Disorder Relevant or Disorder Specific: Measuring Fear of Losing Control in Relation To the Experience of Anxiety and Related Issues
Bibliographic record
Abstract
Abstract Objectives Research suggests fear of losing control may play a role in multiple anxiety disorders. However, the question of disorder specificity versus disorder relevance has not been examined in fear of losing control. Focusing on cognitive factors related to the experience of OCD and panic disorder, this study aimed to develop an extended questionnaire—the Fear of Losing Control Inventory (FOLCI)—that taps into potentially disorder-specific aspects of feared loss of control. Methods A pool of potential FOLCI items was administered to a non-clinical sample ( n = 603), along with the existing Beliefs About Losing Control Inventory-II (BALCI-II) and other psychological measures. FOLCI and BALCI-II items were subjected to exploratory factor analyses. Exploratory regression analyses examined the relationship between FOLCI and BALCI-II subscales, and symptoms of psychopathology. Results Six factors were derived, accounting for 71.25% of variance: ‘Agent of Harm’, ‘Thoughts and Feelings’, ‘Self-appraisals’, ‘Timeframe’, ‘Bodily Sensations’ and ‘Escape and Avoidance’. In exploratory regression analyses, the FOLCI and BALCI-II were significant predictors of symptoms of OCD, panic, generalized anxiety, depression and functional impairment, as was the FOLCI’s Thoughts and Feelings subscale, and the BALCI-II’s inflated beliefs about Probability/Severity subscale. Conclusions Fear of losing control may be relevant across anxiety disorders, and possibly in depression too. Exploratory analyses suggest fear of losing control of thoughts and feelings, and inflated beliefs about the probability and severity of loss of control, are potentially transdiagnostic. Possible domains of disorder specificity include fear of losing control of bodily sensations, and the timeframe within which a catastrophe would occur following a feared loss of control.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".