Supper Heroes: Feasibility & Preliminary Impact of a Family-Based Mobile Health Sustainable Eating Intervention
Bibliographic record
Abstract
Background: Fostering healthy and environmentally sustainable eating is necessary to protect human and planetary health. Dietary behaviours aligned with healthy and environmentally sustainable eating include reducing household food waste, increasing consumption of plant-based proteins, and reducing intake of highly processed foods by cooking at home more often. Despite the benefits of sustainable eating, past research indicates that Canadian families require support to implement associated dietary behaviours. Objective: To test the feasibility and preliminary impact of "Supper Heroes", a superhero-themed mobile health (mHealth) intervention designed to promote healthy and environmentally sustainable eating among families with children aged 9-14 in Ontario, Canada. Methods: A single arm, pre-post design was used to evaluate the intervention. Designed using Michie's Behaviour Change Wheel and informed by the Theory of Planned Behaviour, the mHealth intervention featured 7 "missions" which included infographics, videos, and family-based activities completed over 4 months during May 2023 to January 2024. Behaviour change goals were to reduce food waste, increase consumption of plant-based proteins, and cook more meals at home. Online surveys were conducted pre and post intervention to assess feasibility, frequency of plant-based intake, and frequency of cooking at home. Food waste was measured and reported by families using a weighed food waste diary. Results: 23 out of 30 families (77%) were retained from baseline to post-intervention. Most parents (97%) reported that they were satisfied or highly satisfied with the intervention and that they would recommend or highly recommend the program. Approximately 88% reported that the amount of content was just right, and 82% reported that the length of the intervention was just right. There was a significant reduction in food waste post intervention compared to pre intervention (change = -1133 g; p = 0.002). There was a non-significant increase in plant-based protein consumption (change = 0.27 times/week) and no change in cooking at home (change = 0.03 times/week) from baseline to post intervention. Conclusion: The intervention was feasible and well-accepted by parents. Preliminary evidence suggests that the program may be effective in reducing household food waste. A randomized controlled trial among a larger sample is recommended to further evaluate intervention impacts. These results can inform future research and public health interventions aimed at promoting sustainable eating.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 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 teacher head, 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".