Psychiatry Investigation最新文献

Objective: This study aimed to use deep learning (DL) to develop a cost-effective and accessible screening tool to improve the detection of cognitive decline, a precursor of Alzheimer's disease (AD). This study integrating a comprehensive battery of neuropsychological tests adjusted for individual demographic variables such as age, sex, and education level.

Methods: A total of 2,863 subjects with subjective cognitive complaints who underwent a comprehensive neuropsychological assessment were included. A random forest classifier was used to discern the most predictive test combinations to distinguish between dementia and nondementia cases. The model was trained and validated on this dataset, focusing on feature importance to determine the cognitive tests that were most indicative of decline.

Results: Subjects had a mean age of 72.68 years and an average education level of 7.62 years. The DL model achieved an accuracy of 82.42% and an area under the curve of 0.816, effectively classifying dementia. Feature importance analysis identified significant tests across cognitive domains: attention was gauged by the Trail Making Test Part B, language by the Boston Naming Test, memory by the Rey Complex Figure Test delayed recall, visuospatial skills by the Rey Complex Figure Test copy score, and frontal function by the Stroop Test Word reading time.

Conclusion: This study showed the potential of DL to improve AD diagnostics, suggesting that a wide range of cognitive assessments could yield a more accurate diagnosis than traditional methods. This research establishes a foundation for future broader studies, which could substantiate the approach and further refine the screening tool.

Objective: The Impact of Event Scale-Revised (IES-R) is a widely used self-report for assessing posttraumatic stress disorder (PTSD), originally aligned with Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV diagnostic criteria. This study aimed to evaluate the applicability of the IES-R under the DSM-5 guidelines and establish a cutoff point for DSM-5 PTSD diagnosis.

Methods: A total of 238 participants recruited from multiple psychiatric centers, including 67 patients with PTSD, 72 patients with psychiatric controls, and 99 healthy controls, were included in the study. All participants completed the Korean version of the Structured Clinical Interview for the DSM-5 research version to confirm the presence of PTSD, the Korean version of PTSD Checklist for DSM-5 (PCL-5), the Beck Depression Inventory-II, the Beck Anxiety Inventory, and the Spielberger State Trait Anxiety Inventory.

Results: The IES-R demonstrated good internal consistency and a high correlation with the PCL-5. Through factor analysis, 5 distinct dimensions emerged within the IES-R: sleep disturbance, intrusion, hyperarousal, avoidance, and numbness-dissociation. A proposed cutoff score of 25 on the IES-R was suggested for identifying patients with PTSD.

Conclusion: These findings underscore the scale's concurrent validity with the DSM-5 PTSD criteria and its effectiveness as a screening tool. Implementing a cutoff score of 25 on the IES-R can enhance its utility in identifying DSM-5 PTSD cases.

The circadian rhythm for mood (CRM) is a digital therapeutic, which aims to prevent mood episode and improve clinical course in patients with major mood disorders. Developed on the circadian rhythm hypothesis of mood disorder, CRM predicts the impending risk of mood episode with its built-in algorithm, utilizing wearable devices data and daily self-reports, and provides personalized feedback. In a pilot study of the CRM, the users experienced less frequent and shorter duration of mood episodes than the non-users. To investigate the efficacy of the upgraded CRM, a double-blind, randomized, sham-controlled, parallel-group trial is designed. Patients aged between 19 and 70, diagnosed with bipolar I disorder, bipolar II disorder, or major depressive disorder, in a euthymic state for more than two months, can participate. During this 12-month trial, participants are assessed for episode recurrence every three months, and the efficacy of the CRM as a potential digital therapeutic is evaluated. Trial registration: ClinicalTrials.gov Identifier: NCT05400785.

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: Cognition impairments are considered as a fundamental characteristic of severe mental disorders (SMD). Recent studies suggest that hyperprolactinemia may exert a detrimental influence on cognitive performance in patients with SMD. The objective of this study was to investigate the correlation between serum prolactin levels and cognitive function in female individuals diagnosed with SMD.

