Given South Korea's rapidly aging population, mental health and quality of life (QoL) in older adults are increasingly becoming important. Self-compassion (SC), defined as extending compassion to oneself in times of suffering, has been found to have associations with positive mental health outcomes. This study was performed to examine associations between self-compassion and mental health symptoms, sleep disturbance, life satisfaction, and health-related quality of life (HR-QoL) among older Korean adults. The participants in this cross-sectional study included 203 older Korean adults aged 65 and over. Findings of this study suggest that self-compassion in older adults protects them from developing mental health and sleep disturbance symptoms while enhancing their life satisfaction, self-care, and usual activities. Therefore, interventions fostering self-compassion may benefit older adults' mental health and quality of life.

Simulation-based education using standardized patients or high fidelity patient simulators is resource-intensive and can be limited in its consistency and repeatability. Standardized, interactive, and effective computer simulation-based education programs that improve communication skills among nursing students are greatly needed. This study aimed to (1) compare the efficacy of a computer simulation-based, interactive communication education (ComEd) program and an attention control (AC) program on communication knowledge, learning self-efficacy, and communication efficacy at baseline and twice after the intervention (immediately after and two weeks after); and (2) assess the acceptability and satisfaction of the ComEd reported by the participants. This study employed a mixed-method, randomized controlled design with repeated measures. Students were recruited from four nursing schools and randomly assigned to either the intervention or AC group. They received either the ComEd or AC program installed on a tablet PC or a desktop computer in the classrooms and completed a 15-item communication knowledge scale, 10-item learning self-efficacy scale, 22-item communication efficacy scale, and 14-item satisfaction scale. In addition, six open-ended questions were used to help participants reflect on their learning experiences and explore their satisfaction with the programs. The Generalized Estimating Equation (GEE) model was the main model employed to examine the effects of the ComEd program over time in comparison with the AC program, and the content analysis method was used for qualitative data. In total, 131 nursing students (66 in ComEd and 65 in AC) completed the programs and 127 participated through the two-week follow-up test. Compared to the AC group, the ComEd group significantly improved communication knowledge, learning self-efficacy, and communication efficacy; these effects were maintained at two weeks. The ComEd program was well accepted by the participants. The ComEd is a promising approach because it is highly accessible, consistent, and repeatable, and has positive learning effects.

This cross-sectional descriptive study identified risk factors and predictors related to the perpetration of and potential for cyberbullying among adolescents, respectively. The analysis included a zero-inflated negative binomial regression model. Data were assessed from 2590 middle-school student panels obtained during the first wave of the Korean Child and Youth Panel Survey 2018. Of these respondents, 63.7% said they had not experienced the perpetration of cyberbullying. However, a subsequent count model analysis showed that several factors were significantly associated with cyberbullying, including offline delinquency, aggression, smartphone dependency, and smartphone usage on weekends (either 1–3 h or over 3 h). A logit model analysis also showed several predictive factors that increased the likelihood of cyberbullying, including gender (boys), offline delinquency, aggression, smartphone usage during weekdays (1–3 h), computer usage during weekends (1–3 h), and negative parenting. These identified risks and predictors should be useful for interventions designed to prevent the perpetration of cyberbullying among middle school students.