• Why was the author interested in investigating the suicide problem in Thailand during the time?
The researcher aims to identify the significant factors influencing suicide rates in Thailand. This study is prompted by the rising number of suicide cases, which ranged from 3,600 to 4,000 annually between 2005 and 2014. The average suicide rate exceeded 6 cases per 100,000 population, especially after 2011. While numerous studies have been conducted in developed countries to address the increasing trend of suicide, this research focuses on exploring the factors affecting suicide rates within the Thai context. The study is designed as a cross-sectional analysis to examine how cultural, social, and economic factors influence the population across different regions of the country.
• Each of students picks one potential risk factor mentioned in the paper and explains how the variable can contribute to the suicide rate?
The researcher aims to identify the significant factors influencing suicide rates in Thailand, noting a concerning rise in the number of suicide cases, which ranged from 3,600 to 4,000 annually between 2005 and 2014. The average suicide rate exceeded 6 cases per 100,000 population, particularly following 2011. While numerous studies have been conducted in developed countries to address the increasing trend of suicide, this research seeks to explore the specific factors affecting suicide rates within the Thai context. It was conducted as a cross-sectional study examining how cultural, social, and economic influences vary across different regions of the country.
• How statistical modeling can contribute to investigate the epidemiology and spatial aspects of Thai suicide problem?
The primary contribution of statistical modeling in epidemiology is its ability to identify patterns and correlations between various risk factors and outcomes, such as suicide rates. By employing multiple regression analysis with two models, the study can investigate the impact of economic and social factors related to suicide rates in Thailand. Additionally, spatial analysis can reveal disparities across different geographical areas, providing insights into the suicide problem. This approach allows for the identification of high-risk areas and can assist policymakers in implementing targeted interventions and allocating resources effectively.