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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.
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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.
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Schizophrenia (SPR) is the most devastating mental illness that causes severe deterioration in social and occupational functioning, but, the etiology remains unknown. The objective of this study is to explore the genetic underpinnings of novelty seeking behavior in schizophrenic family within the Korean population. By conducting a family-based genome-wide association study, we aim to identify potential genetic markers and variations associated with novelty seeking traits in the context of SPR. We have recruited 27 probands (with SPR) with their parents and siblings whenever possible. DNA was extracted from blood sampling of 58 individuals in 27 families and analyzed in an Illumina core exome single nucleotide polymorphism (SNP) array. A family-based association test (qFAM) was used to derive SNP association values across all chromosomes. Although none of the final 800,000 SNPs reached the genome-wide significant threshold of 8.45â ×â 10-7, the most significant 4 SNPs were within the 10-5 to 10-7. This study identifies genetic associations between novelty seeking behavior and SPR within families. RAPGEF5 emerges as a significant gene, along with other neuropsychiatric-related genes. Noteworthy genes like DRD4 and COMT did not show associations, possibly due to the focus on schizophrenic family. While shedding light on this complex relationship, larger studies are needed for robust conclusions and deeper mechanistic insights.
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Comportamento Exploratório , Estudo de Associação Genômica Ampla , Polimorfismo de Nucleotídeo Único , Esquizofrenia , Humanos , Esquizofrenia/genética , Masculino , Feminino , República da Coreia/epidemiologia , Projetos Piloto , Adulto , Pessoa de Meia-Idade , Predisposição Genética para Doença , Adulto JovemRESUMO
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.
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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.
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Objective: Although maintenance treatment for mood disorders is important, the treatment discontinuation rate is reported to be high. This study aimed to investigate the dropout rates and associated factors in mood disorders. Methods: The patients in a mood disorder clinic (n = 535) were examined. Demographic and clinical factors, scores of psychometric scales, time to dropout from initial treatment in patients with bipolar disorder (BP) (n = 288) and depressive disorder (DD) (n = 143) were evaluated based on database of the mood disorder clinic. Results: Among the studied patients with BP and DD, 50% showed dropout in 4.05 and 2.17 years, respectively. The mean survival times were 8.90 years in bipolar disorder I (BP-I), 5.19 years in bipolar II disorder, 3.22 years in bipolar disorder not otherwise specified, 4.24 years in major depressive disorder, and 4.03 years in other depressive disorders. In the multivariate Cox proportional hazards regression model in the BP group, diagnosis BP-I was found to be significantly related to the decrease in dropout rate (hazard ratio [HR] = 0.22, p = 0.001); however, increased past suicide attempt number was significantly related to the increase in dropout rate (HR = 1.13, p = 0.017). In the DD group, none of anxiety disorders as comorbidity, increased scores of openness, and extraversion personality were related to the increase in dropout rate. Conclusion: Patients with BP, especially BP-I, showed a lower dropout rate as compared to patients with other mood disorders.
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We investigate the predictive factors of the mood recurrence in patients with early-onset major mood disorders from a prospective observational cohort study from July 2015 to December 2019. A total of 495 patients were classified into three groups according to recurrence during the cohort observation period: recurrence group with (hypo)manic or mixed features (MMR), recurrence group with only depressive features (ODR), and no recurrence group (NR). As a result, the baseline diagnosis of bipolar disorder type 1 (BDI) and bipolar disorder type 2 (BDII), along with a familial history of BD, are strong predictors of the MMR. The discrepancies in wake-up times between weekdays and weekends, along with disrupted circadian rhythms, are identified as a notable predictor of ODR. Our findings confirm that we need to be aware of different predictors for each form of mood recurrences in patients with early-onset mood disorders. In clinical practice, we expect that information obtained from the initial assessment of patients with mood disorders, such as mood disorder type, family history of BD, regularity of wake-up time, and disruption of circadian rhythms, can help predict the risk of recurrence for each patient, allowing for early detection and timely intervention.
