Purpose
To identify factors associated with Quality of Life (QOL) in disaster female victims.
Methods
A descriptive cross-sectional design used secondary data from the 2018 long-term survey on the change of life of disaster victims conducted by the National Disaster Management Research Institute (NDMI). The participants were 1,267 female victims over the age of 20 who completed a survey including QOL, resilience, perceived health status, depression, anxiety, Post-Traumatic Stress (PTS), social adaptation, and social support. Descriptive statistics, chi-square-test, independent t-test, and a decision tree were used for data analysis.
Results
The decision tree identified 8 final nodes predicting QOL of disaster female victims. Resilience was associated with quality of life (△p<.001, F=115.14). The mean QOL was 2.81 with predicted rate of 55.7% in the Low Resilience Group (LRG) and 3.24 with predicted rate of 44.3% in the High Resilience Group (HRG). The highest QOL group in LRG was Node 9 with perceived health status of more than 3 and low depression (mean=3.17), while the lowest QOL group was Node 3 with perceived health status of less than 2 (mean=2.54). The highest QOL group in HRG was Node 8 with social support of more than 3.92 (mean=3.57), while the lowest group was Node 12 with high anxiety (mean=2.81).
Conclusion
Factors predicting the QOL of disaster victims differed between HRG and LRG. In order to improve QOL of disaster victims, customized interventions according to the level of resilience are needed.

Citations

• Trajectories of quality of life among disaster victims: A national longitudinal study
  Haeyoung Lee, Yujeong Kim
  International Nursing Review.2025;[Epub]     CrossRef
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  Scientific Reports.2025;[Epub]     CrossRef
• Prediction model for post-retirement depression in the older population: A cross-sectional study
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  Journal of Korean Gerontological Nursing.2025; 27(1): 21.     CrossRef
• Prediction model of weight control experience in men with obesity in their 30 s and 40 s using decision tree analysis
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  Scientific Reports.2024;[Epub]     CrossRef
• Prediction model of health checkup and cancer screening experience of elderly population using 2021 Community Health Survey
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• Prediction model for identifying high-risk groups for overweight or obesity among Korean men in their 30s and 40s
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  BMC Public Health.2024;[Epub]     CrossRef
• Prediction model of quality of life using the decision tree model in older adult single-person households: a secondary data analysis
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  Frontiers in Public Health.2023;[Epub]     CrossRef
• A model for predicting fall experience in the elderly population over 65 years old: Decision tree analysis
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  Journal of Korean Gerontological Nursing.2022; 24(4): 366.     CrossRef