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Record W4414384798 · doi:10.22215/cujs.v5i2.5378

Stress, Relationship Satisfaction, and the Moderating Role of Self-Esteem

2025· article· en· W4414384798 on OpenAlexaff
Cheryl Harasymchuk

Bibliographic record

VenueCarleton undergraduate journal of science. · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPsychosocial Factors Impacting Youth
Canadian institutionsCarleton University
Fundersnot available
KeywordsContingencyMirroringRomanceStress (linguistics)Quality (philosophy)Positive relationshipInterpersonal relationshipLife satisfaction

Abstract

fetched live from OpenAlex

Stress is a mental and physical reaction experienced whenever one faces demands believed to exceed their current resources. Operationalized, perceived stress is “a psychological state reflecting an individual’s evaluation of life events as uncontrollable, unpredictable, and overwhelming”(Gniewosz, 2024, p. 1). According to Karney and Bradbury’s (1995) Vulnerability-Stress-Adaptation model, individual differences, such as self-esteem, and past experiences can play a role in shaping relationship quality under stress. Self-esteem, an individual difference trait, refers to one’s overall evaluation of self-worth which for some can be tied into romantic relationship content (i.e. relationship contingency of self-worth). The current study assessed the link between perceived stress and relationship satisfaction with relationship contingency of self-worth as a moderator. A community sample of individuals (N = 257) who were involved in a romantic relationship, completed weekly measures of perceived stress and relationship quality over six weeks of pandemic lockdown in spring 2020. Mirroring previous research, stress was found to be negatively associated with relationship satisfaction. However, contrary to the hypothesis, relationship contingency of self-worth did not significantly moderate the association. Surprisingly, there was evidence of positive correlation between relationship contingency of self-worth and relationship satisfaction that future research could explore.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.305
Teacher spread0.291 · 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 designTheoretical or conceptual
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 routes1
Has abstractyes

Explore more

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