Existing digital mental health interventions are mainly focused on the symptoms of specific mental disorders such as depression and anxiety. However, digital mental health interventions aiming enhancement of mental health in the general population are rare. Considering that the psychological discomfort of the general public is more complex and subtle, interventions focusing on maladaptive personality and interpersonal schema rather than symptoms per se can be an alternative.

To this end, concise tools for measuring the core personality and interpersonal patterns known to cause psychological discomfort among potential users of digital mental health interventions are essential. For this purpose, the Schema Scale was developed and our study aims to validate and confirm psychometric properties of the scale.

This cross-sectional study was carried out between July and August 2022. Participants were 234 adults aged between 19 to 39 who completed an online survey including the Schema Scale and other 15 questionnaires. Exploratory factor analysis were conducted to construct the factorial structure model.

Exploratory factor analysis showed a five-factor structure with a total variance of 57%; factor 1 consisted of lack of belongingness and poor social skills, factor 2 of lack of patience hot-tempered coping style, factor 3 of maladaptive perfectionism, factor 4 of self-sacrifice and lack of self-confidence and factor 5 of items representing pessimistic and anxious mindset. Internal consistency of each factor was good(Cronbach’s alpha=0.712~0.882), and correlations with existing measures were significant.

The five personality Schema Scale appears to be a short(total 35 items) and a valid tool for measuring five essential personality and interpersonal patterns for adults aged 20~30 years. This tool has been developed for online use and therefore has the advantage of being easily accessible. Most importantly, based on the results of the Schema Scale, the individualized digital interventions can be recommended that targets maladaptive psychological patterns.

None Declared

Some incidents require early deployment of emergency department personnel not designated as disaster medical assistance team (DMAT). Although not as trained as DMAT members, they should be aware of basic disaster response concepts and knowledge. Educating disaster readiness to every healthcare staff in emergency departments would be ideal but it is very costly in both time and expense. To overcome this problem, we tried to evaluate the effectiveness of teaching basic concept and knowledge to non-designated personnel in a short-session and measure the effect.

This study is a before-and-after comparison study. From July 2020 to July 2022, a two-hour education was given to volunteers among doctors, nurses, paramedics and administrative staff working in emergency departments across four hospitals in Korea. Educational sessions consisted of basic disaster concept, pre-deployment DMAT preparations, initial actions required on incident site, key elements of incident response (command, control, safety, communication), and triage. Attendees were given a pretest before the session and another test after the session. Chi-square test and Wilcoxon rank test were used to compare the results.

Total of 105 volunteers participated in the study. Participants were mostly nurses (62.9%) followed by paramedics (23.8%). Overall knowledge level reported to be increased, including knowledge regarding DMAT deployment (29.5% to 93.3%, p<0.001), DMAT personnel (26.7% to 94.3%, p<0.001), DMAT-designated equipment (23.8% to 60.0%, p<0.001), initial response (27.6% to 69.5%, p<0.001) and patient transport priority (74.3% to 94.3%, p<0.001). Questions testing triage and rate of participants answering every question showed improvement with post-test median score of 67% and rate of 1.0% to post-test median score of 100% and rate of 35.2%, respectively (both p<0.001).

Educating non-DMAT personnel in emergency departments with a short session showed significant improvement in basic knowledge of disaster response. It may help institutions with limited resources.

Identifying more homogenous subtypes of patients with obsessive–compulsive disorder (OCD) using biological evidence is critical for understanding complexities of the disorder in this heterogeneous population. Age of onset serves as a useful subtyping scheme for distinguishing OCD into two subgroups that aligns with neurodevelopmental perspectives. The underlying neurobiological markers for these distinct neurodevelopmental differences can be identified by investigating gyrification changes to establish biological evidence-based homogeneous subtypes.

We compared whole-brain cortical gyrification in 84 patients with early-onset OCD, 84 patients with late-onset OCD, and 152 healthy controls (HCs) to identify potential markers for early neurodevelopmental deficits using the local gyrification index (lGI). Then, the relationships between lGI in clusters showing significant differences and performance in visuospatial memory and verbal fluency, which are considered trait-related neurocognitive impairments in OCD, were further examined in early-onset OCD patients.

The early-onset OCD patients exhibited significantly greater gyrification than those with late-onset OCD patients and HCs in frontoparietal and cingulate regions, including the bilateral precentral, postcentral, precuneus, paracentral, posterior cingulate, superior frontal, and caudal anterior cingulate gyri. Moreover, impaired neurocognitive functions in early-onset OCD patients were correlated with increased gyrification.

