Depression sum-scores don’t add up: why analyzing specific depression symptoms is essential

By Eiko I. Fried, R. Nesse. BMC Medicine, 2015

843 citations recorded by the source corpus.

Most measures of depression severity are based on the number of reported symptoms, and threshold scores are often used to classify individuals as healthy or depressed. This method – and research results based on it – are valid if depression is a single condition, and all symptoms are equally good severity indicators. Here, we review a host of studies documenting that specific depressive symptoms like sad mood, insomnia, concentration problems, and suicidal ideation are distinct phenomena that differ from each other in important dimensions such as underlying biology, impact on impairment, and risk factors. Furthermore, specific life events predict increases in particular depression symptoms, and there is evidence for direct causal links among symptoms. We suggest that the pervasive use of sum-scores to estimate depression severity has obfuscated crucial insights and contributed to the lack of progress in key research areas such as identifying biomarkers and more efficacious antidepressants. The analysis of individual symptoms and their causal associations offers a way forward. We offer specific suggestions with practical implications for future research.

Subfields: Biological Psychiatry, Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/b60fbb2ac465438dbf2f84700c24153c4e884487

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biological Psychiatry

In Cognitive Neuroscience

In Experimental and Cognitive Psychology

Citations in the corpus

Network Analysis of Depression and Anxiety Symptom Relations in a Psychiatric Sample (2016, background): “Similarly, the use of sum scores to describe psychopathology severity assumes that symptoms are interchangeable indicators of the same underlying condition and can thus be summed to create a total score (see Fried & Nesse, 2015a, b).”
Emotion Regulation Difficulties Related to Depression and Anxiety: A Network Approach to Model Relations Among Symptoms, Positive Reappraisal, and Repetitive Negative Thinking (2019, background): “…on the disorder level may be problematic because depression and different anxiety disorders are heterogeneous syndromes characterized by diverse affective, cognitive, and somatic symptoms (Fried & Nesse, 2015; Nandi, Beard, & Galea, 2009; Zimmerman, Ellison, Young, Chelminski, & Dalrymple, 2015).”
What do centrality measures measure in psychological networks? (2019, neutral): “(Fried & Nesse, 2015; Wichers, 2014) – but also due to the useful visualization tools (Epskamp, Cramer, Waldorp, Schmittmann, & Borsboom, 2012), that depict partial correlation and vector autoregressive models as a network in an intuitive way (Bringmann & Eronen, 2018).”
Mental disorders as networks of problems: a review of recent insights (2016, neutral): “This implies that the nature of symptoms may play an important role above and beyond the number of symptoms [45].”
Moving Forward: Challenges and Directions for Psychopathological Network Theory and Methodology (2017, background): “As we discussed in more detail above, there is considerable heterogeneity within diagnoses such as PTSD and MD, and patients may exhibit very different problems (Fried & Nesse, 2015a; Galatzer-Levy & Bryant, 2013; Olbert et al., 2014).”