• International journal of advanced smart convergence
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• v.8 no.3
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• pp.7-12
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• 2019

This study aimed that certain risk factors are linked to the risk of developing depression and decreasing quality of life. This study was implemented using data from the 6th and 7th Korea National Health and Nutritional Examination Survey. The National Health and Nutrition Survey consist of health surveys, screenings, and nutrition surveys. Among the risk factors, data on adult diseases such as depression, hypertension, arthritis, diabetes, cataract, glaucoma, and macular degeneration were used. In total, 12,768 adults over 20 years of age were selected, of whom 520 were diagnosed with depression. The most common risk factors in adults over 20 years of age were hypertension, arthritis, cataract, diabetes, depression, glaucoma, and macular degeneration. Their risk factors were analyzed if these were associated with depression and quality of life. The results revealed that hypertension, arthritis, diabetes, cataract, glaucoma, and macular degeneration were predictors for the occurrence of depression in adults. The factors associated with the highest risk for depression were arthritis and glaucoma. Furthermore, the study investigated the effect of certain factors on the quality of life; the factor associated with the greatest impact on quality of life was arthritis. This study verified that the aforementioned factors were related to the risk of developing depression and decreasing quality of life.

• Korean Journal of Adult Nursing
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• v.12 no.1
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• pp.147-162
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• 2000

Predicting factors of post-stroke depression were investigated. The subjects were 254 stroke patients who had been discharged and visited regularly the outpatient clinic for follow up care. The influencing factors were classified into five categories : demographic, disease-related, current state, social support, and illness intrusiveness. Sex, age, job, and educational level were defined as the demographic factor. The disease-related factors included stroke type, illness duration, attack frequency, and NIH score. ADL, cognitive function, and social activity were considered as the current state factors. The social support was measured as the perceived amount of social support. Illness intrusiveness means the perceived illness induced life style disruptions. Demographic, disease-related, current state, and social support were hypothesized to directly and indirectly affect post-stroke depression through illness intrusiveness. The illness intrusiveness was hypothesized to directly affect post-stroke depression. The hierarchial multiple regression was used to identify significant factors. The result showed that this model explained 43.3% of variance of post-stroke depression. And the prevalence of post-stroke depression was 38.8%. Among the demographic factors, job was identified as a main contributor to indirectly increase the post-stroke depression. Among the disease-related factors, stroke type, attack frequency, and NIH score were found to indirectly affect the post-stroke depression. Among the current state factors, ADL and social activity indirectly affected the post-stroke depression through illness intrusiveness. Social support and illness intrusiveness were identified to directly affect the post-stroke depression. This study has proved the factors likely to be implicated in the development of post-stroke depression. Based upon these results, it is recommended that the nurses who take care of post-stroke patients consider the risk factors such as social support, illness intrusiveness et al. Also programs which decrease the illness intrusiveness and increase the social support to reduce post-stoke depression recommended to be developed.

• Korean Journal of Biological Psychiatry
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• v.18 no.4
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• pp.181-188
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• 2011

Major depression is a devastating disorder of which lifetime prevalence rate is as high as up to 25% in general population. Although the etiology of the disorder is still poorly understood, it is generally accepted that both genetic and environmental factors are involved in the precipitation of depression. Stressful lifetime events are potent precipitating environmental factors for major depression and early-life stress is in particular an important element that predisposes individuals to major depression later in life. How environmental factors such as stress can make our neural networks susceptible to depression and how those factors leave long-lasting influences have been among the major questions in the field of depression research. Epigenetic regulations can provide a bridging mechanism between environmental factors and genetic factors so that these two factors can additively determine individual predispositions to major depression. Here we introduce epigenetic regulations as candidate mechanisms that mediate the integration of environmental adversaries with genetic predispositions, which may lead to the development of major depression, and summarize basic molecular events that underlie epigenetic regulations as well as experimental evidences that support the active role of epigenetic regulation in major depression.