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Transtorno Bipolar , Transtorno Depressivo Maior , Humanos , Transtornos do Humor/diagnóstico , Estudos Prospectivos , Transtorno Depressivo Maior/diagnóstico , Transtorno Bipolar/diagnóstico , Ritmo Circadiano , RecidivaRESUMO
Objective: : As dopamine is closely linked to locomotor activities, animal studies on locomotor activities using dopaminergic agents were widely done. However, most of animal studies were performed for a short period that there is a lack of longitudinal study on the effects of dopaminergic agents on locomotor activities. This study aimed to examine the longterm effect of a dopamine D2, D3 agonist quinpirole on locomotor activities in mice using a home-cage monitoring system. Methods: : The locomotor activities of Institute Cancer Research mice were measured by infrared motion detectors in home-cages under the 12-hour dark and 12-hour light condition for three days after the quinpirole injection. Quinpirole was injected at a concentration of 0.5 mg/kg intraperitoneally in the beginning of the dark phase. The locomotor activities before and after the quinpirole administration were compared by the Wilcoxon signed-rank test and one-way repeated measures ANOVA. Results: : After the quinpirole administration, the 24-hour total locomotor activity did not change (p = 0.169), but activities were significantly increased in the 12-hour dark phase sum (p = 0.013) and decreased in the 12-hour light phase sum (p = 0.009). Significant increases in the activities were observed in the dark-light difference (p = 0.005) and dark-light ratio (p = 0.005) as well. Conclusion: : This study suggests that quinpirole injection entrains the circadian rest-activity rhythm of locomotor activities. Therefore, quinpirole can be a drug that mediates locomotor activity as a dopamine agonist as well as a modulator of the circadian rhythms.
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BACKGROUND: Given the increasing incidence of early-onset Alzheimer disease, strategies for early diagnosis and swift treatment interventions are crucial for mitigating cognitive problems in women and middle-aged individuals who face a high risk of cognitive impairment. OBJECTIVE: This study aimed to assess the effectiveness of individual cognitive training programs based on virtual reality (VR), a nonpharmacological intervention, on cognitive function and depression in middle-aged women at risk of cognitive impairment. It used VR technology, which has recently been recognized as a promising tool. METHODS: We administered a VR-based cognitive training program for 30 minutes daily, twice a week, for 12 weeks (24 sessions). This study included middle-aged women residing in older adults' welfare facilities in G-gu, Busan, from May to August 2021. A total of 60 participants were randomly divided into the training (n=30) and control (n=30) groups. Cognitive and depressive functions were assessed using the Korean versions of the Montreal Cognitive Assessment (K-MoCA), Digit Span Test (DST), Korean-Color Word Stroop Test (K-CWST), and Short Form of the Geriatric Depression Scale (SGDS-K) before the intervention. The training group underwent a VR-based cognitive training program, whereas the control group was educated to maintain regular daily activities. The same assessments were performed 12 weeks after treatment. RESULTS: A comparison of the mean scores before and after K-MoCA in the training group revealed a significant increase from 24.87 (SD 2.62) to 27.50 (SD 1.70; P<.01), indicating substantial cognitive improvement. Similarly, the mean DST forward scores increased significantly from 6.97 (SD 1.10) to 7.90 (SD 1.18; P<.01), suggesting enhanced short-term auditory memory and attention. The mean DST backward scores also showed a significant improvement from 4.10 (SD 0.71) to 4.77 (SD 1.2; P=.01). Notably, the mean SGDS-K scores decreased significantly from 3.97 (SD 2.51) to 2.13 (SD 1.87; P<.01), indicating a reduction in depression within the training group. CONCLUSIONS: The VR-based cognitive training programs significantly enhanced cognitive function and reduced depression in middle-aged women. Consequently, these programs are considered beneficial nonpharmacological cognitive training interventions for middle-aged women at high risk of cognitive impairment. TRIAL REGISTRATION: UMIN Clinical Trials Registry UMIN000049752; https://tinyurl.com/z5du989z.
