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Record W2147910373 · doi:10.1001/archpsyc.62.8.911

Crime Victimization in Adults With Severe Mental Illness

2005· article· en· W2147910373 on OpenAlexaboutno aff
Linda A. Teplin, Gary M. McClelland, Karen M. Abram, Dana Weiner

Bibliographic record

VenueArchives of General Psychiatry · 2005
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsnot available
FundersNational Institute on Drug AbuseNational Institute of Mental Health
KeywordsDemographyPopulationEthnic groupMental healthQuarter (Canadian coin)Incidence (geometry)MedicineMental illnessPsychiatryPsychologyEnvironmental healthGeography

Abstract

fetched live from OpenAlex

CONTEXT: Since deinstitutionalization, most persons with severe mental illness (SMI) now live in the community, where they are at great risk for crime victimization. OBJECTIVES: To determine the prevalence and incidence of crime victimization among persons with SMI by sex, race/ethnicity, and age, and to compare rates with general population data (the National Crime Victimization Survey), controlling for income and demographic differences between the samples. DESIGN: Epidemiologic study of persons in treatment. Independent master's-level clinical research interviewers administered the National Crime Victimization Survey to randomly selected patients sampled from 16 randomly selected mental health agencies. SETTING: Sixteen agencies providing outpatient, day, and residential treatment to persons with SMI in Chicago, Ill. PARTICIPANTS: Randomly selected, stratified sample of 936 patients aged 18 or older (483 men, 453 women) who were African American (n = 329), non-Hispanic white (n = 321), Hispanic (n = 270), or other race/ethnicity (n = 22). The comparison group comprised 32 449 participants in the National Crime Victimization Survey. MAIN OUTCOME MEASURE: National Crime Victimization Survey, developed by the Bureau of Justice Statistics. RESULTS: More than one quarter of persons with SMI had been victims of a violent crime in the past year, a rate more than 11 times higher than the general population rates even after controlling for demographic differences between the 2 samples (P<.001). The annual incidence of violent crime in the SMI sample (168.2 incidents per 1000 persons) is more than 4 times higher than the general population rates (39.9 incidents per 1000 persons) (P<.001). Depending on the type of violent crime (rape/sexual assault, robbery, assault, and their subcategories), prevalence was 6 to 23 times greater among persons with SMI than among the general population. CONCLUSIONS: Crime victimization is a major public health problem among persons with SMI who are treated in the community. We recommend directions for future research, propose modifications in public policy, and suggest how the mental health system can respond to reduce victimization and its consequences.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.265
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations609
Published2005
Admission routes1
Has abstractyes

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