Development and validation of the multidimensional version of the fear of self questionnaire: Corrupted, culpable and malformed feared possible selves in obsessive–compulsive and body‐dysmorphic symptoms
Bibliographic record
Abstract
In recent years, cognitive-behavioural models of OCD have increasingly recognized the potential role of feared possible selves in the development and maintenance of OCD, while simultaneously re-examining factors that have historically been linked to self-perceptions in OCD. The current article describes the development and validation of a multidimensional version of the Fear of Self Questionnaire (FSQ-EV) in a non-clinical (N = 626) and clinical OCD sample (N = 79). Principal component analyses in the non-clinical sample revealed three conceptually and factorially distinct components revolving around a feared corrupted possible self, a feared culpable possible self and a feared malformed possible self. The questionnaire showed a strong internal inconsistency, and good divergent and convergent validity, including strong relationships to obsessional symptoms. In particular, the corrupted feared self predicted OCD symptoms independently from depression and other related self-constructs and obsessive beliefs, while also strongly interacting with importance and control of thoughts in the prediction of almost all specific symptoms of OCD. Results are consistent with the notion that self-constructs can be conceptually and empirically distinguished from obsessive beliefs and appraisals with significant potential to improve our understanding of OCD and related disorders.
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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 | 0.010 | 0.016 |
| 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 | 0.001 |
| 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".