Cross‐cultural adaptation and validation of the Italian version of the Montreal Children's Hospital Feeding Scale in a special healthcare needs population
Bibliographic record
Abstract
BACKGROUND: The Montreal Children's Hospital Feeding Scale (MCH-FS) allows paediatricians and other health care professionals to identify feeding difficulties among children. AIM: To translate and adapt the MCH-FS into Italian, and to evaluate the validity and reliability of this Italian version of the Montreal Children's Hospital Feeding Scale (I-MCH-FS). METHODS & PROCEDURES: A total of 150 children with special healthcare needs were admitted to the Rare Disease Unit of the Paediatrics Department at the Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy, between March 2021 and March 2022 (74 males; mean age = 3.85 ± 1.96 years; median age = 4 years; age range = 6 months-6 years and 11 months) and 150 healthy participants (83 males; mean age = 3.5 ± 1.98 years; median age = 3 years; age range = 6 months-6 years and 11 months) were included in the study, which was approved by the local ethics committee. The original version of the MCH-FS was translated and cross-cultural adapted through five stages: (1) initial translation, (2) synthesis of the translations, (3) back translation, (4) expert committee and (5) test of the prefinal version. Test-retest reliability and internal consistency were assessed using Pearson r, Spearman r and Cronbach's alpha, respectively. Construct validity was established by comparing data obtained from patients with those of healthy participants using the Mann-Whitney U-test. OUTCOMES & RESULTS: A Pearson r of 0.98, a Spearman r of 0.95 and Cronbach's alpha value of 0.86 were obtained. In the clinical group, 40.6% children were classified as having feeding disorders (n = 61), while in the normative group 4.7% were diagnosed with feeding problems (n = 7). Mean total score of the clinical group was significatively different from the normative's. CONCLUSIONS & IMPLICATIONS: The I-MCH-FS is a valid and reliable one-page, quick screening tool used to identify feeding disorders among children with special needs in outpatient paediatric setting. WHAT THIS PAPER ADDS: What is already known on the subject The MCH-FS is a valid and reliable parent-report measure aimed at discriminating between children presenting or not feeding disorders. What this paper adds to existing knowledge This paper presents the translation and cross-cultural adaptation of the scale into the Italian language. What are the potential or actual clinical implications of this work? The Italian version of the MCH-FS can be used in the special healthcare needs population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".