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Record W4407587754 · doi:10.1111/jmft.70009

Is Our Attachment Hurting Us? Unraveling the Associations Between Partners' Attachment Pairings, Negative Emotions During Conflict, and Intimate Partner Violence

2025· article· en· W4407587754 on OpenAlexafffund
Apollonia Helena Pudelko, Brenda Ramos, Marianne Emond, Katherine Péloquin, Marie‐Ève Daspe

Bibliographic record

VenueJournal of Marital and Family Therapy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec-Société et Culture
KeywordsPsychologyDomestic violenceIntervention (counseling)Insecure attachmentAssociation (psychology)AnxietySocial psychologyIntimate partnerDevelopmental psychologyNegative emotionAttachment theoryPoison controlClinical psychologyHuman factors and ergonomicsPsychotherapistMedicineMedical emergencyPsychiatry

Abstract

fetched live from OpenAlex

Attachment insecurities and heightened negative emotions during conflict are significant risk factors for intimate partner violence (IPV). Previous research mainly examined each partner's attachment separately and overlooked negative emotions as a mechanism in the attachment-IPV link. This dyadic observational study conducted among 178 young adult couples examined (1) the interplay between both partners' attachment (i.e., pairings) in association with their IPV perpetration and (2) the contribution of negative emotions during a conflict discussion in these associations. Results revealed that one's avoidance was positively linked with their IPV only when their partner showed low levels of avoidance. One's avoidance was also indirectly associated with their own IPV through their own negative emotions, and to their partner's IPV via their partner's negative emotions. Finally, one's anxiety was indirectly linked with their own IPV through their own negative emotions. Findings support prevention and intervention strategies for IPV that target attachment and negative emotions.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.048
GPT teacher head0.374
Teacher spread0.326 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Marital and Family TherapySame topicIntimate Partner and Family ViolenceFrench-language works237,207