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OBJECTIVE: Face-to-face evaluation is the most important in psychiatric evaluation, but smart healthcare, including non-face-to-face evaluation, can be beneficial considering the situation in which face-to-face evaluation is limited or the preventive aspect of mental illness. In this paper, we aimed to check whether mental health screening tests have the same significance as paper-based tests even when collected through mobile applications. METHODS: A smart mental healthcare screening test was conducted on the 1,327 community subjects. We measured two indicators of depression (Patient Health Questionnaire 9-item scale, PHQ-9) and anxiety (Generalized Anxiety Disorder 7-item scale, GAD-7) to check mental health conditions. RESULTS: The average Cronbach's alpha value of the PHQ-9 questionnaire was good at 0.870. As a result of PHQ-9's principal component analysis, one component with an eigenvalue of 1 or more was identified, which is suitable to be described as a single factor. The average Cronbach's alpha value of the GAD-7 was 0.919. The structural validity of the GAD-7 was confirmed through principal component analysis. CONCLUSION: Our results show that PHQ-9 and GAD-7 scales performed through mobile applications can have the same meaning as paper-based tests. Surveys using a tablet PC, or smartphone application can monitor residents' mental health and accumulate data. Based on these data, smart mental health management can check the mental health of residents and treat mental illness in connection with medical services.
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OBJECTIVE: Various and accurate psychiatric assessments in patients with breast cancer who frequently suffer from psychological problems due to long-term survivors are warranted. This systematic review aimed to investigate the current evidence on psychometric properties of psychiatric assessment for evaluating psychological problems in breast cancer patients. METHODS: This systematic review progressed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline. Four electronic databases such as Web of Science, PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature were searched. This study protocol was registered on Open Science Framework. RESULTS: Of the 2,040 articles, 21 papers were finally included. Among them, only five studies showed the performance of psychiatric assessment tools. Among 13 assessment tools used in the selected articles, the Hospital Anxiety and Depression Scale (HADS), Distress Thermometer (DT), or Mini-Mental Adjustment to Cancer Scale was frequently used for the evaluation of psychological problems. The DT and Psychosocial Distress Questionnaire-Breast Cancer showed acceptable performances for the prediction of depression and anxiety assessed by the HADS. CONCLUSION: This systematic review found psychiatric assessment tools with acceptable reliability and validity for breast cancer patients. However, comparative studies on reliability and validity of various scales are required to provide useful information for the selection of appropriate assessment tools based on the clinical settings and treatment stages of breast cancer. Joint research among the fields of psychiatry and breast surgery is needed for research to establish the convergent, concurrent, and predictive validity of psychiatric assessment tools in breast cancer patients.
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OBJECTIVE: It is necessary to identify the mental health types of young women considering the importance of the mental health during the peripartum period. This study aimed to classify the mental health types in a community sample of young women with pre-pregnancy, pregnancy, or the postpartum period. METHODS: A total of 293 young women during pre-pregnancy, pregnancy, or the postpartum period were included in this study. The clinical characteristics of depression, anxiety, perceived stress, and quality of life were assessed. The clinical characteristics of the subject were classified by cluster analysis and compared by analysis of variance. RESULTS: From the cluster analysis, the subjects were classified into three groups. Cluster 1 showed significantly lower depression and anxiety and higher quality of life than those of cluster 2 and 3. Cluster 2 demonstrated significantly higher depression and anxiety and lower quality of life than those of cluster 3 and 1. Cluster 3 represented the intermediate levels between cluster 2 and 1. CONCLUSION: This study suggested that young women during pre-pregnancy, pregnancy, or the postpartum period might be in a good mental health group, a high-risk group requiring active monitoring, or a group in need of treatment. By monitoring mental health, the groups with high risk or requiring treatment could be discovered and proper management for prevention or improvement of mental health and quality of life can be provided.
