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Record W2625657956 · doi:10.1093/schbul/sbx079

Aggressive Behavior Among Persons With Schizophrenia and Those Who Are Developing Schizophrenia: Attempting to Understand the Limited Evidence on Causality

2017· review· en· W2625657956 on OpenAlexaff
Sheilagh Hodgins

Bibliographic record

VenueSchizophrenia Bulletin · 2017
Typereview
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversité de MontréalHôpital Louis-H Lafontaine
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Causality (physics)PsychologyJuvenile delinquencyPsychiatryPsychosisCommitClinical psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

People with, and those who are developing, schizophrenia are at increased risk to engage in aggressive behavior (AGB). Some incidents lead to criminal prosecution. Most people with schizophrenia who commit crimes engage in delinquency and/or AGB prior to first episode. A large proportion of these individuals have a history of childhood conduct disorder (CD) and brain abnormalities suggestive of abnormal neural development distinctive from that of others with schizophrenia. Factors contributing to schizophrenia that is preceded by CD include failing to learn not-to-behave aggressively in early childhood, impairments in understanding emotions in the faces of others, maltreatment, and subsequent re-victimization. Others with no history of antisocial behavior begin engaging in AGB as positive symptoms increase and illness onsets. They too are at elevated risk to be victimized. Specific genetic variants linked to stress regulation in combination with adversity have been associated both with AGB and psychotic symptoms. Effectively treating conduct problems and preventing victimization would reduce AGB by persons with schizophrenia.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.002

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 head0.171
GPT teacher head0.397
Teacher spread0.226 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations57
Published2017
Admission routes1
Has abstractyes

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