Functional analysis screening for inappropriate mealtime behavior
Bibliographic record
Abstract
Abstract Inappropriate mealtime behavior (IMB) is a class of food refusal behavior that is commonly observed in children with neurodevelopmental disorders or avoidant/restrictive food intake disorder. An abundance of research has demonstrated that IMB is commonly maintained by negative reinforcement in the form of escape from food or drink presentation. Given the common association between IMB and escape as a reinforcer, more efficient methods of conducting functional analyses have been called for. The present study examined the extent to which indirect assessments and a functional analysis screening process reliably predicted an escape function in three children with autism spectrum disorder who engaged in IMB. The results of the two assessments were then compared to a standard functional analysis. For all participants, the functional analysis identified an escape function, which corresponded with both the indirect assessment and screening. Additionally, within‐session analyses of screening sessions further validated the screening process. The functional analysis screening of IMB is discussed in terms of its efficiency, practicality, and experimental design. The results of this study offer a framework for efficiently assessing the function of IMB, while providing recommendations for future research.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".