Back to Search
Start Over
Parsing the heterogeneity of depression: An exploratory factor analysis across commonly used depression rating scales.
- Source :
-
Journal of affective disorders [J Affect Disord] 2018 Apr 15; Vol. 231, pp. 51-57. Date of Electronic Publication: 2018 Feb 05. - Publication Year :
- 2018
-
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).<br />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.<br />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.<br />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.<br />Conclusions: The empirical identification of unidimensional constructs creates more refined scores that may elucidate the connection between specific symptoms and underlying pathophysiology.<br /> (Published by Elsevier B.V.)
- Subjects :
- Adult
Antidepressive Agents therapeutic use
Bipolar Disorder drug therapy
Bipolar Disorder psychology
Depressive Disorder, Major drug therapy
Depressive Disorder, Major psychology
Factor Analysis, Statistical
Female
Humans
Ketamine therapeutic use
Male
Middle Aged
Psychotropic Drugs therapeutic use
Symptom Assessment methods
Young Adult
Bipolar Disorder diagnosis
Depressive Disorder, Major diagnosis
Psychiatric Status Rating Scales statistics & numerical data
Symptom Assessment statistics & numerical data
Subjects
Details
- Language :
- English
- ISSN :
- 1573-2517
- Volume :
- 231
- Database :
- MEDLINE
- Journal :
- Journal of affective disorders
- Publication Type :
- Academic Journal
- Accession number :
- 29448238
- Full Text :
- https://doi.org/10.1016/j.jad.2018.01.027