Psychometric Properties of the Reflective Function Questionnaire in Iranian Prisoners
Bibliographic record
Abstract
Reflective functioning is the process of reflecting on the thoughts and feelings of oneself and others and is foundational to healthy human relationships. The 54-item Reflective Function Questionnaire (RFQ) is a self-report measure that assesses reflective functioning, initially developed while studying individuals with borderline personality disorder (BPD) . The purpose of the present study was to translate the RFQ from English to Persian and evaluate its reliability and validity among Iranian prisoners. The sample of this study included 509 (455 men and 54 women) Iranian prisoners. Findings confirm the translated measure had acceptable face and content validity. A confirmatory factor analysis (CFA) confirmed two dimensions of certainty (RFQ-c) and uncertainty (RFQ-u) of reflective functioning. The correlation analysis showed positive relationships between the dimensions of the RFQ and the borderline personality symptoms questionnaire and the emotional dissatisfaction questionnaire. Correlation analysis also showed negative associations between the dimensions of the RFQ and the Toronto Basic Empathy Scale (BES) and the Kentucky Inventory of Mindfulness Skills (KIMS) questionnaire, confirming the concurrent validity of the RFQ. The Cronbach's alphas of the RFQ-c and RFQ-u subscales were .69 and .7 respectively, which demonstrated relatively acceptable internal consistency. The results of the analysis demonstrated that the translated RFQ had desirable psychometric properties for evaluating reflective function among Iranian prisoners.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".