Psychological Characteristics and Quality of Life of Patients With Functional Dyspepsia.

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 (ß=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.

Risk Factors and Trends in Adolescent's Suicide Attempt Rates Before and After the Coronavirus Disease 2019 Pandemic.

BACKGROUND: Understanding adolescents' mental health during the coronavirus disease 2019 (COVID-19) pandemic and identifying those most at risk is an urgent public health challenge. This study explored the trend of suicide attempts and the association between loneliness, family financial stress, and suicide attempts during the COVID-19 pandemic among adolescents. METHODS: Data of the 2020 to 2022 Korea Youth Risk Behavior Surveys for adolescents aged 13-18 years were used. Multivariate logistic regression analyses were performed to examine the association between suicide attempts, family financial stress, and loneliness during the COVID-19 pandemic. RESULTS: The trend of suicide attempt rates was lowest in 2020 (1.9%, 1,034 out of 53,534) and it showed an increasing trend with rates of 2.2% (1,159 out of 53,445) in 2021 and 2.5% (1,271 out of 50,455) in 2022. The risk of suicide attempt was higher among adolescents who experienced financial stress (in 2020: adjusted odds ratio [AOR], 1.53, 95% confidence interval [CI], 1.26-1.88; in 2021: AOR, 1.63, 95% CI, 1.03-1.54) and felt lonely (in 2020: AOR, 2.19, 95% CI, 1.78-2.70; in 2021: AOR, 2.65, 95% CI, 2.16-3.26; in 2022: AOR, 1.3, 95% CI, 1.04-1.55) than those who did not. CONCLUSION: The COVID-19 pandemic affected the suicide attempts of adolescents, with financial stress and feelings of loneliness closely linked to this impact. Although the pandemic nears its end, the persistent risk of suicide attempts among adolescents remains a concern. Therefore, it is imperative to implement targeted screening and interventions to address adolescent suicide risk.

Classifying Children with ADHD Based on Prefrontal Functional Near-infrared Spectroscopy Using Machine Learning.

Objective: : Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children and adults characterized by cognitive and emotional self-control deficiencies. Previous functional near-infrared spectroscopy (fNIRS) studies found significant group differences between ADHD children and healthy controls during cognitive flexibility tasks in several brain regions. This study aims to apply a machine learning approach to identify medication-naive ADHD patients and healthy control (HC) groups using task-based fNIRS data. Methods: : fNIRS signals from 33 ADHD children and 39 HC during the Stroop task were analyzed. In addition, regularized linear discriminant analysis (RLDA) was used to identify ADHD individuals from healthy controls, and classification performance was evaluated. Results: : We found that participants can be correctly classified in RLDA leave-one-out cross validation, with a sensitivity of 0.67, specificity of 0.93, and accuracy of 0.82. Conclusion: : RLDA using only fNIRS data can effectively discriminate children with ADHD from HC. This study suggests the potential utility of the fNIRS signal as a diagnostic biomarker for ADHD children.

Classification of fNIRS signals from adolescents with MDD in suicide high- and low-risk groups using machine learning.

Prefrontal cortex activation is attenuated during cognitive tasks in patients with suicidal ideation or major depressive disorder (MDD). However, the apparent relationship between patients with MDD, especially suicide high-risk (SHR) adolescents, and the characteristics of their hemodynamic responses has not yet been elucidated. To investigate this relationship, we recruited 30 patients with MDD aged 13-19. Functional near-infrared spectroscopy (fNIRS) data were collected for all patients during a Stroop test. Through a ten-time iterative leave-one-out cross-validation via 1000 iterative random search-based feature selections, we achieved a generalized classification accuracy of 70.3±5.0 % (from min. 63.3 % to max. 76.7 %). From the results of random search-based feature selection, Ch08oxy and Ch09deoxy were identified as the two most relevant fNIRS channels. This finding implies that these fNIRS channels can be used as neurological biomarkers to distinguish SHR adolescents with MDD from suicide low-risk (SLR) adolescents. In addition, we determined the oxy-Hb channels of the SHR group, except for Ch01oxy, Ch02oxy, Ch11oxy, and Ch14oxy, were hyperactivated compared to the SLR group.

Simultaneous establishment of pancreatic cancer organoid and cancer-associated fibroblast using a single-pass endoscopic ultrasound-guided fine-needle biopsy specimen.

