Abstract
Background The symptoms for Major Depression (MD) defined in the DSM-5 differ markedly from symptoms assessed in common rating scales, and the empirical question about core depression symptoms is unresolved. Here we conceptualize depression as a complex dynamic system of interacting symptoms to examine what symptoms are most central to driving depressive processes. Methods We constructed a network of 28 depression symptoms assessed via the Inventory of Depressive Symptomatology (IDS-30) in 3,463 depressed outpatients from the Sequenced Treatment Alternatives to Relieve Depression (STAR∗D) study. We estimated the centrality of all IDS-30 symptoms, and compared the centrality of DSM and non-DSM symptoms; centrality reflects the connectedness of each symptom with all other symptoms. Results A network with 28 intertwined symptoms emerged, and symptoms differed substantially in their centrality values. Both DSM symptoms (e.g., sad mood) and non-DSM symptoms (e.g., anxiety) were among the most central symptoms, and DSM criteria were not more central than non-DSM symptoms. Limitations Many subjects enrolled in STAR∗D reported comorbid medical and psychiatric conditions which may have affected symptom presentation. Conclusion The network perspective neither supports the standard psychometric notion that depression symptoms are equivalent indicators of MD, nor the common assumption that DSM symptoms of depression are of higher clinical relevance than non-DSM depression symptoms. The findings suggest the value of research focusing on especially central symptoms to increase the accuracy of predicting outcomes such as the course of illness, probability of relapse, and treatment response.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 314-320 |
| Number of pages | 7 |
| Journal | Journal of Affective Disorders |
| Volume | 189 |
| DOIs | |
| State | Published - Jan 1 2016 |
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Keywords
- Centrality
- Depression symptoms
- Major depression
- Network analysis
ASJC Scopus subject areas
- Psychiatry and Mental health
- Clinical Psychology
Cite this
What are 'good' depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. / Fried, Eiko I.; Epskamp, Sacha; Nesse, Randolph; Tuerlinckx, Francis; Borsboom, Denny.
In: Journal of Affective Disorders, Vol. 189, 01.01.2016, p. 314-320.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - What are 'good' depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis
AU - Fried, Eiko I.
AU - Epskamp, Sacha
AU - Nesse, Randolph
AU - Tuerlinckx, Francis
AU - Borsboom, Denny
PY - 2016/1/1
Y1 - 2016/1/1
N2 - Background The symptoms for Major Depression (MD) defined in the DSM-5 differ markedly from symptoms assessed in common rating scales, and the empirical question about core depression symptoms is unresolved. Here we conceptualize depression as a complex dynamic system of interacting symptoms to examine what symptoms are most central to driving depressive processes. Methods We constructed a network of 28 depression symptoms assessed via the Inventory of Depressive Symptomatology (IDS-30) in 3,463 depressed outpatients from the Sequenced Treatment Alternatives to Relieve Depression (STAR∗D) study. We estimated the centrality of all IDS-30 symptoms, and compared the centrality of DSM and non-DSM symptoms; centrality reflects the connectedness of each symptom with all other symptoms. Results A network with 28 intertwined symptoms emerged, and symptoms differed substantially in their centrality values. Both DSM symptoms (e.g., sad mood) and non-DSM symptoms (e.g., anxiety) were among the most central symptoms, and DSM criteria were not more central than non-DSM symptoms. Limitations Many subjects enrolled in STAR∗D reported comorbid medical and psychiatric conditions which may have affected symptom presentation. Conclusion The network perspective neither supports the standard psychometric notion that depression symptoms are equivalent indicators of MD, nor the common assumption that DSM symptoms of depression are of higher clinical relevance than non-DSM depression symptoms. The findings suggest the value of research focusing on especially central symptoms to increase the accuracy of predicting outcomes such as the course of illness, probability of relapse, and treatment response.
AB - Background The symptoms for Major Depression (MD) defined in the DSM-5 differ markedly from symptoms assessed in common rating scales, and the empirical question about core depression symptoms is unresolved. Here we conceptualize depression as a complex dynamic system of interacting symptoms to examine what symptoms are most central to driving depressive processes. Methods We constructed a network of 28 depression symptoms assessed via the Inventory of Depressive Symptomatology (IDS-30) in 3,463 depressed outpatients from the Sequenced Treatment Alternatives to Relieve Depression (STAR∗D) study. We estimated the centrality of all IDS-30 symptoms, and compared the centrality of DSM and non-DSM symptoms; centrality reflects the connectedness of each symptom with all other symptoms. Results A network with 28 intertwined symptoms emerged, and symptoms differed substantially in their centrality values. Both DSM symptoms (e.g., sad mood) and non-DSM symptoms (e.g., anxiety) were among the most central symptoms, and DSM criteria were not more central than non-DSM symptoms. Limitations Many subjects enrolled in STAR∗D reported comorbid medical and psychiatric conditions which may have affected symptom presentation. Conclusion The network perspective neither supports the standard psychometric notion that depression symptoms are equivalent indicators of MD, nor the common assumption that DSM symptoms of depression are of higher clinical relevance than non-DSM depression symptoms. The findings suggest the value of research focusing on especially central symptoms to increase the accuracy of predicting outcomes such as the course of illness, probability of relapse, and treatment response.
KW - Centrality
KW - Depression symptoms
KW - Major depression
KW - Network analysis
UR - http://www.scopus.com/inward/record.url?scp=84943609022&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84943609022&partnerID=8YFLogxK
U2 - 10.1016/j.jad.2015.09.005
DO - 10.1016/j.jad.2015.09.005
M3 - Article
VL - 189
SP - 314
EP - 320
JO - Journal of Affective Disorders
JF - Journal of Affective Disorders
SN - 0165-0327
ER -