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Record W1999330676 · doi:10.1080/14999013.2012.667513

Non-Suicidal Self-Injury Within Offender Populations: A Systematic Review

2012· review· en· W1999330676 on OpenAlexaff
Katherine L. Dixon–Gordon, Natalie A. Harrison, Ronald Roesch

Bibliographic record

VenueInternational Journal of Forensic Mental Health · 2012
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPsychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Non-suicidal self-injury (NSSI), defined as deliberate self-directed tissue damage, presents a serious health concern for offender populations. Approximately one-third of offenders report a history of NSSI, and it is the most common reason for mental health treatment within correctional settings. To date, no review exists with a specific focus on NSSI in criminal justice contexts. Therefore, the primary aim of this article is to review research on NSSI within correctional settings. Specifically, we explore the role of risk factors for NSSI. We also examine the functions of NSSI within correctional contexts. In addition, we evaluate the evidence for potential assessment tools and treatments for NSSI. Taken together, our review suggests that risk factors for NSSI must be considered differently in correctional settings, due to the high base rates of these vulnerabilities. Further, although environmental control is a more salient function of NSSI within correctional settings, the primary motive for engaging in this behavior remains emotion regulation. Finally, despite the emergence of several promising treatments for NSSI within correctional settings, larger scale studies are necessary to determine the efficacy of these interventions.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.120
GPT teacher head0.451
Teacher spread0.331 · 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 designSystematic review
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

Citations132
Published2012
Admission routes1
Has abstractyes

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