The purpose of the present study was to examine the severity of suicidal ideation of the older adults according to the amount of involvement in grandchild care. Data for this research were drawn from a cross-sectional study conducted on community-dwelling adults aged 65 years or older. The 922 participants were divided into three groups according to their involvement in grandchild care: 18.5% had provided daily care, 12.4% had provided occasional care, and 69.1% had never cared for their grandchildren. ANCOVA analysis showed that the scores for depression was significantly lower in the group which took care of their grandchildren occasionally compared to the other two groups. The scores for suicidal ideation was significantly higher in the group which had never taken care of their grandchildren compared to the other two groups. Current study suggests that grandparenting may have a positive effect on suicidal ideation of the older adults.
Adult ; Aged ; Cross-Sectional Studies ; Depression ; Humans ; Suicidal Ideation

OBJECTIVES: The aim of this study was to investigate the variables influencing acceptability and perception towards suicide among the elderly in Bucheon city, South Korea. METHODS: A total of 1099 elderly over 65 years old participated in this study. The subjects completed a self-questionnaire including their demographic characteristics, psychiatric characteristics, factor 1 and 4 of the Attitudes Towards Suicide-20, and Geriatric Depression Scale Short Form Korea Version. One-way analysis of variance was performed to identify the variables associated with the acceptability and perception towards suicide. RESULTS: As result of this study, the demographic characteristics (older age, lower education level, lower economic state, bereavement, divorce or separated marital status, and life without spouse) and psychiatric characteristics (psychiatric past history, treatment history, and suicidal attempt history) were found to be associated with a more acceptable attitude toward suicide. In addition, a lower education level, no psychiatric history, and no psychiatric treatment history influenced the lack of perception to suicide. CONCLUSION: For public services to prevent suicide of the elderly population who lack spontaneity and accessibility to suicidal evaluations, it would be important to focus on the variables identified in this study for enhancing the effectiveness of the services.
Aged* ; Bereavement ; Depression ; Divorce ; Education ; Gyeonggi-do* ; Humans ; Korea ; Marital Status ; Suicide*

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020‒December 31, 2020 and January 20, 2020‒January 31, 2021) and testing data (January 1, 2021‒February 28, 2021 and February 1, 2021‒February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values’ comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020‒December 31, 2020 and January 20, 2020‒January 31, 2021) and testing data (January 1, 2021‒February 28, 2021 and February 1, 2021‒February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values’ comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.

Balloon tamponade using Sengstaken–Blakemore (SB) tube is employed as a bridging therapy in cases in which endoscopic therapy fails to control esophageal variceal bleeding. Although SB tube insertion can lead to successful hemostasis, it is accompanied by numerous complications, with SB tube transection being one of the rarest complications. A 53-year-old man with liver cirrhosis and hepatocellular carcinoma presented with massive esophageal variceal bleeding. Therapeutic endoscopic variceal ligation failed, and SB tube was inserted. The SB tube was unexpectedly disconnected because of the patient's irritability due to hepatic encephalopathy. The esophageal and gastric balloon of the SB tube remained inflated in the stomach. Whereas the use of other endoscopic instruments was ineffective, endoscopic removal was successfully accomplished using endoscopic scissors. In conclusion, we detected SB tube transection in a patient with hepatic encephalopathy and removed remnants of the inflated tube using endoscopic scissors.
Balloon Occlusion ; Carcinoma, Hepatocellular ; Esophageal and Gastric Varices ; Gastric Balloon ; Hemostasis ; Hepatic Encephalopathy ; Humans ; Ligation ; Liver Cirrhosis ; Middle Aged ; Stomach