Bibliographic record
Abstract
Health anxiety (HA) describes worry about one’s health, and can range on a continuum from mild to severe. For example, someone with severe HA might be convinced a headache is indicative of a brain tumour. They may continue to have this belief despite medical reassurance that they do not have a tumour. The DSM defines eating disorders (ED) as an impairment in functioning caused by a disturbance in eating, which leads to the altered consumption of food. Previous research has found increased body checking behaviours in ED and HA when compared to healthy controls. However, there is a lack of research looking at other important cognitive factors in individuals high in both HA and ED. The present study will compare four groups, those high in only HA, those high in only ED behaviours, those high in both HA and ED behaviours, and a control group of those low in both HA and ED behaviours. This study will first explore if the groups report different levels of body checking behaviours. The second factor to be explored is metacognitive beliefs, which are the positive or negative beliefs people have about their thinking. Finally, the study will examine differences in intolerance of uncertainty, which is when an individual has negative beliefs surrounding uncertain situations. Past research has shown that both those with HA and ED have reported high levels of these factors, though research has not looked at levels of these factors when someone is high in both HA and ED. 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 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".