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Record W1588414373 · doi:10.1002/jclp.22115

Rumination and Emotions in Nonsuicidal Self‐Injury and Eating Disorder Behaviors: A Preliminary Test of the Emotional Cascade Model

2014· article· en· W1588414373 on OpenAlexafffund
Alexis E. Arbuthnott, Stephen P. Lewis, Heidi N. Bailey

Bibliographic record

VenueJournal of Clinical Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Guelph
FundersCanadian Institutes of Health Research
KeywordsRuminationPsychologyTraitContext (archaeology)Clinical psychologyDevelopmental psychologyCognitionPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: This study examined relations between repeated rumination trials and emotions in nonsuicidal self-injury (NSSI) and eating disorder behaviors (EDBs) within the context of the emotional cascade model (Selby, Anestis, & Joiner, 2008). METHOD: Rumination was repeatedly induced in 342 university students (79.2% female, Mage = 18.61, standard error = .08); negative and positive emotions were reported after each rumination trial. Repeated measures analyses of variance were used to examine the relations between NSSI and EDB history and changes in emotions. RESULTS: NSSI history associated with greater initial increases in negative emotions, whereas EDB history associated with greater initial decreases in positive emotions. Baseline negative emotional states and trait emotion regulation mediated the relation between NSSI/EDB history and emotional states after rumination. CONCLUSION: Although NSSI and EDBs share similarities in emotion dysregulation, differences also exist. Both emotion dysregulation and maladaptive cognitive processes should be targeted in treatment for NSSI and EDBs.

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 score0.011
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.073
GPT teacher head0.447
Teacher spread0.374 · 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

Citations51
Published2014
Admission routes2
Has abstractyes

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