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Record W1854998665

The Thai version of the Montreal Children's Hospital Feeding Scale (MCH-FS): psychometric properties.

2015· article· en· W1854998665 on OpenAlexaboutno aff
Banchaun Benjasuwantep, Suthee Rattanamongkolgul, Maria Ramsay

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCronbach's alphaAnthropometryScale (ratio)PediatricsInternal consistencyPsychometricsClinical psychologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To standardize and evaluate the psychometric properties of the Thai version of the Montreal Children's Hospital Feeding Scale (MCH-FS). MATERIAL AND METHOD: The MCH-FS was translated and the cultural effects of the Thai version (Thai.MCH-FS) were reviewed. Caregivers of 200 children between the age of12 and 48 months were interviewed and completed the Thai.MCH-FS. In addition to demographic information, each child had a physical exam and anthropometric measures were taken. Each child was classified with or without feeding problems by at least two of three pediatricians who were blind to the results of the feeding scale. RESULTS: Internal consistency for reliability was high (Cronbach's alpha at 0.835). The area under the ROC curve was 0.864. With a discrimination score of 40, both sensitivity (72%) and specificity (80.67%) were at acceptable levels. Factor analysis resulted in three factors accounting for 52.3%. Of the 200 children, 150 children were classified with nofeedingproblems and 50 with feeding problems. There were no significant differences in the characteristics of the two groups; however the Thai.MCH-FS scores were significantly different for the two groups. CONCLUSION: The Thai version of the MCH-FS has been shown to be a valid and reliable short scale for detecting feeding problems in a pediatric care setting.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.221

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.215
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2015
Admission routes1
Has abstractyes

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