The Experience of Embodiment Scale: An examination of its psychometric properties in women from the Republic of Cyprus
Bibliographic record
Abstract
The Experience of Embodiment Scale (EES) is a recently developed instrument that assesses experiences of living in the body. Here, we prepared a novel Greek translation of the EES and examined its psychometric properties. We initially prepared a Greek translation of the EES using a 5-step procedure recommended for test adaptation studies. Next, in a cross-sectional study, we asked a sample of 933 women from Cyprus to complete the Greek EES, alongside additional, previously validated measures assessing body appreciation, psychological well-being (self-esteem, life satisfaction), eating restriction, perfectionism, and internalisation of appearance ideals. Our analyses showed that EES factorial models based on confirmatory factor analysis (CFA) roundly had poor fit. Conversely, models based on exploratory structural equation modelling (ESEM)-which accounts for the fact that EES items cross-load across factors-had adequate fit to the data. Additionally, we found that both higher-order and bifactor-ESEM models that controlled for the uniqueness of negatively worded items had adequate fit. The bifactor-ESEM model had the best fit of all the models tested, and was invariant across ethnicity (Greeks and Greek-Cypriots) and was unaffected by differential item functioning based on age and body mass index. Additionally, construct validity of the final, optimal model was adequate, especially for its G-factor, as indicated by significant associations with additional constructs in expected directions. These results suggest that a bifactor-ESEM model of the Greek EES has adequate psychometric properties. Our work highlights important psychometric issues relating to the manner in which the EES should (or could) be conceptualised and modelled, which should be considered more fully in future work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".