Journal of Korean Academy of Nursing

Research Papers

Formative versus reflective measurement models in nursing research: a secondary data analysis of a cross-sectional study in Korea: Eun Seo Park, Young Il Cho, Hyo Jin Kim, YeoJin Im, Dong Hee Kim; J Korean Acad Nurs 2025;55(1):107-118. Published online February 19, 2025; DOI: https://doi.org/10.4040/jkan.24095

Abstract PDF ePub: Purpose
This study aimed to empirically verify the impact of measurement model selection on research outcomes and their interpretation through an analysis of children’s emotional and social problems measured by the Pediatric Symptom Checklist (PSC) using both reflective and formative measurement models. These models were represented by covariance-based structural equation modeling (CB-SEM) and partial least squares SEM (PLS-SEM), respectively.
Methods
This secondary data analysis evaluated children’s emotional and social problems as both reflective and formative constructs. Reflective models were analyzed using CB-SEM, while formative models were assessed using PLS-SEM. Comparisons between these two approaches were based on model fit and parameter estimates.
Results
In the CB-SEM analysis, which assumed a reflective measurement model, a model was not identified due to inadequate fit indices and a Heywood case, indicating improper model specification. In contrast, the PLS-SEM analysis, assuming a formative measurement model, demonstrated adequate reliability and validity with significant path coefficients, supporting the appropriateness of the formative model for the PSC.
Conclusion
The findings indicate that the PSC is more appropriately analyzed as a formative measurement model using PLS-SEM, rather than as a reflective model using CB-SEM. This study highlights the necessity of selecting an appropriate measurement model based on the theoretical and empirical characteristics of constructs in nursing research. Future research should ensure that the nature of measurement variables is accurately reflected in the choice of statistical models to improve the validity of research outcomes.

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An Investigation of the Cumulative Effects of Depressive Symptoms on the Cognitive Function in Community-Dwelling Older Adults: Analysis of the Korean Longitudinal Study of Aging: Kim, Eunmi , Oh, Jinkyung , Huh, Iksoo; J Korean Acad Nurs 2023;53(4):453-467. Published online August 31, 2023; DOI: https://doi.org/10.4040/jkan.23018

Purpose
This study investigated the cumulative effects of depressive symptoms on cognitive function over time in community-dwelling older adults. Methods: Data were investigated from 2,533 community-dwelling older adults who participated in the Korean Longitudinal Study of Aging (KLoSA) from the 5th (2014) to the 8th wave (2020). The association between cumulative depressive symptoms and cognitive function was identified through multiple regression analysis. Results: When the multiple regression analysis was conducted from each wave, the current depressive symptoms scores and cognitive function scores were negatively associated, regardless of the waves (B5th = - 0.26, B6th = - 0.26, B7th = - 0.26, and B8th = - 0.27; all p < .001). Further, when all the previous depressive symptoms scores were added as explanatory variables in the 8th wave, the current one (B8th = - 0.09, p < .001) and the previous ones (B5th = - 0.11, B6th = - 0.09, and B7th = - 0.13; all p < .001) were also negatively associated with the cognitive function score. The delta R² , which indicates the difference between the model’s R² with and without the depressive symptoms scores, was greater in the model with all the previous and current depressive symptoms scores (6.4%) than in the model with only the current depressive symptoms score (3.6%). Conclusion: Depressive symptoms in older adults have a long-term impact. This results in an accumulated adverse effect on the cognitive function. Therefore, to prevent cognitive decline in older adults, we suggest detecting their depressive symptoms early and providing continuous intervention to reduce exposure to long-term depressive symptoms.

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Systematic identification and quantification of factors and their interactions with age, sex, and panel wave influencing cognitive function in Korean older adults
Eunmi Kim, Jinkyung Oh, Jungsoo Gim, Iksoo Huh
Frontiers in Public Health.2025;[Epub] CrossRef

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Influence of Social Capital on Depression of Older Adults Living in Rural Area: A Cross-Sectional Study Using the 2019 Korea Community Health Survey: Jung, Minho , Kim, Jinhyun; J Korean Acad Nurs 2022;52(2):144-156. Published online April 30, 2022; DOI: https://doi.org/10.4040/jkan.21239

Abstract PDF

Purpose
This study aimed to investigate the influence of social capital on the depression of older adults living in rural areas.
Methods
Data sets were obtained from the 2019 Korea Community Health Survey. The participants were 39,390 older adults over 65 years old living in rural areas. Indicators of social capital included trust, reciprocity, network, and social participation. Depression—the dependent variable—was measured using the Patient Health Questionnaire-9 (PHQ-9). Hierarchical ordinal logistic regression was conducted to identify factors associated with depression after adjusting the data numbers to 102,601 by applying the Synthetic Minority Oversampling Technique (SMOTE).
Results
The independent variables—indicators of social capital—exhibited significant association with the depression of older adults. The odds ratios of depression were higher in groups without social capital variables.
Conclusion
To reduce depression, we recommend increasing social capital. Factors identified in this study need to be considered in older adult depression intervention programs and policies.

