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KMID : 0869120180200020103
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기초간호자연과학회지
2018 Volume.20 No. 2 p.103 ~ p.113
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Identification of Risky Subgroups with Sleep Problems Among Adult Cancer Survivors Using Decision-tree Analyses: Based on the Korean National Health and Nutrition Examination Survey from 2013 to 2016
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Kim Hee-Sun
Park Sook-Kyoung
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Abstract
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Purpose: This study was performed to assess problems associated with sleep (short and long sleep duration) and to identify risky subgroups with sleep problems among adult cancer survivors. The study is based on the Korea National Health and Nutrition Exami- nation Survey (KNHANES VI and VII) from 2013 to 2016.
Methods: The sociodemographic and clinical data of 504 Korean cancer sur- vivors aged 20-64 years was extracted from the KNHANES VI and VII database. Descriptive statistics for complex samples was used, and decision-tree analyses were performed using the SPSS WIN 24.0 program.
Results: The mean age for survivors was approximate- ly 51 years. The mean sleep duration was 6.97 hours; 36.2% of participants had short ( < 7 hours) and 9.9% had long ( > 8 hours) sleep duration. From the decision-trees analyses, the characteristics of the adult cancer survivors related to sleep problems were presented with six different pathways. Sleep problems were analyzed according to the survivors’ sociodemographic information (age, educa- tion, living status, and occupation), clinical characteristics (body mass index, hypercholesterolemia, and anemia) and health-related quality of life (HRQoL). The HRQoL ( ≤ 0.5 or > 0.5 cutoff point) was a significant predictor of the participants’ sleep problems because all six pathways were started from this predictor in the model.
Conclusion: Health care professionals could use the decision-tree model for screening adult cancer survivors with sleep problems in clinical or community settings. Nursing interventions considering these specific individual characteristics and HRQoL level should be developed to have adequate sleep duration for Korean adult can- cer survivors.
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KEYWORD
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Neoplasm, Sleep, Decisiontrees
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