Longitudinal impact of trauma in the North American Prodrome Longitudinal Study‐3
Bibliographic record
Abstract
AIM: Individuals at clinical high risk (CHR) for psychosis have been shown to experience more trauma than the general population. However, although the effects of trauma appear to impact some symptoms it does not seem to increase the risk of transition to psychosis. The aim of this article was to examine the prevalence of trauma, and its association with longitudinal clinical and functional outcomes in a large sample of CHR individuals. METHODS: From the North American Prodrome Longitudinal Study-3 (NAPLS-3) 690 CHR individuals and 91 healthy controls from nine study sites between 2015 and 2018 were assessed. Historical trauma experiences were captured at baseline. Participants completed longitudinal assessments measuring clinical outcomes including positive and negative symptoms, depression, social and role functioning and assessing transition to psychosis. RESULTS: From the 690 CHR participants and 96 healthy controls, 343 (49.6%) and 15 (15.6%), respectively, reported a history of trauma (p < .001). Emotional neglect (70.3%) was the most commonly reported type of trauma, followed by psychological abuse (57.4%). Among CHR participants, time to transition to psychosis was not associated with trauma. Baseline depression and suspiciousness/persecutory ideas were statistically significantly different between CHR individuals who did or did not experience trauma. However, when examining clinical and functional outcomes over 12-months of follow-up, there were no differences between those who experienced trauma and those who did not. CONCLUSION: Overall, trauma is a significantly prevalent among CHR individuals. The effects of trauma on transition and longitudinal clinical and functional outcomes were not significant.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".