution (DP) and probation, defined as non-custodial education programmes (NCEPs), for drug abusers in South Korea. We analysed participants\u0026rsquo; questionnaire responses in the DP (\u003cem\u003eN\u0026thinsp;=\u003c/em\u003e\u0026thinsp;203) and probation (\u003cem\u003eN\u0026thinsp;=\u003c/em\u003e\u0026thinsp;254) groups over a two-year period (January 2022\u0026ndash;December 2023). The Wilcoxon signed-rank test was used to compare pre-and post-programme questionnaires on knowledge of drug addiction and the Hanil Drug Insight Scale (HDIS) for participants in DP and probation. Using multivariate logistic analysis, we examined the factors influencing effectiveness, including previous treatment experience, Meaning of Life Questionnaire (MLQ) scores, and mental health status. NCEP effectiveness was assessed based on the participants\u0026rsquo; reported intentions for future treatment at the end of the NCEP. DP participants and probationers showed significant increases in their knowledge of drug addiction and HDIS scores (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001). Results showed that treatment experience (odds ratio [OR] 3.73, 95% confidence interval [CI] 1.30\u0026ndash;10.71), poor mental health (OR 2.45, 95% CI 1.01\u0026ndash;5.95), and good MLQ (OR 2.90, 95% CI 1.50\u0026ndash;5.63) were significantly associated with improved NCEP effectiveness. This study provides the first evidence of the beneficial outcomes of the NCEP and identifies the factors influencing its effectiveness.\u003c/p\u003e","manuscriptTitle":"Evaluation of the Outcomes and Influencing Factors of Non-Custodial Educational Programmes for Drug Abusers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-26 14:02:32","doi":"10.21203/rs.3.rs-4748630/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9522b92a-a7d0-4231-9cce-939a3c96c5c6","owner":[],"postedDate":"August 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":36171789,"name":"Health sciences/Health care/Drug regulation"},{"id":36171790,"name":"Health sciences/Health care/Health policy"},{"id":36171791,"name":"Health sciences/Health care/Public health"}],"tags":[],"updatedAt":"2025-03-18T04:08:17+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-26 14:02:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4748630","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4748630","identity":"rs-4748630","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}