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Record W4414970817 · doi:10.1111/pere.70033

Do Crushes Pose a Problem for Exclusive Relationships? Trajectories of Attraction Intensity to Extradyadic Others and Links to Primary Relationship Commitment and Satisfaction

2025· article· en· W4414970817 on OpenAlexafffund
Lucia F. O’Sullivan, Charlene F. Belu, Lucía Tramonte

Bibliographic record

VenuePersonal Relationships · 2025
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of New Brunswick
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAttractionRomanceQuality (philosophy)Cluster (spacecraft)Sexual attraction

Abstract

fetched live from OpenAlex

ABSTRACT This study examined individuals who had an active agreement to be exclusive with their relationship partner but who also reported romantic or sexual attraction to someone outside of their relationship (a “crush”). We tracked participants over time, measuring attraction intensity and relationship quality, to help clarify when an extradyadic attraction might challenge the quality of the primary relationship in some way. Of 567 individuals ( M age = 28.52; 55.4% women; 82.2% heterosexual) who reported an extradyadic attraction, 172 (30.3%) completed all assessments and maintained their primary relationship over a one‐year period. We used HLM and cluster analysis to examine patterns of associations among these 172 participants and to capture typologies for extradyadic attraction. Overall, many harbor attraction to people outside of their relationship with no corresponding harms noted in that primary relationship, regardless of whether that attraction varied or was stable in its target. However, some had extradyadic attractions that were linked to decreases in primary relationship romantic and sexual satisfaction over time, especially among those whose relationship quality was lower at baseline. The findings have implications for researchers, counselors, and educators invested in supporting couples and for understanding relationship maintenance processes generally.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.090
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.066
GPT teacher head0.375
Teacher spread0.309 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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