Hye Kyung Lee

Cognitive decline is an increasingly important public health issue among older adults, particularly those residing in medically underserved areas with limited access to healthcare services. This study aimed to examine the associations of presbycusis, loneliness, frailty, and depression with cognitive function and to identify factors independently associated with cognitive function among community-dwelling older adults residing in medically underserved areas. A cross-sectional survey was conducted among 149 community-dwelling older adults aged 65 years or older residing in medically underserved areas of South Korea. Standardized questionnaires were administered to assess presbycusis, loneliness, frailty, depression, and cognitive function. Data were analyzed using Pearson correlation coefficients and stepwise multiple linear regression to identify factors independently associated with cognitive function. Cognitive function was significantly and negatively correlated with presbycusis ( r = −.32, P < .001), loneliness ( r = −.20, P = .001), frailty ( r = −.40, P < .001), and depression ( r = −.43, P < .001). In the multiple regression analysis, completion of middle school or higher ( β = .47, P < .001), age 65 to 74 years ( β = .29, P < .001), completion of elementary school ( β = .25, P < .001), absence of back pain ( β = .16, P = .010), lower depression scores ( β  = −.14, P = .027), and absence of stroke ( β = .13, P = .024) were independently associated with cognitive function. The final stepwise regression model was statistically significant ( F = 29.88, P < .001) and explained 53.9% of the variance in cognitive function. Educational attainment, age, depression, stroke, and back pain were independently associated with cognitive function among community-dwelling older adults residing in medically underserved areas. These findings support the importance of community-based strategies that consider educational, physical, and psychological factors to promote cognitive health in this population. However, because of the cross-sectional design, causal relationships could not be established. Future longitudinal studies are warranted to confirm these associations and further clarify the mechanisms underlying these associations among older adults living in medically underserved areas.

Purpose: The purpose of this study was to identify the relationships between aging anxiety, social support, and self-efficacy, and to determine the factors influencing health-promoting behaviors among late middle-aged women. Methods: This study utilized a descriptive research design. The participants were 136 late middle-aged women visiting vocational training centers in Sejong Special Self-Governing City. Data were collected using structured questionnaires regarding general characteristics, aging anxiety, social support, and self-efficacy. Physiological indicators, including blood glucose levels and body mass index (BMI), were also measured. Results: The factors significantly influencing health-promoting behaviors in late middle-aged women were social support (β=.40, p<.001), subjective health status categorized as "healthy" (β=.27, p=.019) or "average" (β=.29, p=.009), blood glucose levels (β=.17, p=.010), BMI (β=.16, p=.012), and aging anxiety (β=-.16, p=.042). These factors explained 48.9% of the total variance in health-promoting behaviors (adjusted R²=.489). Conclusion: The findings suggest that psychological, social, and physiological factors should be considered when developing health promotion strategies for late middle-aged women. Community-based programs that enhance social support and nursing interventions addressing health perception, aging anxiety, and physiological health management may help support health-promoting behaviors in this population.

Purpose: This descriptive correlational study investigated the influence of depression, diabetes-related stress, and stress coping strategies on the quality of life of parents of children with Type 1 Diabetes Mellitus. Methods: Data were collected from 153 parents using structured questionnaires and analyzed with IBM SPSS/WIN 27.0 using descriptive and inferential statistics. Results: Depression (β=-.42, p<.001) and diabetes-related stress (β=-.23, p<.001) were significant negative predictors of quality of life. Positive coping strategies were positively associated with higher quality of life. Conclusion: Early interventions targeting depression and diabetes-related stress are essential. Interventions that strengthen positive coping strategies are recommended to enhance the well-being of parents of children with type 1 Diabetes.

