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Record W7111833574

Investigating the Potential Contributors to Non-Suicidal Self-Injury: Stress, Emotional Dysregulation, and Alexithymia

2009· article· en· W7111833574 on OpenAlexaboutno aff

Bibliographic record

VenueUNI ScholarWorks (University of Northern Iowa) · 2009
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaEmotional dysregulationToronto Alexithymia ScaleStress (linguistics)Emotional regulationEmotional intelligence
DOInot available

Abstract

fetched live from OpenAlex

Research has investigated perceived stress, non-suicidal self-injury (NSSI), emotional dysregulation, and alexithymia independently. However, there have been no studies to date that have simultaneously examined the relationship among all these variables. The purpose of this study was to examine these variables among those who had or had not engaged in NSSI. Five hundred seventy-seven college students completed self report measures of non-suicidal self-injury, perceived stress level, emotional dysregulation, and alexithymia. As hypothesized, those who had engaged in self-harm behaviors reported higher levels of perceived stress, emotional dysregulation, and alexithymia. There were no gender differences except on perceived stress levels, where women reported a greater level of stress than men. As hypothesized, there was a significant positive correlation between alexithymia and perceived stress. Contrary to the hypothesis, the emotional dysregulation and alexithymia scales were strongly correlated. Lastly, emotional dysregulation was found to be the best predictor of group classification (had ever engaged in self-harm or not), followed by perceived stress, and lastly alexithymia. Further implications are discussed.

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)0.000
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 score0.025
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.233
Teacher spread0.224 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

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