Developmental Trajectories of Feeding Problems in Children with Autism Spectrum Disorder
Bibliographic record
Abstract
OBJECTIVE: Although feeding problems are a common concern in children with autism spectrum disorder (ASD), few longitudinal studies have examined their persistence over time. The purpose of this study was to examine the developmental progression of feeding problems across four time points in preschoolers with ASD. METHODS: Group-based trajectory analyses revealed four distinct trajectories of feeding problems in our sample (N = 396). RESULTS: The majority of children showed levels of feeding problems that were low from the outset and stable (Group 1; 26.3%) or moderate and declining over time (Group 2; 38.9%). A third group (26.5%) showed high levels of feeding problems as preschoolers that declined to the average range by school age. Few participants (8.3%) showed evidence of severe chronic feeding problems. Feeding problems were more highly correlated with general behavior problems than with autism symptom severity. CONCLUSIONS: Overall, our findings demonstrated that in our sample of children with ASD, most feeding problems remitted over time, but a small subgroup showed chronic feeding problems into school age. It is important to consider and assess feeding problems in ASD against the backdrop of typical development, as many children with ASD may show improvement with age.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".