Dimensions of Delusions in Major Depression: Socio-demographic and Clinical Correlates in an Unipolar-Bipolar Sample

OBJECTIVE: The present study aims at exploring associations between a continuous measure of distorted thought contents and a set of demographic and clinical features in a sample of unipolar/bipolar depressed patients. METHODS: Our sample included 1,833 depressed subjects. Severity of mood symptoms was assessed by the 21 items Hamilton Depression Rating Scale (HAM-D). The continuous outcome measure was represented by a delusion (DEL) factor, extracted from HAM-D items and including items: 2 ("Feelings of guilt"), 15 ("Hypochondriasis"), and 20 ("Paranoid symptoms"). Each socio-demographic and clinical variable was tested by a generalized linear model test, having depressive severity (HAM-D score-DEL score) as the covariate. RESULTS: A family history of major depressive disorder (MDD; p=0.0006), a diagnosis of bipolar disorder, type I ( p=0.0003), a comorbid general anxiety disorder (p<0.0001), and a higher number of manic episodes during lifetime (p<0.0001), were all associated to higher DEL scores. Conversely, an older age at onset (p<0.0001) and a longer duration of hospitalization for depression over lifetime (p=0.0003) had a negative impact over DEL scores. On secondary analyses, only the presence of psychotic features (p<0.0001) and depressive severity (p<0.0001) were found to be independently associated to higher DEL scores. CONCLUSION: The retrospective design and a non validated continuous measure for distorted thought contents were the main limitations of our study. Excluding the presence of psychotic features and depressive severity, no socio-demographic or clinical variable was found to be associated to our continuous measure of distorted thinking in depression.

Animal models of post-traumatic stress disorder.

Animal behavioral studies have commonly regarded the entire group of animals subjected to the study conditions as homogeneous, disregarding individual differences in response patterns. The following discussion will focus on a method of analyzing data that aims to model clinical diagnostic criteria applied to individual patterns of response using data from behavioral measures, and employing cut-off scores to distinguish between extremes of response versus non-response and the sizeable proportion of study subjects in-between them. This protocol unit will present the concept of the model and its background, provide detailed protocols for each of its components, and present a selection of studies employing and examining the model, alongside the underlying translational rationale of each.

Animal model for PTSD: from clinical concept to translational research.

In humans, the diagnosis of PTSD is made only if an individual exhibits a certain number of symptoms from each of three quite well defined symptom clusters over a certain period of time. Animal behavioral studies, however, have generally tended to overlook this aspect and have commonly regarded the entire group of animals subjected to certain study conditions as homogeneous. Thus, in an attempt to develop animal models of long-term chronic behavioral responses to stress (i.e. PTSD) in a comparable manner to human diagnosis, we applied cut-off inclusion/exclusion criteria to behavioral data for a cohort of animals exposed to a stress paradigm. This grouped them as behaviorally affected or unaffected by the stress. This model takes into account the variability in degree of the individual's response to the stress paradigm, thereby modeling the fact that not all humans exposed to traumatic stress respond with affective disorder. This article will present and discuss findings from a series of studies employing a model of individual behavioral response classification. This article will discuss the concept of the model and its background and present a selection of studies employing and examining the model, alongside the underlying translational rationale of each. This article is part of a Special Issue entitled 'Post-Traumatic Stress Disorder'.