Increasing evidence has established a strong association between social anxiety disorder and suicidal behaviours, including suicidal ideation and suicide attempts. However, the association between social anxiety disorder and suicide mortality remains unclear.

This study analysed data from 15,776 patients with social anxiety disorder, extracted from a nationwide Taiwanese cohort between 2003 and 2017. Two unexposed groups without social anxiety disorder, matched by birth year and sex in 1:4 and 1:10 ratios, respectively, were used for comparison. Suicide deaths during the same period were examined. Psychiatric comorbidities commonly associated with social anxiety disorder, including schizophrenia, bipolar disorder, major depression, alcohol use disorder (AUD), substance use disorder (SUD), obsessive-compulsive disorder, autism, and attention deficit hyperactivity disorder, were identified.

Time-dependent Cox regression models, adjusted for demographic factors and psychiatric comorbidities, revealed that individuals with social anxiety disorder had an increased risk of suicide (hazard ratio: 3.49 in the 1:4 matched analysis and 2.84 in the 1:10 matched analysis) compared with those without the disorder. Comorbidities such as schizophrenia, bipolar disorder, major depression, AUD, and SUD further increased the risk of suicide in patients with social anxiety disorder.

Social anxiety disorder is an independent risk factor for suicide death. Additional psychiatric comorbidities, including schizophrenia, major affective disorders, and AUD, further increased social anxiety disorder-related suicide risk. Therefore, mental health officers and clinicians should develop targeted suicide prevention strategies for individuals with social anxiety disorder.

Panic disorder (PD) may increase the likelihood of suicidal ideation and behaviors because of psychiatric comorbidities such as major depressive disorder (MDD). However, research has yet to demonstrate a direct relationship between PD and suicide mortality.

Using data from Taiwan’s National Health Insurance Research Database, we identified 171,737 individuals with PD and 686,948 age- and sex-matched individuals without PD during 2003–2017. We assessed the risk of suicide within the same period. Psychiatric comorbidities such as schizophrenia, bipolar disorder, MDD, obsessive-compulsive disorder (OCD), autism, alcohol use disorder (AUD), and substance use disorder (SUD) were also evaluated. Time-dependent Cox regression models were used to compare the risk of suicide in different groups after adjustment for demographic data and psychiatric comorbidities.

Our Cox regression model revealed that PD was an independent risk factor for suicide (hazard ratio [HR] = 1.85, 95% confidence interval [CI] = 1.59–2.14), regardless of psychiatric comorbidities. Among all comorbidities, MDD with PD was associated with the highest risk of suicide (HR = 6.08, 95% CI = 5.48–6.74), followed by autism (HR = 4.52, 95% CI = 1.66–12.29), schizophrenia (HR = 3.34, 95% CI = 2.7–4.13), bipolar disorder (HR = 3.20, 95% CI = 2.71–3.79), AUD (HR = 2.99, 95% CI = 2.41–3.72), SUD (HR = 2.82, 95% CI = 2.28–3.47), and OCD (HR = 2.10, 95% CI = 1.64–2.67).

PD is an independent risk factor for suicide. Psychiatric comorbidities (i.e. schizophrenia, bipolar disorder, MDD, OCD, AUD, SUD, and autism) with PD increase the risk of suicide.

The aim of this 4-year follow-up study was to examine the predictive effects of demographics, three types of sexual stigma, three types of self-identity confusion, anxiety, depression, family support and problematic Internet use before the coronavirus disease 2019 (COVID-19) pandemic on new-onset suicide risk and persistent suicide risk in young adult lesbian, gay and bisexual individuals who experienced the COVID-19 pandemic in Taiwan.

Baseline data were collected from 1,000 lesbian, gay and bisexual individuals in 2018 and 2019. Outcome data on suicide risk were collected again in 2023. The suicide module of the Mini International Neuropsychiatric Interview was used to assess suicide risk in terms of thoughts of death, desire to self-harm, thoughts of suicide, plans for suicide and suicide attempts in the preceding month at the initial and follow-up assessments. Baseline three types of sexual stigma, self-identity disturbance, depression, anxiety and problematic Internet use were used to examine their prediction of new-onset suicide risk and persistent suicide risk at follow-up.

