Diagnostic Criteria as Dysfunction Indicators: Bridging the Chasm between the Definition of Mental Disorder and Diagnostic Criteria for Specific Disorders
Bibliographic record
Abstract
According to the introduction to the Diagnostic and Statistical Manual of Mental Disorders (DSM), Fifth Edition, each disorder must satisfy the definition of mental disorder, which requires the presence of both harm and dysfunction. Constructing criteria sets to require harm is relatively straightforward. However, establishing the presence of dysfunction is necessarily inferential because of the lack of knowledge of internal psychological and biological processes and their functions and dysfunctions. Given that virtually every psychiatric symptom characteristic of a DSM disorder can occur under some circumstances in a normally functioning person, diagnostic criteria based on symptoms must be constructed so that the symptoms indicate an internal dysfunction, and are thus inherently pathosuggestive. In this paper, we review strategies used in DSM criteria sets for increasing the pathosuggestiveness of symptoms to ensure that the disorder meets the requirements of the definition of mental disorder. Strategies include the following: requiring a minimum duration and persistence; requiring that the frequency or intensity of a symptom exceed that seen in normal people; requiring disproportionality of symptoms, given the context; requiring pervasiveness of symptom expression across contexts; adding specific exclusions for contextual scenarios in which symptoms are best understood as normal reactions; combining symptoms to increase cumulative pathosuggestiveness; and requiring enough symptoms from an overall syndrome to meet a minimum threshold of pathosuggestiveness. We propose that future revisions of the DSM consider systematic implementation of these strategies in the construction and revision of criteria sets, with the goal of maximizing the pathosuggestiveness of diagnostic criteria to reduce the potential for diagnostic false positives. Selon l'introduction du Manuel diagnostique et statistique des troubles mentaux (DSM), 5 e édition, chaque trouble doit satisfaire à la définition d'un trouble mental, qui exige la présence de préjudice et de dysfonctionnement. Construire des ensembles de critères requérant un dommage est relativement simple. Cependant, établir la présence d'une dysfonction est nécessairement inférentiel en raison du manque de connaissances des processus psychologique et biologique internes ainsi que de leurs fonctions et dysfonctions. Étant donné qu'à peu près chaque caractéristique d'un symptôme psychiatrique d'un trouble du DSM peut se manifester dans certaines circonstances chez une personne fonctionnant normalement, les critères diagnostiques basés sur les symptômes doivent être construits de manière à ce que les symptômes indiquent une dysfonction interne, et qu'ils soient donc intrinsèquement pathosuggestifs.
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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 | 0.055 | 0.176 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".