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Record W2602579003 · doi:10.1093/schbul/sbx021.287

209. Risk of Violence in Attenuated Psychosis Symptoms Syndrome and its Relationship With Symptomology

2017· article· en· W2602579003 on OpenAlexaff
Heline Mirzakhanian, Sandra Sanchez, Jean Addington, Carrie E. Bearden, Tyrone D. Cannon, Barbara A. Cornblatt, Daniel H. Mathalon, Thomas H. McGlashan, Diana O. Perkins, Larry J. Seidman, Ming T. Tsuang, Elaine F. Walker, Scott W. Woods, Kristin S. Cadenhead

Bibliographic record

VenueSchizophrenia Bulletin · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychosisPsychiatryMedicinePoison controlInjury preventionSuicide preventionSchizophrenia (object-oriented programming)Clinical psychologyHuman factors and ergonomicsRisk assessmentPsychologyMedical emergency

Abstract

fetched live from OpenAlex

Background: Contrary to popular belief the majority of patients with schizophrenia will never commit an act of severe violence. Highest risk for violent offending appears to be during the first episode of psychosis (FEP), a meta-analysis by Large and Nielssen (2010) reporting that about a third of patients in the FEP exhibited some violent behavior before initial treatment. However, most acts involve minor violence and fewer than 1 in 100 patients committed assaults resulting in serious injury. Risk of violence in clinical high risk populations, those with attenuated psychosis symptoms (APS) remains unexplored although recent findings by Marshall and colleagues (2016) suggest that a significant amount of APS involve violent content although most is self-directed violence. The aim of the current study was to explore risk of violence in individuals with attenuated psychosis symptom syndrome (APSS). We were also interested to investigate whether risk of violence as assessed was associated with symptomology. Methods: The Structured Assessment of Violence Risk in Youth (SAVRY) was completed for 285 individuals who met criteria for APSS as well as 44 Healthy Controls. The SAVRY is a clinician rated assessment tool and provides a clinical risk rating for each individual by assessing multiple domains including Historical Risk Factors, Social/Contextual Risk Factors, and Individual/Clinical Factors. Results: Violence risk was significantly different between the two groups with healthy controls assessed to be at a lower risk than individuals in the attenuated psychosis symptoms group, χ2(2) = 13.03, P < .001. Only 2 of the APSS group and none of the healthy controls were rated to be at high level of risk for violence. Violence risk was not different between men and women, χ2(2) = 4.58, P = 1.01. A between-group ANOVA conducted to compare severity of attenuated psychotic symptoms and risk of violence within the APSS group showed that symptom severity was significantly different across levels of violence risk, F(2, 235) = 6.32; P < .002. This was largely driven by negative symptoms severity. Individuals with low risk for violence as compared to moderate level of violence risk had lower negative symptoms, F(2, 235) = 13.42; P < .000. Severity of positive, disorganized, or general symptoms independently did not differ across levels of violence risk. This relationship remained unchanged when income level was adjusted. Level of income, age, ethnicity, or parental education was not associated with level of risk. Conclusion: To our knowledge this is the first study to assess violence risk in individuals with APSS. While, the APSS group was assessed to be at a higher risk for violence as compared to healthy controls, the majority were judged to be at a moderate risk and high risk ratings were rare. In the APSS group higher risk was associated with symptoms. Specifically, results suggest that negative symptoms uniquely contribute to risk 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.279
Teacher spread0.263 · 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.

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

Citations1
Published2017
Admission routes1
Has abstractyes

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