Clinical staging for youth at‐risk for serious mental illness
Bibliographic record
Abstract
AIM: The first aim of this project was to identify a sample of youth who met different stages of risk for the development of a serious mental illness (SMI) based on a published clinical staging model. The second aim was to determine whether participants allocated to the different stages were a good fit to the model by comparing these groups on a range of clinical measures. METHODS: This two-site longitudinal study recruited 243 youth, ages 12 to 25. The sample included (a) 42 healthy controls, (b) 43 non-help seeking individuals with no mental illness but with some risk of SMI, such as having a first-degree relative with a SMI (stage 0), (c) 52 help-seeking youth experiencing distress and possibly mild symptoms of anxiety or depression (stage 1a) and (d) 108 youth with attenuated symptoms of SMI, such as bipolar disorder or psychosis (stage 1b). Participants completed a range of measures assessing depression, anxiety, mania, suicide ideation, attenuated psychotic symptoms, negative symptoms, anhedonia and beliefs about oneself. RESULTS: There were no clinical differences between HCs and participants in stage 0. For most of the clinical measures, participants in stage 1b had more severe ratings than participants in stages 1a and 0 and HCs; those in stage 1a had more severe ratings than HCs and stage 0 participants. CONCLUSIONS: These results suggest that the staging process used to allocate participants to various stages is a good fit. That is, the clinical ratings followed an ordering effect consistent with that hypothesized in the staging model.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".