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The Effects of Perceived Stress on Depression among Middle-aged Adults with Diabetes Mellitus in Korea: Exploring the Mediating Role of Social Capital through a Descriptive Correlational Study
Kyung Ae Kim, Mi Ran Bang
Korean Journal of Adult Nursing.2025; 37(1): 50. CrossRef
An Observational Study on the Association Between Nutritional Intake and Mental Health Among Older Adults in Rural Areas
Kyeongmin Jang
Nursing & Health Sciences.2025;[Epub] CrossRef
Prediction model of weight control experience in men with obesity in their 30 s and 40 s using decision tree analysis
Myeunghee Han
Scientific Reports.2024;[Epub] CrossRef
The relationship between human capital and depression among middle-aged rural adults: The multiple-parallel mediating effects of social capital
Soo Mi Jang, Hyung Mi Ha
Korean Journal of Health Education and Promotion.2023; 40(1): 33. CrossRef

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Development of a Diabetic Foot Ulceration Prediction Model and Nomogram: Lee, Eun Joo , Jeong, Ihn Sook , Woo, Seung Hun , Jung, Hyuk Jae , Han, Eun Jin , Kang, Chang Wan , Hyun, Sookyung; J Korean Acad Nurs 2021;51(3):280-293. Published online June 30, 2021; DOI: https://doi.org/10.4040/jkan.20257

Abstract PDF

Purpose
This study aimed to identify the risk factors for diabetic foot ulceration (DFU) to develop and evaluate the performance of a DFU prediction model and nomogram among people with diabetes mellitus (DM).
Methods
This unmatched case-control study was conducted with 379 adult patients (118 patients with DM and 261 controls) from four general hospitals in South Korea. Data were collected through a structured questionnaire, foot examination, and review of patients’ electronic health records. Multiple logistic regression analysis was performed to build the DFU prediction model and nomogram. Further, their performance was analyzed using the Lemeshow–Hosmer test, concordance statistic (C-statistic), and sensitivity/specificity analyses in training and test samples.
Results
The prediction model was based on risk factors including previous foot ulcer or amputation, peripheral vascular disease, peripheral neuropathy, current smoking, and chronic kidney disease. The calibration of the DFU nomogram was appropriate (χ² = 5.85, p = .321). The C-statistic of the DFU nomogram was .95 (95% confidence interval .93~.97) for both the training and test samples. For clinical usefulness, the sensitivity and specificity obtained were 88.5% and 85.7%, respectively at 110 points in the training sample. The performance of the nomogram was better in male patients or those having DM for more than 10 years.
Conclusion
The nomogram of the DFU prediction model shows good performance, and is thereby recommended for monitoring the risk of DFU and preventing the occurrence of DFU in people with DM.

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A Simple Nomogram for Predicting Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke
Youn-Jung Lee, Hee Jung Jang
Healthcare.2023; 11(23): 3015. CrossRef
Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis
Xiaobing Liu, Caili Yan, Xiuxiu Niu, Jiechun Zeng, Fahd Abd Algalil
Applied Bionics and Biomechanics.2022; 2022: 1. CrossRef
Prognostic factors in diabetes: Comparison of Chi-square automatic interaction detector (CHAID) decision tree technology and logistic regression
Hae-Young Choi, Eun-Yeob Kim, Jaeyoung Kim
Medicine.2022; 101(42): e31343. CrossRef

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Comparison of the Prediction Model of Adolescents’ Suicide Attempt Using Logistic Regression and Decision Tree: Secondary Data Analysis of the 2019 Youth Health Risk Behavior Web-Based Survey: Lee, Yoonju , Kim, Heejin , Lee, Yesul , Jeong, Hyesun; J Korean Acad Nurs 2021;51(1):40-53. Published online February 28, 2021; DOI: https://doi.org/10.4040/jkan.20207

Abstract PDF

Purpose
The purpose of this study was to develop and compare the prediction model for suicide attempts by Korean adolescents using logistic regression and decision tree analysis. Methods: This study utilized secondary data drawn from the 2019 Youth Health Risk Behavior web-based survey. A total of 20 items were selected as the explanatory variables (5 of sociodemographic characteristics, 10 of health-related behaviors, and 5 of psychosocial characteristics). For data analysis, descriptive statistics and logistic regression with complex samples and decision tree analysis were performed using IBM SPSS ver. 25.0 and Stata ver. 16.0.
Results
A total of 1,731 participants (3.0%) out of 57,303 responded that they had attempted suicide. The most significant predictors of suicide attempts as determined using the logistic regression model were experience of sadness and hopelessness, substance abuse, and violent victimization. Girls who have experience of sadness and hopelessness, and experience of substance abuse have been identified as the most vulnerable group in suicide attempts in the decision tree model.
Conclusion
Experiences of sadness and hopelessness, experiences of substance abuse, and experiences of violent victimization are the common major predictors of suicide attempts in both logistic regression and decision tree models, and the predict rates of both models were similar. We suggest to provide programs considering combination of high-risk predictors for adolescents to prevent suicide attempt.

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Meekang Sung, Jihye Han, Carrie G. Wade, Vaughan W. Rees
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Risk prediction models for adolescent suicide: A systematic review and meta-analysis
Ruitong Li, Yuchuan Yue, Xujie Gu, Lingling Xiong, Meiqi Luo, Ling Li
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A prediction model for adolescents’ skipping breakfast using the CART algorithm for decision trees: 7th (2016–2018) Korea National Health and Nutrition Examination Survey
Sun A Choi, Sung Suk Chung, Jeong Ok Rho
Journal of Nutrition and Health.2023; 56(3): 300. CrossRef
Development of Prediction Model for Suicide Attempts Using the Korean Youth Health Behavior Web-Based Survey in Korean Middle and High School Students
Younggeun Kim, Sung-Il Woo, Sang Woo Hahn, Yeon Jung Lee, Minjae Kim, Hyeonseo Jin, Jiyeon Kim, Jaeuk Hwang
Journal of Korean Neuropsychiatric Association.2023; 62(3): 95. CrossRef
Effects of Stress on Suicide Behavior among Adolescents: An Analysis of Online Survey Data on Youth Health Behavior Using Propensity Score Matching
Chung Hee Woo, Ju Young Park
Korean Journal of Stress Research.2021; 29(3): 199. CrossRef

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Original Articles

Scale Development and Model Validation for the Process of Exercise Engagement for People with Prediabetes: Chang, Shu-Chuan , Yeh, Hsiu-Chen , Kuo, Yu-Lun; J Korean Acad Nurs 2020;50(2):298-312. Published online April 30, 2020; DOI: https://doi.org/10.4040/jkan.2020.50.2.298