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Objective: Even though studies using machine learning on sleep-wake states have been performed, studies in various conditions are still necessary. This study aimed to examine the performance of the prediction model of locomotor activities on sleep-wake states using machine learning algorithms. Methods: The processed data using moving average of locomotor activities were used as predicting features. The sleep-wake states were used as true labels. The prediction models were established by machine learning classifiers such as support vector machine with radial basis function (SVM-RBF), linear discriminant analysis (LDA), naïve Bayes, and random forest (RF). The prediction model was evaluated by a six-fold cross validation. Results: The SVM-RBF and RF showed acceptable performance within a window of moving average from 480 to 1,200 seconds. The highest accuracy (0.869) was shown by the RF at the interval of 480 seconds. Meanwhile, the highest area under the curve (0.939) was shown by LDA at the interval of 870 seconds. Conclusion: This study suggested that the prediction model on sleep-wake state using machine learning could show an improvement of the model performance when using moving average with raw data. The prediction model using locomotor activity can be useful in research on sleep-wake state.
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OBJECTIVE: Optimism, social support, and spirituality can be important factors related to coronavirus disease-2019 (COVID-19) stress. However, studies investigating the influence and interplay of optimism, social support, and spirituality on COVID-19 simultaneously are still few. This study is aimed to explore the influence of optimism, social support, and spirituality on COVID-19 stress in the Christian church community. METHODS: A total 350 participants were included in this study. This study was cross-sectionally conducted by using an online survey on optimism, social support, spirituality, and COVID-19 stress that were measured by the Life Orientation Test-Revised (LOT-R), Multidimensional Scale of Perceived Social Support Scale (MSPSS), Spiritual Well-Being Scale (SWBS), and COVID-19 Stress Scale for Korean People (CSSK). The prediction models for COVID-19 stress were analyzed by using univariate and multiple linear regression. RESULTS: Based on the results of univariate linear regression, subjective feelings on income (p<0.001) and health status (p<0.001), LOTR (p<0.001), MSPSS (p=0.025), and SWBS (p<0.001) scores were significantly associated with COVID-19 stress. The multiple linear regression model with subjective feelings on income and health status and SWSB score was significant (p<0.001) and explained 17.7% of the variance (R2=0.177). CONCLUSION: This study showed that subjective feeling on low income, those who had poor health status, lower optimism, lower perceived social support, and lower spirituality were significantly affected with COVID-19 stress. Especially, the model with subjective feelings on income and health status, and spirituality showed highly significant effects, despite the interaction with associated factors. To cope with unpredictable stressful situations like the COVID-19 pandemic, integrated interventions on psycho-socio-spiritual aspect are warranted.
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BACKGROUND: Mood disorders require consistent management of symptoms to prevent recurrences of mood episodes. Circadian rhythm (CR) disruption is a key symptom of mood disorders to be proactively managed to prevent mood episode recurrences. This study aims to predict impending mood episodes recurrences using digital phenotypes related to CR obtained from wearable devices and smartphones. METHODS: The study is a multicenter, nationwide, prospective, observational study with major depressive disorder, bipolar disorder I, and bipolar II disorder. A total of 495 patients were recruited from eight hospitals in South Korea. Patients were followed up for an average of 279.7 days (a total sample of 75 506 days) with wearable devices and smartphones and with clinical interviews conducted every 3 months. Algorithms predicting impending mood episodes were developed with machine learning. Algorithm-predicted mood episodes were then compared to those identified through face-to-face clinical interviews incorporating ecological momentary assessments of daily mood and energy. RESULTS: Two hundred seventy mood episodes recurred in 135 subjects during the follow-up period. The prediction accuracies for impending major depressive episodes, manic episodes, and hypomanic episodes for the next 3 days were 90.1, 92.6, and 93.0%, with the area under the curve values of 0.937, 0.957, and 0.963, respectively. CONCLUSIONS: We predicted the onset of mood episode recurrences exclusively using digital phenotypes. Specifically, phenotypes indicating CR misalignment contributed the most to the prediction of episodes recurrences. Our findings suggest that monitoring of CR using digital devices can be useful in preventing and treating mood disorders.
