Clinical staging for youth at‐risk for serious mental illness: A longitudinal perspective
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to identify a sample of youth in distinct stages of risk for the development of a serious mental illness (SMI) according to a published clinical staging model and to follow this sample longitudinally to determine clinical changes over time. This article reports the 6- and 12-month follow-up of the cohort. METHODS: This study recruited 243 youth, ages 12 to 25. The sample included (a) 42 healthy controls, (b) 41 nonhelpseeking individuals with no mental illness but some risk of SMI, for example, having a first-degree relative with an SMI (stage 0), (c) 53 youth experiencing distress and mild symptoms of anxiety or depression (stage 1a), and (d) 107 youth with attenuated symptoms of SMIs 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 at baseline, 6- and 12-months. RESULTS: There were few changes for healthy controls and stage 0 participants, although approximately 7% did move to a symptomatic stage within 12-months. Of stage 1a participants, 50% remained symptomatic, with 7.5% moving to stage 1b or developing a SMI. Approximately 9% of stage 1byouth developed a SMI within 12-months and approximately one-third had remission of symptoms during the follow-up. CONCLUSIONS: Results suggest that the implementation of a transdiagnostic staging model may be useful in youth mental health and support consideration of clinical stage-based treatment for youth with early features of risk.
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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 | 0.003 | 0.004 |
| 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 | 0.001 |
| 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".