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An exploratory statistical approach to depression pattern identification
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Feng, Qing Yi, Griffiths, Frances, Parsons, Nicholas R. and Gunn, Jane, Prof. (2013) An exploratory statistical approach to depression pattern identification. Physica A: Statistical Mechanics and its Applications, Volume 392 (Number 4). pp. 889-901. doi:10.1016/j.physa.2012.10.025 ISSN 0378-4371 .
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Official URL: http://dx.doi.org/10.1016/j.physa.2012.10.025
Abstract
Depression is a complex phenomenon thought to be due to the interaction of biological, psychological and social factors. Currently depression assessment uses self-reported depressive symptoms but this is limited in the degree to which it can characterise the different expressions of depression emerging from the complex causal pathways that are thought to underlie depression. In this study, we aimed to represent the different patterns of depression with pattern values unique to each individual, where each value combines all the available information about an individual’s depression. We considered the depressed individual as a subsystem of an open complex system, proposed Generalized Information Entropy (GIE) to represent the general characteristics of information entropy of the system, and then implemented Maximum Entropy Estimates to derive equations for depression patterns. We also introduced a numerical simulation method to process the depression related data obtained by the Diamond Cohort Study which has been underway in Australia since 2005 involving 789 people. Unlike traditional assessment, we obtained a unique value for each depressed individual which gives an overall assessment of the depression pattern. Our work provides a novel way to visualise and quantitatively measure the depression pattern of the depressed individual which could be used for pattern categorisation. This may have potential for tailoring health interventions to depressed individuals to maximize health benefit.
| Item Type: | Journal Article | ||||
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| Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences > Social Science & Systems in Health (SSSH) |
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| Journal or Publication Title: | Physica A: Statistical Mechanics and its Applications | ||||
| Publisher: | Elsevier BV | ||||
| ISSN: | 0378-4371 | ||||
| Official Date: | 15 February 2013 | ||||
| Dates: |
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| Volume: | Volume 392 | ||||
| Number: | Number 4 | ||||
| Page Range: | pp. 889-901 | ||||
| DOI: | 10.1016/j.physa.2012.10.025 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access |
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