Measuring Anxiety in the Pediatric Emergency Department
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to evaluate the agreement between the State Trait Anxiety Inventory (STAI) and other anxiety scales to determine whether these shorter to administer scales could replace the STAI. METHODS: This was a prospective cohort study on a convenience sample of children, aged 9 to 17 years, presenting to a pediatric emergency department. Patients were divided into 2 groups: preteens (PT) (aged 9-12 years) completed the pediatric STAI and teens (T) (aged 13-17 years) completed the adult STAI. Participants also completed a visual analog scale (0-100 mm), a Likert scale (1-5), and a short version of the STAI. Intraclass correlation (2-way mixed model, average measures) was used to evaluate agreement between the STAI and the other scales. A sample size of 100 patients per group was estimated as sufficient. RESULTS: The median (interquartile range) STAI state anxiety scores were 33 (28.25-36.75) and 37.5 (32-44), in the PT (n = 100) and T (n = 100) groups, respectively. The median (interquartile range) STAI trait anxiety scores were 33.5 (28-38.75) and 36 (31-44), in the PT and T groups, respectively. Agreements between the STAI and the other scales were poor for all scales. At best, the intraclass correlation was 0.71 for the agreement between the STAI and the short version of the STAI. CONCLUSIONS: There appears to be poor agreement between the STAI and the other scales designed to measure anxiety in children 9 to 17 years presenting to the pediatric emergency department.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".