Objective: Recently, various mental health promotion programs using virtual reality (VR) technology have been tried in the psychiatric field. Considering the importance of mental health in pregnant women, VR-assisted mental health promotion programs for pregnant women are needed to be developed. This study aimed to prospectively investigate the efficacy of a VR-assisted mental health promotion program for pregnant women. Methods: Fifty-five pregnant women were participated in this study. Mental health states such as depression, anxiety, perceived stress, and quality of life were assessed by Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Perceived Stress Scale, and World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF) before and after using VR program treatment. Based on the mental health types of pregnant women classified by cluster analysis, the effects of the VR program were analyzed by paired t test and Wilcoxon signed rank test. Results: The VR program significantly reduced PHQ-9 (p = 0.033) and GAD-7 (p = 0.046) scores, and significantly increased WHOQOL-BREF (p = 0.026) score of the participants. Additionally, when classifying the mental health types of pregnant women, the VR program was significantly effective to improve depression, anxiety, and quality of life in the most severe group based on the cluster analysis. Conclusion The results of this study suggest that VR program may be effective to improve the mental health of pregnant women. Particularly, VR programs for the high-risk group of depression might be the most effective. Therefore, VR-assisted mental health promotion programs could be useful for managing the mental health in pregnant women.

Objective: Recently, various mental health promotion programs using virtual reality (VR) technology have been tried in the psychiatric field. Considering the importance of mental health in pregnant women, VR-assisted mental health promotion programs for pregnant women are needed to be developed. This study aimed to prospectively investigate the efficacy of a VR-assisted mental health promotion program for pregnant women. Methods: Fifty-five pregnant women were participated in this study. Mental health states such as depression, anxiety, perceived stress, and quality of life were assessed by Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Perceived Stress Scale, and World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF) before and after using VR program treatment. Based on the mental health types of pregnant women classified by cluster analysis, the effects of the VR program were analyzed by paired t test and Wilcoxon signed rank test. Results: The VR program significantly reduced PHQ-9 (p = 0.033) and GAD-7 (p = 0.046) scores, and significantly increased WHOQOL-BREF (p = 0.026) score of the participants. Additionally, when classifying the mental health types of pregnant women, the VR program was significantly effective to improve depression, anxiety, and quality of life in the most severe group based on the cluster analysis. Conclusion The results of this study suggest that VR program may be effective to improve the mental health of pregnant women. Particularly, VR programs for the high-risk group of depression might be the most effective. Therefore, VR-assisted mental health promotion programs could be useful for managing the mental health in pregnant women.

Objective: Recently, various mental health promotion programs using virtual reality (VR) technology have been tried in the psychiatric field. Considering the importance of mental health in pregnant women, VR-assisted mental health promotion programs for pregnant women are needed to be developed. This study aimed to prospectively investigate the efficacy of a VR-assisted mental health promotion program for pregnant women. Methods: Fifty-five pregnant women were participated in this study. Mental health states such as depression, anxiety, perceived stress, and quality of life were assessed by Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Perceived Stress Scale, and World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF) before and after using VR program treatment. Based on the mental health types of pregnant women classified by cluster analysis, the effects of the VR program were analyzed by paired t test and Wilcoxon signed rank test. Results: The VR program significantly reduced PHQ-9 (p = 0.033) and GAD-7 (p = 0.046) scores, and significantly increased WHOQOL-BREF (p = 0.026) score of the participants. Additionally, when classifying the mental health types of pregnant women, the VR program was significantly effective to improve depression, anxiety, and quality of life in the most severe group based on the cluster analysis. Conclusion The results of this study suggest that VR program may be effective to improve the mental health of pregnant women. Particularly, VR programs for the high-risk group of depression might be the most effective. Therefore, VR-assisted mental health promotion programs could be useful for managing the mental health in pregnant women.