Considering the critical roles of cancer-associated fibroblasts (CAFs) in pancreatic cancer, recent studies have attempted to incorporate stromal elements into organoid models to recapitulate the tumor microenvironment. This study aimed to evaluate the feasibility of patient-derived organoid (PDO) and CAF cultures by using single-pass endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) samples from prospectively enrolled pancreatic cancer patients. The obtained samples were split into two portions for PDO and CAF cultures. PDOs and CAFs were cultured successfully in 54.4% (31/57) and 47.4% (27/57) of the cases, respectively. Both components were established in 21 cases (36.8%). Various clinicopathologic factors, including the tumor size, tumor location, clinical stage, histologic subtype, and tumor differentiation, did not influence the PDO establishment. Instead, the presence of necrosis in tumor samples was associated with initial PDO generation but no further propagation beyond passage 5 (P = 0.024). The "poorly cohesive cell carcinoma pattern" also negatively influenced the PDO establishment (P = 0.018). Higher stromal proportion in tumor samples was a decisive factor for successful CAF culture (P = 0.005). Our study demonstrated that the coestablishment of PDOs and CAFs is feasible even with a single-pass EUS-FNB sample, implying an expanding role of endoscopists in future precision medicine.

The Korean Version of Pandemic Stress Questionnaire: Validation in Korean Population.

Objective: The spread of Coronavirus disease 2019 (COVID-19) has acted as a significant stressor among individuals, causing a variety of psychological problems. The purpose of this study is to determine the level of stress caused by COVID-19 by translating and validating the Pandemic Stress Questionnaire (PSQ) in Korean, which measures stressful event caused by COVID-19. Methods: A statistical analysis was performed on 167 participants. The scale's internal consistency was verified using Cronbach's α. Furthermore, a correlation analysis was carried out to examine the relationships between Perceived Stress Scale, Patient Health Questionnaire-9, Generalized Anxiety Disorder Questionnaire-7, Patient Health Questionnaire-15, and World Health Organization Quality of Life Assessment Instrument Brief Form. Lastly, a multiple regression analysis was performed to determine the effect of pandemic-related stressful events on depression, anxiety, and somatic symptoms. Results: Cronbach's α for Korean version of PSQ (K-PSQ) Severity was 0.79, and that for K-PSQ Event was 0.78. The results of the multiple regression analysis revealed that pandemic stress events have an effect on anxiety and somatic symptoms. Conclusion: The K-PSQ is a tool in which individuals can simultaneously measure the occurrence of stressful events caused by COVID-19 and the severity of stress that is often experienced as a result. It is expected that this tool will be useful in the mental health field for measuring COVID-19-related stress.

Korean Medication Algorithm Project for Bipolar Disorder 2022: Comparisons with Other Treatment Guidelines.

The objective of this study was to compare recommendations of the Korean Medication Algorithm Project for Bipolar Disorder 2022 (KMAP-BP 2022) with other recently published guidelines for treating bipolar disorder. We reviewed a total of six recently published global treatment guidelines and compared treatment recommendation of the KMAP-BP 2022 with those of other guidelines. For initial treatment of mania, there were no significant differences across treatment guidelines. All guidelines recommended mood stabilizer (MS) or atypical antipsychotic (AAP) monotherapy or a combination of an MS with an AAP as a first-line treatment strategy in a same degree for mania. However, the KMAP-BP 2022 recommended MS + AAP combination therapy for psychotic mania, mixed mania and psychotic depression as treatment of choice. Aripiprazole, quetiapine and olanzapine were the first-line AAPs for nearly all phases of bipolar disorder across guidelines. Some guideline suggested olanzapine is a second-line options during maintenance treatment, related to concern about long-term tolerability. Most guidelines advocated newer AAPs (asenapine, cariprazine, long-acting injectable risperidone, and aripiprazole once monthly) as first-line treatment options for all phases while lamotrigine was recommended for depressive and maintenance phases. Lithium and valproic acid were commonly used as MSs in all phases of bipolar disorder. KMAP-BP 2022 guidelines were similar to other guidelines, reflecting current changes in prescription patterns for bipolar disorder based on accumulated research data. Strong preference for combination therapy was characteristic of KMAP-BP 2022, predominantly in the treatment of psychotic mania, mixed mania and psychotic depression.

Effects of Psychosocial Interventions for Patients with Breast Cancer: A Meta-analysis.

