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Objective: : The present study was performed to investigate the validity and reliability of the Korean version of the THINC-it tool (THINC-it-K) in adult patients with major depressive disorder (MDD)., Methods: : Subjects aged 19-65 years with recurrent MDD experiencing moderate to severe major depressive episode (n = 44) were evaluated and compared to age and sex matched healthy controls (n = 44). Subjects completed the THINC-it-K which includes variants of the Identification Task (IDN) using Choice Reaction Time, One-Back Test, Digit Symbol Substitution Test, Trail Making Test-Part B, and the Perceived Deficits Questionnaire for Depression-5-item (PDQ-5-D)., Results: : A total of 75.0% of patients with MDD exhibited cognitive performance 1 standard deviation or below. The differences in Spotter ( p = 0.001), Codebreaker ( p = 0.001), PDQ-5-D ( p ＜ 0.001) and objective THINC-it-K composite score ( p = 0.002) were significant between the two groups. Concurrent validity of the THINC-it-K based on a calculated composite score was good (r = 0.856, p ＜ 0.001), and ranges for each component tests were from 0.076 (IDN) to 0.928 (PDQ-5-D)., Conclusion: : The THINC-it-K exhibits good reliability and validity in adults with MDD. It could be a useful tool for the measurement of cognitive deficits in persons with MDD and should be implemented in clinical practice.

Purpose: As science and technology advance, older people's ability to use smart devices in their daily living is becoming more demanding. This study addresses the increasing use of smartphones by the older adults, who often struggle with technology due to lack of competence. We developed an educational app tailored for older adults users and compare its effectiveness with existing educational videos., Methods: An app was created based on the learning characteristics of the older adults, using the ADDIE model, and compared with traditional video education. It involved six participants aged 65 or older, and convenience sampling method was used, evaluating the app and video through usability assessments and eye tracking. Quantitative and qualitative analyzes were conducted with focus groups under the researcher's control., Results: The app received higher usability scores than the video in content, motivation, and interaction. Eye tracking showed users paid more consistent attention to the app., Conclusion: The smartphone app facilitates learning for the older adults without the constraints of time and place, improving their quality of life and technology skills. Eye tracking can be instrumental in future app development for this demographic., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Woo, Shin and Park.)

Previous studies suggested effectiveness of psilocybin in the field of mental health. FDA designated psilocybin as a "breakthrough therapy" for the treatment of treatment-resistant depression (TRD) in 2018. This paper provided a review of psilocybin's potential role in treatment of depression by focusing on published clinical trials. Studies showed that psilocybin, an agonist on 5-HT 2A receptors, manifests antidepressant and anxiolytic effects by increasing glutamate transmission, reducing brain inflammation, decreasing default mode network activity. In terms of clinical trials, eleven studies (six open-label and five double blinded randomized clinical trials [DB-RCTs]) trials exploring psilocybin's impact on depression were found. Among open-label studies, a pilot study on TRD patients demonstrated significant reductions in depressive symptoms after two psilocybin sessions. Psilocybin also improved cognitive bias associated with depression. Extension studies confirmed sustained improvements and high remission rates. Among five DB-RCTs, two showed that psilocybin led to significant reductions in anxiety and depression in cancer patients, and the improvements sustained for over six months. In MDD, psilocybin showed rapid reductions in depression, with higher remission rates compared to escitalopram in a DB-RCT. Another DB-RCT showed that psilocybin induced higher decrease in depression around 6 hours after their administrations than placebo. The last DB-RCT showed that in patients with TRD, a single dose of psilocybin 25 mg, but not psilocybin 10 mg, resulted in superior antidepressant effect than psilocybin 1 mg. Overall, psilocybin showed promise in treating depression and anxiety, with notable safety profiles. Further research should explore optimal dosages and long-term effects.

