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Purpose: This cross-sectional study aimed to explore the factors that affect quality of life (QOL) in patients diagnosed with primary lung cancer. Methods: Data were collected from 129 patients with stages 1 to 3 primary lung cancer who had visited the outpatient oncology-hematology department of a university-affiliated hospital in Gyeonggi Province from January 2024 to March 2024. The data were then analyzed using descriptive statistics, an independent t-test, one-way ANOVA, Pearson's correlation coefficient, and hierarchical regression analysis using the SPSS 25.0 program. Results: The mean score of QOL in the participants was 74.62±19.84. A hierarchical regression analysis revealed that symptom experience (β=-0.29, p<.001), depression (β=-0.46, p<.001), social support (β=0.18, p=.003), and marital status (β=0.11, p=.047) significantly affected QOL among patients with primary lung cancer. The regression model explained 64% of the variation in QOL. Conclusion: The results demonstrated that patients would benefit from the development and implementation of nursing interventions that focus on reducing symptoms and depression, as well as improving social support, in order to improve their QOL. [ABSTRACT FROM AUTHOR]

Purpose: This study examined the prevalence and severity of symptoms and symptom clusters and the relationship between symptom clusters and quality of life (QoL) in people with long COVID. Methods: This descriptive study analyzed data from 220 adults with at least one symptom of long COVID for at least 4 weeks through an online survey from August 18 to September 5, 2022. Results: The most frequent symptoms of long COVID were fatigue (94.5%), sore throat (89.1%), post-exertional malaise (88.2%), cough (88.2%), and fever (85.5%), and the most severe symptoms were fatigue (6.21±2.31), sore throat (5.78±2.78), cough (5.64±2.84), post-exertional malaise (5.46±2.64), and fever (5.21±2.90). Exploratory factor analysis revealed five distinct symptom clusters: digestive-cognitive, respiratory-fatigue, pain-dermatological, sensory, and emotional clusters. The QoL of the higher-symptom group was lower than that of the lower-symptom group (t=2.34; p=.020). Furthermore, the symptom clusters experienced by people with long COVID were associated with QoL. Conclusion: Healthcare providers must recognize symptom clusters and intervene accordingly, and nursing interventions should be developed to effectively care for individuals in these symptom clusters. [ABSTRACT FROM AUTHOR]

Background: Individuals with schizophrenia experience premature mortality by approximately 15 to 20 years compared to the general population. The most common cause of death in schizophrenia is cardiovascular disorder, yet cardiovascular disease-related conditions are often neglected in the treatment of schizophrenia. Current Concepts: The overall incidence rate of cardiovascular disorders in patients with schizophrenia is about 10%. Diverse risk factors likely contribute to the association, with increased risk of metabolic syndrome, unhealthy lifestyle behaviors like smoking and a sedentary lifestyle, and an unhealthy diet playing a prominent role. While the effects of certain psychotropic medications, particularly atypical antipsychotics, may contribute to the presence of metabolic syndrome, their ability to reduce the psychiatric symptom burden reduces mortality. Shared pathophysiological mechanisms, including genetic, psychological, and inflammatory factors, have also been suggested. In particular, increased inflammation directly associated with disease-related brain activity may further impact the cardiovascular risk. Discussion and Conclusion: Regular monitoring of metabolic syndrome, with psychoeducation for patients and their caregivers, is crucial to promote optimal cardiovascular health. Implementation of active psychosocial interventions targeted at behavior change is necessary. In addition, education to reduce stigma among medical professionals is warranted to improve communication between patients and medical professionals. [ABSTRACT FROM AUTHOR]

Purpose: The number of breast cancer patients in Korea has steadily increased. However, there are few studies addressing quality of life of patients undergoing breast cancer treatment in Korea. This study aimed to identify predictors of quality of life among patients undergoing breast cancer treatment. Methods: This descriptive, cross-sectional study included 142 patients with breast cancer undergoing treatment in a cancer hospital. Data were collected using the MD Anderson Symptom Inventory, Multidimensional Scale of Perceived Social Support, Breast Cancer Survivors Scale, eHealth Literacy Scale, and the Functional Assessment of Cancer Therapy-Breast Cancer through self-administered questionnaires from January 12 to December 6, 2022. Differences in the level of quality of life according to demographic and clinical variables and correlations among continuous variables were identified using univariate statistics, and hierarchical multiple regression was used to identify predictors of quality of life. Results: Employment status, comorbidities, disease duration, and cancer stage were demographic and clinical variables that showed significant associations with quality of life. Symptom burden, social support, self-efficacy, and eHealth literacy were also significantly associated with quality of life. The predictors of quality of life were employment status (β=.13, p=.009), cancer stage (β=.12, p=.033), symptom severity (p=-.14, p=.044), symptom interference (β=-.30, p<.001), social support (β=.13, p=.025), and self-efficacy (β=.46, p<.001). The explanatory power was approximately 69% (F=26.90, p<.001). Conclusion: Nursing interventions should be implemented for patients undergoing breast cancer treatment to improve their quality of life while reducing the symptom burden and enhancing self-efficacy and social support. [ABSTRACT FROM AUTHOR]