Psychosocial Profiles of Patients Admitted to Psychiatric Emergency Services: Results from the Signature Biobank Project
Bibliographic record
Abstract
OBJECTIVES: Patients admitted to psychiatric emergency services (PES) are highly heterogenous. New tools based on a transdiagnosis approach could help attending psychiatrists in their evaluation process and treatment planning. The goals of this study were to: (1) identify profiles of symptoms based on self-reported, dimensional outcomes in psychiatric patients upon their admission to PES, (2) link these profiles to developmental variables, that is, history of childhood abuse (CA) and trajectories of externalizing behaviours (EB), and (3) test whether this link between developmental variables and profiles was moderated by sex. METHODS: In total, 402 patients were randomly selected from the Signature Biobank, a database of measures collected from patients admitted to the emergency of a psychiatric hospital. A comparison group of 92 healthy participants was also recruited from the community. Symptoms of anxiety, depression, alcohol and drug abuse, impulsivity, and psychosis as well as CA and EB were assessed using self-reported questionnaires. Symptom profiles were identified using cluster analysis. Prediction of profile membership by sex, CA, and EB was tested using structural equation modelling. RESULTS: Among patients, four profiles were identified: (1) low level of symptoms on all outcomes, (2) high psychotic symptoms, (3) high anxio-depressive symptoms, and (4) elevated substance abuse and high levels of symptoms on all scales. An indirect effect of CA was found through EB trajectories: patients who experienced the most severe form of CA were more likely to develop chronic EB from childhood to adulthood, which in turn predicted membership to the most severe psychopathology profile. This indirect effect was not moderated by sex. CONCLUSION: Our results suggest that a transdiagnostic approach allows to highlight distinct clinical portraits of patients admitted to PES. Importantly, developmental factors were predictive of specific profiles. Such transdiagnostic approach is a first step towards precision medicine, which could lead to develop targeted interventions.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".