BackgroundOne of the major challenges in mental medical care is finding out new instruments for an accurate and objective evaluation of the attention deficit hyperactivity disorder (ADHD). Early ADHD identification, severity assessment, and prompt treatment are essential to avoid the negative effects associated with this mental condition.ObjectiveThe aim of our study was to develop a novel ADHD assessment instrument based on Microsoft Kinect, which identifies ADHD cardinal symptoms in order to provide a more accurate evaluation.MethodsA group of 30 children, aged 8-12 years (10.3 [SD 1.4]; male 70% [21/30]), who were referred to the Child and Adolescent Psychiatry Unit of the Department of Psychiatry at Fundación Jiménez Díaz Hospital (Madrid, Spain), were included in this study. Children were required to meet the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria of ADHD diagnosis. One of the parents or guardians of the children filled the Spanish version of the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior (SWAN) rating scale used in clinical practice. Each child conducted a Kinect-based continuous performance test (CPT) in which the reaction time (RT), the commission errors, and the time required to complete the reaction (CT) were calculated. The correlations of the 3 predictors, obtained using Kinect methodology, with respect to the scores of the SWAN scale were calculated.ResultsThe RT achieved a correlation of -.11, -.29, and -.37 with respect to the inattention, hyperactivity, and impulsivity factors of the SWAN scale. The correlations of the commission error with respect to these 3 factors were -.03, .01, and .24, respectively.ConclusionsOur findings show a relation between the Microsoft Kinect-based version of the CPT and ADHD symptomatology assessed through parental report. Results point out the importance of future research on the development of objective measures for the diagnosis of ADHD among children and adolescents.
This article presents a novel method for predicting suicidal ideation from Electronic Health Records (EHR) and Ecological Momentary Assessment (EMA) data using deep sequential models. Both EHR longitudinal data and EMA question forms are defined by asynchronous, variable length, randomly-sampled data sequences. In our method, we model each of them with a Recurrent Neural Network (RNN), and both sequences are aligned by concatenating the hidden state of each of them using temporal marks. Furthermore, we incorporate attention schemes to improve performance in long sequences and time-independent pre-trained schemes to cope with very short sequences. Using a database of 1023 patients, our experimental results show that the addition of EMA records boosts the system recall to predict the suicidal ideation diagnosis from 48.13% obtained exclusively from EHR-based state-of-the-art methods to 67.78%. Additionally, our method provides interpretability through the t-SNE representation of the latent space. Further, the most relevant input features are identified and interpreted medically.
Purpose of Review Since the declaration of the COVID-19 pandemic, there have been numerous social changes to try to contain the spread of the disease. These sudden changes in daily life have also changed the way we relate to others, in addition to creating a climate of uncertainty and fear. Therefore, the objective of this review is to compile published data of the consequences of suicidal behavior in the first months from the onset of the pandemic. Recent Findings The analysis reflects a concern about issues related to suicide since the beginning of the pandemic. A large number of online surveys have been released and have provided data on relatively large populations. The percentage of the population with suicidal ideation in that period seems to be approximately 5–15%. Many studies associate suicidal ideation with being young, female, and presence of sleep problems. Surveys of healthcare workers do not seem to indicate a higher prevalence of suicidal ideation compared to the general population. The incidence of suicide attempts seen in emergency departments did not seem to change, while the number of visits for other issues, unrelated to suicide, did decrease. The few studies on completed suicide do not indicate an increase in incidence in these first 6 months since March 2020, when the WHO declared the start of the pandemic. Summary It does not seem that there have been major changes in the figures related to suicidal behavior in the studies from the first wave of the COVID-19 pandemic, although it is still too early to know the consequences it will have long term. The social and economic damages resulting from the pandemic will certainly take a long time to recover.
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