Abstract PDF

Purpose
This study had two objectives: 1) to develop a scale for the process of exercise engagement (SPEE) for prediabetic individuals (PDIs); 2) to validate a structural model for the process of exercise engagement for PDIs.
Methods
A cross-sectional survey with simple random sampling was conducted from September 2013 to December 2015 (in Taiwan). A total of 310 PDIs were enrolled for scale development and model validation via item analysis, factor analyses, and structural equation modeling. The Kuo model was used as the basis for developing the Chinese version of the SPEE for PDIs.
Results
The SPEE contains five subscales with a total of twenty-one items that account for 54.9% to 65.9% of the total variance explained for assessing participants’ process of engagement during exercise. For Kuo model validation, the model measures indicated goodness of fit between the Kuo model and sample data. Analysis further revealed a direct effect between the creating health blueprints (CHB) stage and the spontaneous regular exercise (SRE) stage (b=.60).
Conclusion
The SPEE includes five subscales for assessing the psychological transition and behavioral expression at each stage of the process of exercise engagement for PDIs. The SPEE for people with prediabetes provides deeper insights into the factors of behavioral change stages that are required to initiate long-term health care outcomes and avoid developing diabetes. These insights are significant as they allow for patient- specific mapping and behavior modification to effect exercise.

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Prediyabet hastalarında egzersiz katılım süreci ölçeği geçerlik-güvenirlik çalışması
Melek Öztürk, Tülay Ortabağ
Health Care Academician Journal.2024;[Epub] CrossRef
Prediyabetli hastalarda Egzersiz Yarar/Engel Ölçeği Türkçe versiyonunun güvenirliği ve geçerliliği
Tülay ORTABAĞ, Melek ÖZTÜRK
Journal of Exercise Therapy and Rehabilitation.2023; 10(2): 147. CrossRef
The COVID-19 Vaccine Knowledge and Attitude Scale: A Methodological Study
Kemal Elyeli, Hatice Bebiş
Cyprus Journal of Medical Sciences.2022; 7(3): 312. CrossRef

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Prediction Models of Mild Cognitive Impairment Using the Korea Longitudinal Study of Ageing: Park, Hyojin , Ha, Juyoung; J Korean Acad Nurs 2020;50(2):191-199. Published online April 30, 2020; DOI: https://doi.org/10.4040/jkan.2020.50.2.191

Abstract PDF

Purpose
The purpose of this study was to compare sociodemographic characteristics of a normal cognitive group and mild cognitive impairment group, and establish prediction models of Mild Cognitive Impairment (MCI).
Methods
This study was a secondary data analysis research using data from “the 4th Korea Longitudinal Study of Ageing” of the Korea Employment Information Service. A total of 6,405 individuals, including 1,329 individuals with MCI and 5,076 individuals with normal cognitive abilities, were part of the study. Based on the panel survey items, the research used 28 variables. The methods of analysis included a c2-test, logistic regression analysis, decision tree analysis, predicted error rate, and an ROC curve calculated using SPSS 23.0 and SAS 13.2.
Results
In the MCI group, the mean age was 71.4 and 65.8% of the participants was women. There were statistically significant differences in gender, age, and education in both groups. Predictors of MCI determined by using a logistic regression analysis were gender, age, education, instrumental activity of daily living (IADL), perceived health status, participation group, cultural activities, and life satisfaction. Decision tree analysis of predictors of MCI identified education, age, life satisfaction, and IADL as predictors.
Conclusion
The accuracy of logistic regression model for MCI is slightly higher than that of decision tree model. The implementation of the prediction model for MCI established in this study may be utilized to identify middle-aged and elderly people with risks of MCI. Therefore, this study may contribute to the prevention and reduction of dementia.

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Nomogram for predicting changes in cognitive function in community dwelling older adults with mild cognitive impairment based on Korea Longitudinal Study of Ageing Panel Data: a retrospective study
Hyuk Joon Kim, Hye Young Kim
Journal of Korean Academy of Nursing.2025; 55(1): 50. CrossRef
Cognitive Dysfunction Prediction Model with Lifelog Dataset based on Random Forest and SHAP
Myeongjin Lee, Jongun Lee, Hanjun Lee
The Journal of Korean Institute of Information Technology.2024; 22(1): 1. CrossRef
Sociodemographic Factors Predict Incident Mild Cognitive Impairment: A Brief Review and Empirical Study
Shuyi Jin, Chenxi Li, Jiani Miao, Jingyi Sun, Zhenqing Yang, Xingqi Cao, Kaili Sun, Xiaoting Liu, Lina Ma, Xin Xu, Zuyun Liu
Journal of the American Medical Directors Association.2023; 24(12): 1959. CrossRef
Characteristics and Factors Associated with Cognitive Decline of Elderly with Mild Cognitive Impairment
Eul Hee Roh
Journal of Health Informatics and Statistics.2023; 48(3): 179. CrossRef
Detection and Intervention of Subjective Cognitive Decline in Pre-Alzheimer’s Disease
雅红何
International Journal of Psychiatry and Neurology.2022; 11(04): 65. CrossRef
Influencing Factors of Subjective Cognitive Impairment in Middle-Aged and Older Adults
Min Roh, Hyunju Dan, Oksoo Kim
International Journal of Environmental Research and Public Health.2021; 18(21): 11488. CrossRef

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The Structural Analysis of Variables Related to Posttraumatic Growth among Psychiatric Nurses: Hyun Ju Yeo, Hyun Suk Park; J Korean Acad Nurs 2020;50(1):26-38. Published online January 31, 2020; DOI: https://doi.org/10.4040/jkan.2020.50.1.26

Abstract PDF

Abstract Purpose:

The purpose of this study was to explain a structural model of posttraumatic growth among psychiatric nurses based on existing models and a literature review and verify its effectiveness.

