Relationship among symptoms, resilience, post-traumatic growth, and quality of life in patients with glioma. (October 2020)

• Record Type: Journal Article
• Authors: Kim, Sung Reul; Kim, Hye Young; Nho, Ju-Hee; Ko, Eun; Moon, Kyung-Sub; Jung, Tae-Young
• Is Part Of: European journal of oncology nursing. Volume 48(2020)
• Publication Date: 2020-10
• Subjects: Glioma -- Post-traumatic growth -- Quality of life -- Resilience -- Symptoms; Cancer -- Nursing -- Periodicals; Cancer -- Research -- Periodicals; Oncology -- Periodicals; Oncology Nursing -- Periodicals; Neoplasms -- nursing -- Periodicals; Cancer -- Soins infirmiers -- Périodiques; Cancer -- Recherche -- Périodiques; Cancérologie -- Périodiques; Verpleegkunde; Kanker; Cancer -- Nursing; Cancer -- Research; Oncology; Electronic journals; Periodicals; Electronic journals; 616.9940231
• DOI: 10.1016/j.ejon.2020.101830
• Languages: English
• ISSNs: 1462-3889

Abstract

Abstract: Purpose: The aims of this study were to explore the relationship among symptoms, resilience, post-traumatic growth, and quality of life, and to identify the influence of these variables on quality of life in patients with glioma. Methods: A correlational, cross-sectional research design was used. A convenience sample of 120 patients was recruited from an outpatient neurosurgery clinic. Data analyses included descriptive statistics, independent t -test, one-way ANOVA, Pearson's correlation coefficient, and hierarchical regression analysis and were performed with the SPSS WIN 25.0 program. Results: Quality of life positively correlated with the duration of disease diagnosis and resilience and negatively correlated with age, age at onset, severity of symptoms, and interference in symptoms. Resilience was negatively correlated with severity of symptoms and interference with symptoms, and was positively correlated with post-traumatic growth. Hierarchical regression analysis showed that demographic and clinical factors explained 39.3% of the variance in quality of life in glioma patients. The explanatory power increased by 22.1% and 15.1%, respectively, when interference in symptoms and resilience were considered. Conclusions: Assessment of quality of life in patients with glioma should consider symptoms and resilience, along with demographic and clinical factors. Interventions developed to improve quality of life in glioma patients must also consider these factors. Highlights: Resilience had the greatest influence on quality of life among patients for glioma. Assessment of quality of life should consider symptoms and resilience, along with demographic and clinical factors. Interventions developed to improve quality of life in glioma patients must consider these factors.