29,920 research outputs found

    Family-Expressed Emotion, Childhood-Onset Depression, and Childhood-Onset Schizophrenia Spectrum Disorders: Is Expressed Emotion a Nonspecific Correlate of Child Psychopathology or a Specific Risk Factor for Depression?

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    Expressed emotion (EE) was examined, using the brief Five Minute Speech Sample measure, in families of (1) children with depressive disorders, (2) children with schizophrenia spectrum disorders, and (3) normal controls screened for the absence of psychiatric disorder. Consistent with the hypothesis of some specificity in the association between EE and the form of child disorder, rates of EE were significantly higher among families of depressed children compared to families of normal controls and families of children with schizophrenia spectrum disorders. Within the depressed group, the presence of a comorbid disruptive behavior disorder was associated with high levels of critical EE, underscoring the need to attend to comorbid patterns and subtypes of EE in future research

    A Review of Atrial Fibrillation Detection Methods as a Service

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    Atrial Fibrillation (AF) is a common heart arrhythmia that often goes undetected, and even if it is detected, managing the condition may be challenging. In this paper, we review how the RR interval and Electrocardiogram (ECG) signals, incorporated into a monitoring system, can be useful to track AF events. Were such an automated system to be implemented, it could be used to help manage AF and thereby reduce patient morbidity and mortality. The main impetus behind the idea of developing a service is that a greater data volume analyzed can lead to better patient outcomes. Based on the literature review, which we present herein, we introduce the methods that can be used to detect AF efficiently and automatically via the RR interval and ECG signals. A cardiovascular disease monitoring service that incorporates one or multiple of these detection methods could extend event observation to all times, and could therefore become useful to establish any AF occurrence. The development of an automated and efficient method that monitors AF in real time would likely become a key component for meeting public health goals regarding the reduction of fatalities caused by the disease. Yet, at present, significant technological and regulatory obstacles remain, which prevent the development of any proposed system. Establishment of the scientific foundation for monitoring is important to provide effective service to patients and healthcare professionals
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