The Loss of Sadness

Allan V. Horwitz, Jerome Wakefield

The Loss of Sadness argues that the increased prevalence of major depressive disorder- 10% of all American adults are said to be afflicted with it, according to recent estimates- is due not to a genuine rise in mental disease, as many claim, but to the way that normal human sadness has been pathologized since 1980. In that year, the field of psychiatry published its landmark third edition of The Diagnostic and Statistical Manual of Mental Disorders (DSM-III), which has since become a dominant force behind our current understanding of mental illness overall. The result: in the past 25 years since the DSM-III's appearance, virtually all research and all clinical approaches to depression have been based on an invalid definition of the condition, resulting in far-reaching scientific, social, and political implications that affect us all.

Medicine & Public HealthMedicine & Public Health · medium confidenceMedicine & Public Health81 signalsLlm Classifier: Medicine & Public Health -> Medicine & Public HealthKeyword Classifier: American History -> American HistoryAward Category: PROSE Award for Psychology -> Medicine & Public HealthDisease, Epidemics & DrugsMental Health & PsychologyRegional & Local History
Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies

This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.

  1. 01 Central figures

    None extracted with sufficient confidence.

  2. 02 Central places

    None extracted with sufficient confidence.

  3. 03 Suggested argument

    Major depressive disorder’s increased prevalence is due to the pathologizing of normal sadness since 1980, driven by DSM-III’s invalid definition rather than a genuine rise in mental disease.

    Model confidence 78%

  4. 04 Reading orientation

    72 / 100 academic

    Academic

    An estimate of intended readership and scholarly apparatus—not quality or importance.

Confidence percentages are the model's own estimates. Profile confidence: 62%.