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Record W4225830001 · doi:10.1186/s40337-022-00541-w

Psychometric comparison of the Persian Salzburg Emotional Eating Scale and Emotional Eater Questionnaire among Iranian adults

2022· article· en· W4225830001 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Eating Disorders · 2022
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyConfirmatory factor analysisScale (ratio)PersianReliability (semiconductor)Content validityConstruct validityValidityClinical psychologyPsychometricsApplied psychologyStructural equation modelingStatisticsPower (physics)

Abstract

fetched live from OpenAlex

BACKGROUND: The Salzburg Emotional Eating Scale (SEES) and the Emotional Eater Questionnaire (EEQ) are self-reported measures developed to evaluate emotional eating in adults in Western countries. To date, the psychometric properties of the SEES and the EEQ have not been studied among Iranian adults. The aim of the current study is to translate the SEES and the EEQ from English to Persian and examine the psychometric properties of the SEES and EEQ. METHOD: The sample of this study comprised of 489 Iranian adults who completed the SEES and the EEQ questionnaires online. RESULTS: Findings of face, content, and construct validity tests confirmed that the SEES and the EEQ had acceptable validity and appropriate reliability. The results from confirmatory factor analysis showed acceptable goodness-of-fit indices for two measures. CONCLUSION: Results of Average Variance Extracted, Construct Reliability, and goodness-of-fit indices showed that the SEES was better for evaluating emotional eating among Iranian adults than the EEQ.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.293
Teacher spread0.279 · 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