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Transtorno Bipolar , Transtorno Depressivo Maior , Humanos , Transtorno Bipolar/diagnóstico , Transtorno Bipolar/tratamento farmacológico , Transtorno Depressivo Maior/diagnóstico , Depressão , Estudos de Coortes , Estudos Prospectivos , Mania , Fenótipo , RecidivaRESUMO
Objective: This study aimed to explore the relationship among several indices of circadian rhythms and lipid peroxidation of brain tissue in mice. Methods: After entrainment of 4-week-old mice, one group was disrupted their circadian rhythms for three days and the other group for seven days (n = 10, respectively). After a recovery period, the Y-maze test, the elevated plus maze test, the tail suspension test, and the forced swimming test were conducted. To assess lipid peroxidation in brain tissue, thiobarbituric acid reactive substances were measured in the cortex, hippocampus, and cerebellum. Results: When circadian rhythms were disrupted and adapted back to their original rhythm, the recovery time of the 7-day disruption group (median 3.35 days) was significiantly faster than one of the 3-day disruption group (median 4.87 days). In the group with a 7-day disruption, mice that had recovered their rhythms early had higher malondialdehyde levels in their hippocampus compared to those with delayed recovery. The entrainment of circadian rhythms was negatively correlated with the malondialdehyde level of brain tissue. The behavioral test results showed no differences depending on the disruption durations or recovery patterns of circadian rhythms. Conclusion: These results suggest that disruption types, recovery patterns, and the entrainment of circadian rhythms are likely to affect oxidative stress in adolescents or young adult mice. Future study is needed to confirm and specify these results on the effects of circadian rhythms on oxidative stress and age-dependent effects.
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PURPOSE OF REVIEW: We present a review of research on the role of melatonin in the management of sleep and circadian disorders, stressing current overall view of the knowledge across psychiatric disorders. RECENT FINDINGS: Dysregulation of sleep and circadian rhythms has been established in several psychiatric and neurocognitive disorders for long. Recent research confirms this finding consistently across disorders. The secretion of melatonin in schizophrenia and neurocognitive disorders is reduced due to a smaller volume and enlarged calcification of the pineal gland. On the other hand, melatonin dysregulation in bipolar disorder may be more dynamic and caused by light-sensitive melatonin suppression and delayed melatonin secretion. In both cases, exogenous melatonin seems indicated to correct the dysfunction. However, a very limited number of well-designed trials with melatonin to correct sleep and circadian rhythms exist in psychiatric disorders, and the evidence for efficacy is robust only in autism, attention deficit hyperactivity disorder (ADHD), and neurocognitive disorders. This topic has mainly not been of interest for recent work and well-designed trials with objective circadian parameters are few. Overall, recent studies in psychiatric disorders reported that melatonin can be effective in improving sleep parameters such as sleep onset latency, sleep efficiency, and sleep quality. Recent meta-analysis suggests that optimal dosage and dosing time might be important to maximize the efficacy of melatonin. The knowledge base is sufficient to propose well-designed, larger trials with circadian parameters as inclusion and outcome criteria. Based on the partly fragmentary information, we propose testing efficacy in disorders with neurocognitive etiopathology with later and higher dosing, and affective and anxiety disorders with lower and earlier dosing of melatonin. Melatonin is promising for the correction of sleep and circadian abnormalities in psychiatric disorders. However, research results on its effect are still few and need to be accumulated. For effective use of melatonin, it is necessary to consider the appropriate dosage and administration time, depending on the individual abnormality of sleep and circadian rhythms.
