Health Anxiety in Children: Development and Psychometric Properties of the Childhood Illness Attitude Scales
Bibliographic record
Abstract
The course of severe anxiety surrounding health issues is unknown. The available literature suggests that adults who are overly anxious about health issues often interpret or misinterpret their bodily signs and symptoms to be indicative of a serious illness. The construct of health anxiety has not been examined in children and, to date, there has not been an instrument developed for this purpose. The Illness Attitude Scales is one of the most commonly used instruments for evaluating fears, beliefs, and attitudes that are associated with hypochondriasis and abnormal illness behaviour in adults. We sought to adapt the Illness Attitude Scales for use with children ages 8-15 years. The adapted Illness Attitude Scales was renamed the Childhood Illness Attitude Scales. Revisions to the adult version consisted of simplification of language, revision of Likert scale (i.e. 5-point to 3-point scale), and the addition of 7 questions to evaluate the role parents/guardians play in facilitating medical attention or treatment. Correlations between Childhood Illness Attitude Scales total scores and other self-report measures were supportive of the construct-related validity of the Childhood Illness Attitude Scales and suggested that it is a useful measure of health anxiety in school-age children. Practical and theoretical implications of the present results 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".