A NEET distinction: youths not in employment, education or training follow different pathways to illness and care in psychosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: The early phases of psychosis, including the prodrome, often feature educational/occupational difficulties and various symptoms and signs, that can render or keep youths "Not in Employment, Education or Training" (NEET). Conversely, NEET status itself may increase risk for illness progression and impaired functioning, and impede access to appropriate services for psychosis. As these issues have not been investigated, we aimed to examine differences in the illness and care pathways and characteristics of youths with psychosis who are NEET and non-NEET. METHODS: Youths entering a catchment-based Canadian early intervention service for psychosis (N = 416) were assessed as being NEET or non-NEET and compared on symptomatology, premorbid adjustment, prodrome and duration of untreated psychosis (DUP). RESULTS: Thirty-nine percent of the sample was NEET. Compared to non-NEET youths, NEET youths had 34% higher negative symptoms scores, longer prodromes (median of 52 weeks vs. 24 weeks), and were more often continuously ill after their first psychiatric change until the onset of psychosis (62% vs. 45%). Both groups had similar premorbid adjustment scores until late adolescence when scores were significantly worse for NEET youths. Accounting for other predictors, NEET youths had 23% longer DUPs on average, despite having made more help-seeking attempts. CONCLUSIONS: Despite being more narrowly defined, NEET status was thrice as prevalent in our sample as in the Canadian population. The NEET group followed a distinct trajectory of persistent symptoms and functional decline before presenting with a psychotic disorder. The systemic delays that NEET youths encountered indicate a need for better-targeted early identification efforts.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it