Psychiatry Investigation最新文献

Objective: This study aimed to investigate how shift-working nursing professionals perceive the current lights-off time in wards as early, appropriate, or late and how their perceptions can be influenced when considering people's usual bedtimes.

Methods: An online survey was conducted comprising queries about the current lights-off time in wards and respondents' opinions, self-rated psychological status, and perceptions of the current lights-off time considering others' usual bedtimes. Psychological status was evaluated using the Insomnia Severity Index, the Patient Health Questionnaire-9, the Dysfunctional Beliefs and Attitudes about Sleep-16, and the Discrepancy between Desired Time in Bed and Desired Total Sleep Time (DBST) Index, along with the expected DBST Index of others.

Results: Of 159 nursing professionals, 88.7% regarded the current lights-off time of 9:46±0:29 PM as appropriate. However, when considering others' usual bedtimes, the proportion perceiving the lights-off time as too early rose from 6.9% to 28.3%. Participants recommended delaying the lights-off time to 10:06±0:42 PM for patients' sleep and 10.22±0:46 PM for nursing care activities. Nursing professionals' insomnia severity was significantly higher among who responded that current light off time is too early after considering usual bedtime of other people.

Conclusion: This study underscores the need to reassess lights-off times in wards given individuals' typical bedtimes. The findings emphasize the need to address nursing professionals' perspectives and insomnia severity when optimizing lights-off schedules in healthcare settings.

Objective: It takes significant time and energy to collect data on explicit networks. This study used graph machine learning to identify hidden networks and predict mental health conditions in the middle-aged and old.

Methods: Data came from the Korean Longitudinal Study of Ageing (2016-2018), with 2,000 participants aged 56 or more. The dependent variable was mental disease (no vs. yes) in 2018. Twenty-eight predictors in 2016 were included. Graph machine learning with systematic hyper-parameter selection was conducted.

Results: The area under the curve was similar across different models in different scenarios. However, sensitivity (93%) was highest for the graph random forest in the scenario of 2,000 participants and the centrality requirement of life satisfaction 90. Based on the graph random forest, top-10 determinants of mental disease were mental disease in previous period (2016), age, income, life satisfaction-health, life satisfaction-overall, subjective health, body mass index, life satisfaction-economic, children alive and health insurance. Especially, life satisfaction-overall was a top-5 determinant in the graph random forest, which considers life satisfaction as an emotional connection and a group interaction.

Conclusion: Improving an individual's life satisfaction as a personal condition is expected to strengthen the individual's emotional connection as a group interaction, which would reduce the risk of the individual's mental disease in the end. This would bring an important clinical implication for highlighting the importance of a patient's life satisfaction and emotional connection regarding the diagnosis and management of the patient's mental disease.

Objective: To investigate the impact of circadian rhythm disruptions on mental health among college students and explore effective interventions for maintaining stable circadian rhythms.

Methods: A comprehensive review of literature was conducted, focusing on sleep patterns, circadian rhythms, and their effects on mental health. Studies were analyzed to identify common factors contributing to circadian misalignment in college students and effective treatments. Data from large-scale studies and specific clinical trials were utilized to understand the relationship between circadian rhythms and psychiatric disorders.

Results: Disruptions in circadian rhythms were linked to increased prevalence of psychiatric disorders such as depression, anxiety, and bipolar disorder. Biological changes during adolescence, academic pressures, and extensive use of electronic devices were major contributing factors. Effective interventions included light therapy, chronotherapy, melatonin supplementation, and cognitive behavioral therapy for insomnia.

Conclusion: Stable circadian rhythms are crucial for mental health, particularly in college students who are vulnerable to disruptions due to lifestyle factors. Implementing interventions such as regular sleep schedules, light exposure management, and behavioral therapies can significantly improve mental health outcomes. Further research and targeted mental health programs are essential to address circadian misalignment and its associated psychiatric disorders in this population.

Objective: Previous studies have investigated obesity and appetite changes in patients with depression, which consisted of a small age range of adults and used body mass index rather than abdominal obesity. The objective of this study is to examine the relationship between abdominal obesity and the risk of depression by sex and age groups.

Methods: This study utilized the National Health Insurance Sharing Service (NHISS) database of South Korea, which includes those over 20 years old and who had undergone a health examination in 2009 and their claims data between 2009 and 2018. The diagnosis of depressive episodes was based on the International Statistical Classification of Disease and Related Health Problems 10th revision. Abdominal obesity was measured by waist circumference (WC) and was divided into six levels (cm). Cox proportional-hazard regression analyses were conducted to examine the relationship between abdominal obesity and the risk of depression by sex and age groups.

