Exploring the Use of a Web-Based Menu Planning Tool in Childcare Services: Qualitative Cross-sectional Survey Study
Bibliographic record
Abstract
BACKGROUND: Early childhood is a critical period for supporting the development of healthy eating habits, which may affect lifelong health. Childcare services are important settings for promoting early childhood nutrition; however, food provision in childcare frequently does not align with dietary guidelines. Web-based menu planning tools are well suited to support healthy food provision in childcare, although little is known about their use. Research is needed to understand how web-based menu planning tools are used in the childcare setting and how they can effectively support healthy menu planning and food provision for children in childcare. OBJECTIVE: We aimed to explore the use of a web-based menu planning tool called FoodChecker, which is available to childcare services in Victoria, Australia. We also aimed to gain insights and perspectives from childcare staff involved in menu planning about their use of the tool to plan healthy menus and guide healthy food provision for children. METHODS: We conducted a qualitative descriptive study using a cross-sectional web-based survey completed by the staff involved in menu planning in childcare services. Thematic analysis was performed using NVivo software. Emergent themes were mapped against constructs of the Technology Acceptance Model regarding perceived usefulness, perceived ease of use, and external variables influencing perceptions and use. RESULTS: The participants included 30 cooks and 34 directors from 53 childcare services. Participants perceived the web-based menu planning tool as useful for supporting child nutrition and health, improving organizational processes, and aiding the menu planner role. Perceptions regarding ease of use were mixed. External variables influencing perceptions and use included awareness of the tool, perceived need, time, resources, organizational support, and the food budget. Participants made recommendations to improve the tool, particularly the need to integrate functionality to make it easier and faster to use or to include more links to resources to support healthy menu planning. CONCLUSIONS: The web-based menu planning tool was perceived as useful for cooks and directors in childcare services. Areas for improvement were identified; for example, the need for integrated digital features to make the tool easier and faster to use. As the first qualitative study to explore childcare staff experiences with a web-based menu planning tool, these findings inform future research and development of such tools to aid scalable and sustainable support for healthier food provision in the childcare sector.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".