Objective: This study involved a meta-analysis of South Korean studies regarding psychosocial interventions for patients with breast cancer to provide basic data to support the development of an integrated healthcare service model. Methods: Randomized controlled studies with a pretest-posttest design were selected, and those presenting means, standard deviations, and standardized mean differences were included. For quality evaluation and heterogeneity testing, the Jadad scale and the Q-value and I2 were used. To estimate the effect size of each study, Hedge's g was used. Publication bias was analyzed with the Funnel plot and Egger's regression test. Results: Of the 28 studies selected for the, meta-analysis was performed on eight. The total number of datasets included in the meta-analysis was 33. The evaluation based on the Jadad scale revealed no significant inter-rater variation (p = 0.35). The mean number of sessions was 7.93 and the mean intervention time was 13.2 hours. The interventions were mostly administered in a group structure (94%) and, regarding the type, they were categorized as integrated (36.4%), cognitive (30.3%), and meditation (24.2%). The mean effect size was 1.21 against no treatment group. Conclusion: The analyzed studies showed heterogeneity, with a corresponding asymmetry found on the Funnel plot. Despite the heterogeneity and publication bias, the mean effect size was significantly large. Cognitive interventions, meditation, and psychological education programs are expected to assist in reducing negative emotions and enhancing quality of life in patients with breast cancer.

Prediction Models for Suicide Attempts among Adolescents Using Machine Learning Techniques.

Objective: Suicide attempts (SAs) in adolescents are difficult to predict although it is a leading cause of death among adolescents. This study aimed to develop and evaluate SA prediction models based on six different machine learning (ML) algorithms for Korean adolescents using data from online surveys. Methods: Data were extracted from the 2011-2018 Korea Youth Risk Behavior Survey (KYRBS), an ongoing annual national survey. The participants comprised 468,482 nationally representative adolescents from 400 middle and 400 high schools, aged 12 to 18. The models were trained using several classic ML methods and then tested on internal and external independent datasets; performance metrics were calculated. Data analysis was performed from March 2020 to June 2020. Results: Among the 468,482 adolescents included in the analysis, 15,012 cases (3.2%) were identified as having made an SA. Three features (suicidal ideation, suicide planning, and grade) were identified as the most important predictors. The performance of the six ML models on the internal testing dataset was good, with both the area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC) ranging from 0.92 to 0.94. Although the AUROC of all models on the external testing dataset (2018 KYRBS) ranged from 0.93 to 0.95, the AUPRC of the models was approximately 0.5. Conclusion: The developed and validated SA prediction models can be applied to detect high risks of SA. This approach could facilitate early intervention in the suicide crisis and may ultimately contribute to suicide prevention for adolescents.

Korean Medication Algorithm Project for Bipolar Disorder 2022, Fifth Revision: An Executive Summary.

Objective: We revised the Korean Medication Algorithm Project for Bipolar Disorder (KMAP-BP), first published in 2002 and revised in 2006, 2010, 2014, and 2018, to reflect recent progress in the treatment of bipolar disorder. Methods: The questionnaires consisted of 56 items for adult patients and 7 items for child/adolescent patients, and were used to obtain the consensus of experts regarding pharmacological treatment strategies for various phases of bipolar disorder. The review committee included 87 Korean psychiatrists and 40 child and adolescent psychiatry experts. Results: For treatment of manic episodes, a combination of a mood stabilizer (MS) and atypical antipsychotics (AAP), or monotherapy with MS or AAP were recommended as first-line treatments. Combinations of MS and AAP, or AAP and lamotrigine (LMT) were recommended as first-line treatments for depressive episodes regardless of the severity. Monotherapy with MS, AAP, or LMT were also first-line treatments for mild to moderate depressive episodes. For mixed features, a combination of MS and AAP, or monotherapy with AAP or MS were recommended as first-line treatments, and a combination of AAP and LMT, or MS and LMT were the first-line treatments for depressive mixed state. Conclusion: The recommendations of the KMAP-BP 2022 have changed from the previous version, to reflect the evolution of the social culture and healthcare system in Korea and recent evidence regarding pharmacotherapy of bipolar disorder. The KMAP-BP 2022 provides clinicians with a wealth of information regarding appropriate strategies to treat patients with bipolar disorder.

miR-4742-5p promotes invasiveness of gastric cancer via targeting Rab43: An in vitro study.

