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Record W2951907194

Health Anxiety and Disordered Eating

2018· article· en· W2951907194 on OpenAlexaff
Christine O’Brien

Bibliographic record

VenueStudent Research Proceedings · 2018
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsMacEwan University
Fundersnot available
KeywordsWorryAnxietyPsychologyEating disordersDisordered eatingCognitionClinical psychologyPsychiatryDevelopmental psychology
DOInot available

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.238
GPT teacher head0.578
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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