Development of the Empathy in Romantic Relationships Scale: Validity and Reliability Study
Bibliographic record
Abstract
The present study aimed to develop the Empathy in Romantic Relationships Scale and to examine its psychometric properties to assess empathy skills within romantic relationships. To develop the scale, an extensive literature review was first conducted, resulting in a preliminary pool. Expert opinions were then obtained, and the items were revised accordingly. Data were collected from 504 individuals (293 females, 58.1%; 211 males, 41.9%) who were married (60.1%), engaged (10.1%), or in a dating relationship (29.8%) to conduct an exploratory factor analysis. The results revealed a two-dimensional structure consisting of nine items. These dimensions were identified as Emotional Empathy and Cognitive Empathy. In the second phase, data were gathered from 222 individuals (158 females, 71.2%; 64 males, 28.8%) who were married (34.7%), engaged (18%), or in a dating relationship (47.3%) to perform a confirmatory factor analysis based on the previously obtained structure. Reliability was examined through Cronbach’s alpha internal consistency coefficients and test–retest analyses. In the item analyses, correlations among the items were assessed, and the mean scores of the lower 27% and upper 27% groups were compared using independent samples t-tests. Criterion-related validity was evaluated by calculating Pearson’s product–moment correlation coefficients between the new scale and the Toronto Empathy Scale as well as the Tolerance Tendency Scale. The findings indicated that the Empathy in Romantic Relationships Scale is a valid and reliable instrument for measuring empathy in romantic relationships.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".