TY - JOUR
T1 - Relationship among symptoms, resilience, post-traumatic growth, and quality of life in patients with glioma
AU - Kim, Sung Reul
AU - Kim, Hye Young
AU - Nho, Ju Hee
AU - Ko, Eun
AU - Moon, Kyung Sub
AU - Jung, Tae Young
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/10
Y1 - 2020/10
N2 - 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.
AB - 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.
KW - Glioma
KW - Post-traumatic growth
KW - Quality of life
KW - Resilience
KW - Symptoms
UR - http://www.scopus.com/inward/record.url?scp=85091082572&partnerID=8YFLogxK
U2 - 10.1016/j.ejon.2020.101830
DO - 10.1016/j.ejon.2020.101830
M3 - Article
C2 - 32971413
AN - SCOPUS:85091082572
SN - 1462-3889
VL - 48
JO - European Journal of Oncology Nursing
JF - European Journal of Oncology Nursing
M1 - 101830
ER -