The effects of shared medical appointment multidisciplinary interventions for non-organic feeding disorders in infants and young children during the self-feeding transition period
Bibliographic record
Abstract
Objective: This study aimed to implement shared medical appointment multidisciplinary interventions for non-organic feeding disorders in infants and young children and evaluate their effects. Methods: A total of 52 children aged 6-24 months and their respective feeders were included in the study. Of them, 26 were classified into the intervention group, and 26 were classified into the control group. Routine child health care measures were applied to the control group. The child health care measures combined with shared medical appointment multidisciplinary interventions, including 3 collective interventions and 3 months of follow-up, were applied in the intervention group. Data concerning physical growth indicators, Montreal Children's Hospital Feeding Scale (MCH-FS) scores, Infant and Child Feeding Index (ICFI) scores, and Self-Rating Anxiety Scale (SAS) scores in the two groups were collected. Results: Due to insufficient participation in interventions, loss of follow-up, and withdrawal from the study, 46 cases were finally included in this study, with 23 cases in each group. The physical growth indicators in the intervention group were better than the control group, with the effects of time. The intervention group had lower MCH-FS score, higher ICFI score and lower SAS score. Conclusions: These results provide preliminary evidence of the effectiveness and feasibility of shared medical appointment multidisciplinary interventions, which help promote feeding and physical growth in infants and young children and provide a reference for improving management for feeding in infants and young children.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".