Suchergebnisse

In the context of strong development of science and technology, more and more social networking platforms are appearing, which has greatly impacted all areas of human activity and daily life, especially young people and high school student. Researching the effects of using social networks is one of the common problems of modern society around the world in general and Vietnam in particular. Therefore, researching the effects of social networks on high school students is extremely urgent. The article addresses research directions on the effects of using social networks on high school students through understanding concepts, tools, methods, content and general findings on positive and negative effects of social networks on high school students in some countries around the world and in Vietnam. Thereby, we propose some solutions to improve the effectiveness of using social networks for high school students.

Population growth is one factor relevant to land-use transformation and expansion in urban areas. This creates a regular mission for local governments in evaluating land resources and proposing plans based on various scenarios. This paper discussed the future trend of three kinds of land-use in the five central coast provinces. Afterwards, the paper deployed machine learning such as Multivariate Adaptive Regression Splines (MARS), Random Forest Regression (RFR), and Lasso Linear Regression (LLR) to analyze the trend of rural land use and industrial land-use to urban land-use in the Central Coast Region of Vietnam. The input variables of land-use from 2010 to 2020 were obtained by the five provinces of the Department of Natural Resources and Environment (DONRE). The results showed that these models provided pieces of information about the relationship between urban, rural, and industrial land-use change data. Furthermore, the MARS model proved to be accurate in the Quang Binh, Quang Tri, and Quang Nam provinces, whereas RFR demonstrated efficiency in the Thua Thien-Hue province and Da Nang city in the fields of land change prediction. Furthermore, the result enables to support land-use planners and decision-makers to propose strategies for urban development.

OBJECTIVE: We examined the association of U.S. Reserve Component (RC) personnel separating from military service with risk of mental health problems at three time periods. METHODS: Structured interviews were conducted with a nationally representative sample of 1,582 RC personnel at baseline and three follow-up waves from 2010–2013. Multivariate logistic regression analyses examined posttraumatic stress disorder (PTSD), major depressive disorder (MDD), binge drinking, suicide ideation, and mental health diagnosis by a health provider. RESULTS: Approximately 10%, 20% and 28% of RC personnel reported separating from military service at waves 2–4. At an estimated 6 months since leaving military service, there was no differences between those who left and those who remained in service. However, at 1 year after leaving service, those who had left had higher risk of MDD, suicidal ideation, and reporting having mental health diagnosis by a health provider. At 1.6 years after leaving military service, those who had left had higher risk of reporting having mental health diagnosis by a health provider. The results were essentially unchanged after adjusting for baseline mental disorder for each outcome. CONCLUSION: Results suggest a higher risk of mental health problems in RC veterans separating, compared to those who remained in the military. This risk may not occur immediately following separation but may occur within the first year or two after separation. Transition from military to civilian life may be a critical period for interventions to address the unique needs of the RC's citizen-soldiers and reduce their risk of adverse mental health outcomes.

OBJECTIVE: We examined early first deployment and subsequent suicide attempt among U.S. Army soldiers. METHOD: Using 2004-2009 administrative data and person-month records of first-term, Regular Army, enlisted soldiers with one deployment (89.2% male), we identified 1,704 soldiers with a documented suicide attempt during or after first deployment and an equal-probability control sample (n=25,861 person-months). RESULTS: Logistic regression analyses indicated soldiers deployed within the first 12 months of service were more likely than later deployers to attempt suicide (OR=1.7 [95% CI=1.5-1.8]). Adjusting for socio-demographic characteristics, service-related characteristics, and previous mental health diagnosis slightly attenuated this association (OR=1.6 [95% CI=1.5-1.8]). Results were not modified by gender, deployment status, military occupation, or mental health diagnosis. The population-attributable risk proportion for deploying within the first 12 months of service was 17.8%. Linear spline models indicated similar risk patterns over time for early and later deployers, peaking at month 9 during deployment and month 5 post-deployment; however, monthly suicide attempt rates were consistently higher for early deployers. CONCLUSIONS: Enlisted soldiers deployed within the first 12 months of service have elevated risk of suicide attempt during and after first deployment. Improved understanding of why early deployment increases risk can inform development of policies and intervention programs.