How Problematic Assumptions Have Slowed Depression Research

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In Frontiers in Psychology, Belgian psychologist Eiko Fried argues for a different approach to understanding depression — not as a discrete disease, but as a cluster of otherwise independent symptoms that trigger and reinforce each other.

Fried reviews the history and limitations with the current disease model of depression and illustrates how a different approach would open new avenues of research and potential treatment. In his model, he writes, depression is not a discrete, underlying disease that causes a wide variety of symptoms; rather, it is a “network of symptoms that have direct causal influence on each other: insomnia can cause fatigue which then triggers concentration and psychomotor problems.”

“This network approach focuses on smaller and more valid and reliable units of observation – symptoms – that are likely associated with more distinct underlying pathophysiological processes,” writes Fried. “The framework not only acknowledges the highly heterogeneous nature of MD [major depression], its complexity, and its fuzzy boundaries, it also puts the focus on the dynamic interactions among symptoms that have received comparably little attention. The investigation of the differences between symptoms in terms of risk factors or biomarkers, as well as their causal pathways may be a great opportunity. In addition, future network studies could reveal that variables such as life stress, personality traits, and pathophysiology moderate specific symptom pathways: some individuals may be especially vulnerable to develop fatigue in response to insomnia, depending on their life situation or genetic background.”

Fried, Eiko I. “Problematic Assumptions Have Slowed down Depression Research: Why Symptoms, Not Syndromes Are the Way Forward.” Psychopathology, 2015, 309. doi:10.3389/fpsyg.2015.00309. (Full text)

4 COMMENTS

  1. “In his model, he writes, depression is not a discrete, underlying disease that causes a wide variety of symptoms; rather, it is a “network of symptoms that have direct causal influence on each other: insomnia can cause fatigue which then triggers concentration and psychomotor problems.”

    Yes, chain-reactions of negative consequences (including emotional ones) accumulate and further harm the sufferer.

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  2. And insomnia can be due to sleep disorders like apnea that once treated usually completely take depression out of the equation. Very frustrating that this seems to be continuously ignored in mental health circles.

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  3. This got me thinking about the failure of clinical trials (whether fabricated or done correctly) to predict the post-marketing usefulness, tolerability, and destructiveness of new drugs.

    In a sense, the best a drug can do in a trial is drive responses to the measuremen instruments in the right direction. How well the instruments measure the subjective experience of depression is not known. Two people who complete questionnaire with the same answers could be describing different inner states. In other words, just as there is heterogeneity in depression, there is heterogeneity in how people use language to describe their symptoms.

    Clinical trials of psych drugs reliably report improvement in the placebo groups’ symptoms that is worryingly close to that in treated groups. Given the similarity in placebo and treatment participants’ reports, it might be they relfect a third variable, “time elapsed since baseline,” to a greater degree than they measure improvement in symptoms.

    I’d like to see clinical trials add seemingly bone-headed questions like “Do you like this drug?” How does it make you feel? (No one can fault the wisdom in “say what you mean and mean what you say.)

    Depression surely is heterogeneous, making it hard to define and measure. We can get around that by remembering that drugs are intended to help people, not clinical trial outcomes.

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  4. “Problematic Assumptions Have Slowed Depression Research”
    Of course they did. Scientists who use DSM labels as a basis for their studies end up chasing their own tail. I’ve heard that from many people that these labels are useless in terms of driving scientific progress yet they are still trumpeted as “science-based”.

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