Generic preference‐based health‐related quality of life in children with neurodevelopmental disorders: a scoping review
Bibliographic record
Abstract
AIM: To describe how generic preference-based health-related quality of life (HRQoL) instruments have been used in research involving children with neurodevelopmental disorders (NDD). METHOD: A systematic search of nine databases identified studies that used generic preference-based HRQoL instruments in children with NDD. Data extracted following the Preferred Reporting Items for Systematic Review and Meta-Analyses extension for Scoping Review guidelines included type of NDD, instrument used, respondent type, justification, and critical appraisal for these selections. RESULTS: Thirty-six studies were identified: four cost-utility analyses; 15 HRQoL assessments; five economic burden studies; three intervention studies; and nine 'other'. The Health Utilities Index (Mark 2 and Mark 3) and EuroQoL 5D (EQ-5D; three-level EQ-5D, five-level EQ-5D, and the youth version of the EQ-5D) instruments were most frequently used (44% and 31% respectively). The relatively low use of these instruments overall may be due to a lack of psychometric evidence, inconsistency in justification for and lack of clarity on appropriate respondent type and age, and geographical challenges in applying preference weights. INTERPRETATION: This study highlights the dearth of studies using generic preference-based HRQoL instruments in children with NDD. The use of cost-utility analysis in this field is limited and validation of these instruments for children with NDD is needed. The quality of data should be considered before guiding policy and care decisions. WHAT THIS PAPER ADDS: Limited use of generic preference-based health-related quality of life (HRQoL) instruments in studies on children with neurodevelopmental disorders. Only 11% of studies were cost-utility analyses. Inconsistencies in justification for choosing generic preference-based HRQoL instruments and respondent types.
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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 | 0.030 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".