PURPOSE: The aim of this study was to explore the significant factors that influence quality of life in elderly patients with colorectal cancer. METHODS: A total of 107 patients with colorectal cancer completed the self-reported MD Anderson Symptom Inventory (MDASI-GI), Patient Generated Subjective Global Assessment (PG-SGA), self-care, and Functional Assesment of Illness Therapy-Colorectal (FACT-C). RESULTS: The mean scores were 87.20±19.84 for QOL, 2.80±2.25 for symptom experience, 6.84±0.58 for nutritional status, and 3.81±0.62 for self-care. The highest score was emotional well-being whereas the lowest score was social/family well-being. Factors affecting quality of life were analyzed by hierarchical multiple regression. As a result, self-care (β=.36, p<.001), symptom experience (β=-.34, p<.001), and nutritional status (β=-.25, p=.001) were identified as factors affecting quality of life. The explanation power of this regression model was 52.0% and it was statistically significant (F=23.55, p<.001). CONCLUSION: The quality of life can be improved by evaluating the comprehensive symptoms experienced by the elderly patients after colorectal cancer treatment, helping self-care, and maintaining proper nutritional status.
Aged ; Colorectal Neoplasms ; Equidae ; Humans ; Nutritional Status ; Quality of Life ; Self Care

Background: The purpose of this study was to examine the relationships between smartphone addiction of middle school students and smartphone usage types, depression, attention deficit hyperactivity disorder (ADHD), stress, interpersonal problems, and parenting attitude. In particular, we wanted to find out how smartphone usage types predict smartphone addiction when controlling depression, ADHD, perceived stress, interpersonal problems, and parenting attitudes, which are the main predictors of existing smartphone addiction in this study. Methods: The subjects of this study included 487 local middle school students (253 girls and 234 boys). The measurement instruments used were the smartphone addiction scale, patient health questionnaire-9 (PHQ-9), Korean ADHD rating scales (K-ARS), perceived stress scale (PSS), Short form of the Korean-inventory of interpersonal problems circumplex scales (KIIP-SC), and the parenting attitude scale. We identified the relationships between the variables with correlation analysis and examined the predictors of smartphone addiction with hierarchical multiple regression analysis.Result: The factors that influence smartphone addiction were sex (β = 3.14, P < 0.01), stress (β = 2.99, P < 0.01), and interpersonal problems (β = 3.81, P < 0.001). In addition, when the confounding variables of smartphone addiction were controlled to examine the effects of smartphone usage types on smartphone addiction, social network service (SNS) (β = 2.66, P < 0.01) and music/videos (β = 2.73, P < 0.01) were found to significantly positively affect smartphone addiction, whereas study (β = −2.54, P < 0.05) had a significantly negatively effect. And these factors explained 29.5% of the variance in smartphone addiction. Conclusion The order of the usage types with the highest influence on smartphone addiction was: enjoying music/videos, SNS, and study. This suggests that selective intervention depending on the main smartphone usage type can be effective.

Background: The purpose of this study was to examine the relationships between smartphone addiction of middle school students and smartphone usage types, depression, attention deficit hyperactivity disorder (ADHD), stress, interpersonal problems, and parenting attitude. In particular, we wanted to find out how smartphone usage types predict smartphone addiction when controlling depression, ADHD, perceived stress, interpersonal problems, and parenting attitudes, which are the main predictors of existing smartphone addiction in this study. Methods: The subjects of this study included 487 local middle school students (253 girls and 234 boys). The measurement instruments used were the smartphone addiction scale, patient health questionnaire-9 (PHQ-9), Korean ADHD rating scales (K-ARS), perceived stress scale (PSS), Short form of the Korean-inventory of interpersonal problems circumplex scales (KIIP-SC), and the parenting attitude scale. We identified the relationships between the variables with correlation analysis and examined the predictors of smartphone addiction with hierarchical multiple regression analysis.Result: The factors that influence smartphone addiction were sex (β = 3.14, P < 0.01), stress (β = 2.99, P < 0.01), and interpersonal problems (β = 3.81, P < 0.001). In addition, when the confounding variables of smartphone addiction were controlled to examine the effects of smartphone usage types on smartphone addiction, social network service (SNS) (β = 2.66, P < 0.01) and music/videos (β = 2.73, P < 0.01) were found to significantly positively affect smartphone addiction, whereas study (β = −2.54, P < 0.05) had a significantly negatively effect. And these factors explained 29.5% of the variance in smartphone addiction. Conclusion The order of the usage types with the highest influence on smartphone addiction was: enjoying music/videos, SNS, and study. This suggests that selective intervention depending on the main smartphone usage type can be effective.

No abstract available.
Colon ; Colonic Neoplasms ; Polyps