Separation of anxiety and depressive disorders: blind alley in psychopharmacology and classification of disease
Bibliographic record
Abstract
No new drugs for mood and anxiety disorders have reached the market for over a decade. Why is there so little innovation in a sector that accounts for the largest proportion by far of sales of psychiatric drugs? The current division between anxiety and depression is increasingly recognised as inadequate. In the community, most mood disorders present as a combination of depression and anxiety. Yet the Food and Drug Administration in the United States, which has become the world bellwether of drug approval, indicates drugs either for major depression or for the various forms of anxiety recognised by the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (DSM). As a result, the pharmaceutical industry is compelled to develop drugs for diagnoses that are of questionable clinical relevance. This is one reason for the big slowdown in drug discovery in psychiatric drugs. A return to the former unitary classification of mood and anxiety disorders as nervousness or cothymia might represent a way out of this blind alley. In 1980, the American Psychiatric Association revised its standard system of diagnoses in the third edition of its diagnostic manual (DSM-III).1 This document erected a firewall between depression and anxiety. Indeed, in drafting this edition the association appointed separate committees to study depression and anxiety and stated that any overlap between the two disorders would henceforth be considered mainly as comorbidity. Although this division was controversial at the time, DSM-III became the accepted psychiatric nosology worldwide, and its successors dominate the picture today.2 Recent observers, however, suggest that
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.042 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.009 | 0.018 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.021 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".