Methods: We conducted a study on 294 patients with SMD and 195 healthy controls, aged between 14 to 55 years old. Cognitive function was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), while prolactin levels were measured in serum. Descriptive analysis and comparative analysis were performed to compare cognitive function and prolactin levels between groups, and linear regression models were used to explore the relationship between prolactin and cognitive function.

Results: Compared to the healthy control, individuals with SMD exhibited significantly higher levels of prolactin, while scoring lower on RBANS total and every index scores. Furthermore, a negative association between prolactin levels and cognitive function (RBANS total index score, attention, and delayed memory) was observed in SMD patients. Importantly, this inverse correlation between prolactin and cognition function (RBANS total index score, total scale score, and attention) persisted in patients who were not taking medications that could potentially influence serum prolactin levels.

Conclusion: Our study reveals a significant correlation between elevated prolactin levels and cognitive impairment in female patients with SMD, underscoring the importance of monitoring prolactin levels in order to prevent cognitive deterioration among female SMD patients.

Objective: Obsessive-compulsive disorder (OCD) is a psychiatric condition that causes significant distress and social costs and often follows a chronic course with frequent relapses. Approximately 20% of patients do not respond to medication or cognitive behavioral therapy; gamma knife surgery (GKS) has been proposed as a treatment option for these patients. However, research on GKS for OCD patients is rare.

Methods: In this study, 10 patients with treatment-resistant OCD underwent GKS, and the treatment response and side effects were assessed. The improvement in patients' obsessive-compulsive symptoms was evaluated using the Yale-Brown Obsessive Compulsive Scale (YBOCS) scores following GKS. Additionally, the characteristics distinguishing the groups with favorable responses to GKS from those with less favorable responses were examined.

Results: GKS was well tolerated, and patients demonstrated a statistically significant reduction in YBOCS scores before and after GKS (p=0.016). Patients that responded to GKS exhibited distinct characteristics from those who did not respond. Patients who responded poorly tended to present an earlier age of onset, a longer duration of illness, more frequent hospitalizations, poorer social functioning, and a greater incidence of suicide attempts/thoughts.

Conclusion: This study not only demonstrated that GKS is a safe and effective treatment method for intractable OCD but also revealed characteristics distinguishing patients who respond well to GKS from those who do not. These results may aid in the selection of patients for future application of GKS.

Objective: This study aims to investigate the thoughts of the general population regarding life-sustaining treatment for both oneself and family members and to assess the factors associated with those thoughts.

Methods: A total of 1,500 individuals participated in this study by completing a questionnaire consisting of self-reporting items with some instructions, basic demographic information, thoughts on life-sustaining treatment, and psychosocial scales. The disease status was calculated using the Charlson Comorbidity Index. The psychosocial scales included the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Pittsburgh Sleep Quality Index, and Multidimensional Scale of Perceived Social Support.

Results: The majority of participants did not want to receive life-sustaining treatment for both themselves and their families. However, more people wanted life-sustaining treatment for their family members (35.9%) than for themselves (21.6%). Among the basic demographic characteristics, there were significant differences in age, sex, marital status, living arrangements, occupational status, religion, and disease status. Regarding the psychosocial scales, there were significant differences in the PHQ-9 and GAD-7 scores between the group that preferred life-sustaining treatment for family members and the group that did not.

Conclusion: The findings suggest that life-sustaining treatment decisions for oneself and for one's family members can be different. We recommend a more clear expression of one's preferences regarding the last moments of one's life, including advance directives.

Objective: Increased fast food consumption can have adverse effects on health and well-being among adolescents, posing a significant public health concern. The school closures due to the coronavirus disease-2019 (COVID-19) pandemic have led to changes in eating patterns and disrupted a balance diet among adolescents. This study explored the factors associated with fast food consumption among adolescents during school closures due to the COVID-19 pandemic.

Methods: A total of 1,710 middle and high school students in Gwangju, South Korea participated in a cross-sectional survey. The self-administered questionnaire included items assessing dietary intake, physical activity, sleep, media use, and sociodemographic information. The Patient Health Questonnaire-9, Generalized Anxiety Disorder-7, and three item version of the UCLA Loneliness Scale were also administered. Multivariable logistic regression was used to examine the factors associated with increased fast food consumption.

