Clinical characteristics associated with functioning trajectories following admission to a psychiatric institution: A prospective cohort study of individuals with psychosis
Bibliographic record
Abstract
Psychotic disorders can be severely enabling, and functional recovery is often difficult to achieve. Admission to a psychiatric unit represents a key opportunity to implement strategies that will improve functional outcomes. In the current literature, there is a lack of consensus on which factors influence functional recovery. Therefore, the present longitudinal cohort study aimed to identify factors associated with functional trajectories following hospital admission for acute psychosis. A sample of 453 individuals with acute psychosis was extracted from the Signature Biobank database. Participants were followed for up to a year following admission. Various clinical indicators were documented over time. Functional trajectories were calculated based on the World Health Organization Disability Assessment Schedule 2.0. Three groups were identified: "improving", "stable", and "worsening" function. Individuals with a more severe symptomatic presentation at baseline were found to have better functional improve more over time. Over time, individuals in the "improving" and "stable" groups had significant improvements in their psychiatric symptoms. Finally, individuals following a "worsening" functional trajectory initially improved in terms of psychotic symptoms, but it did not persist over time. These results highlight the importance of studying function as a key component of recovery rather than solely focusing on relapse prevention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".