miRNA (miR)-4742-5p is a recently identified microRNA regarding progression and metastasis in gastric cancer (GC). However, the biological function of this novel miRNA is largely unknown. We identified that the miR-4742-5p expression level was variably increased in GC cell lines. Suppression of miR-4742-5p using miR-inhibitor reduced the proliferation, migration, and invasion of GC cells with high miR-4742-5p expression, whereas overexpression of miR-4742-5p-mimic enhanced the aforementioned properties in GC cells with low miR-4742-5p expression. miR-4742-5p expression induced the decreases of Zo-1 and E-cadherin expression as well as the increases of vimentin and N-cadherin expression, leading to epithelial-mesenchymal transition (EMT) of cancer cells. RNA sequencing results indicated Ras-related GTP-binding protein 43 (Rab43) as a potential target gene. We identified that the expression of Rab43 is associated with activation of AKT and nuclear factor-kappa B (NF-κB) which are key oncogenic pathways in cancer cells. Our results demonstrate a new component in GC progression, promising a potential therapeutic strategy.

Mental Health and Quality of Life for Disaster Service Workers in a Province under COVID-19.

Objective: Healthcare workers and disaster service workers have been reported to be vulnerable to mental health problems during outbreaks of infectious diseases such as the COVID-19 pandemic. This study aimed to investigate the psychosocial characteristics of disaster service workers in charge of COVID-19-related work and also identify the factors affecting their quality of life. Methods: From June 2020 to June 2021, a survey was conducted of 526 disaster service workers in charge of COVID-19-related work. This included those working in public health care centers (PHC), 119 rescue and emergency medical services (119 REMS), public servants of city hall (PS), and police officers. The Korean version of the Fear of COVID-19 Scale, Patient Health Questionnaire-15, Hospital Anxiety and Depression Scale, Insomnia Severity Index, Connor−Davidson Resilience Scale, and World Health Organization quality of life assessment instrument brief form were used. A one-way ANOVA was conducted, and a stepwise regression analysis was carried out to determine the factors affecting quality of life. Results: Regarding quality of life, 119 REMS (180.64 ± 26.20) scored significantly higher than PHC (165.76 ± 23.73) and PS (163.90 ± 23.60), while police officers (176.87 ± 23.17) scored significantly higher than PS (163.90 ± 23.60) (F = 12.373, p < 0.001). Resilience (ß = 0.897, p < 0.01) was the most significant explanatory variable, and together with insomnia (ß = 0.154, p < 0.01), depression (ß = −0.152, p < 0.01), and COVID-19 anxiety (ß = −0.057, p < 0.01) accounted for 91.8% of the explanatory variance with regard to quality of life. Discussion: Quality of life was found to be negatively correlated with insomnia, depression, and COVID-19 anxiety while being positively correlated with resilience. Therefore, active interventions are needed to improve the resilience of disaster service workers.

The Korean Medication Algorithm Project for Depressive Disorder 2021: Comparisons with Other Treatment Guidelines.

The Korean Medication Algorithm Project for Depressive Disorder (KMAP-DD) first was published in 2002, and has been revised four times, in 2006, 2012, 2017, and 2021. In this review, we compared recommendations from the recently revised KMAP-DD 2021 to four global clinical practice guidelines (CPGs) for depression published after 2010. The recommendations from the KMAP-DD 2021 were similar to those from other CPGs, although there were some differences. The KMAP-DD 2021 reflected social culture and the healthcare system in Korea and recent evidence about pharmacotherapy for depression, as did other recently published evidence-based guidelines. Despite some intrinsic limitations as an expert consensus-based guideline, the KMAP-DD 2021 can be helpful for Korean psychiatrists making decisions in clinical settings by complementing previously published evidence-based guidelines, especially for some clinical situations lacking evidence from rigorously designed clinical trials.

Mental Health and Quality of Life for Healthcare Workers in a University Hospital Under COVID-19.

OBJECTIVE: The aim of this study was to assess the psychosocial characteristics of the employees working at a university hospital and investigated the factors affecting their quality of life (QOL) under COVID-19. METHODS: This study enrolled 1,191 healthcare workers from a university hospital, including doctors, nurses, administrative officer and technicians. Besides demographic information, depression, anxiety, somatization, insomnia, resilience, and QOL were assessed. RESULTS: The nurses presented significantly higher scores for anxiety, depression and showed significantly higher insomnia scores and significantly lower resilience scores. The occupations showed significant differences in the QOL and sub-groups, including the overall quality of life and general health (F=4.774, p<0.001), psychological domain (F=6.230, p<0.001), and environment domain (F=5.254, p<0.001). There was a positive correlation between the QOL and resilience (r=0.608, p<0.01). However, depression (r=-0.502, p<0.01), anxiety (r=-0.425, p<0.01), somatization (r=-0.364, p<0.01), and insomnia (r=-0.385, p<0.01) showed negative correlations with the QOL. Resilience was the most important factor influencing the QOL. CONCLUSION: The results of this study showed that low resilience adversely affected the QOL and the mental health of the healthcare workers, which consequently had a direct effect on the quality of medical care given to patients.

