Parent-report instruments for assessing feeding difficulties in children with neurological impairments: a systematic review
Bibliographic record
Abstract
AIM This study aimed to review the psychometric properties and clinical application of parent-report instruments that assess feeding difficulties in children with neurological impairments. METHOD Papers were identified through five electronic databases based on 15 keywords and were included if they met the following criteria: published in English, described the implementation of parent-report instruments, and included children with neurological impairments (either in the report or a related study population). RESULTS In total, 1220 relevant abstracts were screened and 22 full-text articles were evaluated. The following six parent-report instruments met the inclusion criteria: (1) Screening Tool of Feeding Problems applied to children, (2) Paediatric Eating Assessment Tool, (3) Paediatric Assessment Scale for Severe Feeding Problems, (4) Montreal Children’s Hospital Feeding Scale, (5) Children’s Eating Behaviour Inventory, and (6) Behavioural Paediatric Feeding Assessment Scale (BPFAS). Based on comprehensive psychometric testing and consistently good results, the BPFAS was considered the most valid and reliable instrument. The BPFAS also showed good clinical applicability because it was readily available, required a short administration time, and used a simple scoring system. INTERPRETATION We reviewed the available parent-report instruments for assessing feeding difficulties in children with neurological impairments. The BPFAS had the best psychometric properties and clinical applicability.
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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 | 0.018 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".