• The Korean Journal of Health Service Management
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• v.8 no.3
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• pp.169-179
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• 2014

The aim of this study was to understand the factors related to depression according to gender in vulnerable elderly. We conducted a cross-sectional study with 1,709 elderly beneficiaries of the visiting health care program in Seoul. Depression was measured using the Geriatric Depression Scale Short Form Korea Version(GDSSF-K) questionnaire. Depression score was mild level in vulnerable elderly. There was no gender difference in depression level. Factors related to depression differ by gender. In the elderly men, higher depression showed significant correlation with a lower level of health-related quality of life(HRQOL) and self-rated health(SRH). In addition, higher depression was observed for elderly men living alone than for those living with family. These factors explained depression by 23.1%. In the elderly women, higher depression showed significant correlation with a lower level of HRQOL, SRH and a higher dependence of instrumental activities of daily living. In addition, higher depression was observed for elderly women who has fall experience. These factors explained depression by 22.8%. Gender-specific nursing strategies may be required for prevention of depression in vulnerable elderly.

• Women's Health Nursing
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• v.27 no.4
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• pp.326-336
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• 2021

Purpose: This study explored the prevalence of prenatal and postpartum depression in Korea and its influencing factors from 20 weeks of pregnancy to 12 weeks postpartum. Methods: Using a prospective cohort study design, data on women's depression and its influencing factors were collected at 20, 28, and 36 weeks of pregnancy and at 2, 6, and 12 weeks postpartum. The participants were 219 women and 181 spouses during pregnancy; and 183 mothers and 130 spouses after childbirth. Depressive symptoms were assessed by the Edinburgh Postnatal Depression Scale and influencing factors were measured by the Postpartum Depression Predictors Inventory-Revised, parity, and spousal depression. Results: The prevalence of maternal depression was 10.5% to 21.5% before birth, and it was 22.4% to 32.8% postpartum. The prevalence slightly decreased during the prenatal period but peaked at 2 weeks postpartum. Antenatal depression was influenced by low socioeconomic status, lower self-esteem, having experienced prenatal depression, having experienced prenatal anxiety, a previous history of depression, lower social support, lower marital satisfaction, and higher life stress. The factors influencing postpartum depression were lower self-esteem, having experienced prenatal depression, having experienced prenatal anxiety, lower social support, lower marital satisfaction, and higher life stress, as well as infant temperament and maternal blues. Parity and spousal depression had no impacts. Conclusion: The prevalence and influencing factors of maternal depression changed over time. Nurses need to screen women accordingly during the perinatal period and should provide education or counseling to prevent depression and promote adjustment to parenthood.

• Research in Community and Public Health Nursing
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• v.33 no.4
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• pp.418-431
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• 2022

Purpose: The aims of this study were to examine the rate of depression among older adults living alone and to identify factors associated with depression in older adults living alone during the COVID-19 pandemic. Methods: A secondary data analysis was performed using data from the 2020 Korea Community Health Survey. The study participants were 18,824 older adults aged 65 years and over living alone. The data of the complex sample design was analyzed with consideration for weights, stratification, and clustering. Complex sample multiple logistic regression was conducted to identify factors associated with depression in older adults living alone during the COVID-19 pandemic. Results: The results showed that the rate of depression in older adults living alone was 6.3%. Older adults living alone with decreased physical activity, decreased hours of sleep, and an increased or similar frequency of meeting with friends or neighbors were found to be more likely to have depression. In terms of factors related to the practice of COVID-19 infection prevention and control rules, not disinfecting regularly and not wearing a mask indoors were related to depression. For health-related factors, fair or poor self-rated health status, not having breakfast every day, and feeling stressed were related to depression. Conclusion: It is recommended to develop tailored interventions to prevent depression among older adults living alone by considering the factors related to their depression during the COVID-19 pandemic.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.449-455
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• 2023

The purpose of this study is to explore adolescent depression, increase understanding of social problems, and develop prevention and intervention strategies. As a research method, social big data was used to collect information related to 'youth depression', and related factors were identified through data mining and analysis of related rules. We used 'Sometrend Biz Tool' to collect and clean data from the web and then analyzed data in various languages. The study found that online articles about depression decreased during the school holidays (January to March), then increased from March to the end of June, and then decreased again from July. Therefore, it is important to establish a government-wide depression management monitoring system that can detect risk signs of adolescent depression in real time. In addition, regular stress relief and mental health education are needed during the semester, and measures must be prepared to deal with at-risk youth who share their depressed feelings in cyberspace. Results from these studies can be expected to provide important information in investigating and preventing youth depression and to contribute to policy development and intervention.