Methods:

Data were collected from psychiatric nurses in one special city, four metropolitan cities, and three regional cities from February to March 2016. Exogenous variables included hardiness and distress perception, while endogenous variables included self-disclosure, social support, deliberate rumination, and posttraumatic growth. Data from 489 psychiatric nurses were analyzed using IBM SPSS Statistics 19.0 and AMOS 20.0.

Results:

The modified model was a good fit for the data. Tests on significance of the pathways of the modified model showed that nine of the 14 paths were supported, and the explanatory power of posttraumatic growth by included variables in the model was 69.2%. For posttraumatic growth among psychiatric nurses, deliberate rumination had a direct effect as the variable that had the largest influence. Indirect effects were found in the order of hardiness, social support, and distress perception. Self-disclosure showed both direct and indirect effects.

Conclusion

A strategy to improve deliberate rumination is necessary when seeking to improve posttraumatic growth among psychiatric nurses. Enhancing psychiatric nurses’ hardiness before trauma would enable them to actively express negative emotions after trauma, allowing them to receive more social support. This would improve deliberate rumination and consequently help promote psychological growth among psychiatric nurses who have experienced trauma.

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Factors Affecting Posttraumatic Growth of Nurses Caring for Patients with COVID-19 in Regional Medical Centers
Jaehwa Bae, Eun Suk Choi
Research in Community and Public Health Nursing.2025; 36: 9. CrossRef
Mediating mechanism of posttraumatic growth as buffers of burnout and PTSD among nurses during the COVID-19 pandemic
Jae-Chang Sim, Sun-Kyung Cha, Sun-Young Im
Frontiers in Public Health.2024;[Epub] CrossRef
The effect of alexithymia on distress disclosure among nurses: the mediating role of resilience
Qianru Liu, Xuetai Jian, Fangyu Peng, Meng Wang, Jiaxin Li, Xinru Deng, Yinglu Wan, Li Geng
Current Psychology.2024; 43(25): 21931. CrossRef
Effects of compassion satisfaction and compassion fatigue on posttraumatic growth of psychiatric nurses: A cross‐sectional study
Li Zeng, Guiling Liu, Fen Feng, Yinong Qiu, Shuping Wang, Meng Yu, Jialin Wang
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Soo Young An, Heejung Choi
Journal of Korean Academy of Nursing.2023; 53(3): 309. CrossRef
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Jing Liu, Sha Wei, Guohong Qiu, Ni Li, Delin Wang, Xiaohou Wu, Xiangzhi Gan, Hongmei Yi
Preventive Medicine Reports.2023; 34: 102266. CrossRef
Promotion factors of emergency nurses’ post-traumatic growth during the COVID-19 pandemic in Shanghai: a qualitative study
Jinxia Jiang, Peng Han, Yue Liu, Qian Wu, Haiyan Shao, Xia Duan, Yan Shi
BMC Nursing.2023;[Epub] CrossRef
Post-traumatic growth experience of first-line emergency nurses infected with COVID-19 during the epidemic period—A qualitative study in Shanghai, China
Jinxia Jiang, Peng Han, Xiangdong Huang, Yue Liu, Haiyan Shao, Li Zeng, Xia Duan
Frontiers in Public Health.2022;[Epub] CrossRef
Post-Traumatic Growth of Nurses in COVID-19 Designated Hospitals in Korea
Suk-Jung Han, Ji-Young Chun, Hye-Jin Bae
International Journal of Environmental Research and Public Health.2022; 20(1): 56. CrossRef
Factors Influencing Post-traumatic Growth of Nurses at Nationally Designated Infectious Disease Hospital
Ji Eun Oh, Ju Young Park
Journal of Korean Academy of Nursing Administration.2022; 28(5): 499. CrossRef
Factors influencing posttraumatic growth among nurses caring for COVID‐19 patients: A path analysis
Ju Young Yim, Jung A Kim
Journal of Nursing Management.2022; 30(6): 1940. CrossRef
Post-traumatic Growth and it’s associations with Deliberate Rumination, Self-disclosure, and Social Support among Intensive Care Unit Nurses
Sae Mi Min, Hee Jun Kim, Chun-Ja Kim, Jeong-Ah Ahn
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Predictors of posttraumatic growth of intensive care unit nurses in Korea
Ae Kyung Chang, Hyejin Yoon, Ji Hyun Jang
Japan Journal of Nursing Science.2021;[Epub] CrossRef
Association of Nursing Work Environment, Relationship with the Head Nurse, and Resilience with Post-Traumatic Growth in Emergency Department Nurses
Sun-Young Jung, Jin-Hwa Park
International Journal of Environmental Research and Public Health.2021; 18(6): 2857. CrossRef

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A Structural Equation Model for Happiness in Mothers with Young Children: Mijung Yeom, Soo Yang; J Korean Acad Nurs 2019;49(3):241-253. Published online January 15, 2019; DOI: https://doi.org/10.4040/jkan.2019.49.3.241

Abstract PDF

Abstract Purpose

This study aimed to develop and test a model of the happiness of mothers with young children based on the stress-coping-adaptation model of Lazarus and Folkman.

Methods

The data collection period was from May to July 2016. A self-report questionnaire was used to collect data from 210 mothers with children under 5 years of age living in Seoul, Gyeonggi, and Gangwon provinces. The exogenous variable was parenting stress, and the endogenous variables were parenting alliance, depression, optimism, ways of coping, and happiness. Data from 201 questionnaires were analyzed using the SPSS 22.0 and AMOS 20.0 programs. Data analyses included descriptive statistics, factor analysis, and structural equation modeling.

