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Record W2972623439 · doi:10.1002/jaba.637

A systematic review of functional analysis in pediatric feeding disorders

2019· review· en· W2972623439 on OpenAlexaff
Valdeep Saini, Heather J. Kadey, Katherine Paszek, Henry S. Roane

Bibliographic record

VenueJournal of Applied Behavior Analysis · 2019
Typereview
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsBrock University
Fundersnot available
KeywordsPsycINFOPsychologyFunctional analysisMeta-analysisApplied behavior analysisClinical psychologyDescriptive statisticsDevelopmental psychologySystematic reviewMEDLINEAutismMedicine

Abstract

fetched live from OpenAlex

We conducted a systematic review of the functional analysis of inappropriate mealtime behavior in peer-reviewed studies in PsycINFO, ERIC, PubMed, and the Journal of Applied Behavior Analysis between 2000-2016. We identified 18 studies involving 86 functional analyses. We coded descriptive data and calculated summary statistics in addition to conducting a quality appraisal of the literature. We identified escape, exclusively or in part, as the maintaining reinforcer for inappropriate mealtime behavior in 92% of cases. Results indicate that differentiated functional analyses of inappropriate mealtime behavior can be obtained, and outcomes are consistent with etiological theories of food refusal behavior. We discuss procedural differences across studies as well as directions for future research.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.074
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.074
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.006
Bibliometrics0.0180.015
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.038
GPT teacher head0.343
Teacher spread0.305 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations33
Published2019
Admission routes1
Has abstractyes

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