Results: Approximately 34.6% of the surveyed adolescents reported increased fast food consumption during school closures, as well as increased sleep duration, increased sedentary behaviors including watching TV and using the internet, and reduced physical activity. Multivariable logistic regression analysis revealed that fast food consumption during school closures was associated with irregular patterns of main meals and sleep, decreased physical activity, increased internet use, and a lack of daytime adult supervision.

Conclusion: Our results highlight the need for dietary and lifestyle monitoring and guidelines to promote health among adolescents, especially during school closures. In conclusion, nutrition intervention programs aiming to limit fast food consumption and enhance healthy dietary habits among adolescents during long-term school closures are warranted.

Objective: The objective of this study is to compare the psychosocial characteristics of functional dyspepsia (FD) with its subgroups, epigastric pain syndrome (EPS) and postprandial distress syndrome (PDS), against a healthy control group, and to investigate the quality of life (QoL).

Methods: All of the subjects were 210 adults, 131 patients with FD were diagnosed by gastroenterologist and 79 adults with no observable symptoms of FD were selected as the normal control group. Demographic factors were investigated. The Korean-Beck Depression Inventory-II, Korean-Beck Anxiety Inventory, Korean-Childhood Trauma Questionnaire, Multidimensional Scale of Perceived Social Support, Connor-Davidson Resilience Scale, and WHO Quality of Life Assessment Instrument Brief Form were used to assess psychological factors. A one-way analysis of variance was used to compare differences among the groups. Further, a stepwise regression analysis was conducted to determine factors affecting the QoL of the FD group.

Results: Between-group differences in demographic characteristics were not significant. Depression (F=37.166, p<0.001), anxiety (F=30.261, p<0.001), and childhood trauma (F=6.591, p<0.01) were all significantly higher in FD group compared to the normal control. Among FD subgroups, EPS exhibited higher levels of both depression and anxiety than PDS. Social support (F=17.673, p<0.001) and resilience (F=8.425, p<0.001) were significantly lower in FD group than in other groups, and the values were higher in PDS than in EPS. Resilience (β=0.328, p<0.001) was the most important explanatory variable. The explained variance was 46.6%.

Conclusion: Significantly more symptoms of depression, anxiety, childhood trauma was observed for both FD sub-group. These groups also had less social support, resilience, and QoL than the control groups.

Objective: This study examined the factors affecting depression, anxiety, and suicidal ideation among patients with coronavirus disease-2019 (COVID-19) during the early phase of COVID-19 in South Korea and investigated the role of stigma in moderating the effects of loneliness on mental health problems among these patients.

Methods: Conducted as part of the COVID-19 Mental Health Panel Survey over 12 weeks in 2021, this survey enrolled participants aged 15-79 years, applying standardized weights for ratio correction, and collected 640 completed questionnaires. Demographic characteristics were analyzed using descriptive statistics. Suicidal ideation, anxiety, and depression post-COVID-19 were examined using t-tests and logistic regression. The PROCESS macro explored stigma's moderating effects on loneliness and mental health outcomes.

Results: Results showed that 7.9% and 10.0% of the enrolled participants were at risk for anxiety and depression, respectively, with 3% contemplating suicide post-COVID-19. Stigma positively impacted depression and anxiety, acting as a significant moderator for loneliness, and mental health, with a stronger effect for higher stigma perception. Unemployment and college education elevated mental health risks in COVID-19 cases. Low health satisfaction and poor sleep were linked to suicidal ideation, while fatigue and COVID-19 stigma increased depression and anxiety risks. Loneliness was significantly associated with suicidal ideation, depression, and anxiety.

Conclusion: Unemployment, college education, low health satisfaction, and poor sleep were linked to suicidal ideation. Fatigue and COVID-19 stigma raised depression/anxiety risks. Loneliness correlated with suicidal thoughts, depression, and anxiety. Stigma moderated the link between loneliness and mental health issues.