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Record W7073758512

Association of schizophrenia spectrum disorders and violence perpetration in adults and adolescents from 15 countries: a systematic review and meta-analysis

2022· article· en· W7073758512 on OpenAlexaboutno aff

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationSchizophrenia (object-oriented programming)Poison controlSchizoaffective disorderEpidemiologyInjury preventionPsychosisSuicide preventionObservational study
DOInot available

Abstract

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<p><strong>Importance</strong> Violence perpetration outcomes in individuals with schizophrenia spectrum disorders contribute to morbidity and mortality at a population level, disrupt care, and lead to stigma.</p>\n\n<p><strong>Objective</strong> To conduct a systematic review and meta-analysis of the risk of perpetrating interpersonal violence in individuals with schizophrenia spectrum disorders compared with general population control individuals.</p>\n\n<p><strong>Data Sources</strong> Multiple databases were searched for studies in any language from January 1970 to March 2021 using the terms violen* or homicid* and psychosis or psychoses or psychotic or schizophren* or schizoaffective or delusional and terms for mental disorders. Bibliographies of included articles were hand searched.</p>\n\n<p><strong>Study Selection</strong> The study included case-control and cohort studies that allowed risks of interpersonal violence perpetration and/or violent criminality in individuals with schizophrenia spectrum disorders to be compared with a general population group without these disorders.</p>\n\n<p><strong>Data Extraction and Synthesis</strong> The study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and the Meta-analyses of Observational Studies in Epidemiology (MOOSE) proposal. Two reviewers extracted data. Quality was assessed using the Newcastle-Ottawa Quality Assessment Scale. Data were pooled using a random-effects model.</p>\n\n<p><strong>Main Outcomes and Measures</strong> The main outcome was violence to others obtained either through official records, self-report and/or collateral-report, or medical file review and included any physical assault, robbery, sexual offenses, illegal threats or intimidation, and arson.</p>\n\n<p><strong>Results</strong> The meta-analysis included 24 studies of violence perpetration outcomes in 15 countries over 4 decades (N = 51 309 individuals with schizophrenia spectrum disorders; reported mean age of 21 to 54 years at follow-up; of those studies that reported outcomes separately by sex, there were 19 976 male individuals and 14 275 female individuals). There was an increase in risk of violence perpetration in men with schizophrenia and other psychoses (pooled odds ratio [OR], 4.5; 95% CI, 3.6-5.6) with substantial heterogeneity (I2 = 85%; 95% CI, 77-91). The risk was also elevated in women (pooled OR, 10.2; 95% CI, 7.1-14.6), with substantial heterogeneity (I2 = 66%; 95% CI, 31-83). Odds of perpetrating sexual offenses (OR, 5.1; 95% CI, 3.8-6.8) and homicide (OR, 17.7; 95% CI, 13.9-22.6) were also investigated. Three studies found increased relative risks of arson but data were not pooled for this analysis owing to heterogeneity of outcomes. Absolute risks of violence perpetration in register-based studies were less than 1 in 20 in women with schizophrenia spectrum disorders and less than 1 in 4 in men over a 35-year period.</p>\n\n<p><strong>Conclusions and Relevance</strong> This systematic review and meta-analysis found that the risk of perpetrating violent outcomes was increased in individuals with schizophrenia spectrum disorders compared with community control individuals, which has been confirmed in new population-based longitudinal studies and sibling comparison designs.</p>

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.222
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2022
Admission routes1
Has abstractyes

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