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Record W2605985598 · doi:10.1017/s0954579417000050

Preoccupied but not dismissing attachment states of mind are associated with nonsuicidal self-injury

2017· article· en· W2605985598 on OpenAlexaff
Jodi Martin, Jean‐François Bureau, Marie‐France Lafontaine, Paula Cloutier, Celia Hsiao, Dominique Pallanca, Paul Meinz

Bibliographic record

VenueDevelopment and Psychopathology · 2017
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsWestern UniversityCentre Hospitalier Universitaire Sainte-JustineChildren's Hospital of Eastern OntarioUniversity of OttawaYork University
Fundersnot available
KeywordsPsychologySelf-destructive behaviorClinical psychologyPsychoanalysisPoison controlInjury preventionDevelopmental psychologyMedical emergency

Abstract

fetched live from OpenAlex

In this investigation the factor structure of the Adult Attachment Interview was studied in a partially at-risk sample of 120 young adults. More specifically, 60 participants had engaged in nonsuicidal self-injury (NSSI; 53 females, M age = 20.38 years), and 60 were non-self-injuring controls matched by age and sex. Theoretically anticipated differential associations between preoccupied (but not dismissing) states of mind and NSSI were then examined. Exploratory factor analyses identified evidence for two weakly correlated state of mind dimensions (i.e., dismissing and preoccupied) consistently identified in factor analyses of normative-risk samples. As hypothesized, results further showed that preoccupied (but not dismissing) states of mind were associated with NSSI behavior. Findings support existing arguments suggesting that the regulatory strategy adults adopt when discussing attachment-related experiences with primary caregivers, particularly passive, angry, or unresolved discourse patterns, is uniquely correlated with 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.037
GPT teacher head0.327
Teacher spread0.290 · 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.

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

Citations17
Published2017
Admission routes1
Has abstractyes

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