Objective: Recently, various mental health promotion programs using virtual reality (VR) technology have been tried in the psychiatric field. Considering the importance of mental health in pregnant women, VR-assisted mental health promotion programs for pregnant women are needed to be developed. This study aimed to prospectively investigate the efficacy of a VR-assisted mental health promotion program for pregnant women. Methods: Fifty-five pregnant women were participated in this study. Mental health states such as depression, anxiety, perceived stress, and quality of life were assessed by Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Perceived Stress Scale, and World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF) before and after using VR program treatment. Based on the mental health types of pregnant women classified by cluster analysis, the effects of the VR program were analyzed by paired t test and Wilcoxon signed rank test. Results: The VR program significantly reduced PHQ-9 (p = 0.033) and GAD-7 (p = 0.046) scores, and significantly increased WHOQOL-BREF (p = 0.026) score of the participants. Additionally, when classifying the mental health types of pregnant women, the VR program was significantly effective to improve depression, anxiety, and quality of life in the most severe group based on the cluster analysis. Conclusion The results of this study suggest that VR program may be effective to improve the mental health of pregnant women. Particularly, VR programs for the high-risk group of depression might be the most effective. Therefore, VR-assisted mental health promotion programs could be useful for managing the mental health in pregnant women.

Background: Although exercising can be effective in alleviating mood symptoms, implementing an exercise regimen can be challenging. This study aims to evaluate the subjective experience and satisfaction with an exercise program that uses augmented reality (AR) developed to improve exercise adherence in patients with mood disorders. Methods: Thirty patients diagnosed with mood disorders participated in this study. Before and after the AR-based exercise program, psychological states were assessed using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Perceived Stress Scale (PSS), and World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF). In addition, the satisfaction survey conducted after participating in the exercise program was analyzed. Results: The mean score of PHQ-9 decreased significantly following the exercise program. Moreover, the mean scores for GAD-7 and PSS significantly decreased when compared before and after the exercise program. Meanwhile, the mean score of WHOQOL-BREF for physical and social satisfaction increased significantly. Furthermore, this program received positive responses on the satisfaction survey. Conclusion In patients with mood disorders, the AR-based exercise program showed remarkable positive effects on psychological states and satisfaction levels. The exercise program using AR technology may effectively improve exercise program adherence in patients with mood disorders.

Objective: Mental health promotion programs using virtual reality (VR) technology have been developed in various forms. This study aimed to investigate the subjective experience of a VR-assisted mental health promotion program for the community population, which was provided in the form of VR experience on a bus to increase accessibility. Methods: Ninety-six people participated in this study. The relationship between the subjective experience and mental health states such as depression, anxiety, perceived stress, and quality of life was explored. The subjective experience on depression and stress before and after VR program treatment was compared using the Wilcoxon signed-rank test. The satisfaction with the VR-assisted mental health promotion program was examined after using the VR program. Results: The VR-assisted mental health promotion program on a bus significantly improved subjective symptoms such as depression (p=0.036) and perceived stress (p=0.010) among all the participants. Among the high-risk group, this VR program significantly relieved subjective depressive feeling score (p=0.033), and subjective stressful feeling score (p=0.035). In contrast, there were no significant changes in subjective depressive feelings (p=0.182) and subjective stressful feelings (p=0.058) among the healthy group. Seventy-two percent of the participants reported a high level of satisfaction, scoring 80 points or more. Conclusion The findings of this study suggest that the VR-assisted mental health promotion program may effectively improve the subjective depressive and stressful feelings. The use of VR programs on buses to increase of accessibility for the community could be a useful approach for promoting mental health among the population.

Objective: Bipolar and depressive disorders are distinct disorders with clearly different clinical courses, however, distinguishing between them often presents clinical challenges. This study investigates the utility of self-report questionnaires, the Mood Disorder Questionnaire (MDQ) and Bipolar Spectrum Diagnostic Scale (BSDS), with machine learning-based multivariate analysis, to classify patients with bipolar and depressive disorders. Methods: A total of 189 patients with bipolar disorders and depressive disorders were included in the study, and all participants completed both the MDQ and BSDS questionnaires. Machine-learning classifiers, including support vector machine (SVM) and linear discriminant analysis (LDA), were exploited for multivariate analysis. Classification performance was assessed through cross-validation. Results: Both MDQ and BSDS demonstrated significant differences in each item and total scores between the two groups. Machine learning-based multivariate analysis, including SVM, achieved excellent discrimination levels with area under the ROC curve (AUC) values exceeding 0.8 for each questionnaire individually. In particular, the combination of MDQ and BSDS further improved classification performance, yielding an AUC of 0.8762. Conclusion This study suggests the application of machine learning to MDQ and BSDS can assist in distinguishing between bipolar and depressive disorders. The potential of combining high-dimensional psychiatric data with machine learning-based multivariate analysis as an effective approach to psychiatric disorders.