Results: Among 9,041,751 participants, 1,376,279 were diagnosed with depression. Those with higher WC (90 cm or higher for males, 85 cm or higher for females) showed an increased risk for depression in both sexes (hazard ratio [HR]=1.09, 95% confidence interval [CI]: 1.07-1.11 for males, HR=1.03, 95% CI: 1.02-1.05 for females). Underweight males (WC<80 cm) also showed an increased risk for depression (HR=1.05, 95% CI: 1.04-1.05).

Conclusion: It has been found that higher WC was associated with increased risks of depression in both sexes. Although underweight males showed an elevated risk of depression, a healthy weight is associated with fewer depression symptoms.

Objective: The purpose of this study was to investigate the different categories of males within two groups, namely a community male sample who engaged in online sexual activities (OSAs) and a subclinical male sample who were out of control in viewing pornography and had sought help. Additionally, the study aimed to determine the threshold for excessive OSAs in both samples.

Methods: A total of 568 community adult males who engaged in OSAs and 567 adult males seeking help for pornography use were recruited online. A latent profile analysis (LPA) was used to identify potential profiles within the samples. Cut-point analyses were conducted to determine optimal cutoff scores for OSAs in each sample.

Results: The LPA revealed two categories with different cutoff scores for OSAs within each sample. Excessive OSA can be a screening tool for detecting out-of-control behavior. More stringent criteria for identifying excessive OSAs can aid in distinguishing problematic pornography use (PPU) from impaired control in viewing sexually-explicit materials (SEMs). Two subcategories of loss of control emerged: high OSAs frequency impaired control and high viewing SEMs impaired control.

Conclusion: The threholds of excessive OSAs varies among community and sub-clinical male samples; this knowledge can assist in screening out individuals with impaired control and selecting individuals with PPU from the subclinical sample.

Objective: This study compared adaptive functioning measured by the Korean version of Vineland Adaptive Behavior Scales, Second Edition (K-VABS-II), in preschool children with developmental disabilities (DD) and those with typical development (TD). We also examined the correlation of K-VABS-II adaptive profiles with developmental and behavioral assessments.

Methods: Two hundred preschool children (73 females and 127 males, mean age 54.7±9.1 months) were recruited from special educational centers, community-based daycare centers, and kindergartens. Eighty-one with DD comprising 61 with autism spectrum disorder, 63 with intellectual disability, 12 with language disorder, and 119 with TD were included. Their developmental profiles were measured by the Psychoeducational Profile-Revised (PEP-R), Preschool Receptive-Expressive Language Scale (PRES), K-VABS-II, Social Responsiveness Scale (SRS), and the Korean version of the Childhood Autism Rating Scale (K-CARS). The parent completed the Child Behavior Checklist (CBCL), and Aberrant Behavior Checklist (ABC).

Results: The K-VABS-II Adaptive Behavior Composite and all domain scores of K-VABS-II differed significantly between children with DD and TD (all p<0.001). In most domains, K-VABS-II had moderate-to-strong correlations with PEP-R, PRES, K-CARS, and SRS. The Maladaptive Behavior Index domain of K-VABS-II had moderate correlations with behavioral assessments, including CBCL and ABC.

Conclusion: These findings suggest that K-VABS-II is useful in evaluating developmental levels and adaptive and maladaptive behaviors of preschool children with DD. K-VABS-II also had significant correlations with cognitive, language, social, and behavioral assessments.

Objective: Understanding the specific fears associated with coronavirus disease-2019 (COVID-19), particularly within different cultural contexts, is crucial for developing effective mental health interventions. This study aims to develop and validate the COVID-19 Infection Fear Scale (CIFS) in a collectivist cultural context such as Korea.

Methods: A total of 1,002 adults aged 19 to 70 participated in an online survey in May 2020. The CIFS was developed through a multidisciplinary approach, categorizing public fears into two domains: fear of infection and fear of negative outcomes post-infection. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to validate the factor structure. Reliability and construct validity were assessed through correlations with anxiety (Generalized Anxiety Disorder-7), depression (Patient Health Questionnaire-9), suicidal ideation, and coping strategies.