Results

The final modified model showed a reasonable fit to the data, and out of 25 paths, 13 were statistically significant. This model explained 78.4% of the variance in the happiness of mothers with young children and confirmed that depression, optimism, parenting alliance, and social support-focused coping have a direct effect on the subject's happiness. Parenting stress also influenced happiness through parenting alliance, depression, and optimism.

Conclusion

In order to bolster the happiness of mothers with young children, positive psychological interventions that can minimize psychological vulnerabilities, such as depression, and that can enhance their strengths, such as optimism, may serve as effective ways of coping with and adapting to stress.

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Spousal support, parent–nurse partnership and caregiver burden among parents of children with chronic diseases: A cross‐sectional study
Jihye Kim, Heemin Chae, Yoonjung Kim
Journal of Clinical Nursing.2024; 33(7): 2649. CrossRef
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Gijung Jung, Ji Sun Ha, Mihyeon Seong, Ji Hyeun Song
Sage Open.2023;[Epub] CrossRef
The significant mediators between depression and mental health recovery among community-dwelling people with a diagnosed mental disorder
Won Hee Jun, Gyungjoo Lee
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Testing a Model to Predict Problem Gambling in Speculative Game Users: Hyangjin Park, Suk-Sun Kim; J Korean Acad Nurs 2018;48(2):195-207. Published online January 15, 2018; DOI: https://doi.org/10.4040/jkan.2018.48.2.195

Abstract PDF: Abstract Purpose
The purpose of the study was to develop and test a model for predicting problem gambling in speculative game users based on Blaszczynski and Nower's pathways model of problem and pathological gambling.
Methods
The participants were 262 speculative game users recruited from seven speculative gambling places located in Seoul, Gangwon, and Gyeonggi, Korea. They completed a structured self-report questionnaire comprising measures of problem gambling, negative emotions, attentional impulsivity, motor impulsivity, non-planning impulsivity, gambler's fallacy, and gambling self-efficacy. Structural Equation Modeling was used to test the hypothesized model and to examine the direct and indirect effects on problem gambling in speculative game users using SPSS 22.0 and AMOS 20.0 programs.
Results
The hypothetical research model provided a reasonable fit to the data. Negative emotions, motor impulsivity, gambler's fallacy, and gambling self-efficacy had direct effects on problem gambling in speculative game users, while indirect effects were reported for negative emotions, motor impulsivity, and gambler's fallacy. These predictors explained 75.2% problem gambling in speculative game users.
Conclusion
The findings suggest that developing intervention programs to reduce negative emotions, motor impulsivity, and gambler's fallacy, and to increase gambling self-efficacy in speculative game users are needed to prevent their problem gambling.

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A Structural Model for Premenstrual Coping in University Students: Based on Biopsychosocial Model: Myung-Ock Chae, Hae Ok Jeon, Ahrin Kim; J Korean Acad Nurs 2017;47(2):257-266. Published online April 28, 2017; DOI: https://doi.org/10.4040/jkan.2017.47.2.257

Abstract PDF

Purpose

The aims of this study were to construct a hypothetical structural model which explains premenstrual coping in university students and to test the fitness with collected data.

Methods

Participants were 206 unmarried women university students from 3 universities in A and B cities. Data were collected from March 29 until April 30, 2016 using self-report structured questionnaires and were analyzed using IBM SPSS 23.0 and AMOS 18.0.

Results

Physiological factor was identified as a significant predictor of premenstrual syndrome (t=6.45, p<.001). This model explained 22.1% of the variance in premenstrual syndrome. Psychological factors (t=-2.49, p=.013) and premenstrual syndrome (t=8.17, p<.001) were identified as significant predictors of premenstrual coping. Also this model explained 30.9% of the variance in premenstrual coping in university students. A physiological factors directly influenced premenstrual syndrome (β=.41, p=.012). Premenstrual syndrome (β=.55, p=.005) and physiological factor (β=.23, p=.015) had significant total effects on premenstrual coping. Physiological factor did not have a direct influence on premenstrual coping, but indirectly affected it (β=.22, p=.007). Psychological factors did not have an indirect or total effect on premenstrual coping, but directly affected it (β=-.17, p=.036).

Conclusion

These findings suggest that strategies to control physiological factors such as menstrual pain should be helpful to improve premenstrual syndrome symptoms. When developing a program to improve premenstrual coping ability and quality of menstrual related health, it is important to consider psychological factors including perceived stress and menstrual attitude and premenstrual syndrome.

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Investigation of coping behaviors and premenstrual syndrome among university students
Özlem Akın, Nülüfer Erbil
Current Psychology.2024; 43(2): 1685. CrossRef
Investigating influencing factors on premenstrual syndrome (PMS) among female college students
Su Jeong Yi, Miok Kim, Ina Park
BMC Women's Health.2023;[Epub] CrossRef
Effects of Sleep Pattern, Stress, Menstrual Attitude, and Behavior That Reduces Exposure to Endocrine Disrupting Chemicals on Premenstrual Syndrome in Adolescents
Hye Jin Kim, So Young Choi, Haeyoung Min
Korean Journal of Women Health Nursing.2019; 25(4): 423. CrossRef

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Identifying Latent Classes of Risk Factors for Coronary Artery Disease: Eunsil Ju, JiSun Choi; J Korean Acad Nurs 2017;47(6):817-827. Published online January 15, 2017; DOI: https://doi.org/10.4040/jkan.2017.47.6.817

Abstract PDF

Abstract Purpose

This study aimed to identify latent classes based on major modifiable risk factors for coronary artery disease.

Methods

This was a secondary analysis using data from the electronic medical records of 2,022 patients, who were newly diagnosed with coronary artery disease at a university medical center, from January 2010 to December 2015. Data were analyzed using SPSS version 20.0 for descriptive analysis and Mplus version 7.4 for latent class analysis.