Alterations in Social Brain Network Topology at Rest in Children With Autism Spectrum Disorder.

OBJECTIVE: Underconnectivity in the resting brain is not consistent in autism spectrum disorder (ASD). However, it is known that the functional connectivity of the default mode network is mainly decreased in childhood ASD. This study investigated the brain network topology as the changes in the connection strength and network efficiency in childhood ASD, including the early developmental stages. METHODS: In this study, 31 ASD children aged 2-11 years were compared with 31 age and sex-matched children showing typical development. We explored the functional connectivity based on graph filtration by assessing the single linkage distance and global and nodal efficiencies using resting-state functional magnetic resonance imaging. The relationship between functional connectivity and clinical scores was also analyzed. RESULTS: Underconnectivities within the posterior default mode network subregions and between the inferior parietal lobule and inferior frontal/superior temporal regions were observed in the ASD group. These areas significantly correlated with the clinical phenotypes. The global, local, and nodal network efficiencies were lower in children with ASD than in those with typical development. In the preschool-age children (2-6 years) with ASD, the anterior-posterior connectivity of the default mode network and cerebellar connectivity were reduced. CONCLUSION: The observed topological reorganization, underconnectivity, and disrupted efficiency in the default mode network subregions and social function-related regions could be significant biomarkers of childhood ASD.

A Dimensional Understanding of Borderline Personality Disorder Using MMPI-2 PSY-5 Scales in Clinical Samples.

OBJECTIVE: This study aims to understand borderline personality disorder (BPD) features by employing the Personality Psychopathology Five (PSY-5) scales from the Minnesota Multiphasic Personality Inventory-2 (MMPI-2). METHODS: A total of 156 psychiatric patients completed PSY-5 scales of MMPI-2 and Personality Assessment Inventory-Borderline Subscale (PAI-BOR). Pearson's partial correlation analysis was conducted to control the impact of age and gender and to determine the relationship between PSY-5 scales and BOR. A hierarchical multiple regression analysis was implemented to examine whether PSY-5 scales predicted the BOR-total, and a path analysis was performed to determine whether PSY-5 scales predicted each PAI-BOR subscale. RESULTS: The BOR-total score had a significant correlation with all PSY-5 scores, even after controlling for age and gender. However, only aggressiveness (AGGR), disconstraint (DISC), negative emotionality/neuroticism (NEGE), and introversion/low positive emotionality (INTR), excluding psychoticism (PSYC), significantly predicted BOR-total. The path analysis indicates that PSYC did not predict any BOR subscale, while NEGE predicted all BOR subscales. CONCLUSION: The study findings indicate that NEGE best reflects BPD features, while PSYC is far from the core domain that describes BPD. In addition, the influence of age should be considered when understanding BPD, since age predicted the BOR-total and two BOR subscales.

Classification of Adolescent Psychiatric Patients at High Risk of Suicide Using the Personality Assessment Inventory by Machine Learning.

OBJECTIVE: There are growing interests on suicide risk screening in clinical settings and classifying high-risk groups of suicide with suicidal ideation is crucial for a more effective suicide preventive intervention. Previous statistical techniques were limited because they tried to predict suicide risk using a simple algorithm. Machine learning differs from the traditional statistical techniques in that it generates the most optimal algorithm from various predictors. METHODS: We aim to analyze the Personality Assessment Inventory (PAI) profiles of child and adolescent patients who received outpatient psychiatric care using machine learning techniques, such as logistic regression (LR), random forest (RF), artificial neural network (ANN), support vector machine (SVM), and extreme gradient boosting (XGB), to develop and validate a classification model for individuals with high suicide risk. RESULTS: We developed prediction models using seven relevant features calculated by Boruta algorithm and subsequently tested all models using the testing dataset. The area under the ROC curve of these models were above 0.9 and the RF model exhibited the best performance. CONCLUSION: Suicide must be assessed based on multiple aspects, and although Personality Assessment Inventory for Adolescent assess an array of domains, further research is needed for predicting high suicide risk groups.