In total, 673 individuals participated in the follow-up survey. Notably, 16.5% of the participants who had no suicide risk at baseline had new-onset suicide risk at follow-up; 46.4% of the participants who had suicide risk at baseline also had suicide risk at follow-up. Participants who were transgender (p = .003), who perceived greater levels of microaggression (p < .001), and who had greater levels of problematic Internet use at baseline (p = .024) were more likely to have new-onset suicide risk at follow-up. Participants who had greater levels of self-identity confusion were more likely to have persistent suicide risk at follow-up (p = .023).

Intervention strategies for reducing suicide risk in lesbian, gay and bisexual individuals should be developed with consideration of the predictors identified in this study.

Severe mental illness (SMI), which includes schizophrenia, schizoaffective disorder and bipolar disorder, has profound health impacts, even in the elderly.

To evaluate relative risk of hospital admission and length of hospital stay for physical illness in elders with SMI.

To construct a population-based retrospective cohort observed from April 2007 to March 2016, data from a case registry with full but de-identified electronic health records were retrieved for patients of the South London and Maudsley NHS Foundation Trust, the single secondary mental healthcare service provider in south-east London. We compared participants with SMI aged >60 years old with the general population of the same age and residing in the same areas through data linkage by age-, sex- and fiscal-year-standardised admission ratios (SARs) for primary diagnoses at hospital discharge. Furthermore, we compared the duration of hospital stay with an age-, sex- and cause-of-admission-matched random group by linear regression for major causes of admission.

In total, records for 4175 older people with SMI were obtained, relating to 10 342 admission episodes, showing an overall SAR for all physical illnesses of 5.15 (95% CI: 5.05, 5.25). Among the top causes of admission, SARs ranged from 3.87 for circulatory system disorders (ICD-10 codes: I00–I99) to 6.99 for genitourinary system or urinary conditions (N00–N39). Specifically, the diagnostic group of ‘symptoms, signs and findings, not elsewhere classified’ (R00–R99) had an elevated SAR of 6.56 (95% CI: 6.22, 6.90). Elders with SMI also had significantly longer hospital stays than their counterparts in the general population, especially for digestive system illnesses (K00–K93), after adjusting for confounding.

Poorer overall physical health and specific patterns were identified in elders with SMI.

Research evidence has established an association of obsessive-compulsive disorder (OCD) with suicidal thoughts and suicide attempts. However, further investigation is required to determine whether individuals with OCD have higher risk of death by suicide compared with those without OCD.

Of the entire Taiwanese population, between 2003 and 2017, 56,977 individuals with OCD were identified; they were then matched at a 1:4 ratio with 227,908 non-OCD individuals on the basis of their birth year and sex. Suicide mortality was assessed between 2003 and 2017 for both groups. Time-dependent Cox regression models were used to investigate the difference in suicide risk between individuals with versus without OCD.

After adjustment for major psychiatric comorbidities (i.e., schizophrenia, bipolar disorder and major depressive disorder), the OCD group had higher risk of suicide (hazard ratio: 1.97, 95% confidence interval: 1.57–2.48) during the follow-up compared with the comparison group. Furthermore, OCD severity, as indicated by psychiatric hospitalizations due to OCD, was positively correlated with suicide risk.

Regardless of the existence of major psychiatric comorbidities, OCD was found to be an independent risk factor for death by suicide. A suicide prevention program specific to individuals with OCD may be developed in clinical practice in the future.

Divergent thinking is a critical creative cognitive process. Its neural mechanisms have been well-studied through structural and functional imaging in healthy individuals but are less explored in patients with bipolar disorder (BD). Because of the traditional link between creativity and BD, this study investigated the structural correlates of divergent thinking in patients with BD through surface-based morphometry.

Fifty-nine patients diagnosed with BD I or BD II (35.3 ± 8.5 years) and 56 age- and sex-matched controls (33.9 ± 7.4 years) were recruited. The participants underwent structural magnetic resonance imaging and an evaluation of divergent thinking by using the Chinese version of the Abbreviated Torrance Test for Adults (ATTA). FreeSurfer 7.0 was used to generate thickness and surface area maps for each participant. Brainwise regression of the association between cortical thickness or surface area and ATTA performance was conducted using general linear models.

