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.

Objective: Suicide is a significant public health issue, particularly among older adults, where the risk is heightened.Early identification of individuals at risk for suicidal ideation is essential for timely interventions, greatly improving prevention efforts. This study aimed to develop a predictive model for suicidal ideation in community-dwelling older adults using psychiatric self-report scales and machine learning classifiers. Methods: A total of 238 older adults were assessed using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7, Perceived Stress Scale-10, and World Health Organization Quality of Life Scale – Abbreviated Version.A nested 5-fold cross-validation procedure repeated 100 times was used for feature selection and model evaluation.Various classifiers—including support vector machines, random forest, logistic regression, linear discriminant analysis, and gradient boosting—were employed. Results: As the number of PHQ-9 items increased from two to six, the area under the curve (AUC) rose from 0.835 to 0.892. When a set of nine features—selected based on feature stability across iterations—was used, the AUC further improved to 0.904. This progression indicates that inclusion of additional informative items enhances classification performance. Conclusion This study demonstrates that psychiatric self-report scales can effectively predict suicidal ideation risk in community-dwelling older adults. By utilizing efficient features, the predictive accuracy of the model can be enhanced, offering valuable insights for developing early identification systems for high-risk groups. These findings suggest that a community-based suicide prevention program could be promoted by implementing a screening system to identify individuals at high risk for suicidal ideation among the elderly.

Objective: This study aimed to develop a machine learning-based classification model to differentiate bipolar disorder from major depressive disorder using self-report scales, including the Mood Disorder Questionnaire (MDQ), Bipolar Spectrum Diagnostic Scale (BSDS), and Anger Coping Scale (ACS). Methods: A total of 122 bipolar and 67 depressive patients participated. Recursive feature elimination with 1,000 iterations was used to identify the most informative features. Machine learning classifiers assessed combinations of MDQ, BSDS, and ACS items for classification performance. Results: The AUC values for MDQ and BSDS were 0.8212 and 0.7934, respectively. Combining MDQ and BSDS increased the AUC to 0.8477, which improved further to 0.8548 when ACS was included. For MDQ, the best performance was achieved when all 13 items were included. In contrast, the combined model of MDQ, BSDS, and ACS showed optimal performance when BSDS items 18 (conflicts with colleagues or police), 19 (alcohol or substance use), and ACS item 15 (beating others) were excluded. Conclusion Integrating anger coping styles with mood symptoms enhanced diagnostic accuracy, particularly when items related to undesirable behaviors were excluded. This machine learning approach shows potential for effectively evaluating bipolarity and underscores the importance of refining self-report scales to optimize diagnostic tools. Future research should incorporate clinical and objective data to enhance classification models.

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: Stress management is an important component of management of mental health. Stress processing can be understood as the appraisal of and coping with stress. This study aimed to compare positive and negative perceptions of stress according to patterns of coping strategies. Methods: The study recruited 116 college students who completed the Perceived Stress Scale and Coping Inventory for Stressful Situations using a tablet PC or smartphone application. K-means cluster analysis was used to categorize the subjects into three clusters. Results: Positive perceptions were highest in Cluster 2 (i.e., task and avoidance dominant) at 3.18±0.66 followed by 2.30±0.65 in Cluster 1 (passive coping) and lowest in Cluster 3 (emotion dominant) at 1.75±0.63. Negative perceptions were highest in Cluster 3 at 2.45±0.66 followed by Cluster 1 at 1.66±0.65 and Cluster 2 at 1.07±0.68. Conclusion Differences in coping patterns can reduce the negative effects of stress. Thus, assessing the perception and management of stress can be useful and help people change their coping styles to more adaptive ones. Toward this end, a mobile application can be an appropriate tool.

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.