Background and Objective Males and females who use methamphetamine (MA) differ in socio-demographics, MA diagnoses, co-morbidities, and brain activity. The objective of this study was to investigate sex differences in the characteristics of MA use and dependence in patients at a Thai substance treatment center. Methods Demographic, MA use, and diagnostic data for 782 MA users were obtained by using the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA), Thai version. Categorical comparisons of males (n=413, 53%) and females (n=369, 47%) were made by chi-square test. Factors significantly differentiating men and women with respect to MA dependence were identified by logistic regression analysis controlling for demographic, diagnostic, and MA use variables. Results Males admitted to residential drug treatment for MA use had an earlier age of onset for both MA use (17.7±4.1 vs. 19.7±6.2 years, t=-5.3, p<0.001) and dependence (20.4±5.2 vs. 22.2±6.4 years, t=-3.6, p<0.001). Females were more likely than males to be MA dependent (79% vs. 60%, χ21=33.7, p<0.001), and to experience MA withdrawal (65.3% vs. 48.9%, χ21=21.4, p<0.001), withdrawal related hypersomnia (77.2% vs. 64.8%, χ21=14.5, p<0.001), fatigue (77.5% vs. 70.3%, χ21=5.2, p=0.02) and psychomotor retardation (64.5% vs. 57.0%, χ21=4.5, p=0.03). Similarly, females had heavier (e.g., largest daily amount (χ21=12.4, p<0.001), more frequent (χ21 =5.1, p=0.02)) and greater lifetime episodes of MA use (χ21=24.1, p<0.001) than males. After controlling for such variables by logistic regression, being female remained a significant factor influencing the occurrence of MA dependence (OR=2.7, 95% CI=1.8-4.1, p<0.001). Shared associated factors (or comorbidities) for MA dependence in both sexes included nicotine dependence (in males; OR=4.1, 95% CI=2.4-7.0, p<0.001 and in females; OR=2.4, 95% CI=1.3-4.4, p=0.007), greater lifetime episodes of MA use (in males; OR=3.5, 95% CI=1.9-6.4, p<0.001 and in females; OR=5.9, 95% CI=3.1-11.4, p<0.001) and more frequent use (in males; OR=5.1, 95% CI=2.8-9.1, p<0.001 and in females; OR=3.6, 95% CI=1.9-6.9, p<0.001). Comorbid antisocial personality disorder predicted MA dependence in males only (OR=3.7, 95% CI=1.6-8.6, p=0.002). Conclusions The current study highlights both common (e.g., nicotine dependence and severity of MA use) and sex-specific differences (e.g., MA use/dependence characteristics and comorbidities), including sex itself, with respect to MA dependence in a Thai treatment cohort.

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Background The main objective of this study was to investigate the association between parental supply of alcohol, alcohol–related harms, and the severity of alcohol use disorder in Thai 7th grade middle school students. Methods A cross–sectional descriptive study obtained the baseline data from the project named the Thailand Parental Supply and Use of Alcohol, Cigarettes & Drugs Longitudinal Study Cohort in Secondary School Students in 2018. The sample size was 1187 students who have ever sipped or drank alcohol in the past 12 months. Pearson’s Chi square, binary logistic regression, and ordinal logistic regression are applied in the analysis. Results A single source of parental supply is not significantly associated with any alcohol-related harm and the severity of alcohol use disorder, while parental supply with peers and siblings supply of alcohol plays an important role in both outcomes. The increasing number of sources of alcohol supply increases the risk of alcohol–related harm and the severity of alcohol use disorder. Other risk factors found in both associations included binge drinking, alcohol flushing, low household economic status, distance from the student’s family, and poor academic performance. Gender, exposure to alcohol ads on social media and location of residency were not associated with alcohol–related harms or severity of alcohol use disorder. Conclusions The results did not support parental guidance in teaching or giving children a drink or sip of alcohol within family to prevent related harms when drinking outside with their peers.

Background The objectives of this study were to investigate the proportion of treatment-resistant depression (TRD) among patients with diagnosed major depressive disorder (MDD), to estimate the economic cost of MDD and TRD, and to examine the differences between MDD and TRD in a Thai public tertiary hospital. Methods This was a combined study between retrospective review of medical records and a cross-sectional survey. The sample size was 500 dyads of MDD patients and their unpaid caregivers. The concept of healthcare resource utilization, the Work Productivity and Activity Impairment Questionnaire: depression and mood & mental state versions (WPAI: D, MM), the Class Impairment Questionnaire (CIQ), and the Family Experiences Interview Schedule (FEIS) were applied as the tools of the study. Pearson Chi’s square, Fisher’s Exact test, and independent T-test were employed for statistical analysis. Results The proportion of TRD was 19.6% among MDD patients in a Thai tertiary public hospital. Age, age of onset of MDD, BMI, history of suicide attempt and self-harm, and frequent smoking behavior were significantly associated with TRD. The annualized economic cost of TRD was 276,059.97 baht per person ($7,668.33), which was significantly higher than this cost of non-TRD (173,487.04 baht or $4,819.08). The aggregated economic costs of MDD were 96.8 million baht annually ($2.69M) if calculated from 500 MDD patients and unpaid caregivers. This contributed to the economic cost of TRD 27.05 million baht (98 respondents) and the economic cost of non-TRD 69.74 million baht (402 respondents). Conclusions The economic cost of TRD was significantly higher than those of non-TRD, especially direct medical costs and indirect costs.

Psychoactive substances – chemical compounds which can alter a person’s mood, thoughts, and behaviors may be liable to misuse and cause addiction. Internationally, many strategies have been implemented in order to limit the supply and demand of illegal substances, with a wide variation at the country level. Thailand is an upper-middle income country in Southeast Asia. Since 2015, Thai authorities and policymakers have instituted many changes to the legal controls on illegal drugs. The aim of this review was to summarise the history of drug control and regulation in Thailand, focusing on opioids (including Kratom), methamphetamines and cannabis, and the outcome of recent strategies. Recent measures towards decriminalising substance use disorders are also discussed.

Background: Methamphetamine (MA) is one of the most common drugs of abuse in Thailand. MA use may cause neurotoxicity, immune-inflammatory and oxidative stress responses and, consequently, MA-induced psychosis (MIP).Aims: This study aims to examine the effects of MA use and dependence and MA withdrawal symptoms on the telomere to single copy gene (T/S) ratio and whether shortening of the latter is associated with MIP.Methods: This study included 185 MA-abuse, 118 MA-dependent, and 67 MIP patients, diagnosed using DSM-IV-TR criteria. The Semi-structured Assessment for Drug Dependence and Alcoholism (SSADDA) questionnaire was employed to collect clinical and MA-related data. MIP was confirmed using the Methamphetamine Experience Questionnaire (MEQ). The leukocyte telomere length was measured in all participants using real-time polymerase chain reaction measuring the Telomere/Single gene ratio (T/S ratio). Results: There were no significant associations between the T/S ratio and severity of MA-use, MIP, MA withdrawal symptoms including depression and psychomotor retardation. MIP was significantly predicted by alcohol dependence, antisocial personality disorder, and MA-use severity. There were significant and positive associations between the T/S ratio and previous traumatic events and life-threatening accidents. The T/S ratio was not affected by comorbid alcohol and nicotine dependence. Alcohol and nicotine dependence, antisocial personality, and severity of MA use increased risk of MA withdrawal symptoms. Conclusion: MIP and MA-use severity do not affect leukocyte telomere length, but telomere length may be affected by previous traumatic events and life-threatening accidents.