Stress, Relationship Satisfaction, and the Moderating Role of Self-Esteem
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".