INTRODUCTION Although Thailand has banned the import of electronic cigarettes (e-cigarettes) into the kingdom, a range of evidence has revealed the widespread use of these illegal products, especially among university students. Too little is known about personal and perceptual factors for such behavior. This study aimed to investigate the prevalence and factors associated with the use of e-cigarettes among university students in Northern Thailand METHODS A cross-sectional study was conducted with 792 university students in Northern Thailand between June and July 2020. An anonymous, self-administered questionnaire was implemented to collect relevant information. Bivariate and multivariate logistic regression analyses were applied to identify factors associated with the use of e-cigarettes in the last 30 days. RESULTS The study revealed that 18.1% of the participants used e-cigarettes in the past 30 days. The personal factors associated with e-cigarette use among Thai university students included: studying in non-health related faculties (AOR=11.21; 95% CI: 4.88–25.71); having a friend using e-cigarettes (AOR=10.48; 95% CI: 5.96–18.41); having a lower GPA than the mean (AOR=1.93; 95% CI: 1.14– 3.28); and having a monthly income higher than the mean (AOR=1.74; 95% CI: 1.09–2.78). Regarding perceptual factors, there was a significant link between e-cigarette use and the perception that these modern cigarettes are less harmful than conventional cigarettes (AOR=2.47; 95% CI: 1.50–4.07), and perception that using e-cigarettes in public is not illegal (AOR=1.93; 95% CI: 1.19–3.15). CONCLUSIONS E-cigarette use is widespread among Thai university students. Maintaining the enforcement policy on banning the importation of e-cigarettes into the country is thus needed. Also, further communication and public relations on the risks and legal prohibitions of e-cigarette use are needed among university students in the Northern Thailand.

PURPOSE This study aimed to examine the quality of life of tobacco farmers and their desire to stop growing tobacco. METHODS A cross-sectional home-based survey was conducted between October 2021 and January 2022 among 2,970 Virginia and Burley tobacco farmers in Northern Thailand. Multivariate logistic regression models were used to determine the association between farmers' characteristics and their quality of life and a desire to stop planting tobacco. RESULTS In total, 58.5% of the participants wanted to stop growing tobacco, and most had a lower quality of life than the mean. Nine independent variables were associated with a desire to stop tobacco farming: having a low level of economic quality of life (adjusted odds ratio [ORAdj], 5.42; 95% CI, 3.8 to 7.8); having a high environmental quality of life (ORAdj, 4.60; 95% CI, 3.3 to 6.5); belonging to the Tobacco Farmers' Association (ORAdj, 3.04; 95% CI, 2.1 to 4.5); growing tobacco on their own land (ORAdj, 2.12; 95% CI, 1.8 to 2.6); having a low social quality of life (ORAdj, 1.69; 95% CI, 1.4 to 2.1); having a low health quality of life (ORAdj, 1.69; 95% CI, 1.4 to 2.1); having a low spiritual quality of life (ORAdj, 1.41; 95% CI, 1.2 to 1.7); being Burley tobacco farmers (ORAdj, 1.33; 95% CI, 1.0 to 1.8); and having a low family quality of life (ORAdj, 0.49; 95% CI, 0.4 to 0.6). CONCLUSION The majority of the tobacco farmers had a declining quality of life, particularly economic and environmental quality of life, resulting in reducing growing tobacco. National and regional support are needed to help these farmers effectively grow alternative crops, and financial support to make such conversions.

INTRODUCTION To prevent youth from becoming smokers, it is essential to understand factors contributing to them becoming susceptible to smoking. The aim of this study was thus to estimate the prevalence of smoking susceptibility among neversmoking youth in Thailand and to identify determinants associated with such behavior. METHODS Cross-sectional data for 4572 eighth-grade students (aged 13-15 years) from 120 secondary schools were obtained from a classroom-based survey using a self-administered questionnaire. Using data from never-smoking students (n=3180), simple and multiple logistic regression analyses were performed to identify factors associated with smoking susceptibility. Frequencies and proportions for descriptive statistics are reported along with adjusted odds ratios and 95% confidence intervals for logistic regression models. RESULTS A total of 16.4% of Thai never-smoking youth were susceptible to smoking. Several variables of interest were identified in multivariable analysis as significantly associated with increased susceptibility to smoking: being male (AOR=3.16; 95% CI: 25.4-3.92), having a positive attitude toward smoking -agreeing that smoking displays maturity (AOR=1.49; 95% CI: 1.07-2.09), the perception that smoking helps relieve stress (AOR=1.57; 95% CI: 1.14-2.15), the presence of current smoking peers (AOR=2.04; 95% CI: 1.57-2.66), exposure to secondhand smoking in public (AOR=1.51; 95% CI: 1.17-1.94), exposure to online cigarette and smoking-related advertising occasionally (AOR=1.98; 95% CI: 1.49-2.65), attendance at schools where there are sometimes anti-smoking education activities (AOR=1.57; 95% CI: 1.18-2.07); as well as exposure to anti-tobacco messages rarely (AOR=1.40; 95% CI: 1.05-1.87), occasionally (AOR=1.48; 95% CI: 1.12-1.96) and infrequently (AOR=1.41; 95% CI: 1.07-1.87). CONCLUSIONS Approximately one in six Thai never-smoking youth was found to be susceptible to smoking. Findings suggest it should be useful to supplement relevant tobacco prevention and control efforts by considering such interpersonal and socio-environmental determinants, among vulnerable people to smoke.

Introduction: Youth are increasingly playing mobile games, which distinct from traditional games, but there is limited research investigating the causal relationship between mobile game addiction and mental health problems in Thailand. This cross-sectional study investigated the association between mobile game addiction and depression, loneliness, and social anxiety as well as academic performance. Methods: Data were collected from 3,427 students in Thailand, using a 5-part self-report questionnaire. Descriptive statistics and Structural Equation Modelling (SEM) were used to analyse the data. Results: The prevalence of mobile game addiction among Thai youth was 22.2%, which was higher among females (25.6%) than males (17.9%) and higher among high school students (25.6%) than vocational (20.6%) and undergraduate students (20.0%). According to the SEM analysis, mobile game addiction was significantly associated with depression (β = 0.36), loneliness (β = 0.31), social anxiety (β = 0.28), and Grade Point Average (GPA) mediated by social anxiety (β = 0.10). Conclusion: The identification of a substantial group of addicted mobile gamers and the addiction effects on mental health issues supports efforts by all stakeholders to prevent youth from becoming game addicted as well as treat addicted gamers.