Predicting and preventing symptom onset and relapse in schizophrenia—A metareview of current empirical evidence.
Bibliographic record
Abstract
The stress-vulnerability-protective factors model is often used to explain the etiology and known risk and protective factors of initial psychotic symptoms and symptomatic relapses. Over the past 40 years since its initial conception, the model has evolved and gathered a plethora of evidence of varying quality for its different components. The objective of this metareview is to analyze the quality of the evidence and the effect sizes for each component of the model not previously reviewed. Recent meta-analyses covering each component of the model in relation to the onset of psychotic symptoms or symptomatic relapse in schizophrenia were reviewed with the grading of recommendations, assessment, development, and evaluation system. Thirty-one meta-analyses were kept, from 3,044 papers reviewed. We did not add to previous metareviews in terms of obstetric/prenatal or genetic vulnerabilities. For stressors, moderate to strong research evidence was found for childhood adversity, cannabis, methamphetamine abuse, and expressed emotions as triggers of psychotic relapse or as linked to the onset of psychotic symptoms. For protective factors, moderate to strong evidence was found for antipsychotic medication in adults, family interventions, social skills training, as well as interventions focusing on recovery management skills. Poor evidence or no evidence (i.e., absence of meta-analyses) were found for the other components of the model. More rigorous studies and systematic reviews are needed in order to validate the various components of the model in regard to symptom onset and relapse. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 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".