Natural language processing of multi-hospital electronic health records for public health surveillance of suicidality.

There is an urgent need to monitor the mental health of large populations, especially during crises such as the COVID-19 pandemic, to timely identify the most at-risk subgroups and to design targeted prevention campaigns. We therefore developed and validated surveillance indicators related to suicidality: the monthly number of hospitalisations caused by suicide attempts and the prevalence among them of five known risks factors. They were automatically computed analysing the electronic health records of fifteen university hospitals of the Paris area, France, using natural language processing algorithms based on artificial intelligence. We evaluated the relevance of these indicators conducting a retrospective cohort study. Considering 2,911,920 records contained in a common data warehouse, we tested for changes after the pandemic outbreak in the slope of the monthly number of suicide attempts by conducting an interrupted time-series analysis. We segmented the assessment time in two sub-periods: before (August 1, 2017, to February 29, 2020) and during (March 1, 2020, to June 31, 2022) the COVID-19 pandemic. We detected 14,023 hospitalisations caused by suicide attempts. Their monthly number accelerated after the COVID-19 outbreak with an estimated trend variation reaching 3.7 (95%CI 2.1-5.3), mainly driven by an increase among girls aged 8-17 (trend variation 1.8, 95%CI 1.2-2.5). After the pandemic outbreak, acts of domestic, physical and sexual violence were more often reported (prevalence ratios: 1.3, 95%CI 1.16-1.48; 1.3, 95%CI 1.10-1.64 and 1.7, 95%CI 1.48-1.98), fewer patients died (p = 0.007) and stays were shorter (p < 0.001). Our study demonstrates that textual clinical data collected in multiple hospitals can be jointly analysed to compute timely indicators describing mental health conditions of populations. Our findings also highlight the need to better take into account the violence imposed on women, especially at early ages and in the aftermath of the COVID-19 pandemic.

Cortico-Cerebellar neurodynamics during social interaction in Autism Spectrum Disorders.

BACKGROUND: Exploring neural network dynamics during social interaction could help to identify biomarkers of Autism Spectrum Disorders (ASD). A cerebellar involvement in autism has long been suspected and recent methodological advances now enable studying cerebellar functioning in a naturalistic setting. Here, we investigated the electrophysiological activity of the cerebro-cerebellar network during real-time social interaction in ASD. We focused our analysis on theta oscillations (3-8 Hz), which have been associated with large-scale coordination of distant brain areas and might contribute to interoception, motor control, and social event anticipation, all skills known to be altered in ASD. METHODS: We combined the Human Dynamic Clamp, a paradigm for studying realistic social interactions using a virtual avatar, with high-density electroencephalography (HD-EEG). Using source reconstruction, we investigated power in the cortex and the cerebellum, along with coherence between the cerebellum and three cerebral-cortical areas, and compared our findings in a sample of participants with ASD (n = 107) and with typical development (TD) (n = 33). We developed an open-source pipeline to analyse neural dynamics at the source level from HD-EEG data. RESULTS: Individuals with ASD showed a significant increase in theta band power over the cerebellum and the frontal and temporal cortices during social interaction compared to resting state, along with significant coherence increases between the cerebellum and the sensorimotor, frontal and parietal cortices. However, a phase-based connectivity measure did not support a strict activity increase in the cortico-cerebellar functional network. We did not find any significant differences between the ASD and the TD group. CONCLUSIONS: This exploratory study uncovered increases in the theta band activity of participants with ASD during social interaction, pointing at the presence of neural interactions between the cerebellum and cerebral networks associated with social cognition. It also emphasizes the need for complementary functional connectivity measures to capture network-level alterations. Future work will focus on optimizing artifact correction to include more participants with TD and increase the statistical power of group-level contrasts.

Motor Capabilities in Children with ADHD Are Improved after Brief Visuopostural Training.

Children with ADHD show poor motor control. The aim of the present study was to test whether children with ADHD improved their motor performances (oculomotor as well as posture) after a short visuopostural training period. Two groups (G1 trained and G2 non-trained), each comprising 15 children with ADHD matched in IQ (intelligence quotient), sex, and age, participated in the study. Eye movements and postural sway were measured before (T1) and after (T2) 10 min of visuopostural training for the trained group and after 10 min of resting for the non-trained group. Training consisted of a visual search task performed while the child was standing on an unstable platform. At T1, oculomotor and postural abilities were statistically similar for both groups of children with ADHD (trained and non-trained). At T2, significant improvements in both oculomotor and postural capabilities were observed for the trained group but not for the non-trained group. These findings suggest that a short visuopostural training period could help children with ADHD to learn how to focus their visual attention in order to improve motor performance. Visuopostural training could allow a better integration of sensory inputs via central mechanisms, leading to improvement in both oculomotor and postural control. Further studies on a larger number of children with ADHD will be needed to confirm these findings and explore the eventual possible persistence of the training effect.

