Depressive Symptoms, Suicidal Ideation, and Mental Health Service Use of Industrial Workers: Evidence from Vietnam.

Background: Depressive symptoms and suicidal ideation substantially reduce industrial workers' productivity and performance. This study was performed to examine the prevalence of depressive symptoms and suicidal ideation and identify associated factors among industrial workers in different provinces of Vietnam. Materials and Methods: We performed a cross-sectional study in industrial zones of four provinces of Vietnam. The Patient Health Questionnaire (PHQ-9) was employed to screen depressive symptoms and suicidal ideation. Multivariate logistic regression was performed to determine factors related to depressive symptoms and suicidal ideation. Results: Of 1200 industrial workers, 30.5% and 33.6% industrial workers had positive depressive symptoms and suicidal ideation in the last two weeks, respectively. There were 38.3% ever using mental health services in the last 12 months. High school education (OR = 0.64, 95% CI = 0.44-0.95); living in dormitory (OR = 3.07, 95% CI = 1.51-6.24), living with siblings (OR = 2.98; 95% CI = 1.32-6.75), having two children or more (OR = 1.45, 95% CI = 1.03-2.03), high years of experience (OR = 0.94; 95% CI = 0.89-0.98), suffering from burnout, alcohol use disorder (OR = 2.38; 95% CI = 1.72-3.28), and smoking status (OR = 0.38, 95% CI = 0.23-0.61) were associated with positive depressive symptoms. Living with children, working in mechanical/metallurgy/electronics factories, completely exhausted and often thinking of quitting, and alcohol use disorder were positively related to suicidal ideation. Conclusions: This study found a high prevalence of depressive symptoms and suicidal ideation among industrial workers in Vietnam. Regular screening and detecting high-risk groups, along with interventions to reduce health risk behaviors, burnout and on-site medical service quality improvement, are recommended to alleviate the burden of depression in industrial workers.

Modeling Research Topics for Artificial Intelligence Applications in Medicine: Latent Dirichlet Allocation Application Study.

BACKGROUND: Artificial intelligence (AI)-based technologies develop rapidly and have myriad applications in medicine and health care. However, there is a lack of comprehensive reporting on the productivity, workflow, topics, and research landscape of AI in this field. OBJECTIVE: This study aimed to evaluate the global development of scientific publications and constructed interdisciplinary research topics on the theory and practice of AI in medicine from 1977 to 2018. METHODS: We obtained bibliographic data and abstract contents of publications published between 1977 and 2018 from the Web of Science database. A total of 27,451 eligible articles were analyzed. Research topics were classified by latent Dirichlet allocation, and principal component analysis was used to identify the construct of the research landscape. RESULTS: The applications of AI have mainly impacted clinical settings (enhanced prognosis and diagnosis, robot-assisted surgery, and rehabilitation), data science and precision medicine (collecting individual data for precision medicine), and policy making (raising ethical and legal issues, especially regarding privacy and confidentiality of data). However, AI applications have not been commonly used in resource-poor settings due to the limit in infrastructure and human resources. CONCLUSIONS: The application of AI in medicine has grown rapidly and focuses on three leading platforms: clinical practices, clinical material, and policies. AI might be one of the methods to narrow down the inequality in health care and medicine between developing and developed countries. Technology transfer and support from developed countries are essential measures for the advancement of AI application in health care in developing countries.

Characterizing Obesity Interventions and Treatment for Children and Youths During 1991-2018.

Overweight and obesity have become a serious health problem globally due to its significant role in increased morbidity and mortality. The treatments for this health issue are various such as lifestyle modifications, pharmacological therapies, and surgery. However, little is known about the productivity, workflow, topics, and landscape research of all the papers mentioning the intervention and treatment for children with obesity. A total of 20,925 publications from the Web of Science database mentioning interventions and treatment in reducing the burden of childhood overweight and obesity on physical health, mental health, and society published in the period from 1991 to 2018 were in the analysis. We used Latent Dirichlet Allocation (LDA) for identifying the topics and a dendrogram for research disciplines. We found that the number of papers related to multilevel interventions such as family-based, school-based, and community-based is increasing. The number of papers mentioning interventions aimed at children and adolescents with overweight or obesity is not high in poor-resource settings or countries compared to the growth in the prevalence of overweight and obesity among youth due to cultural concepts or nutrition transition. Therefore, there is a need for support from developed countries to control the rising rates of overweight and obesity.