Psychometric properties of the brief fear of negative evaluation scale—Straightforward items
Bibliographic record
Abstract
Objectives: The present study evaluated the psychometric properties of the Brief Fear of Negative Evaluation Scale-straightforward items (BFNE-S) within an Italian sample. Specifically, the study was designed to validate the scale factor structure, reliability, concurrent validity, and measurement invariance across sexes. Method: A total of 652 participants (70.71% female and 29.29% males, aged 18-66) completed the BFNE-S and additional related scales including the Social Interaction Anxiety Scale (SIAS), Social Phobia Scale (SPS), Rosenberg Self-Esteem Scale (RSES), Depression Anxiety Stress Scales (DASS-21), and the SCOFF Questionnaire. Confirmatory factor analyses (CFA) were conducted to assess for a unidimensional structure, followed by testing of measurement invariance test between sexes. Reliability was evaluated using Cronbach's alpha and McDonald's Omega, and concurrent validity was tested through correlations with related measures. Results: The CFA supported the unidimensional structure of the BFNE-S with excellent fit indices (CFI = 0.998, RMSEA = 0.058). No measurement invariance violations were observed between sexes, despite their frequencies being slightly unbalanced. The BFNE-S demonstrated excellent internal consistency (Cronbach's α = 0.96, McDonald's ω = 0.97). There were positive correlations among BFNE-S, the SIAS (ρ = 0.67), SPS (ρ = 0.67), as well as with DASS-21 subscales (i.e., depression, anxiety, stress) and SCOFF, and inverse correlations with RSES. Conclusion: The BFNE-S exhibited robust reliability, validity, and measurement invariance across sexes in an Italian sample. Psychometric evidence supports the BFNE-S as a reliable tool for measuring fear of negative evaluation in the nonclinical population, providing a valuable resource for research and clinical assessments.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".