Bibliographic record
Abstract
Individuals with health anxiety (HA) frequently believe that they have a serious illness, or may develop a serious illness, despite having no clear medical issues. HA has been found to be comorbid with both obsessive-compulsive disorder (OCD) and generalized anxiety disorder (GAD). Underlying cognitive distortions associated with these disorders may help explain their overlap. One cognitive distortion that has previously been found in OCD and GAD is thought-action fusion (TAF). TAF consists of Likelihood-Self TAF, Likelihood-Other TAF, and Moral TAF. Likelihood TAF is the belief that if you think about an event it will make the event more likely to occur, either to yourself (Likelihood-Self) or to someone else (Likelihood-Other). Moral TAF is the belief that an immoral thought is equivalent to an immoral behaviour. The present study used self-report questionnaires to assess the relationships between HA, OCD, GAD, and TAF in a non-clinical university sample (N=230). Using hierarchical regression analyses, Likelihood-Self TAF, p < .001, and Likelihood-Other TAF p < .001, uniquely predicted HA when controlling for OCD and GAD symptoms. Moral TAF, p = .26, was not a unique predictor of HA. These results indicate that both researchers and clinicians may wish to further explore the role of Likelihood TAF in the development and maintenance of HA. Discipline: Psychology (Honours) Faculty Mentor: Dr. Alexander Penney
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".