The Saskatchewan/New Brunswick Healthy Start-Départ Santé intervention: implementation cost estimates of a physical activity and healthy eating intervention in early learning centers
Bibliographic record
Abstract
Abstract Background Participation in daily physical activity and consuming a balanced diet high in fruits and vegetables and low in processed foods are behaviours associated with positive health outcomes during all stages of life. Previous literature suggests that the earlier these behaviours are established the greater the health benefits. As such, early learning settings have been shown to provide an effective avenue for exploring and influencing the physical activity and healthy eating behaviours of children before school entry. However, in addition to improving individual level health of children, such interventions may also result in a number of social benefits for the society. In fact, research among adult populations has shown that sufficient participation in physical activity can significantly lower hospital stays and physician visits, in turn leading to positive economic outcomes. To our knowledge there is very limited literature about economic evaluations of interventions implemented in early learning centers to increase physical activity and healthy eating behaviours among children. The primary purpose of this paper is to identify inputs and costs needed to implement a physical activity and healthy eating intervention (Healthy Start-Départ Santé (HS-DS)) in early learning centres throughout Saskatchewan and New Brunswick over the course of three years. In doing so, implementation cost is estimated to complete the first phase of a social return on investment analysis of this intervention. Methods In order to carry out this evaluation the first step was to identify the inputs and costs needed to implement the intervention, along with the corresponding outputs. With stakeholder interviews and using existing database, we estimated the implementation cost by measuring, valuing and monetizing each individual input. Results Our results show that the total annual cost of implementing HS-DS was $378,753 in the first year, this total cost decreased slightly in the second year ($356,861) and again in the third year ($312,179). On average, the total annual cost is about $350,000 which implies an annual cost of $285 per child. Among all inputs, time–cost accounted for the larger share of total resources need to implement the intervention. Overall, administration and support services accounted for the largest portion of the total implementation cost each year: 74% (year 1), 79% (year 2), and 75% (year 3). Conclusions The results from this study shed lights for future implementation of similar interventions in this context. It also helps to assess the cost effectiveness of future interventions.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".