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Network structure of depression symptomology in participants with and without depressive disorder: the population-based Health 2000-2011 study.

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Title: Network structure of depression symptomology in participants with and without depressive disorder: the population-based Health 2000-2011 study.
Authors: Hakulinen, Christian (AUTHOR), Fried, Eiko I. (AUTHOR), Pulkki-Råback, Laura (AUTHOR), Virtanen, Marianna (AUTHOR), Suvisaari, Jaana (AUTHOR), Elovainio, Marko (AUTHOR)
Source: Social Psychiatry & Psychiatric Epidemiology. Oct2020, Vol. 55 Issue 10, p1273-1282. 10p.
Subjects: Mental depression, Symptoms, Beck Depression Inventory, Spanning trees, Mental illness
Abstract: Purpose: Putative causal relations among depressive symptoms in forms of network structures have been of recent interest, with prior studies suggesting that high connectivity of the symptom network may drive the disease process. We examined in detail the network structure of depressive symptoms among participants with and without depressive disorders (DD; consisting of major depressive disorder (MDD) and dysthymia) at two time points.Methods: Participants were from the nationally representative Health 2000 and Health 2011 surveys. In 2000 and 2011, there were 5998 healthy participants (DD-) and 595 participants with DD diagnosis (DD+). Depressive symptoms were measured using the 13-item version of the Beck Depression Inventory (BDI). Fused Graphical Lasso was used to estimate network structures, and mixed graphical models were used to assess network connectivity and symptom centrality. Network community structure was examined using the walktrap-algorithm and minimum spanning trees (MST). Symptom centrality was evaluated with expected influence and participation coefficients.Results: Overall connectivity did not differ between networks from participants with and without DD, but more simple community structure was observed among those with DD compared to those without DD. Exploratory analyses revealed small differences between the samples in the order of one centrality estimate participation coefficient.Conclusions: Community structure, but not overall connectivity of the symptom network, may be different for people with DD compared to people without DD. This difference may be of importance when estimating the overall connectivity differences between groups with and without mental disorders. [ABSTRACT FROM AUTHOR]
Copyright of Social Psychiatry & Psychiatric Epidemiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Network structure of depression symptomology in participants with and without depressive disorder: the population-based Health 2000-2011 study.
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  Data: <searchLink fieldCode="AR" term="%22Hakulinen%2C+Christian%22">Hakulinen, Christian</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fried%2C+Eiko+I%2E%22">Fried, Eiko I.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pulkki-Råback%2C+Laura%22">Pulkki-Råback, Laura</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Virtanen%2C+Marianna%22">Virtanen, Marianna</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Suvisaari%2C+Jaana%22">Suvisaari, Jaana</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Elovainio%2C+Marko%22">Elovainio, Marko</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Social+Psychiatry+%26+Psychiatric+Epidemiology%22">Social Psychiatry & Psychiatric Epidemiology</searchLink>. Oct2020, Vol. 55 Issue 10, p1273-1282. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Mental+depression%22">Mental depression</searchLink><br /><searchLink fieldCode="DE" term="%22Symptoms%22">Symptoms</searchLink><br /><searchLink fieldCode="DE" term="%22Beck+Depression+Inventory%22">Beck Depression Inventory</searchLink><br /><searchLink fieldCode="DE" term="%22Spanning+trees%22">Spanning trees</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+illness%22">Mental illness</searchLink>
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  Label: Abstract
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  Data: <bold>Purpose: </bold>Putative causal relations among depressive symptoms in forms of network structures have been of recent interest, with prior studies suggesting that high connectivity of the symptom network may drive the disease process. We examined in detail the network structure of depressive symptoms among participants with and without depressive disorders (DD; consisting of major depressive disorder (MDD) and dysthymia) at two time points.<bold>Methods: </bold>Participants were from the nationally representative Health 2000 and Health 2011 surveys. In 2000 and 2011, there were 5998 healthy participants (DD-) and 595 participants with DD diagnosis (DD+). Depressive symptoms were measured using the 13-item version of the Beck Depression Inventory (BDI). Fused Graphical Lasso was used to estimate network structures, and mixed graphical models were used to assess network connectivity and symptom centrality. Network community structure was examined using the walktrap-algorithm and minimum spanning trees (MST). Symptom centrality was evaluated with expected influence and participation coefficients.<bold>Results: </bold>Overall connectivity did not differ between networks from participants with and without DD, but more simple community structure was observed among those with DD compared to those without DD. Exploratory analyses revealed small differences between the samples in the order of one centrality estimate participation coefficient.<bold>Conclusions: </bold>Community structure, but not overall connectivity of the symptom network, may be different for people with DD compared to people without DD. This difference may be of importance when estimating the overall connectivity differences between groups with and without mental disorders. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Social Psychiatry & Psychiatric Epidemiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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