Objective: Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms. Methods: Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Results: Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor. Conclusion Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.

Objective: Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms. Methods: Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Results: Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor. Conclusion Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.

Objective: Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms. Methods: Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Results: Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor. Conclusion Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.

Purpose: This study aimed to identify the effects of shared leadership, communication skills, and team effectiveness, as perceived by nurses and nursing assistants in comprehensive nursing service units. Methods: A cross-sectional research design was adopted, and the sample included 306 nurses, nurse assistants, and caregivers working in nine hospitals with fewer than 500 beds in two South Korean cities. The data were analyzed using descriptive statistics, t-tests, ANOVA, Pearson’s correlation coefficient, and four-step hierarchical regression analysis. Results: The factors influencing team effectiveness in the hierarchal multiple regression analysis were shared leadership (β=.57,p<.001) and communication skills (β=.18, p<.001). These factors explained 49% of the total variance. Conclusion To enhance team effectiveness in compressive nursing service units, educational programs focusing on shared leadership and communication skills among nurses, nursing assistants, and caregivers must be developed.

Purpose: This study aimed to identify the effects of shared leadership, communication skills, and team effectiveness, as perceived by nurses and nursing assistants in comprehensive nursing service units. Methods: A cross-sectional research design was adopted, and the sample included 306 nurses, nurse assistants, and caregivers working in nine hospitals with fewer than 500 beds in two South Korean cities. The data were analyzed using descriptive statistics, t-tests, ANOVA, Pearson’s correlation coefficient, and four-step hierarchical regression analysis. Results: The factors influencing team effectiveness in the hierarchal multiple regression analysis were shared leadership (β=.57,p<.001) and communication skills (β=.18, p<.001). These factors explained 49% of the total variance. Conclusion To enhance team effectiveness in compressive nursing service units, educational programs focusing on shared leadership and communication skills among nurses, nursing assistants, and caregivers must be developed.

Purpose: This study aimed to identify the effects of shared leadership, communication skills, and team effectiveness, as perceived by nurses and nursing assistants in comprehensive nursing service units. Methods: A cross-sectional research design was adopted, and the sample included 306 nurses, nurse assistants, and caregivers working in nine hospitals with fewer than 500 beds in two South Korean cities. The data were analyzed using descriptive statistics, t-tests, ANOVA, Pearson’s correlation coefficient, and four-step hierarchical regression analysis. Results: The factors influencing team effectiveness in the hierarchal multiple regression analysis were shared leadership (β=.57,p<.001) and communication skills (β=.18, p<.001). These factors explained 49% of the total variance. Conclusion To enhance team effectiveness in compressive nursing service units, educational programs focusing on shared leadership and communication skills among nurses, nursing assistants, and caregivers must be developed.

Objective: Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms. Methods: Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Results: Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor. Conclusion Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.

Purpose: This study aimed to identify the effects of shared leadership, communication skills, and team effectiveness, as perceived by nurses and nursing assistants in comprehensive nursing service units. Methods: A cross-sectional research design was adopted, and the sample included 306 nurses, nurse assistants, and caregivers working in nine hospitals with fewer than 500 beds in two South Korean cities. The data were analyzed using descriptive statistics, t-tests, ANOVA, Pearson’s correlation coefficient, and four-step hierarchical regression analysis. Results: The factors influencing team effectiveness in the hierarchal multiple regression analysis were shared leadership (β=.57,p<.001) and communication skills (β=.18, p<.001). These factors explained 49% of the total variance. Conclusion To enhance team effectiveness in compressive nursing service units, educational programs focusing on shared leadership and communication skills among nurses, nursing assistants, and caregivers must be developed.

Objective: Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms. Methods: Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Results: Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor. Conclusion Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.

Purpose: This study performed an integrated review based on Roy’s adaptation modes of physiological-physical and psycho-social integration to identify health problems and measure health management of child and adolescent cancer survivors. Methods: Based on ‘Whittemore and Knafl’s stages’ of an integrative review process (problem identification, literature search, data evaluation, data analysis, and presentation of the results), six databases (Google Scholar, CINAHL, PubMed, RISS, KISS, and DBpia) were used to retrieve relevant articles. A total of 992 variables were collected from 14 studies published between 2011 and 2023. Results: Three thematic categories were identified: physiological-physical and psycho-social health problems (fatigue, diminished physical activity, physical sequela, sleep disorders, endocrine problems, bullying, and prejudice), daily self care management(lifestyles integrating health promotion, adaptation processes, and self-care), and preventive health management(utilization of health checkups and screening tests). Conclusion Nursing interventions that can result in a healthy lifestyle for child and adolescent cancer survivors should be further examined at the individual, community, and national levels.