A Multimethod Investigation of Beliefs about Losing Control in Anxiety-Related Disorders
Bibliographic record
Abstract
Maladaptive beliefs are proposed to be critical in the development and maintenance of anxiety-related disorders. One commonly reported maladaptive belief domain concerns negative beliefs people hold about losing control. These concerns about the likelihood and consequences of losing control over one’s behaviour, thoughts, emotions and/or physical reactions appear to be prevalent in clinical and non-clinical samples. This program of research aimed to better assess, define and delineate the nature of these beliefs using a multi-method approach. In Study 1, undergraduate psychology students (N = 126) were given false feedback that they were either at high or low risk of losing control, and then completed a social interaction task with an actor. The belief that one was at high risk of losing control led to greater anticipatory anxiety leading up to the social interaction task, significant doubt about one’s social performance and significantly more negative post-event processing. In Study 2, an unselected sample of undergraduate participants (N = 21), half of whom met criteria for one or more anxiety-related disorders, was interviewed about their beliefs about losing control. Losses were defined as negative, multifaceted cognitive-behavioural phenomena which included thoughts, behaviours and emotions. Common consequences were perceived harm to oneself or others, powerlessness, and unpleasant emotions during (e.g., sadness, frustration, anxiety) and following (e.g., regret, shame, humiliation) a reported loss of control. In Study 3, undergraduate students (N = 440) completed an expanded set of items designed to better measure maladaptive beliefs about losing control, leading to the assessment of the Beliefs About Losing Control Inventory, Second Edition (BALCI-II). An exploratory factor analysis indicated the BALCI-II captured several domains of feared consequences of losing control: 1) overwhelming emotions 2) dangerous behaviour and 3) madness and 4) inflated beliefs about probability/severity of those losses. The BALCI-II was found to be psychometrically sound and predictive of symptoms of OCD and SAD, above and beyond existing disorder-specific maladaptive beliefs. Implications for cognitive theory and therapy are discussed.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".