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Transtorno do Deficit de Atenção com Hiperatividade , Transtorno Bipolar , Melatonina , Transtornos do Sono-Vigília , Humanos , Melatonina/uso terapêutico , Sono/fisiologia , Ritmo Circadiano/fisiologia , Transtornos do Sono-Vigília/tratamento farmacológicoRESUMO
BACKGROUND: The clinical importance of morningness-eveningness, especially in mood disorders, is prevailing. The differential relation of chronotype with diagnoses of early-onset mood disorders, mood symptoms, anxiety, and quality of life was evaluated. METHODS: Early-onset mood disorder patients [n = 419; 146 major depressive disorder (MDD); 123 bipolar I disorder (BDI); 150 bipolar II disorder (BDII)] from the Mood Disorder Cohort Research Consortium were assessed for chronotype using the composite scale for morningness (CSM) and its association with clinical variables obtained during the clinician-verified euthymic state. RESULTS: The mean total CSM of BDI was significantly higher than MDD and BDII (p < 0.001). In all types of mood disorders, higher total CSM was associated with lower Quick inventory of depressive symptomatology (p < 0.005) and higher WHO quality of life (p < 0.005). Such negative correlations between the total CSM and Montgomery-Asberg depression rating were significant in MDD and BDI (p < 0.05) and marginally significant in BDII (p = 0.077). CSM was a significant contributor to quality of life in BDI (p < 0.001) and BDII (p = 0.011), but it was not for MDD. LIMITATIONS: The defined 'euthymic state' that may not fully reflect the remission of episode; limited generalizability due to clinical characteristic of early-onset mood disorder; the disparity between diurnal preference measured by the CSM and chronotype; possible effects of the last mood episode polarity and medication; and, lack of control group. CONCLUSION: Less eveningness was associated with less severe depressive symptoms and better quality of life. This suggests that morningness may reduce residual depressive symptoms and recover function of patients.
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Transtorno Depressivo Maior , Qualidade de Vida , Ritmo Circadiano , Transtorno Ciclotímico , Humanos , Estudos Prospectivos , Inquéritos e QuestionáriosRESUMO
OBJECTIVE: Data processing in analysis of circadian rhythm was performed in various ways. However, there was a lack of evidence for the optimal analysis of circadian rest-activity rhythm. Therefore, we aimed to perform mathematical simulations of data processing to investigate proper evidence for the optimal analysis of circadian rest-activity rhythm. METHODS: Locomotor activities of 20 ICR male mice were measured by infrared motion detectors. The data of locomotor activities was processed using data summation, data average, and data moving average methods for cosinor analysis. Circadian indices were estimated according to time block, respectively. Also, statistical F and p-values were calculated by zero-amplitude test. RESULTS: The data moving average result showed well-fitted cosine curves independent of data processing time. Meanwhile, the amplitude, MESOR, and acrophase were properly estimated within 800 seconds in data summation and data average methods. CONCLUSION: These findings suggest that data moving average would be an optimal method for data processing in a cosinor analysis and data average within 800-second data processing time might be adaptable. The results of this study can be helpful to analyze circadian restactivity rhythms and integrate the results of the studies using different data processing methods.
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Exogenous melatonergic agents are widely used to treat insomnia and sleep disturbance. Several studies have shown that they might also modulate circadian rhythms. The purpose of this systematic review and meta-analysis was to summarize current knowledge about the effects of melatonin supplements and melatonin agonists on the sleep-wake cycle as well as on the circadian rhythm of melatonin in healthy participants and in patients with psychiatric disorders. The following electronic databases were searched: EMBASE, PubMed, Web of Science, CINAHL, and Cochrane Library. Of the 12,719 articles, we finally selected 30 studies including 1294 healthy participants and 8 studies including 687 patients with psychiatric disorders. Cochrane risk of bias tool was used to assess the risk of bias. Using meta-ANOVA, studies on healthy participants showed advancing effects of melatonergic supplements and agonists on sleep-wake cycle according to dosing time and dosage, despite the fact that the original individual melatonin rhythm was within a normal range (fixed effect model standardized mean difference [95% Confidence Interval] = -0.639[-0.968 to -0.310]). In a limited number of randomized controlled trials with psychiatric patients, the findings seemed similar to those with healthy participants, despite the psychiatric disorders and treatment related factors affecting circadian rhythms. Given the unmet clinical need for evidence-based treatments to correct circadian rhythms in psychiatric disorders, efficacy of melatonergic agents seen in healthy participants, and similarity of findings among psychiatric patients, large scale, well-designed randomized controlled trials are needed to test efficacy on circadian parameters in psychiatric disorders.