An early detection programme reduces the duration of untreated first episode psychosis
Bibliographic record
Abstract
Melle I, Larsen TK, Haahr U, et al . Reducing the duration of untreated first-episode psychosis: Effects on clinical presentation. Arch Gen Psychiatry 2004;61:143–50.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Q Does an early detection programme decrease the duration of untreated first episode psychosis? ### ![Graphic][5]</img>Design: Cohort study. ### ![Graphic][6]</img>Allocation: Open. ### ![Graphic][7]</img>Blinding: Not blinded. ### ![Graphic][8]</img>Follow up period: Three months. ### ![Graphic][9]</img>Setting: Four healthcare sectors in Norway and Denmark; recruitment period 1997 to 2000. ### ![Graphic][10]</img>Patients: The study catchment area had 665 000 inhabitants. 874 people with psychosis like symptoms were assessed. 284 people met inclusion criteria: DSM-IV diagnosis of psychotic disorder; actively psychotic (Positive and Negative Syndrome Scale score (PANSS) ⩾4 on positive subscale items 1, 3, 5, or 6 or general subscale item 9); no adequate previous medication for psychosis (>3.5 haloperidol equivalents for >12 weeks or until resolution of symptoms); no related neurological or endocrine disorders; age 18–65 years, and IQ score >70. ### ![Graphic][11]</img>Intervention: The early detection (ED) programme ran in … [1]: {openurl}?query=rft.jtitle%253DArchives%2Bof%2BGeneral%2BPsychiatry%26rft.stitle%253DArch%2BGen%2BPsychiatry%26rft.aulast%253DMelle%26rft.auinit1%253DI.%26rft.volume%253D61%26rft.issue%253D2%26rft.spage%253D143%26rft.epage%253D150%26rft.atitle%253DReducing%2Bthe%2BDuration%2Bof%2BUntreated%2BFirst-Episode%2BPsychosis%253A%2BEffects%2Bon%2BClinical%2BPresentation%26rft_id%253Dinfo%253Adoi%252F10.1001%252Farchpsyc.61.2.143%26rft_id%253Dinfo%253Apmid%252F14757590%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/external-ref?access_num=10.1001/archpsyc.61.2.143&link_type=DOI [3]: /lookup/external-ref?access_num=14757590&link_type=MED&atom=%2Febmental%2F7%2F3%2F84.atom [4]: /lookup/external-ref?access_num=000188652800004&link_type=ISI [5]: /embed/inline-graphic-1.gif [6]: /embed/inline-graphic-2.gif [7]: /embed/inline-graphic-3.gif [8]: /embed/inline-graphic-4.gif [9]: /embed/inline-graphic-5.gif [10]: /embed/inline-graphic-6.gif [11]: /embed/inline-graphic-7.gif
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".