A Delphi Approach To Characterising 'Relapse' as Used in Uk Clinical Practice
Bibliographic record
Abstract
BACKGROUND: 'Relapse' is a common outcome indicator in intervention studies in schizophrenia. In community studies it is frequently equated with hospitalisation and in psychopharmacological studies with predetermined symptom scores. Its clinical meaning, however, remains undefined. METHOD: Consensus on the defining features of 'relapse' in schizophrenia used by academic and clinical schizophrenia experts in the UK, was investigated using a four stage Delphi process. A two panel, four stage, Delphi based methodology was used to investigate the implicit meanings of 'relapse' in clinical practice. A multidisciplinary panel of twelve members each listed anonymously ten indicators of relapse. A second panel, of ten experienced psychiatrists, rated the 188 submitted indicators from essential-unimportant (1-5). This panel completed a one day workshop during the remaining Delphi rounds ending with a structured discussion of the results. RESULTS: Very strong consensus was achieved on the relative importance of potential relapse indicators. There was complete agreement about some aspects of a definition of relapse (such as recurrence of positive symptoms) and a number of the complex issues underlying the concept were clearly articulated. CONCLUSIONS: This four stage Delphi process achieved consensus on core features of relapse. The elucidation of the "softer" features at the threshold between normal fluctuations in functioning and the start of relapse require continuing investigations.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 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".