Objective: Due to the high frequency of depressive symptoms associated with breast cancer, it is crucial to screen for depression in breast cancer patients. While numerous screening tools are available for depression in this population, there is a need for a brief and convenient tool to enhance clinical use. This study aims to investigate the psychometric properties of the Patient Health Questionnaire-9 (PHQ-9) in patients with breast cancer. Methods: Patients with breast cancer (n=327) who visited the Breast Cancer Clinic were included in this study. The reliability of the PHQ-9 was analyzed by Cronbach’s α, and the construct validity of the PHQ-9 was explored by factor analysis. The concurrent validity of the PHQ-9 was evaluated by Pearson correlation analysis with the Hospital Anxiety and Depression Scale (HADS) and Perceived Stress Scale (PSS). Results: The values of Cronbach’s α ranged from 0.800 to 0.879 was acceptable. The exploratory factor analysis revealed that the one-factor model and two-factor model of the PHQ-9 explained 46% and 57% of the variance, respectively. The PHQ-9 were significantly correlated with those of HADS (r=0.702, p<0.001) and PSS (r=0.466, p<0.001). Consequently, the PHQ-9 demonstrated acceptable reliability and validity in breast cancer patients. Conclusion The findings of this study indicate that the PHQ-9 exhibits acceptable reliability and validity in patients with breast cancer. The convenience of this brief self-report questionnaire suggests its potential as a reliable and valid tool for assessing depression in breast cancer clinics.

Background: Although exercising can be effective in alleviating mood symptoms, implementing an exercise regimen can be challenging. This study aims to evaluate the subjective experience and satisfaction with an exercise program that uses augmented reality (AR) developed to improve exercise adherence in patients with mood disorders. Methods: Thirty patients diagnosed with mood disorders participated in this study. Before and after the AR-based exercise program, psychological states were assessed using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Perceived Stress Scale (PSS), and World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF). In addition, the satisfaction survey conducted after participating in the exercise program was analyzed. Results: The mean score of PHQ-9 decreased significantly following the exercise program. Moreover, the mean scores for GAD-7 and PSS significantly decreased when compared before and after the exercise program. Meanwhile, the mean score of WHOQOL-BREF for physical and social satisfaction increased significantly. Furthermore, this program received positive responses on the satisfaction survey. Conclusion In patients with mood disorders, the AR-based exercise program showed remarkable positive effects on psychological states and satisfaction levels. The exercise program using AR technology may effectively improve exercise program adherence in patients with mood disorders.

Background: Although exercising can be effective in alleviating mood symptoms, implementing an exercise regimen can be challenging. This study aims to evaluate the subjective experience and satisfaction with an exercise program that uses augmented reality (AR) developed to improve exercise adherence in patients with mood disorders. Methods: Thirty patients diagnosed with mood disorders participated in this study. Before and after the AR-based exercise program, psychological states were assessed using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Perceived Stress Scale (PSS), and World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF). In addition, the satisfaction survey conducted after participating in the exercise program was analyzed. Results: The mean score of PHQ-9 decreased significantly following the exercise program. Moreover, the mean scores for GAD-7 and PSS significantly decreased when compared before and after the exercise program. Meanwhile, the mean score of WHOQOL-BREF for physical and social satisfaction increased significantly. Furthermore, this program received positive responses on the satisfaction survey. Conclusion In patients with mood disorders, the AR-based exercise program showed remarkable positive effects on psychological states and satisfaction levels. The exercise program using AR technology may effectively improve exercise program adherence in patients with mood disorders.