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Record W4225865355 · doi:10.1002/jclp.23359

Daily associations of interpersonal and emotional experiences following stressful events among young adults with and without nonsuicidal self‐injury

2022· article· en· W4225865355 on OpenAlexafffund
Christopher R. Berghoff, Katherine L. Dixon–Gordon, Alexander L. Chapman, Margaret M. Baer, Brianna J. Turner, Matthew T. Tull, Kim L. Gratz

Bibliographic record

VenueJournal of Clinical Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of VictoriaSimon Fraser University
FundersCanadian Institutes of Health ResearchCanadian HIV Trials Network, Canadian Institutes of Health Research
KeywordsPsychologyInterpersonal communicationClinical psychologyInterpersonal relationshipInjury preventionPopulationYoung adultPoison controlSuicide preventionHuman factors and ergonomicsDevelopmental psychologyMedicineSocial psychologyMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVES: Emotional and interpersonal dysfunction appears central to nonsuicidal self-injury (NSSI), yet research examining the interplay of these factors among individuals with NSSI is limited. This study aimed to specify such associations before and after daily stressful events among individuals with (vs. without) NSSI. METHODS: = 20.4) with past-year (n = 56) or no history (n = 47) of NSSI completed daily diary assessments over a 2-week period. RESULTS: No differences in rates of positive or negative interpersonal experiences before or after stressful events were identified. NSSI participants, however, reported greater negative emotion following stressful events compared with non-NSSI participants. The presence (vs. absence) of a positive interpersonal experience following a stressful event was related to lower negative emotional responses only in the NSSI group. CONCLUSION: Positive interpersonal experiences may downregulate negative emotions following stressful events among individuals with NSSI, highlighting the potential relevance of interpersonal emotion regulation to this population.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.065
GPT teacher head0.439
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

Citations10
Published2022
Admission routes2
Has abstractyes

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