Our findings provide a neurobiological marker to distinguish the OCD population into more neurodevelopmentally homogeneous subtypes, which may contribute to the understanding of the neurodevelopmental underpinnings of an etiology in early-onset OCD consistent with the accumulated phenotypic evidence of greater neurodevelopmental deficits in early-onset OCD than in late-onset OCD.

Mood disorders require consistent management of symptoms to prevent recurrences of mood episodes. Circadian rhythm (CR) disruption is a key symptom of mood disorders to be proactively managed to prevent mood episode recurrences. This study aims to predict impending mood episodes recurrences using digital phenotypes related to CR obtained from wearable devices and smartphones.

The study is a multicenter, nationwide, prospective, observational study with major depressive disorder, bipolar disorder I, and bipolar II disorder. A total of 495 patients were recruited from eight hospitals in South Korea. Patients were followed up for an average of 279.7 days (a total sample of 75 506 days) with wearable devices and smartphones and with clinical interviews conducted every 3 months. Algorithms predicting impending mood episodes were developed with machine learning. Algorithm-predicted mood episodes were then compared to those identified through face-to-face clinical interviews incorporating ecological momentary assessments of daily mood and energy.

Two hundred seventy mood episodes recurred in 135 subjects during the follow-up period. The prediction accuracies for impending major depressive episodes, manic episodes, and hypomanic episodes for the next 3 days were 90.1, 92.6, and 93.0%, with the area under the curve values of 0.937, 0.957, and 0.963, respectively.

We predicted the onset of mood episode recurrences exclusively using digital phenotypes. Specifically, phenotypes indicating CR misalignment contributed the most to the prediction of episodes recurrences. Our findings suggest that monitoring of CR using digital devices can be useful in preventing and treating mood disorders.

Direct gaze is the most important mediator of social interaction and communication. Existing studies have evaluated eye movements of patients with schizophrenia by presenting stimuli using photographs or pre-recorded videos, but few directly investigated gaze avoidance in real-world situations.

To investigate the correlation between gaze avoidance and psychopathology in patients with schizophrenia through eye movement measurements in real-life interpersonal situations.

We enrolled 52 clinically stable patients with schizophrenia. Psychopathology was evaluated using the Positive and Negative Syndrome Scale (PANSS), Hamilton Depression Rating Scale, and Hamilton Anxiety Rating Scale. After presenting a visual stimulus, eye movements were measured with Tobii Pro Wearable Glasses 2, and deep learning-based emotional recognition using the residual masking network was used for neutral stimulus verification. Statistical analyses were performed using Pearson’s correlation and regression analyses.

Data of 45 participants with verified stimulus neutrality by deep learning image recognition were used for analysis. The first dwelling time was negatively correlated with the PANSS positive syndrome subscale (p=0.028), general psychopathology subscale (p=0.008), total score (p=0.008), 5-factor positive symptoms (p=0.035), and 5-factor depression/anxiety symptoms (p=0.008). The baseline-area of interest (AOI) pupil diameter change was positively correlated with PANSS 5-factor positive symptom scores (p=0.039). After adjusting for additional variables, the same items had a significant effect on the first dwelling time and baseline-AOI pupil diameter change.

Psychopathology, particularly positive symptoms, was associated with gaze avoidance and pupil diameter in patients with schizophrenia. Evaluating the characteristics of eye movements in patients with schizophrenia will enable better understanding of their symptoms.

No significant relationships.

This study evaluated the effect of music intervention on the anxiety and stress responses of patients who underwent an interventional cardiac catheterisation.

The study design was a pre- and post-test randomised controlled trial that included 94 patients who underwent a transcatheter atrial septal defect closure. Patients were allocated to receive either music intervention (n = 47) or usual care (n = 47) during the interventional cardiac catheterisation. Music intervention effectiveness was examined in terms of anxiety, salivary cortisol level, and heart rate variability.

The average age of participants was 45.40 years (±16.04) in the experimental group and 47.26 years (±13.83) in the control group. Two-thirds (66.0%) of the participants in each group were women. State anxiety (F = 31.42, p < 0.001), anxiety-numerical rating scale (F = 20.08, p < 0.001), salivary cortisol levels (F = 4.98, p = 0.021), and low-frequency component/high-frequency component ratio (F = 17.31, p < 0.001) in the experimental group were significantly reduced compared with those in the control group at the end of the music intervention.