Emotional and behavioral changes in French children during the COVID-19 pandemic: a retrospective study.

COVID-19 outbreak caused severe disruptions in daily life, partly due to limitations implemented to prevent the spreading. In France, it included school closures during a national lockdown, then a reopening of schools, with access depending on viral status of students and teachers. Those changes had an impact on children's mental health. We conducted an online cross-sectional study using a parental self-administered survey in December 2021 to explore the emotional and behavioral changes (EBC) during this 5th wave (W5) and retrospectively since the first one (W1) in their children and their multidimensionality with principal factor analysis (PCA) and stability analysis. Out of 4552 parent responders, 62.4% (n = 2839) noticed negative EBC during W1 and 54.1% (n = 2462) during W5 of the pandemic. Only 10.0% of the responders noticed negative EBC at W1 but not during the W5. In younger children (3-6 years old) with significant EBC, PCA revealed three main dimensions at W1 and W5: restlessness, depression and anxiety. In older children (7-13 years old), PCA showed partially similar dimensions: depression-suicidality, anxiety and withdrawal. Almost all correlations between dimensions at W1 and W5 were significantly positive. Every EBC was stable across waves, except for one. Recall bias concerning the EBC during W1 and lack of data concerning parental mental health should be taken into account. Our stability analysis found a strong correlation between dimensions at W1 and W5. Our results highlighted the impact of the COVID-19 outbreak on children's mental health and the predictive aspect of its early deterioration.

Age of onset of social anxiety disorder and psychiatric and mental health outcomes: Results from a nationally representative study.

OBJECTIVE: Prior studies support that younger age of onset would be associated with poorer psychiatric and mental health outcomes for many psychiatric disorders. However, such relationship has never been examined for social anxiety disorder (SAD) in a nationally representative sample. METHODS: Using data from the second Wave of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), we have identified four groups of participants with a lifetime DSM-IV diagnosis of SAD based on the self-reported age of onset (childhood onset (<12 years, N = 658), adolescence onset (12-17 years, N = 663), early-adulthood onset (18-39 years, N = 663), and late-adulthood onset (>39 years, N = 415)), and a control group without a lifetime history of SAD (N = 32,205). We performed multinomial logistic regression models to compare lifetime DSM-IV psychiatric disorders and current mental health-related quality of life (assessed with the mental component summary score (MSC) of the SF-12) across these groups. RESULTS: The lifetime prevalence rates of panic disorder, agoraphobia and post-traumatic stress disorder were significantly higher in the adulthood onset groups than in groups with an onset during childhood or adolescence (p < 0.01 for most models). MCS score was significantly higher in the childhood (46.0 (SE = 0.5)) or adolescence (46.5 (SE = 0.5)) onset groups than in the groups with an onset during adulthood (early-adulthood onset: 43.5 (SE = 0.6), and late-adulthood onset: 43.0 (SE = 0.8)). LIMITATIONS: Our results relied on retrospective self-reported data. CONCLUSION: Among individuals with SAD, a later age of onset was significantly associated with greater lifetime rates of psychiatric disorders and diminished quality of life.

Latent class analysis of the feared situations of social anxiety disorder: A population-based study.

BACKGROUND: Little is known about differences in mental health comorbidity and quality of life in individuals with social anxiety disorder (SAD) according to the number and the types of feared situations. METHODS: Using a US nationally representative sample, the National Epidemiologic Survey on Alcohol and Related Conditions, we performed latent class analysis to compare the prevalence rates of mental disorders and quality of life measures across classes defined by the number and the types of feared social situations among individuals with SAD. RESULTS: Among the 2,448 participants with a lifetime diagnosis of SAD, we identified three classes of individuals who feared most social situations but differed in the number of feared social situations (generalized severe [N = 378], generalized moderate [N = 1,049] and generalized low [N = 443]) and a class of subjects who feared only performance situations [N = 578]. The magnitude of associations between each class and a wide range of mental disorders and quality of life measures were consistent with a continuum model, supporting that the deleterious effects of SAD on mental health may increase with the number of social situations feared. However, we found that individuals with the "performance only" specifier may constitute an exception to this model because these participants had significantly better mental health than other participants with SAD. CONCLUSIONS: Our findings give additional support to the recent changes made in the DSM-5, including the introduction of the "performance only" specifier and the removal of the "generalized" specifier to promote the dimensional approach of the number of social fears.