Divergent thinking performance did not differ significantly between the patients with BD and the healthy controls. In these patients, total ATTA score was negatively correlated with cortical thickness in the right middle frontal gyrus, right occipital, and left precuneus but positively correlated with the surface area of the right superior frontal gyrus. By contrast, total ATTA scores and cortical thickness or surface area were not significantly correlated among the controls.

The findings indicate that divergent thinking involves cerebral structures for executive control, mental imagery, and visual processing in patients with BD, and the right prefrontal cortex might be the most crucial of these structures.

Evidence suggests a familial coaggregation of major psychiatric disorders, including schizophrenia, bipolar disorder, major depression (MDD), autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). Those disorders are further related to suicide and accidental death. However, whether death by suicide may coaggregate with accidental death and major psychiatric disorders within families remains unclear.

To clarify the familial coaggregation of deaths by suicide with accidental death and five major psychiatric disorders.

Using a database linked to the entire Taiwanese population, 68 214 first-degree relatives of individuals who died by suicide between 2003 and 2017 and 272 856 age- and gender-matched controls were assessed for the risks of death by suicide, accidental death and major psychiatric disorders.

A Poisson regression model showed that the first-degree relatives of individuals who died by suicide were more likely to die by suicide (relative risk RR = 4.61, 95% CI 4.02–5.29) or accident (RR = 1.62, 95% CI 1.43–1.84) or to be diagnosed with schizophrenia (RR = 1.53, 95% CI 1.40–1.66), bipolar disorder (RR = 1.99, 95% CI 1.83–2.16), MDD (RR = 1.98, 95% CI 1.89–2.08) or ADHD (RR = 1.34, 95% CI 1.24–1.44).

Our findings identified a familial coaggregation of death by suicide with accidental death, schizophrenia, major affective disorders and ADHD. Further studies would be required to elucidate the pathological mechanisms underlying this coaggregation.

To determine sociodemographics and caregiver burdens associated with overnight hospitalization, hospice utilization, and hospitalization frequency among persons with dementia (PWD).

Cross-sectional analysis of PWD (n = 899) of the National Health and Aging Trends Study linked to the National Study of Caregiving. Logistic and proportional odds regression determined the effects of caregiver burdens on overnight hospitalization, hospice use, and hospitalization frequency. Differences between PWD alive not-alive groups were compared on overnight hospitalization and frequency.

Alive PWD (n = 804) were 2.36 times more likely to have an overnight hospital stay (p = 0.004) and 1.96 times more likely to have multiple hospitalizations when caregivers found it physically difficult to provide care (p = 0.011). Decedents aged 65–74 (n = 95) were 4.55 times more likely to experience overnight hospitalizations than 85+, hospitalizations were more frequent (odds ratio [OR] = 4.84), and there was a significant difference between PWD alive/not alive groups (p = 0.035). Decedents were 5.60 times more likely to experience an overnight hospitalization when their caregivers had financial difficulty, hospitalizations were more frequent when caregivers had too much to handle (OR = 8.44) and/or no time for themselves (OR = 10.67). When caregivers had no time for themselves, a significant difference between alive/not alive groups (p = 0.018) was detected in hospitalization frequency. PWD whose caregivers had emotional difficulty helping were 5.89 times more likely to utilize hospice than caregivers who did not report emotional difficulty.

Care transitions among PWD at the end of life are impacted by the circumstances and experiences of their caregivers. Subjective caregiver burdens represent potentially modifiable risks for undesired care transitions and opportunities for promoting hospice use. Future work is warranted to identify and address these issues as they occur.

Support vector machines (SVMs) based on brain-wise functional connectivity (FC) have been widely adopted for single-subject prediction of patients with schizophrenia, but most of them had small sample size. This study aimed to evaluate the performance of SVMs based on a large single-site dataset and investigate the effects of demographic homogeneity and training sample size on classification accuracy.

