Validity and reliability of the EQ-5D-3L™ among a paediatric injury population
Bibliographic record
Abstract
BACKGROUND: Injuries are a leading cause of death and disabilities for children and youth globally. Measuring the health related quality of life of injured children and youth can help gain understanding of the impact of injuries on this population; however, psychometric evaluation of health related quality of life tools among this population is lacking. The purpose of this study was to determine the construct validity of the EQ-5D-3L™ for use among a population of injured young people and to examine the reliability of different modes of administration including paper and pencil, online and telephone. METHODS: In total, 345 participants (aged 0 - 16) were recruited from a paediatric hospital in a large urban centre in British Columbia, Canada. To capture a variety of injury types and severity, patients were recruited from in-patient units and the emergency department. Data were collected at the time of recruitment and at one month post injury. RESULTS: Repeated measures analysis (rANOVA) showed that EQ-5D-3L™ scores were different before and after injury and significant between group differences (Visual Analog Scale: F = 4.61, p = 0.011; Descriptive Scale: F = 29.58, p < 0.001), within group differences (Visual Analog Scale: F = 60.02, p < 0.001; Descriptive Scale: F = 92.37, p < 0.001), and interaction between variables (Visual Analog Scale: F = 10.89, p < 0.001; Descriptive Scale: F = 19.25, p < 0.001) were detected, indicating its suitability for assessment of post-injury health related quality of life. Bland-Altman plots confirmed that few differences existed between modes of administration. CONCLUSION: The EQ-5D-3L™ is an appropriate instrument for collecting health related quality of life data among injured children and can be administered via paper-pencil, online or by telephone.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".