Korean Medication Algorithm for Depressive Disorder 2021, Fourth Revision: An Executive Summary.

OBJECTIVE: In the 19 years since the Korean College of Neuropsychopharmacology and the Korean Society for Affective Disorders developed the Korean Medication Algorithm Project for Depressive Disorder (KMAP-DD) in 2002, four revisions have been conducted. METHODS: To increase survey efficiency in this revision, to cover the general clinical practice, and to compare the results with previous KMAP-DD series, the overall structure of the questionnaire was maintained. The six sections of the questionnaire were as follows: 1) pharmacological treatment strategies for major depressive disorder (MDD) with/without psychotic features; 2) pharmacological treatment strategies for persistent depressive disorder and other depressive disorder subtypes; 3) consensus for treatment-resistant depression; 4) the choice of an antidepressant in the context of safety, adverse effects, and comorbid physical illnesses; 5) treatment strategies for special populations (children/adolescents, elderly, and women); and 6) non-pharmacological biological therapies. Recommended first-, second-, and third-line strategies were derived statistically. RESULTS: There has been little change in the four years since KMAP-DD 2017 due to the lack of newly introduced drug or treatment strategies. However, shortened waiting time between the initial and subsequent treatments, increased preference for atypical antipsychotics (AAPs), especially aripiprazole, and combination strategies with AAPs yield an active and somewhat aggressive treatment trend in Korea. CONCLUSION: We expect KMAP-DD to provide clinicians with useful information about the specific strategies and medications appropriate for treating patients with MDD by bridging the gap between clinical real practice and the evidence-based world.

The Korean Version of Fear of COVID-19 Scale: Psychometric Validation in the Korean Population.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) has psychological effects such as anxiety and depression as well as direct infection in people. The Fear of COVID-19 scale is a scale that can measure anxiety related to COVID-19 in a short time. The purpose of this study was to verify the reliability and validity the Korean version of Fear of COVID-19 scale (KF-COVID-19S). METHODS: The data of total 186 normal adults and 17 patients were finally used for the statistical analysis. For internal consistency, Cronbach's α was calculated. For concurrent and discriminant validity, the correlations with the Hospital Anxiety and Depression scale (HADS), Patient Health Questionnaire-15 (PHQ-15), World Health Organization Quality of Life Assessment Instrument Brief Form (WHOQOLBREF) were analyzed. For construct validity, exploratory and confirmatory factor analysis were conducted. RESULTS: Cronbach alpha was 0.88. The two-factor model (factor 1: Physical fear, factor 2: Emotional fear) showed significantly positive correlations and appeared to be "good" fitness (CFI=0.906, IFI=0.907, NFI=0.902). CONCLUSION: The KF-COVID-19S can be a useful scale that can measure the physical and emotional fears associated with COVID-19 in a short time. Because the psychiatric patients are a more vulnerable group to the fear, it is thought that the KF-COVID-19S will help to determine the patient's level of anxiety and make a therapeutic plan for the underlying mental disorder.

Reliability and Validity of the Korean Version of Somatic Symptom Scale-8.

OBJECTIVE: Somatic symptoms in psychiatry include underlying depression, anxiety, or other psychiatric disorders. This study aimed to conduct a validation study of a Korean version of the Somatic Symptom Scale-8 (K-SSS-8), and to utilize the K-SSS-8 effectively in clinical settings. METHODS: For reliabilty, test-retest reliability and internal consistency were analyzed. For construct validity, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted. Known-group validity was verified, Jonckheere-Terpstra test (J-T statistic) were used. RESULTS: Maternal Cronbach's alpha was 0.85 and r value of test-retest reliability was 0.777. In the EFA, 2-, 3- and 4-factor model showed cumulative percentile for variance of 60% or more. In the CFA, the 3-factor model was found to be the most appropriated and simplest (χ2=10.992, df=17, CFI=1.000, TLI=1.022, RMSEA=0.000). The verifying the difference in K-SSS-8 also showed significant difference. (J-T statistic=-2.510, p<0.05). CONCLUSION: K-SSS-8 can be useful for exploring symptoms such as panic symptoms, physical pain, and physiological symptoms experienced by patients in a short time. In addition, the K-SSS-8 is expected to be very useful for determining the current severity by using the severity categories and for establish additionally required assessment plans for depression and anxiety symptoms.