Results

Four latent classes of risk factors for coronary artery disease were identified in the final model: ‘smoking-drinking’, ‘high-risk for dyslipidemia’, ‘high-risk for metabolic syndrome’, and ‘high-risk for diabetes and malnutrition’. The likelihood of these latent classes varied significantly based on socio-demographic characteristics, including age, gender, educational level, and occupation.

Conclusion

The results showed significant heterogeneity in the pattern of risk factors for coronary artery disease. These findings provide helpful data to develop intervention strategies for the effective prevention of coronary artery disease. Specific characteristics depending on the subpopulation should be considered during the development of interventions.

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Diagnosis and risk stratification of coronary artery disease in Yemeni patients using treadmill test
NouraddenN Aljaber, ShaneiA Shanei, SultanAbdulwadoud Alshoabi, KamalD Alsultan, MoawiaB Gameraddin, KhaledM Al-Sayaghi
Journal of Family Medicine and Primary Care.2020; 9(5): 2375. CrossRef
Latent Class Analysis for Health-Related Quality of Life in the Middle-Aged Male in South Korea
Youngsuk Cho, Dong Moon Yeum
Journal of Korean Academy of Nursing.2019; 49(1): 104. CrossRef

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Factors Influencing Adolescent Lifetime Smoking and Current Smoking in South Korea: Using data from the 10^th (2014) Korea Youth Risk Behavior Web-Based Survey: Seok Hyun Gwon, Suyong Jeong; J Korean Acad Nurs 2016;46(4):552-561. Published online August 31, 2016; DOI: https://doi.org/10.4040/jkan.2016.46.4.552

Abstract PDF

Purpose

The purpose of this study was to investigate factors influencing lifetime smoking and current smoking among adolescents in South Korea.

Methods

Hierarchical logistic regression was conducted based on complex sample analysis using statistics from the 10th (2014) Korea Youth Risk Behavior Web-Based Survey. The study sample comprised 72,060 adolescents aged 12 to 18.

Results

The significant factors influencing adolescent lifetime smoking were female gender, older age, higher stress, higher weekly allowance, lower economic status, living apart from parents, parental smoking, sibling smoking, peer smoking, observation of school personnel smoking, and coed school compared to boys' school. The significant factors influencing adolescent current smoking were female gender, older age, higher stress, higher weekly allowance, both higher and lower economic status compared to middle economic status, living apart from parents, parental smoking, sibling smoking, peer smoking, observation of school personnel smoking, and coed school compared to boys' school.

Conclusion

Factors identified in this study need to be considered in programs directed at prevention of adolescent smoking and smoking cessation programs, as well as policies.

Citations

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A Study on Adolescent Smoking Prevention and Cessation Policies: Based on the Propensity Score Matching–Difference-in-Differences Method
Seokmin Ji, Byungchan Moon, Younggyu Kwon, Kyumin Kim
Healthcare.2024; 13(1): 30. CrossRef
Estimated prevalence and trends in smoking among adolescents in South Korea, 2005–2021: a nationwide serial study
Hyoin Shin, Sangil Park, Hyunju Yon, Chae Yeon Ban, Stephen Turner, Seong Ho Cho, Youn Ho Shin, Jung U. Shin, Ai Koyanagi, Louis Jacob, Lee Smith, Chanyang Min, Young Joo Lee, So Young Kim, Jinseok Lee, Rosie Kwon, Min Ji Koo, Guillaume Fond, Laurent Boye
World Journal of Pediatrics.2023; 19(4): 366. CrossRef
Health-Related Behavior and Psychosocial Characteristics of Adolescent Female Smokers in Korea, Compared with Adolescent Male Smokers
Yong-Sook Eo, Yeon-Hee Lee, Myo-Sung Kim
Healthcare.2023; 11(12): 1707. CrossRef
Disparity between Subjective Health Perception and Lifestyle Practices among Korean Adolescents: A National Representative Sample
Aniceto Echalico Braza, Jinsoo Jason Kim, Sun Hee Kim
Journal of Lifestyle Medicine.2022; 12(3): 153. CrossRef
Comparison of the Prediction Model of Adolescents' Suicide Attempt Using Logistic Regression and Decision Tree: Secondary Data Analysis of the 2019 Youth Health Risk Behavior Web-Based Survey
Yoonju Lee, Heejin Kim, Yesul Lee, Hyesun Jeong
Journal of Korean Academy of Nursing.2021; 51(1): 40. CrossRef
Factors Associated with Cigarette, E-Cigarette, and Dual Use among South Korean Adolescents
Myong Sun Cho
Healthcare.2021; 9(10): 1252. CrossRef
The Effect of Neighborhood Characteristics and Friends' Smoking Status on the Habitual Smoking Onset in Adolescents
You-Jung Choi, Gwang Suk Kim
Journal of Korean Academy of Nursing.2021; 51(1): 54. CrossRef
Sex Differences in Multilevel Factors of Smoking Experimentation and Age of Initiation in Korean Adolescents
Eun-Mi Kim, Eunhee Park, Heejung Kim
The Journal of School Nursing.2020; 36(5): 348. CrossRef
Multidisciplinary Approach to Smoking Cessation in Late Adolescence: A Pilot Study
Jae Suk Park, Sang Hyung Lee, Ga Hye Lee, Mi Ra Yang, Inhyuk Park, Bumjo Oh
Global Pediatric Health.2020;[Epub] CrossRef
Factors associated with maintenance of smoking cessation in adolescents after implementation of tobacco pricing policy in South Korea: Evidence from the 11th Youth Health Behavior Survey
Eun Gyeong Kim, Sook Kyoung Park, Young‐Me Lee, Mi Yeol Hyun, Laren (Riesche) Narapareddy
Research in Nursing & Health.2020; 43(1): 40. CrossRef
The Association Between Part-time Job Experience and Tobacco Smoking in Adolescents: Analysis on Korea Youth Risk Behavior Survey Data 2017
Kyoungmi Ku, Keum Ji Jung, San Kang, Yoonjeong Choi, Su Hyun Lee, Jakyoung Lee, Heejin Kimm
Journal of the Korean Society for Research on Nicotine and Tobacco.2020; 11(2): 56. CrossRef
Adolescent Abuse and Smoking Behavior Among High School Students in the Republic of Korea
Junghee Kim, Sunhee Park
Journal of Child and Family Studies.2019; 28(1): 52. CrossRef
The influence and interaction of exposure to pro-smoking and anti-smoking messaging on youth smoking behaviour and susceptibility
Jingfen Zhu*, Jiahui Li*, Yaping He^#, Na Li, Gang Xu^#, Jinming Yu
Tobacco Induced Diseases.2019;[Epub] CrossRef
Association Between Socioeconomic Status and Early Initiation of Smoking, Alcohol Drinking, and Sexual Behavior Among Korean Adolescents
Mei Lin C. Valencia, Binh Thang Tran, Min Kyung Lim, Kui Son Choi, Jin-Kyoung Oh
Asia Pacific Journal of Public Health.2019; 31(5): 443. CrossRef
Parent educators for teenage smoking behavior
Lucky Herawati, Johan Arief Budiman, Choirul Hadi, Abdul Khair
International Journal of Adolescent Medicine and Health.2019;[Epub] CrossRef
A Meta-Analytic Study on Differences between Middle and High School Students in Cognitive, Emotional and Social Variables Related to Adolescent Smoking
김인용, 강정석
Locality and Globality: Korean Journal of Social Sciences.2018; 42(3): 83. CrossRef
Impact of nearby smoking on adolescent smoking behavior in Korea
Dong Jun Kim, Sun Jung Kim
Medicine.2018; 97(45): e13125. CrossRef
Trend Analysis for the Choice and Cost of Lung Cancer Treatment in South Korea, 2003-2013
Dohun Kim, So Young Kim, Beomseok Suh, Jong Hyock Park
Cancer Research and Treatment.2018; 50(3): 757. CrossRef
Concept analysis of impressionability among adolescents and young adults
Seok Hyun Gwon, Suyong Jeong
Nursing Open.2018; 5(4): 601. CrossRef
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Kim Eun Soo, 정민수
Health and Social Welfare Review.2017; 37(3): 568. CrossRef

