Early intervention has no effect on symptoms in people with first episode, non-affective psychosis, although it may improve overall function and medication adherence
Bibliographic record
Abstract
Garety PA, Craig TKJ, Dunn G, et al . Specialised care for early psychosis: symptoms, social functioning and patient satisfaction—randomised controlled trial. Br J Psychiatry 2006;188:37–45.[OpenUrl][1][Abstract/FREE Full Text][2] Q Does early intervention improve symptoms, treatment adherence, and functioning in people with early stage psychosis? ### ![Graphic][3] Design: Randomised controlled trial. ### ![Graphic][4] Allocation: Concealed. ### ![Graphic][5] Blinding: Unclear. ### ![Graphic][6] Follow up period: 18 months. ### ![Graphic][7] Setting: Inner city borough of London (Lambeth), UK; recruitment from January 2000 to June 2001. ### ![Graphic][8] Patients: 144 people (aged 16–40 years) with first episode, non-affective psychosis (ICD-10). Exclusions: substance abuse disorders, organic psychosis. ### ![Graphic][9] Intervention: Specifically adapted interventions, including cognitive behavioural therapy, medication management, vocational support, and family interventions provided by early onset psychosis mental health team. Comparator: standard generic community services; no special training or specially adapted support. ### ![Graphic][10] Outcomes: Clinical state (Positive and Negative Syndrome Scale (PANSS)); overall functioning (Global Assessment of Functioning (GAF)); depression (Calgary Depression Rating); treatment … [1]: {openurl}?query=rft.jtitle%253DThe%2BBritish%2BJournal%2Bof%2BPsychiatry%26rft.stitle%253DBr.%2BJ.%2BPsychiatry%26rft.aulast%253DGARETY%26rft.auinit1%253DP.%2BA.%26rft.volume%253D188%26rft.issue%253D1%26rft.spage%253D37%26rft.epage%253D45%26rft.atitle%253DSpecialised%2Bcare%2Bfor%2Bearly%2Bpsychosis%253A%2Bsymptoms%252C%2Bsocial%2Bfunctioning%2Band%2Bpatient%2Bsatisfaction%253A%2BRandomised%2Bcontrolled%2Btrial%26rft_id%253Dinfo%253Adoi%252F10.1192%252Fbjp.bp.104.007286%26rft_id%253Dinfo%253Apmid%252F16388068%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bjprcpsych&resid=188/1/37&atom=%2Febmental%2F9%2F3%2F69.atom [3]: /embed/inline-graphic-1.gif [4]: /embed/inline-graphic-2.gif [5]: /embed/inline-graphic-3.gif [6]: /embed/inline-graphic-4.gif [7]: /embed/inline-graphic-5.gif [8]: /embed/inline-graphic-6.gif [9]: /embed/inline-graphic-7.gif [10]: /embed/inline-graphic-8.gif
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".