15 Ranking and rating severity: stakeholder perspectives of neurodevelopmental impairment after preterm birth
Bibliographic record
Abstract
Abstract Background Children born very preterm are at increased risk of neurodevelopmental impairment (NDI). NDI rates are used to make critical healthcare decisions. The Canadian Neonatal Follow-Up Network (CNFUN) defines severe NDI at age 18–24 months as Bayley-III Cognitive, Motor or Language composite scores <70, need for hearing aids or cochlear implants, bilateral visual impairment or non-ambulatory cerebral palsy (Gross Motor Classification System level 3 or higher). This definition was developed using the perspectives of clinicians and scientists. Stakeholders including parents/caregivers, persons born preterm and community partners have never been asked how they categorize disabilities and rank different impairments. Objectives To evaluate stakeholder perspective of severity of disability and ranking of different health conditions all defined as severe by CNFUN using clinical vignettes. Design/Methods Ten clinical vignettes describing 18 month old children with combinations of single and multiple impairments based on the CNFUN definition of severe NDI and one clinical vignette describing a child without NDI (control) were co-developed by clinicians and parents. The survey of 11 vignettes was distributed to: (1) British Columbian parents of very preterm children during follow-up clinic visits; and (2) Canadian and international parents, families, individuals with lived experience with prematurity and/or NDI and their social networks using a snowball sampling technique. Participants rated the severity of each vignette on a scale from 0 (worst possible health) to 10 (best possible health) and answered if they perceived the vignette to represent a severe disability. Results were analyzed descriptively and mean differences from the control were compared using a linear mixed effects model. Results 827 participants and 4553 vignettes were completed with no significant difference by population sampled. Participants classified the clinical vignettes as describing a severe condition ranging from 5% for the cognitive delay vignette to 55% for the cerebral palsy and language delay vignette. Mean difference in rank compared to control is shown in Figure 1. Only the ranking of the latter vignette was significantly different from the control. Conclusion Most key stakeholders do not perceive clinical vignettes describing CNFUN definitions of severe NDI as truly severe. Components of severe NDI rank differently but only the cerebral palsy and language delay vignette varies significantly. Current CNFUN definitions of severe NDI need to be revised.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".