Measure of Early Vision Use: development of a new assessment tool for children with cerebral palsy
Bibliographic record
Abstract
Purpose To report the development of an assessment tool to describe “how vision is used” for children with cerebral palsy.Method Measurement development consisted of three steps: (i) an online survey to explore the relevance and comprehensiveness of visual behaviours identified in a previous conceptualisation study; (ii) construction of items and a rating scale for the new measure; and (iii) cognitive interviews to explore comprehensibility and refine the measure in preparation for field testing. Survey respondents were 130 parents of children with cerebral palsy, eight adults with cerebral palsy, and 108 clinicians (n = 246). Nine parents participated in the interviews.Results The new tool, the Measure of Early Vision Use, is a 14-item descriptive measure of typical performance of visual behaviours observable in everyday activities, as rated by parent/caregiver observation. Each item is rated on a 4-point ordinal scale.Conclusions This new measure is conceptually grounded within the Activity level domain of the International Classification of Functioning, Disability and Health as a measure of a single visual ability construct. The target population is children with cerebral palsy, and using parent report the Measure of Early Vision Use describes both strengths and limitations in using vision. This study addressed the selection of items and response options for the new scale, and provides evidence to support content relevance, comprehensiveness and comprehensibility from key stakeholders. Further research will explore psychometric properties and clinical utility.Implications for rehabilitationThe ability to use vision in daily activities is relevant to the development and learning of all children, so the availability of a method for describing visual abilities has potential for diverse research and clinical purposes.The Measure of Early Vision Use is a parent-report tool that provides a criterion-referenced method for quantifying and describing how children use vision in typical daily activities to support intervention planning.Clinicians and parents wishing to measure vision use in children with cerebral palsy can be confident about the rigorous methods used to develop this tool, including consultation with key stakeholders.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".