Literature DB >> 29448238

Parsing the heterogeneity of depression: An exploratory factor analysis across commonly used depression rating scales.

Elizabeth D Ballard1, Julia S Yarrington2, Cristan A Farmer2, Marc S Lener2, Bashkim Kadriu2, Níall Lally3, Deonte Williams2, Rodrigo Machado-Vieira4, Mark J Niciu2, Lawrence Park2, Carlos A Zarate2.   

Abstract

BACKGROUND: Due to the heterogeneity of depressive symptoms-which can include depressed mood, anhedonia, negative cognitive biases, and altered activity levels-researchers often use a combination of depression rating scales to assess symptoms. This study sought to identify unidimensional constructs measured across rating scales for depression and to evaluate these constructs across clinical trials of a rapid-acting antidepressant (ketamine).
METHODS: Exploratory factor analysis (EFA) was conducted on baseline ratings from the Beck Depression Inventory (BDI), the Hamilton Depression Rating Scale (HAM-D), the Montgomery-Asberg Depression Rating Scale (MADRS), and the Snaith-Hamilton Pleasure Rating Scale (SHAPS). Inpatients with major depressive disorder (n = 76) or bipolar depression (n = 43) were participating in clinical ketamine trials. The trajectories of the resulting unidimensional scores were evaluated in 41 subjects with bipolar depression who participated in clinical ketamine trials.
RESULTS: The best solution, which exhibited excellent fit to the data, comprised eight factors: Depressed Mood, Tension, Negative Cognition, Impaired Sleep, Suicidal Thoughts, Reduced Appetite, Anhedonia, and Amotivation. Various response patterns were observed across the clinical trial data, both in treatment effect (ketamine versus placebo) and in degree of placebo response, suggesting that use of these unidimensional constructs may reveal patterns not observed with traditional scoring of individual instruments. LIMITATIONS: Limitations include: 1) small sample (and related inability to confirm measurement invariance); 2) absence of an independent sample for confirmation of factor structure; and 3) the treatment-resistant nature of the population, which may limit generalizability.
CONCLUSIONS: The empirical identification of unidimensional constructs creates more refined scores that may elucidate the connection between specific symptoms and underlying pathophysiology. Published by Elsevier B.V.

Entities:  

Keywords:  Clinical trials; Depression; Factor analysis; Ketamine; Psychometrics

Mesh:

Substances:

Year:  2018        PMID: 29448238      PMCID: PMC5852677          DOI: 10.1016/j.jad.2018.01.027

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


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