Adolescents often experience a heightened incidence of depressive symptoms, which can persist without early intervention. However, adolescents often struggle to identify depressive symptoms, and even when they are aware of these symptoms, seeking help is not always their immediate response. This study aimed to explore the relationship between passively collected digital data, specifically keystroke and stylus data collected via mobile devices, and the manifestation of depressive symptoms.

A total of 927 first-year middle school students from schools in Seoul solved Korean language and math problems. Throughout this study, 77 types of keystroke and stylus data were collected, including parameters such as the number of key presses, tap pressure, stroke speed, and stroke acceleration. Depressive symptoms were measured using the self-rated Patient Health Questionnaire-9 (PHQ-9).

Multiple regression analysis highlighted the significance of stroke length, speed, and acceleration, the average y-coordinate, the tap pressure, and the number of incorrect answers in relation to PHQ-9 scores. The keystroke and stylus metadata were able to reflect mood, energy, cognitive abilities, and psychomotor symptoms among adolescents with depressive symptoms.

This study demonstrates the potential of automatically collected data during school exams or classes for the early screening of clinical depressive symptoms in students. This study has the potential to serve as a cornerstone in the development of digital data frameworks for the early detection of depressive symptoms in adolescents.

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.

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.

Epidemiological data on the association between mental disorders and the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) severity are limited.

To evaluate the association between mental disorders and the risk of SARS-CoV-2 infection and severe outcomes following COVID-19.

We performed a cohort study using the Korean COVID-19 patient database based on national health insurance data. Each person with a mental or behavioural disorder (diagnosed during the 6 months prior to their first SARS-CoV-2 test) was matched by age, gender and Charlson Comorbidity Index with up to four people without mental disorders. SARS-CoV-2-positivity risk and the risk of death or severe events (intensive care unit admission, use of mechanical ventilation and acute respiratory distress syndrome) post-infection were calculated using conditional logistic regression analysis.

Among 230 565 people tested for SARS-CoV-2, 33 653 (14.6%) had mental disorders; 928/33 653 (2.76%) tested SARS-CoV-2 positive and 56/928 (6.03%) died. In multivariable analysis using the matched cohort, there was no association between mental disorders and SARS-CoV-2-positivity risk (odds ratio OR = 0.95; 95% CI 0.87–1.04); however, a higher risk was associated with schizophrenia-related disorders (OR = 1.50; 95% CI 1.14–1.99). Among confirmed COVID-19 patients, the mortality risk was significantly higher in patients with than in those without mental disorders (OR = 1.99, 95% CI 1.15–3.43).

Mental disorders are likely contributing factors to mortality following COVID-19. Although the infection risk was not higher for people with mental disorders overall, those with schizophrenia-related disorders were more vulnerable to infection.

Over the past two decades, early detection and early intervention in psychosis have become essential goals of psychiatry. However, clinical impressions are insufficient for predicting psychosis outcomes in clinical high-risk (CHR) individuals; a more rigorous and objective model is needed. This study aims to develop and internally validate a model for predicting the transition to psychosis within 10 years.

Two hundred and eight help-seeking individuals who fulfilled the CHR criteria were enrolled from the prospective, naturalistic cohort program for CHR at the Seoul Youth Clinic (SYC). The least absolute shrinkage and selection operator (LASSO)-penalized Cox regression was used to develop a predictive model for a psychotic transition. We performed k-means clustering and survival analysis to stratify the risk of psychosis.

The predictive model, which includes clinical and cognitive variables, identified the following six baseline variables as important predictors: 1-year percentage decrease in the Global Assessment of Functioning score, IQ, California Verbal Learning Test score, Strange Stories test score, and scores in two domains of the Social Functioning Scale. The predictive model showed a cross-validated Harrell's C-index of 0.78 and identified three subclusters with significantly different risk levels.

Overall, our predictive model showed a predictive ability and could facilitate a personalized therapeutic approach to different risks in high-risk individuals.

Obsession and delusion are theoretically distinct from each other in terms of reality testing. Despite such phenomenological distinction, no extant studies have examined the identification of common and distinct neural correlates of obsession and delusion by employing biologically grounded methods. Here, we investigated dimensional effects of obsession and delusion spanning across the traditional diagnostic boundaries reflected upon the resting-state functional connectivity (RSFC) using connectome-wide association studies (CWAS).

Our study sample comprised of 96 patients with obsessive–compulsive disorder, 75 patients with schizophrenia, and 65 healthy controls. A connectome-wide analysis was conducted to examine the relationship between obsession and delusion severity and RFSC using multivariate distance-based matrix regression.

Obsession was associated with the supplementary motor area, precentral gyrus, and superior parietal lobule, while delusion was associated with the precuneus. Follow-up seed-based RSFC and modularity analyses revealed that obsession was related to aberrant inter-network connectivity strength. Additional inter-network analyses demonstrated the association between obsession severity and inter-network connectivity between the frontoparietal control network and the dorsal attention network.