Purpose: This study was conducted to develop and examine the effects of a fall prevention educational program using virtual reality for nurses in integrated nursing care units to enhance their knowledge of fall prevention, attitude toward fall prevention, self-efficacy for preventing falls, fall prevention behavior, learning satisfaction, and simulation design evaluations. Methods: This study was developed based on the ADDIE (analysis, design, development, implementation, and evaluation) model. The educational contents and methods were determined based on a needs analysis conducted through a literature review, surveys on educational needs, and interviews, and content validity was verified by a group of experts. The participants were 40 nurses. The experimental group (n=20) received the virtual reality program, while the control group (n=20) received an on-the-job training video. Data were collected from March 3 to April 14, 2023, and analyzed using the IBM SPSS/WIN 27.0 program with a chi-squared test, Fisher’s exact test, independent t-test, Mann–Whitney U-test, generalized estimating equations, and a repeated measures ANOVA. Results: Statistically significant differences were found between the experimental group and the control group post-intervention in knowledge of fall prevention (x2=6.06, p=.048), self-efficacy for preventing falls (x2=22.89, p<.001), fall prevention behavior (F=3.29, p=.043), and learning satisfaction (Z=-3.03, p=.004). Conclusion: The fall prevention educational program using virtual reality for nurses enhanced nursing expertise through improved knowledge of fall prevention, self-efficacy for preventing falls, and fall prevention behavior and is expected to be utilized as basic data for patient safety nursing education in integrated nursing care unit environments.

Purpose: The purpose of this study is to determine the impact of adverse childhood experiences, positive childhood experiences, and community integration on resilience in psychiatric outpatients. Methods: The study subjects were 166 psychiatric outpatients in one general hospital in South Korea who were diagnosed with schizophrenia spectrum disorder, bipolar disorder, or depression disorder. The collected data were analyzed with the t-test, ANOVA, Pearson’s correlation coefficient, multiple regression analysis, using the SPSS/WIN 24 program. Results: There were statistically significant differences in resilience in psychiatric outpatients according to age, religion, occupation, type of household, type of diagnosed disorder. In psychiatric outpatients, resilience showed a significant positive correlation with benevolent childhood experiences and community integration, but had a negative correlation with adverse childhood experiences. Multiple regression analysis for resilience in psychiatric outpatients revealed that the significant factors affecting resilience were community integration, benevolent childhood experiences, adverse childhood experiences, housing facilities (type of household), ages 40-49, and living alone (type of household). These factors explained 52.2% of the variance. Conclusion: In order to improve the resilience of mentally ill people, a campaign is needed to increase the accessibility of community participation programs in mental health services for community integration and to publicize the influence of benevolent childhood experiences and adverse childhood experiences. Furthermore, it is necessary to identify individual factors such as residence type and age of mentally ill people, build a customized support system by considering their specific needs, and develop intervention programs to strengthen resilience.

Purpose: This study was conducted to confirm the provision standards and appropriateness of functional recovery training services performed on residents in long-term care facilities. Methods: Twenty-eight service providers working in four long-term care facilities applied the functional recovery training services to 63 older residents for 15 days, integrating them with their existing daily tasks. The contents recorded by the service providers on checklists were analyzed, and the experiences of applying functional recovery training services by the service providers were examined through focus group interviews. Results: Training for activities of daily living, excluding bathing, five items such as dressing and undressing are performed 2 to 4 times per day. The duration for one session is approximately 16 minutes for meals, around 10 minutes for bathing, and about 5 to 7 minutes for the remaining activities. Movement and walking training, covering five items like standing, occurs 2 to 3 times per day, with session durations ranging from 3 to 10 minutes. Physical activity training is conducted 1 to 2 times per day, with each session lasting about 5 to 7 minutes. Cognitive activity training is performed 1 to 2 times per day, with each session lasting approximately 4 to 7 minutes. Conclusion: For functional recovery training to be established in long-term care facilities, it is crucial to share an accurate understanding of the concept of training. Prior to the provision of training services, appropriate personnel such as nurses need to comprehensively assess the individuals and plan the training accordingly.

