Biological, Life Course, and Cross-Cultural Studies All point Toward the Value of Dimensional and Developmental Ratings in the Classification of Psychosis
Bibliographic record
Abstract
The diagnostic criteria for schizophrenia in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) are based on the premise that it is a discrete illness entity, in particular, distinct from the affective psychoses. This assumption has persisted for more than a century, even though patients with a diagnosis of schizophrenia show a wide diversity of symptoms and outcomes, and no biological or psychological feature has been found to be pathognomonic of the disorder. However, there has been sustained, and indeed growing, criticism of the concept. For example, writing about the diagnosis of schizophrenia more than a decade ago,2 one of Britain's most sophisticated nosological experts, Ian Brockington, enjoined "It is important to loosen the grip which the concept of 'schizophrenia' has on the minds of psychiatrists. Schizophrenia is an idea whose very essence is equivocal, a nosological category without natural boundaries, a barren hypothesis. Such a blurred concept is 'not a valid object of scientific enquiry'."3 Should Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition(DSM-V), persist with the neo-Kraepelinian concept of schizophrenia with all its defects, or should it deconstruct psychosis into its component dimensions? In this article, we will address the question by considering 2 main themes, firstly, the role of culture and ethnicity in the diagnosis of psychosis, and secondly, a life course approach to understanding psychosis. We will then discuss whether more progress would be achieved in DSM-V by abandoning the familiar categorical system and instead moving to a dimensional system which rates both developmental impairment and symptom factor scores. However, we will begin by briefly reviewing the recent history of the classification of the psychoses.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".