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A Structural Model for Primiparas' Breastfeeding Behavior: Hyun-Joo Yang, Ji-Min Seo; J Korean Acad Nurs 2013;43(3):399-408. Published online June 28, 2013; DOI: https://doi.org/10.4040/jkan.2013.43.3.399

Abstract PDF

Purpose

The study was done to construct and test a structural model to explain primipara breastfeeding behavior.

Methods

The participants were 213 primiparas on postpartum wards. Data were analyzed using the PASW 18.0 and AMOS 19.0 programs.

Results

Fitness statistics for the hypothetical model were appropriate (χ² =38.50, p=.070, GFI=.96, RMSEA=.05, AGFI=.93, NFI=.95, TLI=.97, CFI=.98, PNFI=.57, χ²/df=1.43). Breastfeeding behaviors were directly influenced by intention to breastfeed, perceived effectiveness of breastfeeding, and the amount of supplementary feeding. The amount of supplementary feeding had the largest direct impact on breastfeeding behavior. The largest total effect on breastfeeding behavior was intention to breastfeed. The environment of the maternity hospital indirectly influenced breastfeeding behavior. These factors explained 18.9% of variance in the primipara breastfeeding behavior.

Conclusion

The results of the study indicate that in order to promote primipara breastfeeding the amount of supplementary feeding immediately after the birth should be limited and an environment that encourages exclusive breastfeeding in the hospital should be provided. The results also suggest it is necessary to provide nursing interventions that increase the intention to breastfeed and the perceived effectiveness of breastfeeding.

Citations

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Predictors of maternal attachment among breastfeeding mothers in Jordan
Sawsan Abuhammad
Nursing Open.2021; 8(1): 123. CrossRef
Factors associated with Maternal Attachment of Breastfeeding Mothers
Sun-Hee Kim
Child Health Nursing Research.2019; 25(1): 65. CrossRef
Impact of Parenting Stress and Husband's Support on Breastfeeding Adaptation among Breastfeeding Mothers
Seung Hui Heo, Yoon Goo Noh
Korean Journal of Women Health Nursing.2017; 23(4): 233. CrossRef
Development of a Breastfeeding Effectiveness Scale (BES)
Hyun-Joo Yang, Min-Young Jeong, Ji-Min Seo
Korean Journal of Women Health Nursing.2016; 22(4): 264. CrossRef
Comparison of Lactation Problems, Knowledge, and Adaptation on Breastfeeding between Users and Non-Users of Lactation Clinic
Myoung Hee Yun, Hye Sook Shin
Journal of East-West Nursing Research.2014; 20(2): 112. CrossRef

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Maternal and Hospital Factors Impacting the Utilization of Rooming-in Care in South Korea: Secondary Analysis of National Health Data: Yunmi Kim, Eun-Young Kim; J Korean Acad Nurs 2011;41(5):593-602. Published online October 31, 2011; DOI: https://doi.org/10.4040/jkan.2011.41.5.593

Abstract PDF

Purpose

Purpose: In this study analysis was done of utilization of rooming-in care in South Korean hospitals in order to examine the factors related to mothers and hospitals that affect rooming-in care.

Methods

With the involvement of 254,414 mothers who gave birth across 953 hospitals, the analysis used the health insurance qualification data of the National Health Insurance Corporations and Health Insurance Review and Assessment Service (2006). Factors associated with rooming-in care were analyzed using a GEE logistic regression analysis to consider factors related to both mothers and hospitals.

