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Violence in Treatment Resistant Psychotic Inpatients

2001· article· en· W2086900973 on OpenAlexaff
Thomas S. Ehmann, Geoffrey N. Smith, Aiko Yamamoto, NATALIA MCCARTHY, Deborah Ross, Tin Au, SEAN W. FLYNN, Siemion Altman, William G. Honer

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2001
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsRiverview HospitalUniversity of WindsorVancouver Infectious Diseases Centre
Fundersnot available
KeywordsPsychiatryHarmPsychopathologyInjury preventionMedicinePoison controlOccupational safety and healthPsychologyClinical psychologyMedical emergencySocial psychology

Abstract

fetched live from OpenAlex

This study sought to: a) ascertain the effect on rates of violence by varying its operational definition and b) compare characteristics of violent and nonviolent patients. Aggressive behavior was recorded daily for every patient (N = 78) during a 2-year period. Standardized rating scales were used to rate psychopathology and functioning. Almost two thirds of patients were aggressive to others, and 26% violently assaulted another person. Official incident reports underestimated rates of violence to others, self- harm, and property damage. Multivariate predictive models that greatly improved accuracy over base rates showed that violent patients tended to be female, schizophrenic (nonparanoid type), and abusive of alcohol before admission. Violence is more common in treatment resistant psychotic inpatients than suggested by incident reports. Standardized definitions of violence are urged in order to accurately study its prevalence and correlates. Models combining both historical/demographic and clinical data may enhance prediction of violence.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.439

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.311
Teacher spread0.288 · 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 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

Citations43
Published2001
Admission routes1
Has abstractyes

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