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Record W3173219568 · doi:10.15557/pipk.2021.0001

Nutritional versus behavioural intervention in children with avoidant/restrictive food intake disorder

2021· article· en· W3173219568 on OpenAlexaboutno aff
Katarzyna Bąbik, Paweł Ostaszewski, Andrea Horvath

Bibliographic record

VenuePsychiatria i Psychologia Kliniczna · 2021
Typearticle
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsnot available
Fundersnot available
KeywordsIntervention (counseling)Psychological interventionFood intakeBody mass indexPsychologyMedicineClinical psychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Objective: The aim of the study was to determine the effectiveness of nutritional intervention compared to behavioural intervention to increase food acceptance and improve the nutritional status among children with avoidant/restrictive food intake disorder. Method: Six participants (3–4 years old) diagnosed with avoidant/restrictive food intake disorder took part in the study. They were randomly assigned to one of the two interventions, either a nutritional or behavioural approach. Results: The percentage of food acceptance increased for patients in the behavioural intervention group, but not for the nutritional intervention group (until later implementation of behavioural intervention). Moreover, the z-score for body mass index increased only after implementing behavioural intervention. The total score on the Montreal Children’s Hospital Feeding Scale decreased only after implementation of intervention based on behavioural approach. Inappropriate mealtime behaviour decreased across all participants after implementation of behavioural intervention. Discussion: Behavioural intervention seems to be promising for children with avoidant/restrictive food intake disorder to increase the oral intake of solid food and improve their growth.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score1.000

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.328
Teacher spread0.289 · 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.

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

Citations6
Published2021
Admission routes1
Has abstractyes

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