Patterns, trends and methodological associations in the measurement and valuation of childhood health utilities
Bibliographic record
Abstract
PURPOSE: To systematically assess patterns and temporal changes in the measurement and valuation of childhood health utilities and associations between methodological factors. METHODS: Studies reporting childhood health utilities using direct or indirect valuation methods, published by June 2017, were identified through PubMed, Embase, Web of Science, PsycINFO, EconLit, CINAHL, Cochrane Library and PEDE. The following were explored: patterns in tariff application; linear trends in numbers of studies/samples and paediatric cost-utility analyses (CUAs) and associations between them; changes in proportions of studies/samples within characteristic-based categories over pre-specified periods; impact of National Institute for Health and Care Excellence (NICE) guidance on primary UK research and associations between valuation method, age and methodological factors. RESULTS: 335 studies with 3974 samples covering all ICD-10 chapters, 23 valuation methods, 12 respondent types and 42 countries were identified by systematic review. 34.0% of samples using indirect methods compatible with childhood applied childhood-derived tariffs. There was no association between numbers of studies/samples and numbers of CUAs. Compared to 1990-2008, 2009-June 2017 saw a significant fall in the proportion of studies using case series; significant compositional changes across ICD-10 chapters and significantly higher sample proportions using childhood-specific and adult-specific indirect valuation methods, and based on pre-adolescents, self-assessment, self-administration and experienced health states. NICE guidance was weakly effective in promoting reference methods. Associations between valuation method, age and methodological factors were significant. CONCLUSION: 1990-2017 witnessed significant changes in primary research on childhood health utilities. Health technology assessment agencies should note the equivocal effect of methodological guidance on primary research.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.337 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".