This study provides practical evidence of a reduction in anxiety and stress response from music intervention preceding an interventional cardiac catheterisation, indicating that this intervention should be considered in clinical management.

There are growing concerns about the impact of the COVID-19 pandemic on the mental health of older adults. We examined the effect of the pandemic on the risk of depression in older adults.

We analyzed data from the prospective cohort study of Korean older adults, which has been followed every 2 years. Among the 2308 participants who completed both the third and the fourth follow-up assessments, 58.4% completed their fourth follow-up before the outbreak of COVID-19 and the rest completed it during the pandemic. We conducted face-to-face diagnostic interviews using Mini International Neuropsychiatric Interview and used Geriatric Depression Scale. We performed generalized estimating equations and logistic regression analyses.

The COVID-19 pandemic was associated with increased depressive symptoms in older adults [b (standard error) = 0.42 (0.20), p = 0.040] and a doubling of the risk for incident depressive disorder even in euthymic older adults without a history of depression (odds ratio = 2.44, 95% confidence interval 1.18–5.02, p = 0.016). Less social activities, which was associated with the risk of depressive disorder before the pandemic, was not associated with the risk of depressive disorder during the pandemic. However, less family gatherings, which was not associated with the risk of depressive disorder before the pandemic, was associated with the doubled risk of depressive disorder during the pandemic.

The COVID-19 pandemic significantly influences the risk of late-life depression in the community. Older adults with a lack of family gatherings may be particularly vulnerable.

In 2015, an international outbreak of Mycobacterium chimaera infections among patients undergoing cardiothoracic surgeries was associated with exposure to contaminated LivaNova 3T heater-cooler devices (HCDs). From June 2017 to October 2020, the Centers for Disease Control and Prevention was notified of 18 patients with M. chimaera infections who had undergone cardiothoracic surgeries at 2 hospitals in Kansas (14 patients) and California (4 patients); 17 had exposure to 3T HCDs. Whole-genome sequencing of the clinical and environmental isolates matched the global outbreak strain identified in 2015.

Investigations were conducted at each hospital to determine the cause of ongoing infections. Investigative methods included query of microbiologic records to identify additional cases, medical chart review, observations of operating room setup, HCD use and maintenance practices, and collection of HCD and environmental samples.

Onsite observations identified deviations in the positioning and maintenance of the 3T HCDs from the US Food and Drug Administration (FDA) recommendations and the manufacturer’s updated cleaning and disinfection protocols. Additionally, most 3T HCDs had not undergone the recommended vacuum and sealing upgrades by the manufacturer to decrease the dispersal of M. chimaera–containing aerosols into the operating room, despite hospital requests to the manufacturer.

These findings highlight the need for continued awareness of the risk of M. chimaera infections associated with 3T HCDs, even if the devices are newly manufactured. Hospitals should maintain vigilance in adhering to FDA recommendations and the manufacturer’s protocols and in identifying patients with potential M. chimaera infections with exposure to these devices.

Prognostic heterogeneity in early psychosis patients yields significant difficulties in determining the degree and duration of early intervention; this heterogeneity highlights the need for prognostic biomarkers. Although mismatch negativity (MMN) has been widely studied across early phases of psychotic disorders, its potential as a common prognostic biomarker in early periods, such as clinical high risk (CHR) for psychosis and first-episode psychosis (FEP), has not been fully studied.

A total of 104 FEP patients, 102 CHR individuals, and 107 healthy controls (HCs) participated in baseline MMN recording. Clinical outcomes were assessed; 17 FEP patients were treatment resistant, 73 FEP patients were nonresistant, 56 CHR individuals were nonremitters (15 transitioned to a psychotic disorder), and 22 CHR subjects were remitters. Baseline MMN amplitudes were compared across clinical outcome groups and tested for utility prognostic biomarkers using binary logistic regression.

MMN amplitudes were greatest in HCs, intermediate in CHR subjects, and smallest in FEP patients. In the clinical outcome groups, MMN amplitudes were reduced from the baseline in both FEP and CHR patients with poor prognostic trajectories. Reduced baseline MMN amplitudes were a significant predictor of later treatment resistance in FEP patients [Exp(β) = 2.100, 95% confidence interval (CI) 1.104–3.993, p = 0.024] and nonremission in CHR individuals [Exp(β) = 1.898, 95% CI 1.065–3.374, p = 0.030].

These findings suggest that MMN could be used as a common prognostic biomarker across early psychosis periods, which will aid clinical decisions for early intervention.