Our CWAS study based on the Research Domain Criteria (RDoC) provides novel evidence for the circuit-level functional dysconnectivity associated with obsession and delusion severity across diagnostic boundaries. Further refinement and accumulation of biomarkers from studies embedded within the RDoC framework would provide useful information in treating individuals who have some obsession or delusion symptoms but cannot be identified by the category of clinical symptoms alone.

Given that only a subgroup of patients with schizophrenia responds to first-line antipsychotic drugs, a key clinical question is what underlies treatment response. Observations that prefrontal activity correlates with striatal dopaminergic function, have led to the hypothesis that disrupted frontostriatal functional connectivity (FC) could be associated with altered dopaminergic function. Thus, the aim of this study was to investigate the relationship between frontostriatal FC and striatal dopamine synthesis capacity in patients with schizophrenia who had responded to first-line antipsychotic drug compared with those who had failed but responded to clozapine.

Twenty-four symptomatically stable patients with schizophrenia were recruited from Seoul National University Hospital, 12 of which responded to first-line antipsychotic drugs (first-line AP group) and 12 under clozapine (clozapine group), along with 12 matched healthy controls. All participants underwent resting-state functional magnetic resonance imaging and [18F]DOPA PET scans.

No significant difference was found in the total PANSS score between the patient groups. Voxel-based analysis showed a significant correlation between frontal FC to the associative striatum and the influx rate constant of [18F]DOPA in the corresponding region in the first-line AP group. Region-of-interest analysis confirmed the result (control group: R2 = 0.019, p = 0.665; first-line AP group: R2 = 0.675, p < 0.001; clozapine group: R2 = 0.324, p = 0.054) and the correlation coefficients were significantly different between the groups.

The relationship between striatal dopamine synthesis capacity and frontostriatal FC is different between responders to first-line treatment and clozapine treatment in schizophrenia, indicating that a different pathophysiology could underlie schizophrenia in patients who respond to first-line treatments relative to those who do not.

There is accumulating evidence for the role of fronto-striatal and associated circuits in obsessive–compulsive disorder (OCD) but limited and conflicting data on alterations in cortical thickness.

To investigate alterations in cortical thickness and subcortical volume in OCD.

In total, 412 patients with OCD and 368 healthy adults underwent magnetic resonance imaging scans. Between-group analysis of covariance of cortical thickness and subcortical volumes was performed and regression analyses undertaken.

Significantly decreased cortical thickness was found in the OCD group compared with controls in the superior and inferior frontal, precentral, posterior cingulate, middle temporal, inferior parietal and precuneus gyri. There was also a group x age interaction in the parietal cortex, with increased thinning with age in the OCD group relative to controls.

Our findings are partially consistent with earlier work, suggesting that group differences in grey matter volume and cortical thickness could relate to the same underlying pathology of OCD. They partially support a frontostriatal model of OCD, but also suggest that limbic, temporal and parietal regions play a role in the pathophysiology of the disorder. The group x age interaction effects may be the result of altered neuroplasticity.

Pathological gambling (PG) is a severe and persistent pattern of problem gambling that has been aligned with obsessive-compulsive disorder (OCD). However, no study has compared the neurocognitive profiles of individuals with PG and OCD.

We compared neurocognitive functioning, including executive function, verbal learning and memory, and visual–spatial organization and memory among 16 pathological gamblers, 31 drug-naïve OCD subjects, and 52 healthy controls.

The only neurocognitive marker common to both groups was increased fragmentation errors on the Rey–Osterrieth Complex Figure Test (ROCF). The PG subjects showed increased nonperseverative error on the Wisconsin Card Sorting Test and organization difficulties in the ROCF, whereas the OCD subjects revealed longer response times on the Stroop test and retention difficulties on the immediate recall scale of the ROCF.

A more careful approach is required in considering whether PG is a part of the OCD spectrum, as little evidence of neurocognitive overlap between PG and OCD has been reported.

Although a number of functional imaging studies are in agreement in suggesting orbitofrontal and subcortical hyperfunction in the pathophysiology of obsessive–compulsive disorder (OCD), the structural findings have been contradictory.

To investigate grey matter abnormalities in patients with OCD by employing a novel voxel-based analysis of magnetic resonance images.

Statistical parametric mapping was utilised to compare segmented grey matter images from 25 patients with OCD with those from 25 matched controls.

Increased regional grey matter density was found in multiple cortical areas, including the left orbitofrontal cortex, and in subcortical areas, including the thalamus. On the other hand, regions of reduction were confined to posterior parts of the brain, such as the left cuneus and the left cerebellum.

Increased grey matter density of frontal–subcortical circuits, consonant with the hypermetabolic findings from functional imaging studies, seems to exist in patients with OCD, and cerebellar dysfunction may be involved in the pathophysiology of OCD.