The Experts below are selected from a list of 17058 Experts worldwide ranked by ideXlab platform
Asa Hammar - One of the best experts on this subject based on the ideXlab platform.
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facing recovery emotional bias in working memory rumination relapse and recurrence of major depression an experimental paradigm conducted five years after first episode of major depression
Applied Neuropsychology, 2020Co-Authors: Eivind Haga Ronold, Jutta Joormann, Asa HammarAbstract:Identifying Vulnerability factors for relapse of depression is essential in planning preventive interventions. Emotional face processing in major depression (MDD) shows promise as a potential cogni...
Jurgenchristian Krieg - One of the best experts on this subject based on the ideXlab platform.
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in quest of Identifying Vulnerability markers for psychiatric disorders by all night polysomnography
Archives of General Psychiatry, 1995Co-Authors: Christoph J Lauer, Wolfgang Schreiber, Florian Holsboer, Jurgenchristian KriegAbstract:Background: The persistence of a depressionlike sleep pattern in fully remitted depressed patients suggests that the pattern is a trait characteristic of sleep measurements. However, in the past, subjects have undergone investigation only after the onset of the disorder, and, therefore, the altered sleep pattern may merely represent a biological scar. Methods: We polysomnographically investigated 54 healthy subjects who had no lifetime or current diagnosis of a psychiatric disorder but had at least one first-degree relative with major depression or a bipolar disorder and at least one further close relative with major depression, a bipolar disorder, or a schizophrenic disorder. Twenty unrelated control probands without a personal and family history of psychiatric disorders and 18 unrelated inpatients with major depression served as reference groups. Prior to investigation, all healthy subjects had been free of any prescription and nonprescription drug for at least 3 months. The depressed patients were free of drugs for at least 1 week. All subjects slept for 2 nights in the sleep research unit. The sleep of the second night was recorded and visually scored. Results: Analysis of the individual sleep cycles in these subjects revealed both a reduced amount of slow wave sleep and increased rapid eye movement density in the first sleep cycle. Discriminant analysis showed that 10 subjects (18%) had sleep patterns similar to those of depressed patients. Conclusions: According to our observations, one fifth of the healthy subjects with a high genetic load for psychiatric disorders showed a conspicuous (depression-like) sleep pattern. The follow-up will determine whether this sleep pattern indeed represents a trait marker indicating Vulnerability.
Christoph J Lauer - One of the best experts on this subject based on the ideXlab platform.
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in quest of Identifying Vulnerability markers for psychiatric disorders by all night polysomnography
Archives of General Psychiatry, 1995Co-Authors: Christoph J Lauer, Wolfgang Schreiber, Florian Holsboer, Jurgenchristian KriegAbstract:Background: The persistence of a depressionlike sleep pattern in fully remitted depressed patients suggests that the pattern is a trait characteristic of sleep measurements. However, in the past, subjects have undergone investigation only after the onset of the disorder, and, therefore, the altered sleep pattern may merely represent a biological scar. Methods: We polysomnographically investigated 54 healthy subjects who had no lifetime or current diagnosis of a psychiatric disorder but had at least one first-degree relative with major depression or a bipolar disorder and at least one further close relative with major depression, a bipolar disorder, or a schizophrenic disorder. Twenty unrelated control probands without a personal and family history of psychiatric disorders and 18 unrelated inpatients with major depression served as reference groups. Prior to investigation, all healthy subjects had been free of any prescription and nonprescription drug for at least 3 months. The depressed patients were free of drugs for at least 1 week. All subjects slept for 2 nights in the sleep research unit. The sleep of the second night was recorded and visually scored. Results: Analysis of the individual sleep cycles in these subjects revealed both a reduced amount of slow wave sleep and increased rapid eye movement density in the first sleep cycle. Discriminant analysis showed that 10 subjects (18%) had sleep patterns similar to those of depressed patients. Conclusions: According to our observations, one fifth of the healthy subjects with a high genetic load for psychiatric disorders showed a conspicuous (depression-like) sleep pattern. The follow-up will determine whether this sleep pattern indeed represents a trait marker indicating Vulnerability.
Eivind Haga Ronold - One of the best experts on this subject based on the ideXlab platform.
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facing recovery emotional bias in working memory rumination relapse and recurrence of major depression an experimental paradigm conducted five years after first episode of major depression
Applied Neuropsychology, 2020Co-Authors: Eivind Haga Ronold, Jutta Joormann, Asa HammarAbstract:Identifying Vulnerability factors for relapse of depression is essential in planning preventive interventions. Emotional face processing in major depression (MDD) shows promise as a potential cogni...
Anand Patwardhan - One of the best experts on this subject based on the ideXlab platform.
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Methodology for Identifying Vulnerability hotspots to tropical cyclone hazard in India
Mitigation and Adaptation Strategies for Global Change, 2008Co-Authors: Upasna Sharma, Anand PatwardhanAbstract:Vulnerability indices are commonly used for characterizing the impacts on a region or comparing relative Vulnerability across regions. Such indices are usually computed as a composite/aggregate across different components of Vulnerability. Though such a single numerical value can be useful in many situations, a major disadvantage is that it leads to loss of information about how the different factors that went into making the composite index interact with each other, and contribute to making a place vulnerable. In this paper we develop an alternative approach for Identifying hotspots, based on cluster analysis that seeks to address this problem by considering the different components of Vulnerability separately. We compute different indices for each of the components of Vulnerability. Cluster analysis helps in Identifying the most vulnerable districts based on different combinations of the components of Vulnerability. In addition to being methodologically more robust than the index approach, the clustering approach may have greater policy-relevance as it provides information about which aspects of Vulnerability, policy needs to address in the most vulnerable districts.