The resting functional Magnetic Resonance Imaging (fMRI) dataset comprised 220 patients with schizophrenia and 220 healthy controls. Brain-wise FCs was calculated for each participant and linear SVMs were developed for automatic classification of patients and controls. First, we evaluated the SVMs based on all participants and homogeneous subsamples of men, women, younger (18–30 years), and older (31–50 years) participants by 10-fold nested cross-validation. Then, we hold out a fixed test set of 40 participants (20 patients and 20 controls) and evaluated the SVMs based on incremental training sample sizes (N = 40, 80, …, 400).

We found that the SVMs based on all participants had accuracy of 85.05%. The SVMs based on male, female, young, and older participants yielded accuracy of 84.66, 81.56, 80.50, and 86.13%, respectively. Although the SVMs based on older subsamples had better performance than those based on all participants, they generalized poorly to younger participants (77.24%). For incremental training sizes, the classification accuracy increased stepwise from 72.6 to 83.3%, with >80% accuracy achieved with sample size >240.

The findings indicate that SVMs based on a large dataset yield high classification accuracy and establish models using a large sample size with heterogeneous properties are recommended for single subject prediction of schizophrenia.

Cognitive impairment is common in late-life depression, which may increase Alzheimer disease (AD) risk. Therefore, we aimed to investigate whether late-life major depressive disorder (MDD) has worse cognition and increases the characteristic AD neuropathology. Furthermore, we carried out a comparison between treatment-resistant depression (TRD) and non-TRD. We hypothesized that patients with late-life depression and TRD may have increased β-amyloid (Aβ) deposits in brain regions responsible for global cognition.

We recruited 81 subjects, including 54 MDD patients (27 TRD and 27 non-TRD) and 27 matched healthy controls (HCs). Neurocognitive tasks were examined, including Mini-Mental State Examination and Montreal Cognitive Assessment to detect global cognitive functions. PET with Pittsburgh compound-B and fluorodeoxyglucose were used to capture brain Aβ pathology and glucose use, respectively, in some patients.

MDD patients performed worse in Montreal Cognitive Assessment (p = 0.003) and had more Aβ deposits than HCs across the brain (family-wise error-corrected p < 0.001), with the most significant finding in the left middle frontal gyrus. Significant negative correlations between global cognition and prefrontal Aβ deposits existed in MDD patients, whereas positive correlations were noted in HCs. TRD patients had significantly more deposits in the left-sided brain regions (corrected p < 0.001). The findings were not explained by APOE genotypes. No between-group fluorodeoxyglucose difference was detected.

Late-life depression, particularly TRD, had increased brain Aβ deposits and showed vulnerability to Aβ deposits. A detrimental role of Aβ deposits in global cognition in patients with late-onset or non-late-onset MDD supported the theory that late-life MDD could be a risk factor for AD.

Recent imaging studies of large datasets suggested that psychiatric disorders have common biological substrates. This study aimed to identify all the common neural substrates with connectomic abnormalities across four major psychiatric disorders by using the data-driven connectome-wide association method of multivariate distance matrix regression (MDMR).

This study analyzed a resting functional magnetic resonance imaging dataset of 100 patients with schizophrenia, 100 patients with bipolar I disorder, 100 patients with bipolar II disorder, 100 patients with major depressive disorder, and 100 healthy controls (HCs). We calculated a voxel-wise 4,330 × 4,330 matrix of whole-brain functional connectivity (FC) with 8-mm isotropic resolution for each participant and then performed MDMR to identify structures where the overall multivariate pattern of FC was significantly different between each patient group and the HC group. A conjunction analysis was performed to identify common neural regions with FC abnormalities across these four psychiatric disorders.

The conjunction of the MDMR maps revealed that the four groups of patients shared connectomic abnormalities in distributed cortical and subcortical structures, which included bilateral thalamus, cerebellum, frontal pole, supramarginal gyrus, postcentral gyrus, lingual gyrus, lateral occipital cortex, and parahippocampus. The follow-up analysis based on pair-wise FC of these regions demonstrated that these psychiatric disorders also shared similar patterns of FC abnormalities characterized by sensory/subcortical hyperconnectivity, association/subcortical hypoconnectivity, and sensory/association hyperconnectivity.

These findings suggest that major psychiatric disorders share common connectomic abnormalities in distributed cortical and subcortical regions and provide crucial support for the common network hypothesis of major psychiatric disorders.