Responsive Feeding Environments in Childcare Settings: A Scoping Review of the Factors Influencing Implementation and Sustainability
Bibliographic record
Abstract
Children benefit from responsive feeding environments, where their internal signals of hunger and satiety are recognized and met with prompt, emotionally supportive and developmentally appropriate responses. Although there is existing research on responsive feeding environments in childcare, there is little synthesized literature on the implementation practices using a behavior change framework. This scoping review sought to explore the factors influencing the implementation and sustainability of responsive feeding interventions in the childcare environment, using the behavior change wheel (BCW). A total of 3197 articles were independently reviewed and 39 met the inclusion criteria. A thematic analysis identified the factors influencing the implementation and sustainability of responsive feeding, including the following: (1) pre-existing nutrition policies, (2) education and training, (3) provider beliefs and confidence, (4) partnership development and stakeholder engagement and (5) resource availability. The most common BCW intervention functions were education (n = 39), training (n = 38), environmental restructuring (n = 38) and enablement (n = 36). The most common policy categories included guidelines (n = 39), service provision (n = 38) and environmental/social planning (n = 38). The current literature suggests that broader policies are important for responsive feeding, along with local partnerships, training and resources, to increase confidence and efficacy among educators. Future research should consider how the use of a BCW framework may help to address the barriers to implementation and sustainability.
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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 | 0.023 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".