Stress management programme may reduce hospital admissions among people with schizophrenia
Bibliographic record
Abstract
Norman R, Malla A, McLean T et al. An evaluation of a stress management program for individuals with schizophrenia. Schizophrenia Res2002 Dec; 58 : 293 –303 [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: Does improving stress management skills enhance outcomes for people with schizophrenia? Randomised trial. Assessors were blind to treatment allocation. One treatment centre in Canada; timeframe not specified. Participants were 121 people aged between 17 and 50 years with a DSM IIIR diagnosis of schizophrenia. Mean age 34 years; 33% women; mean length of illness 9 years. People were excluded if they were hospitalised or had medication increases in the past 3 months due to exacerbation of acute symptoms. Participants received either 1) a 12-week group stress management programme with individual follow up sessions, or 2) social activities. The stress management programme focused on muscular relaxation … [1]: {openurl}?query=rft.jtitle%253DSchizophrenia%2Bresearch%26rft.stitle%253DSchizophr%2BRes%26rft.aulast%253DNorman%26rft.auinit1%253DR.%2BM.%26rft.volume%253D58%26rft.issue%253D2-3%26rft.spage%253D293%26rft.epage%253D303%26rft.atitle%253DAn%2Bevaluation%2Bof%2Ba%2Bstress%2Bmanagement%2Bprogram%2Bfor%2Bindividuals%2Bwith%2Bschizophrenia.%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0920-9964%252801%252900371-1%26rft_id%253Dinfo%253Apmid%252F12409170%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=10.1016/S0920-9964(01)00371-1&link_type=DOI [3]: /lookup/external-ref?access_num=12409170&link_type=MED&atom=%2Febmental%2F6%2F2%2F52.atom [4]: /lookup/external-ref?access_num=000179196000021&link_type=ISI
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".