Results: The CIFS demonstrated high internal consistency. EFA and CFA supported a two-factor model. The Rasch analysis confirmed good item fit, with infit and outfit indices within the acceptable range. Differential item functioning analysis indicated minor sex and age biases, addressed without removing items. Construct validity was supported by significant correlations with anxiety, depression, suicidal ideation, and coping strategies. Fear of negative consequences post-infection showed a stronger correlation with psychological distress than fear of infection.

Conclusion: The CIFS is a reliable and valid tool for measuring fear related to COVID-19 infection and its consequences, particularly within a collectivist cultural context. This scale can aid in identifying individuals at higher risk of psychological distress and inform targeted interventions.

Objective: Previous studies have provided inconclusive results on the association between depression and stroke risk, and the potential modifying effect of comorbid insomnia on this association remains unclear. Our study aimed to clarify the independent roles of depression and insomnia as risk factors for stroke and to investigate the possibility of an interaction effect between these two conditions on stroke incidence.

Methods: We used data from the Korean Genome and Epidemiology Study. The primary exposure was depression, measured by the Beck Depression Inventory. The secondary exposure was insomnia. The main outcome was the occurrence of stroke observed in biennial follow-up surveys. Cox proportional regression analysis was performed to estimate the effects of depression and insomnia on stroke incidence. We also conducted interaction analysis to investigate the interaction between depression and insomnia on stroke incidence.

Results: During 16 years of follow-up involving 3,301 individuals, we documented 172 cases of new-onset stroke (4.3 cases per 1,000 person-years). Cox proportional logistic regression analysis showed that severe depression significantly increased the risk of stroke (hazard ratio [HR]: 2.06, 95% confidence interval [CI]: 1.13-3.75), whereas mild and moderate depression did not increase this risk. Interaction analysis demonstrated that stroke risk was increased with only moderate (HR: 2.04, 95% CI: 1.04-4.00) and severe (HR: 3.01, 95% CI: 1.43-6.31) depression among individuals without insomnia.

Conclusion: Although general depression does not significantly increase stroke risk, moderate-to-severe depression may increase this risk, particularly in individuals without insomnia.

Objective: Suicide poses a significant public health concern with increasing prevalence in the general population, emphasizing the need for effective gatekeeper suicide prevention education. This study assesses the longitudinal effectiveness of the "Suicide CARE" gatekeeper training program within a general community sample. Suicide CARE is representative gatekeeper program in Korea. A total of 5 million individuals completed the training program of Suicide CARE in Korea to date.

Methods: Participants were recruited through the Korea Suicide Prevention Association website, randomly assigned to the experimental (n=49) or control group (n=53). Pre- and post-training surveys, along with a 3-month follow-up, measured perceived knowledge, gatekeeper efficacy, preparedness, and attitudes toward suicide. Longitudinal effects were analyzed using repeated measures analysis of variance.

Results: The experimental group showed significant improvement in perceived knowledge, gatekeeper efficacy, perceived preparedness, and some aspects of attitude towards suicide compared to the control group, with effects declining over time but remaining statistically significant at the 3-month follow-up test.

Conclusion: This study is the first to evaluate the longitudinal effectiveness of Suicide CARE in a community population. Strategic integration of evidence-based gatekeeper training programs like Suicide CARE can contribute to community suicide prevention initiatives.

Objective: The coronavirus disease-2019 (COVID-19) pandemic's social isolation has significantly impacted mental health, increasing depression and anxiety. This study explores the effects of social isolation on both humans and mice, focusing on behavioral changes and hippocampal protein expression. It also investigates genetic alterations through single-cell RNA and whole-genome sequencing (WGS).

Methods: Here we conducted behavioral studies, protein expression studies, single-nucleus sequencing (snRNAseq), and WGS of the hippocampus of mice that underwent early maternal separation and social isolation, and a demographic study of community populations who had been self-quarantined owing to COVID-19 exposure to investigate the link between somatic mutations and stress due to social isolation.

Results: The demographic study demonstrated more negative mental health findings among individuals who live alone or are single. Mice subjected to early maternal separation and social isolation demonstrated increased anxiety-like behaviors and stress-related corticotropin-releasing hormone receptor 1, and neurogenesis-related sex-determining region Y-box 2 and doublecortin expression. In snRNA-seq, differences, such as transthyretin increase, were observed in the maternal separation group, and somatic mutations, including insertion in the intron site of Tmem267, were observed in the social isolation group on WGS.

Conclusion: The results of this study suggest that stress, such as social isolation, can cause changes at the genetic level, as well as behavioral and brain protein changes.