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: Ultradian rhythms are biological rhythms with periods of a few seconds to a few hours. Along with circadian rhythms, ultradian rhythms influence human physiology. However, such rhythms have not been studied as intensively as circadian rhythms. This study aimed to identify ultradian rest-activity rhythms induced by the dopamine D2/D3 agonist quinpirole in mice. Methods: We used 10 mice from the Institute of Cancer Research. Quinpirole was administered at a dose of 0.5 mg/kg.We assessed free rest-activity using infrared detectors and conducted wavelet analysis to measure the period and its variation. We also used the paired t test to compare ultradian rhythm patterns. Results: Quinpirole did not significantly change total 24-hour locomotor activity (p = 0.065). However, it significantly increased locomotor activity during the dark phase (p = 0.001) and decreased it during the light phase (p = 0.016).In the continuous wavelet transform analysis, the mean period was 5.618 hours before quinpirole injection and 4.523 hours after injection. The period showed a significant decrease (p = 0.040), while the variation remained relatively consistent before and after quinpirole injection. Conclusion This study demonstrated ultradian rest-activity rhythms induced by quinpirole using wavelet analysis.Quinpirole-induced ultradian rhythms exhibited rapid oscillations with shortened periods and increased activity during the dark phase. To better understand these changes in ultradian rhythms caused by quinpirole, it is essential to compare them with the effects of other psychopharmacological agents. Furthermore, investigating the pharmacological impact on ultradian rest-activity rhythms may have valuable applications in clinical studies.

Objective: Ultradian rhythms are biological rhythms with periods of a few seconds to a few hours. Along with circadian rhythms, ultradian rhythms influence human physiology. However, such rhythms have not been studied as intensively as circadian rhythms. This study aimed to identify ultradian rest-activity rhythms induced by the dopamine D2/D3 agonist quinpirole in mice. Methods: We used 10 mice from the Institute of Cancer Research. Quinpirole was administered at a dose of 0.5 mg/kg.We assessed free rest-activity using infrared detectors and conducted wavelet analysis to measure the period and its variation. We also used the paired t test to compare ultradian rhythm patterns. Results: Quinpirole did not significantly change total 24-hour locomotor activity (p = 0.065). However, it significantly increased locomotor activity during the dark phase (p = 0.001) and decreased it during the light phase (p = 0.016).In the continuous wavelet transform analysis, the mean period was 5.618 hours before quinpirole injection and 4.523 hours after injection. The period showed a significant decrease (p = 0.040), while the variation remained relatively consistent before and after quinpirole injection. Conclusion This study demonstrated ultradian rest-activity rhythms induced by quinpirole using wavelet analysis.Quinpirole-induced ultradian rhythms exhibited rapid oscillations with shortened periods and increased activity during the dark phase. To better understand these changes in ultradian rhythms caused by quinpirole, it is essential to compare them with the effects of other psychopharmacological agents. Furthermore, investigating the pharmacological impact on ultradian rest-activity rhythms may have valuable applications in clinical studies.

Objective: Ultradian rhythms are biological rhythms with periods of a few seconds to a few hours. Along with circadian rhythms, ultradian rhythms influence human physiology. However, such rhythms have not been studied as intensively as circadian rhythms. This study aimed to identify ultradian rest-activity rhythms induced by the dopamine D2/D3 agonist quinpirole in mice. Methods: We used 10 mice from the Institute of Cancer Research. Quinpirole was administered at a dose of 0.5 mg/kg.We assessed free rest-activity using infrared detectors and conducted wavelet analysis to measure the period and its variation. We also used the paired t test to compare ultradian rhythm patterns. Results: Quinpirole did not significantly change total 24-hour locomotor activity (p = 0.065). However, it significantly increased locomotor activity during the dark phase (p = 0.001) and decreased it during the light phase (p = 0.016).In the continuous wavelet transform analysis, the mean period was 5.618 hours before quinpirole injection and 4.523 hours after injection. The period showed a significant decrease (p = 0.040), while the variation remained relatively consistent before and after quinpirole injection. Conclusion This study demonstrated ultradian rest-activity rhythms induced by quinpirole using wavelet analysis.Quinpirole-induced ultradian rhythms exhibited rapid oscillations with shortened periods and increased activity during the dark phase. To better understand these changes in ultradian rhythms caused by quinpirole, it is essential to compare them with the effects of other psychopharmacological agents. Furthermore, investigating the pharmacological impact on ultradian rest-activity rhythms may have valuable applications in clinical studies.

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: Given the long-term and severe distress experienced during breast cancer treatment, detecting depression among breast cancer patients is clinically crucial. This study aimed to explore a machine-learning model using self-report questionnaires to screen for depression in patients with breast cancer. Methods: A total of 327 patients who visited the breast cancer clinic were included in this study. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9), Beck Depression Inventory (BDI), and Hospital Anxiety and Depression Scale (HADS). The depression was evaluated according to the Diagnostic and Statistical Manual of Mental Disorders 5th edition. The prediction model’s performance based on supervised machine learning was conducted using MATLAB2022. Results: The BDI showed an area under the curve (AUC) of 0.785 when using the logistic regression (LR) classifier.The HADS and PHQ-9 showed an AUC of 0.784 and 0.756 when using the linear discriminant analysis, respectively.The combinations of BDI and HADS showed an AUC of 0.812 when using the LR. The combinations of PHQ-9, BDI, and HADS showed an AUC of 0.807 when using LR. Conclusion The combination model with BDI and HADS in breast cancer patients might be better than the method using a single scale. In future studies, it is necessary to explore strategies that can improve the performance of the model by integrating the method using questionnaires and other methods.