Cheol-Hyun Cho

On the basis of the theoretical basis of chronobiology, this study proposed a good model for future research by developing a mood prediction algorithm using machine learning by processing and reclassifying digital log data. In addition to academic value, it is expected that this study will be of practical help to improve the prognosis of patients with mood disorders by making it possible to apply actual clinical application owing to the rapid expansion of digital technology.

Exposure to artificial light at night (ALAN) has become increasing common, especially in developed countries. We investigated the effect of dALAN exposure during sleep in healthy young male subjects. A total of 30 healthy young male volunteers from 21 to 29 years old were recruited for the study. They were randomly divided into two groups depending on light intensity (Group A: 5 lux and Group B: 10 lux). After a quality control process, 23 healthy subjects were included in the study (Group A: 11

BACKGROUND: This study aimed to investigate the degree of occupational stress and the clinical mental state of dentists. In addition, we investigated the correlation of occupational stress with depression, anxiety, and sleep among dentists in Korea. METHODS: A cross-sectional survey on 231 dentists was conducted using the Doctor Job Stress Scale, Center for Epidemiologic Studies Depression Scale (CES-D), State-Trait Anxiety Index (STAI), and Pittsburgh Sleep Quality Index (PSQI). Correlation of

BACKGROUND: Smartphones and wearable devices can be used to obtain diverse daily log data related to circadian rhythms. For patients with mood disorders, giving feedback via a smartphone app with appropriate behavioral correction guides could play an important therapeutic role in the real world. OBJECTIVE: We aimed to evaluate the effectiveness of a smartphone app named Circadian Rhythm for Mood (CRM), which was developed to prevent mood episodes based on a machine learning algorithm that uses p

Importance: Early detection of attention-deficit/hyperactivity disorder (ADHD) and sleep problems is paramount for children's mental health. Interview-based diagnostic approaches have drawbacks, necessitating the development of an evaluation method that uses digital phenotypes in daily life. Objective: To evaluate the predictive performance of machine learning (ML) models by setting the data obtained from personal digital devices comprising training features (ie, wearable data) and diagnostic re

Background Artificial intelligence (AI) social chatbots represent a major advancement in merging technology with mental health, offering benefits through natural and emotional communication. Unlike task-oriented chatbots, social chatbots build relationships and provide social support, which can positively impact mental health outcomes like loneliness and social anxiety. However, the specific effects and mechanisms through which these chatbots influence mental health remain underexplored. Objecti

This study examined the link between circadian rhythm changes due to bright light exposure and subthreshold bipolarity. Molecular circadian rhythms, polysomnography, and actigraphy data were studied in 25 young, healthy male subjects, divided into high and low mood disorder questionnaire (MDQ) score groups. During the first 2 days of the study, the subjects were exposed to daily-living light (150 lux) for 4 hours before bedtime. Saliva and buccal cells were collected 5 times a day for 2 consecut

BACKGROUND: Although it has been well demonstrated that the efficacy of virtual reality therapy for social anxiety disorder is comparable to that of traditional cognitive behavioral therapy, little is known about the effect of virtual reality on pathological self-referential processes in individuals with social anxiety disorder. OBJECTIVE: We aimed to determine changes in self-referential processing and their neural mechanisms following virtual reality treatment. METHODS: We recruited participan

OBJECTIVE: Light pollution has become a social and health issue. We performed an experimental study to investigate impact of dim light at night (dLAN) on sleep in female subjects, with measurement of salivary melatonin. METHODS: The 25 female subjects (Group A: 12; Group B: 13 subjects) underwent a nocturnal polysomnography (NPSG) session with no light (Night 1) followed by an NPSG session randomly assigned to two conditions (Group A: 5; Group B: 10 lux) during a whole night of sleep (Night 2).

Restless legs syndrome (RLS) is a sensorimotor neurological disturbance causing physical and psychological distress. Here, we investigated the severity and effect of depressive symptoms in RLS among a Korean cohort population. Depressive symptoms were more prevalent in the RLS group than in the non-RLS group [≥mild depression: odds ratio (OR)=1.95, p<0.001; ≥ moderate depression: OR=6.15, p<0.001; and ≥severe depression: OR=56.54, p<0.001], with a predominant proportion of severe depression (97%

The findings affirm that the K-BRIAN has good construct validity and internal consistency. This suggests that the K-BRIAN can be used to assess biological rhythms in the Korean population, especially for patients with mood disorder.

The Mood Disorder Cohort Research Consortium (MDCRC) study is designed as a naturalistic observational prospective cohort study for early-onset mood disorders (major depressive disorders, bipolar disorders type 1 and 2) in South Korea. The study subjects consist of two populations: 1) patients with mood disorders under 25 years old and 2) patients with mood disorders within 2 years of treatment under 35 years old. After successful screening, the subjects are evaluated using baseline assessments

There have been concerns about abuse and unnecessary chronic administration of zolpidem, and zolpidem's relation to suicide risk. To investigate the temporal association of zolpidem with the risk of suicide, we conducted a 12-year, population-based, retrospective cohort study on the National Health Insurance Service-National Sample Cohort (NHIS-NSC), South Korea. Data were collected from 2002 to 2013 from the NHIS-NSC, and data cleaning was performed for 1,125,691 subjects. Cox proportional haza