A critical review of the evolution and interrelation of traumatic stress disorders
Bibliographic record
Abstract
Trauma is a complex and often contentious psychopathological construct. The term trauma has become ubiquitous within mental health literature and practice. It is often used interchangeably to describe the etiology and the reaction to it. In this article we describe its historical and contemporary conceptualization through a review of the disorders that claim a direct relation to traumatic events whether or not they are recognized by official psychiatric classification systems. We critically evaluate the extent to which current understandings of traumatic stress disorders capture the diversity and complexity in trauma experiences and responses across global contexts. Post Traumatic Stress Disorder continues to be the most used clinically and most studied academically. Other diagnoses such as Ongoing Traumatic Stress Reaction and Continuous Traumatic Stress are becoming more prevalent in psychiatry, and simultaneously, Complex PTSD is challenging the way we perceive and address some personality disorders. A realignment of the definition among the various mental health professions, in addition to a comprehensive evaluation of the relevance of current classification for the nature and timeline of traumatic events, in particular in war times, would ensure better research, interventions, and, ultimately, outcomes for individuals and communities affected by traumatic events.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".