Literature DB >> 27422742

Diagnosing melancholic depression: some personal observations.

Gordon Parker1.   

Abstract

OBJECTIVES: The objective of this study was to offer some personal observations as to how melancholia can be diagnosed and differentiated from the non-melancholic depressive conditions.
METHODS: Personal clinical and research-based observations are presented following a critique of common current strategies.
RESULTS: The paper offers views on the most differentiating clinical features, argues for adding illness course variables to symptoms and provides details of the Sydney Melancholic Prototypic Index, a measure with a high overall classification rate in differentiating melancholic and non-melancholic depression.
CONCLUSIONS: Greater precision in differentiating melancholic from non-melancholic depression is advanced by weighting signs and symptoms of psychomotor disturbance, as well as including illness correlates and family history in the diagnostic process.

Entities:  

Keywords:  depression; diagnosis; melancholia

Mesh:

Year:  2016        PMID: 27422742     DOI: 10.1177/1039856216657696

Source DB:  PubMed          Journal:  Australas Psychiatry        ISSN: 1039-8562            Impact factor:   1.369


  1 in total

1.  A neural network approach to optimising treatments for depression using data from specialist and community psychiatric services in Australia, New Zealand and Japan.

Authors:  Aidan Cousins; Lucas Nakano; Emma Schofield; Rasa Kabaila
Journal:  Neural Comput Appl       Date:  2022-01-13       Impact factor: 5.606

  1 in total

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