Results

Only 45.1% of the mothers used rooming-in care. The results of the regression analysis revealed that individual factors of the mothers were not associated with rooming-in care, whereas group factors of the hospitals were. Rooming-in care use was primarily related to small hospital, location of hospital, and higher nurse staffing level.

Conclusion

The findings of this study indicate that the utilization of rooming-in care is not associated with factors an individual mother, but rather with the group factors of the hospitals. Thus, a policy-based approach considering both of these types of factors is required to enhance the utilization of rooming-in care.

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Neonatal seizures and white matter injury: Role of rotavirus infection and probiotics
Jung Sook Yeom, Ji Sook Park, Young-Soo Kim, Rock Bum Kim, Dae-Sup Choi, Ju-Young Chung, Tae-Hee Han, Ji-Hyun Seo, Eun Sil Park, Jae-Young Lim, Hyang-Ok Woo, Hee-Shang Youn, Chan-Hoo Park
Brain and Development.2019; 41(1): 19. CrossRef

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Predictive Bayesian Network Model Using Electronic Patient Records for Prevention of Hospital-Acquired Pressure Ulcers: In Sook Cho, Eunja Chung; J Korean Acad Nurs 2011;41(3):423-431. Published online June 13, 2011; DOI: https://doi.org/10.4040/jkan.2011.41.3.423

Abstract PDF

Purpose

The study was designed to determine the discriminating ability of a Bayesian network (BN) for predicting risk for pressure ulcers.

Methods

Analysis was done using a retrospective cohort, nursing records representing 21,114 hospital days, 3,348 patients at risk for ulcers, admitted to the intensive care unit of a tertiary teaching hospital between January 2004 and January 2007. A BN model and two logistic regression (LR) versions, model-I and -II, were compared, varying the nature, number and quality of input variables. Classification competence and case coverage of the models were tested and compared using a threefold cross validation method.

Results

Average incidence of ulcers was 6.12%. Of the two LR models, model-I demonstrated better indexes of statistical model fits. The BN model had a sensitivity of 81.95%, specificity of 75.63%, positive and negative predictive values of 35.62% and 96.22% respectively. The area under the receiver operating characteristic (AUROC) was 85.01% implying moderate to good overall performance, which was similar to LR model-I. However, regarding case coverage, the BN model was 100% compared to 15.88% of LR.

Conclusion

Discriminating ability of the BN model was found to be acceptable and case coverage proved to be excellent for clinical use.

Citations

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Development of a Pressure Injury Machine Learning Prediction Model and Integration into Clinical Practice: A Prediction Model Development and Validation Study
Ju Hee Lee, Jae Yong Yu, So Yun Shim, Kyung Mi Yeom, Hyun A Ha, Se Yong Jekal, Ki Tae Moon, Joo Hee Park, Sook Hyun Park, Jeong Hee Hong, Mi Ra Song, Won Chul Cha
Korean Journal of Adult Nursing.2024; 36(3): 191. CrossRef
Evaluation of the risk prediction model of pressure injuries in hospitalized patient: A systematic review and meta‐analysis
Yuxia Ma, Xiang He, Tingting Yang, Yifang Yang, Ziyan Yang, Tian Gao, Fanghong Yan, Boling Yan, Juan Wang, Lin Han
Journal of Clinical Nursing.2024;[Epub] CrossRef
The predictive effect of different machine learning algorithms for pressure injuries in hospitalized patients: A network meta-analyses
Chaoran Qu, Weixiang Luo, Zhixiong Zeng, Xiaoxu Lin, Xuemei Gong, Xiujuan Wang, Yu Zhang, Yun Li
Heliyon.2022; 8(11): e11361. CrossRef
Predictive Modeling of Pressure Injury Risk in Patients Admitted to an Intensive Care Unit
Mireia Ladios-Martin, José Fernández-de-Maya, Francisco-Javier Ballesta-López, Adrián Belso-Garzas, Manuel Mas-Asencio, María José Cabañero-Martínez
American Journal of Critical Care.2020; 29(4): e70. CrossRef
Development and Evaluation of Electronic Health Record Data-Driven Predictive Models for Pressure Ulcers
Seul Ki Park, Hyeoun-Ae Park, Hee Hwang
Journal of Korean Academy of Nursing.2019; 49(5): 575. CrossRef
Development and Comparison of Predictive Models for Pressure Injuries in Surgical Patients
Seul Ki Park, Hyeoun-Ae Park, Hee Hwang
Journal of Wound, Ostomy & Continence Nursing.2019; 46(4): 291. CrossRef
Automated Pressure Injury Risk Assessment System Incorporated Into an Electronic Health Record System
Yinji Jin, Taixian Jin, Sun-Mi Lee
Nursing Research.2017; 66(6): 462. CrossRef
Recommendation of Personalized Surveillance Interval of Colonoscopy via Survival Analysis
Jayeon Gu, Eun Sun Kim, Seoung Bum Kim
Journal of Korean Institute of Industrial Engineers.2016; 42(2): 129. CrossRef
Medical Data Based Clinical Pathway Analysis and Automatic Ganeration System
Hanna Park, In Ho Bae, Yong Oock Kim
The Journal of Korea Information and Communications Society.2014; 39C(6): 497. CrossRef
Reusability of EMR Data for Applying Cubbin and Jackson Pressure Ulcer Risk Assessment Scale in Critical Care Patients
Eunkyung Kim, Mona Choi, JuHee Lee, Young Ah Kim
Healthcare Informatics Research.2013; 19(4): 261. CrossRef
Using EHR data to predict hospital-acquired pressure ulcers: A prospective study of a Bayesian Network model
Insook Cho, Ihnsook Park, Eunman Kim, Eunjoon Lee, David W. Bates
International Journal of Medical Informatics.2013; 82(11): 1059. CrossRef

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