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Record W2604675417 · doi:10.1111/jora.12312

Profiles of Emotion Deficits and Adolescent Nonsuicidal Self‐Injury in an Inpatient Sample

2017· article· en· W2604675417 on OpenAlexaff
Kristel Thomassin, Elise Quint, Sage Sezlik, Anne Shaffer

Bibliographic record

VenueJournal of Research on Adolescence · 2017
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAngerSadnessPsychologyClinical psychologyEmotional dysregulationDepressive symptomsPsychiatryAnxiety

Abstract

fetched live from OpenAlex

This study examined profiles of specific emotion deficits, including poor emotion awareness, reluctance to express emotion, sadness inhibition and dysregulation, and anger inhibition and dysregulation. Self-report questionnaires assessed adolescents' emotion skills and nonsuicidal self-injury (NSSI) engagement, frequency, severity, methods, and age of onset. Latent profile analysis yielded a three-profile solution: Low Deficit (LD; n = 49), Unaware/Anger Dysregulated (UAD; n = 24), and Anger Inhibited (AI; n = 20) profiles. Adolescents in the UAD profile were more likely to engage in NSSI, displayed a higher NSSI frequency, and reported a higher number of NSSI methods when compared to adolescents in the LD profile. No links emerged for NSSI severity or age of onset.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.127
GPT teacher head0.450
Teacher spread0.323 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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