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Record W2011617645 · doi:10.1037/a0014826

Non-suicidal self-injury and eating pathology in high school students.

2009· article· en· W2011617645 on OpenAlexaff
Shana Ross, Nancy L. Heath, Jessica R. Toste

Bibliographic record

VenueAmerican Journal of Orthopsychiatry · 2009
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologyEating disordersClinical psychologyInjury preventionSuicide preventionPoison controlPsychiatryImpulse (physics)NorwegianDistrustMedicinePsychotherapistMedical emergency

Abstract

fetched live from OpenAlex

Although past research has explored self-injurious behaviors and disordered eating among adults in clinical settings, little research has been conducted examining nonsuicidal self-injury (NSSI) and eating pathology in community samples of adolescents. Four hundred and 40 students were screened for the presence of NSSI; a prevalence rate of 13.9% was found. Those who indicated that they engaged in NSSI (n = 59) and a comparison group of non-self-injurers (n = 57) completed the Eating Disorders Inventory. Results indicate that students who engage in NSSI display significantly more eating pathology than their non-NSSI peers, including poor interoceptive awareness; difficulties with impulse regulation; an increased sense of ineffectiveness, distrust, and social insecurity; and increased bulimic tendencies and body dissatisfaction. Relationships were found between increased lifetime frequency of NSSI behaviors and poor impulse control and deficits in affective regulation. In addition, adolescents who had stopped self-injuring reported comparable rates of eating pathology as did adolescents who continued to self-injure. The theoretical connection between NSSI and eating pathology are discussed with reference to enhancing knowledge regarding the characteristics of NSSI.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.301
Teacher spread0.295 · 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

Citations159
Published2009
Admission routes1
Has abstractyes

Explore more

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