Depressive disorders are among the leading causes of global disease burden, but there has been limited progress in understanding the causes of and treatments for these disorders. In this Perspective, we suggest that such progress depends crucially on our ability to measure depression. We review the many problems with depression measurement, including the limited evidence of validity and reliability. These issues raise grave concerns about common uses of depression measures, such as for diagnosis or tracking treatment progress. We argue that shortcomings arise because the measurement of depression rests on shaky methodological and theoretical foundations. Moving forward, we need to break with the field’s tradition, which has, for decades, divorced theories about depression from how we measure it. Instead, we suggest that epistemic iteration, an iterative exchange between theory and measurement, provides a crucial avenue for progressing how we measure depression. Depressive disorders are among the leading causes of global disease burden. In this Perspective, Fried et al. argue that limited progress in understanding, predicting and treating depression despite a wealth of empirical research stems from issues in the methodological and theoretical foundations of depression measurement.
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Fried et al. (2022) studied this question.
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