• Journal of Korean Academy of Nursing
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• v.19 no.2
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• pp.173-190
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• 1989

This literature review was undertaken to explore theoretical models of depression for their potential usefulness in nursing research and practice. Depression has bean accounted for by numerous theories or models of causation ; 11 theories selected from psychology, medicine and psychoanalysis and supported by empirical or experimental research were reviewed. These theories identify a variety of precipitating and predisposing factors that may affect the individual's depression. Aggression - turned - inward theory, object loss theory, ego functioning theory, personality organization theory, behavioral theory, learned helplessness theory, cognitive theory, genetic factors, and biological theories conceptualize predisposing factors. Only life stressors theory identifies precipitating facotrs. Each of these theories contributes to an understanding of depression, but many of them use overlapping and interrelated factors. It is also evident from recent. research that there are multiple causes for depression involving an interactive effect among predisposing and precipitating factors that are both biological and psychological in origin. That is, a single theory is not useful, but perhaps a unified theory could be developed that would be helpful to nursing. This review points to the need for continuing development and testing of theories that would integrate the multiple conceptualizations of depression.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2649-2656
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• 2013

Background: Depression is common in breast cancer patients. The aim of this paper was to make a systematic review of its prevalence and associated factors oin breast cancer survivors. Materials and Methods: An extensive systematic electronic review (PUBMED, CINAHL, PsyINFO and Ovid) and handsearch were carried out to retrieve published articles up to November 2012, using Depression OR Dysthymia AND (Cancer OR Tumor OR Neoplasms as the keywords. Information about the design of the studies, measuring scale, characteristics of the participants, prevalence of depression and its associated factors from the included studies were extracted and summarized. Results: We identified 32 eligible studies that recruited 10,826 breast cancer survivors. Most were cross-sectional or prospective designed. The most frequent instrument used to screen depression was the Center for Epidemiological Studies for Depression (CES-D, n=11 studies) followed by the Beck Depression Inventory (BDI, n=6 studies) and the Hospital Anxiety and Depression Scale (HADS, n=6 studies). CES-D returned about similar prevalence of depression (median=22%, range=13-56%) with BDI (median=22%, range=17-48%) but higher than HADS (median=10%, range=1-22%). Depression was associated with several socio-demographic variables, cancer-related factors, treatment-related factors, subject psychological factors, lifestyle factors, social support and quality of life. Conclusions: Breast cancer survivors are at risk for depression so that detection of associated factors is important in clinical practice.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.53-64
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• 2021

Depression is one of the most important psychiatric disorders worldwide. Most depression-related data mining and machine learning studies have been conducted to predict the presence of depression or to derive individual risk factors. However, since depression is caused by a combination of various factors, it is necessary to identify the complex relationship between the factors in order to establish effective anti-depression and management measures. In this study, we propose a methodology for identifying and interpreting patterns of depression expressions using the method of deriving random forest rules, where the random forest rule consists of the condition for the manifestation of the depressive pattern and the prediction result of depression when the condition is met. The analysis was carried out by subdividing into 4 groups in consideration of the different depressive patterns according to gender and age. Depression rules derived by the proposed methodology were validated by comparing them with the results of previous studies. Also, through the AUC comparison test, the depression diagnosis performance of the derived rules was evaluated, and it was not different from the performance of the existing PHQ-9 summing method. The significance of this study can be found in that it enabled the interpretation of the complex relationship between depressive factors beyond the existing studies that focused on prediction and deduction of major factors.