This study presents a comprehensive exploration of topic modeling methods tailored for large language model (LLM) using data obtained from Web of Science and LexisNexis from June 1, 2020, to December 31, 2023. The data collection process involved queries focusing on LLMs, including "Large language model," "LLM," and "ChatGPT." Various topic modeling approaches were evaluated based on performance metrics, including diversity and coherence. latent Dirichlet allocation (LDA), nonnegative matrix factorization (NMF), combined topic models (CTM), and bidirectional encoder representations from Transformers topic (BERTopic) were employed for performance evaluation. Evaluation metrics were computed across platforms, with BERTopic demonstrating superior performance in diversity and coherence across both LexisNexis and Web of Science. The experiment result reveals that news articles maintain a balanced coverage across various topics and mainly focus on efforts to utilize LLM in specialized domains. Conversely, research papers are more concise and concentrated on the technology itself, emphasizing technical aspects. Through the insights gained in this study, it becomes possible to investigate the future path and the challenges that LLMs should tackle. Additionally, they could offer considerable value to enterprises that utilize LLMs to deliver services., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Jung et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: This study determined the threshold for recurrent depressive episodes that predicted conversion from major depressive disorder (MDD) to bipolar disorder (BD)., Methods: We retrospectively reviewed the medical records of 296 patients diagnosed with MDD for a minimum of 5 years in two university hospitals. We examined their the Diagnostic and Statistical Manual of Mental Disorders, 5th edition diagnoses and detailed clinical information at the initial admission and yearly assessments after discharge to establish the threshold for recurrent depressive episodes indicating a risk of diagnostic conversion from MDD to BD. Optimal cut-offs were derived using receiver operating characteristic (ROC) curves., Results: ROC curve analysis revealed that more than four recurrent depressive episodes was indicative of potential diagnostic conversion from MDD to BD (area under the curve, 0.604; sensitivity, 0.353; specificity, 0.855; positive predictive value, 0.421; negative predictive value, 0.816)., Conclusion: These findings suggest that the best predictor of conversion from MDD to BD is more than four recurrent depressive episodes. Our findings have the potential to enhance diagnostic accuracy and treatment efficiency. To validate our results, longitudinal prospective studies are necessary.

Background: We conducted a one-year, retrospective, mirror-image study to investigate the clinical effectiveness and safety of aripiprazole once monthly (AOM) in patients with bipolar disorder (BD). We compared pre-treatment conditions with outcomes after 12 months of AOM treatment., Methods: Seventy-five bipolar patients were recruited from 12 hospitals in Korea. We included 75 patients with BD who had received at least three AOM treatments from September 2019 to September 2022 and had accessible electronic medical record (EMRs) for the year before and after the baseline visit., Results: The overall number of mood episodes significantly decreased from a mean of 1.5 ± 1.2 episodes pre-AOM to 0.5 ± 1.2 episodes post-AOM. Manic episodes significantly decreased from 0.8 ± 0.8 episodes pre-AOM to 0.2 ± 0.5 episodes post-AOM, and depressive episodes significantly decreased from 0.5 ± 0.8 episodes pre-AOM to 0.2 ± 0.6 episodes post-AOM (p = 0.017). Moreover, the number of psychiatric medications and pills and the proportion of patients treated with complex polypharmacy were significantly decreased post-AOM., Limitations: The small sample size was insufficient to fully represent the entire population of individuals with BD, and potential selection bias was introduced due to only including subjects who received AOM three or more times., Conclusion: The results of this study suggest that AOM can reduce mood episode relapse and may be clinically beneficial in the treatment of BD patients, potentially reducing issues associated with polypharmacy in some individuals., Competing Interests: Declaration of competing interest The authors declare no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Objective: We aimed to identify the expectations and preferences for medication and medical decision-making in patients with major psychiatric disorders., Methods: A survey was conducted among patients with major psychiatric disorders who visited psychiatric outpatient clinics at 15 hospitals between 2016 and 2018 in Korea. The survey consisted of 12 questions about demographic variables and opinions on their expectations for medication, important medical decision-makers, and preferred drug type. The most preferred value in each category in the total population was identified, and differences in the preference ratio of each item among the disease groups were compared., Results: A total of 707 participants were surveyed. In the total population, patients reported high efficacy (44.01%±21.44%) as the main wish for medication, themselves (37.39%±22.57%) and a doctor (35.27%±22.88%) as the main decision makers, and tablet/capsule (36.16%±30.69%) as the preferred type of drug. In the depressive disorders group, the preference ratio of high efficacy was significantly lower, and the preference ratio of a small amount was significantly higher than that of the psychotic disorder and bipolar disorder groups. The preference ratio of a doctor as an important decision maker in the bipolar disorder group was higher compared to the other groups., Conclusion: This study revealed the preference for medications and showed differences among patients with psychiatric disorders. Providing personalized medicine that considers a patient's preference for the drug may contribute to the improvement of drug compliance and outcomes.