The role of feared possible selves in obsessive–compulsive and related disorders: A comparative analysis of a core cognitive self‐construct in clinical samples
Bibliographic record
Abstract
Increasingly, cognitive-behavioural models have been considering the role of beliefs about the self in the development and maintenance of obsessive-compulsive disorder (OCD), including sensitive domains of self-concept and feared self-perceptions. This has led to the development of the Fear of Self Questionnaire (FSQ; Aardema et al., ), which has shown strong internal consistency, divergent and convergent validity, and found to be a major predictor of unwanted thoughts and impulses (i.e., repugnant obsessions). The current study aimed to investigate fear of self-perceptions using the FSQ in an OCD sample (n = 144) and related psychological disorders (eating disorders, n = 57; body dysmorphic disorder, n = 33) in comparison to a non-clinical (n = 141) and clinical comparison group (anxiety/depressive disorders, n = 27). Following an exploratory factor analysis of the scale in the OCD sample, the results showed that participants with OCD in general did not score significantly higher on fear of self-perceptions than did the clinical comparison participants. However, consistent with previous findings, fear of self was highly characteristic among OCD patients with unwanted repugnant thoughts and impulses. In addition, fear of self-perceptions were significantly more elevated in those with eating or body dysmorphic disorders relative to the other non-clinical and clinical groups. The construct of a "feared possible self" may be particularly relevant in disorders where negative self-perception is a dominant theme, either involving concerns about one's inner self or concerns related to perceived bodily faults.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".