Implementation of Centre-level Food and Nutrition Policies: A Mixed-Methods Study of Child Care Centres in Alberta
Bibliographic record
Abstract
Child care centres are important spaces for health promotion. Although child care centres have an important role in offering meals that include important nutrients that young children need for healthy growth and development and in supporting young children in developing healthy eating behaviours that can be carried into adulthood, food environments in child care are sub-optimal. Food and Nutrition Policies (FNP) have the potential to improve child care food environments, but evidence is still limited. The purpose of this sequential, mixed-methods study was to: i) perform a scoping review to identify theories, models and frameworks (TMFs) used to inform the implementation of healthy eating interventions in centre-based child care services in developed countries, ii) conduct a cross-sectional survey to describe resources and strategies in place to support FNP implementation in child care centres in Edmonton, Alberta, and iii) complete a theoretically-informed multiple case study to describe characteristics of the innovation, recipients, and context that influence the implementation of FNP among child care centres classified as low and high implementers. The scoping review identified 28 different TMFs targeting different socio-ecological levels across 38 studies. Majority of studies relied on individual-focused TMFs. Poor TMF selection, use and reporting were identified, particularly in the development of implementation strategies, which could limit TMF’s utility. The cross-sectional survey included 43 (13% response rate) child care centres across the Edmonton metropolitan region. Almost all of the participating centres had FNP in place (94%). However, on average, only about 9 of the 17 resources and processes (range 1–17) required to support FNP implementation were well-established across centres. More often, policies lacked a description of goals and providers’ responsibilities, centres did not secure resources for policy implementation and lacked evaluation of policy implementation. The multiple case study presented a comprehensive description of factors that might influence FNP implementation in child care centres. In terms of innovation, lack of clarity on FNP and a limited degree of fit were the main gaps to implementation. Also, providers had limited iii nutrition knowledge and skills, had limited power and authority to enforce policy and reported a perception of low parents’ commitment. In general, child care centres provided a supportive environment for FNP implementation, but mechanisms to embed and evaluate FNP implementation lacked focus on FNP. Overall, cases were influenced by external and system-level factors, such as regulatory frameworks, incentives and environmental stability. Access to inter-organizational networks varied across the different organizational structures (profit, non-profit, franchised). In conclusion, collaborations between researchers, policymakers, practitioners and families can help to build capacity for FNP implementation and to address the gaps identified.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 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".