Yeun YR, et al. Healthc Inform Res. 2016 Jul;22(3):217-230. http://dx.doi.org/10.4258/hir.2016.22.3.217

This study aimed to evaluate the quality of life (QOL) in home health care patients according to change in health status outcomes between the start of care and discharge or 60 days, whichever came first. This is a prospective descriptive study. The convenience sample consisted of 100 home health care patients, who started receiving home health care services from a home health care agency in the United States. The World Health Organization Quality of Life Scale-Brief (WHOQOL-BREF) was used for measuring QOL; activities of daily living (ADLs) and instrumental ADLs were collected from the Outcome and Assessment Information Set data via Centers for Medicare and Medicaid Services-required home health agencies. Descriptive statistics, paired t tests, and multiple linear regressions were used for data analysis. ADLs and instrumental ADLs of participants significantly improved between start of care and discharge or 60 days. Overall QOL, general health, and three of four QOL domains (physical, psychological, and environmental, but not social domain) were significantly improved at discharge or 60 days. Home health care nurses should maintain and improve the functional ability of patients, as this could improve the QOL of these patients.

Nurses primarily focus on caring for others, but they also require care and support to enhance their own resilience. Thus, this study aims to determine the effects of psychological interventions on nurses’ resilience support and to define the influence of moderating variables that can affect these effects. The literature search was conducted in 10 electronic databases, and 5 randomized controlled trials and 10 non-randomized controlled trials were finally selected for analysis (a total of 852 participants). Statistical analyses of the effect sizes and homogeneity of the intervention programs were conducted using RevMan 5.3 from the Cochrane Library and the R program. Publication bias in the retrieved studies was tested using contour-enhanced funnel plots. The meta-analysis found that psychological interventions were effective in improving nurses’ resilience immediately after the intervention (SMD = 0.59, 95% CI 0.31 to 0.86, Z = 4.18, p < 0.001) and in the short term within three months (SMD = 1.52, 95% CI 0.74 to 2.31, Z = 3.80, p < 0.001). Interventions using emotion regulation, relaxation, and self-compassion were particularly effective, and the intervention period was effective in both a short period of 1 day and a long period of more than 12 weeks. In addition, the optimal one-session time was 121–150 min, and offline interventions were more effective than online interventions. Furthermore, the effect size was affected by the intervention time for one session (QB = 12.02, df = 3, p = 0.007) and the on/offline intervention method (QB = 5.85, df = 1, p = 0.015). These findings may inform the development of targeted interventions and resilience support systems for nurses. However, in the future, more rigorous studies, such as randomized controlled trials, should be conducted to ensure strict control over the variables and to establish a stronger evidence base for the effectiveness of these interventions.

(1) Background: Digital addiction has been a global concern, with college students becoming increasingly vulnerable to it. The detrimental psycho-physiological effects of digital addiction have raised concerns regarding college students’ health. This descriptive correlational study was conducted to evaluate the prevalence of digital addiction and identify influencing factors among college students, such as body shape satisfaction, time management, and psychological health. (2) Methods: Data were collected from 199 students at a university in Seoul, South Korea, from 30 May to 13 June 2023. The Digital Addiction Scale (DAS), Time Structure Questionnaire (TSQ), General Health Questionnaire (GHQ), and Body Shape Questionnaire (BSQ) were used for the assessment. Data (N = 199) were analyzed using descriptive statistics, one-way ANOVA, Pearson’s correlation coefficient, and stepwise multiple regression. (3) Results: The mean score for digital addiction was 54 ± 12, with scores ranging from 23.0 to 89.0. Digital addiction had a significant positive correlation with body shape satisfaction (r = 0.156, p = 0.028) and a negative correlation with time management (r = −0.500, p < 0.001). In the stepwise multiple regression model of digital addiction (adjusted ${\mathrm{R}}^2$ = 0.285, p < 0.001), subfactors of body shape satisfaction (fear of fatness β = −0.280, body dissatisfaction β = 0.401) and time management (effective organization β = −0.211, persistence β = −0.209, past orientation β = −0.165) were statistically significant. (4) Conclusions: Body shape satisfaction and time management are important factors influencing digital addiction among college students. However, it does not establish a direct causal relationship. The findings indicate that there is a statistical association or connection between these factors, but they do not definitively state that body shape satisfaction or time management directly cause digital addiction. To decrease digital addiction in this population, interventions should aim to improve body shape satisfaction and time management.

(1) Background: The purpose of this study was to validate a Korean version of the disaster preparedness evaluation tool (DPET-K) for nurses and to verify its validity and reliability for use in community healthcare centers and hospitals in South Korea; (2) Methods: In total, 497 nurses (248 for exploratory factor analysis and 249 for confirmatory factor analysis) at public health centers, public health sub-centers, public health clinics, and general hospitals in Seoul and Gyeonggi, Chungcheong, and Gangwon Provinces participated in this study. The tool went through translation and back-translation, content validity verification, a pilot survey, and validity and reliability testing; (3) Results: The DPET-K had 28 items with five factors (disaster education and training, disaster knowledge and information, bioterrorism and emergency response, disaster response, and disaster evaluation). The Cronbach’s α values for internal consistency were 0.766–0.953 for the five subscales of the DPET-K. A structural equation model was built through confirmatory factor analysis for goodness of fit (χ²/df = 2.193, SRMR = 0.060, RMSEA = 0.069, GFI = 0.831, CFI = 0.927, NFI = 0.875); (4) Conclusions: The DPET-K was confirmed to be a useful tool for assessing the disaster preparedness of nurses in Korea.