Purpose: This study aimed to identify factors influencing the health-related quality of life of elderly men in partial medically underserved rural areas. Methods: The subjects included 182 elderly men aged 65 or older living in the jurisdictions of the Health Care Centers in Gyeryong-, Iin-, and Jeongan-myeon, which were medically underserved rural areas in Gongju city, South Korea. Data were collected on October 13 to November 1, 2020, and were analyzed with descriptive statistics, t-test, ANOVA, Scheffé test, Pearson's correlation coefficient, and hierarchical linear regression. Results: The subjects' scored mean 24.20±3.29 points out of 30 in cognitive functions and mean 17.08±9.40 out of 60 in social support. The influential factors included three chronic diseases (β=-.50, p<.001), two chronic diseases (β=-.30, p<.001), one chronic disease (β=-.21, p=.012); fair subjective health status (β=.24, p<.001); good subjective health status (β=.25, p<.001); cognitive functions (β=.17, p=.004); aged 80 or older (β=-.16, p=.006); and brushing teeth three times per day or more (β=.14, p=.009) with an explanatory power of 53.8%. Conclusion: It is necessary to develop chronic disease management and cognitive function enhancement programs to identify factors influencing the health-related quality of life of elderly men in partial medically underserved rural areas and thus improve their health-related quality of life.

Lee GU, et al. J Korean Acad Community Health Nurs. 2022 Dec;33(4):456-464. https://doi.org/10.12799/jkachn.2022.33.4.456

(1) Background: The MMPI-2-RF is the most widely used and most researched test among the tools for assessing psychopathology, and previous studies have established its validity. Mood disorders are the most common mental disorders worldwide; they present difficulties in early detection, go undiagnosed in many cases, and have a poor prognosis. (2) Methods: We analyzed a total of 8645 participants. We used the PHQ-9 to evaluate depressive symptoms and the MDQ to evaluate hypomanic symptoms. We used the 10 MMPI-2 Restructured Form scales and 23 Specific Problems scales for the MMPI-2-RF as predictors. We performed machine learning analysis using the k-nearest neighbor classification, linear discriminant analysis, and random forest classification. (3) Results: Through the machine learning technique, depressive symptoms were predicted with an AUC of 0.634–0.767, and the corresponding value range for hypomanic symptoms was 0.770–0.840. When using RCd to predict depressive symptoms, the AUC was 0.807, but this value was 0.840 when using linear discriminant classification. When predicting hypomanic symptoms with RC9, the AUC was 0.704, but this value was 0.767 when using the linear discriminant method. (4) Conclusions: Using machine learning analysis, we defined that participants’ mood symptoms could be classified and predicted better than when using the Restructured Clinical scales.

(1) Background: Adult attention-deficit/hyperactivity disorder (ADHD) symptoms cause various social difficulties due to attention deficit and impulsivity. In addition, in contrast to ADHD in childhood, ADHD in adulthood is difficult to diagnose due to mixed psychopathologies. This study aimed to determine whether it is possible to predict ADHD symptoms in adults using the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) with machine learning (ML) techniques; (2) Methods: Data collected from 5726 college students were analyzed. The MMPI-2-Restructured Form (MMPI-2-RF) was used, and ADHD symptoms in adults were evaluated using the Attention-Deficit/Hyperactivity Disorder Self-Report Scale (ASRS). For statistical analysis, three ML algorithms were used, i.e., K-nearest neighbors (KNN), linear discriminant analysis (LDA), and random forest, with the ASRS evaluation result as the dependent variable and the 50 MMPI-2-RF scales as predictors; (3) Results: When the KNN, LDA, and random forest techniques were applied, the accuracy was 93.1%, 91.2%, and 93.6%, respectively, and the area under the curve (AUC) was 0.722, 0.806, and 0.790, respectively. The AUC of the LDA method was the largest, with an excellent level of diagnostic accuracy; (4) Conclusions: ML using the MMPI-2 in a large group could provide reliable accuracy in screening for adult ADHD.