Feasibility, acceptability, and preliminary impact of “Supper Heroes”, a family-based sustainable diet intervention
Bibliographic record
Abstract
The primary objective of this research was to evaluate the feasibility and acceptability of "Supper Heroes", a superhero-themed mobile health (mHealth) intervention designed to reduce food waste and increase plant-based protein food intake among families with children aged 9-14 in Ontario, Canada. A single arm, pre-post mixed methods design was used to evaluate the intervention. The 4-month mHealth intervention included 7 online modules with infographics, videos, and activities to help families reduce their food waste and eat more plant-based protein foods. Feasibility was assessed using website analytics to monitor intervention completion and attrition. Acceptability was assessed at post-intervention using online surveys of parents and children, and in-depth interviews with parents. 23 out of 30 families (77%) were retained from pre-to post-intervention; 33 parents (22 mothers, 10 fathers; and 1 parent who did not disclose their gender) completed the pre-intervention and post-intervention surveys and 33 children (16 girls; 15 boys; 1 child who did not disclose their gender; and 1 non-binary child) completed the post-intervention surveys. Most parents (95% of mothers and 100% of fathers) and children (88%) reported that they were satisfied or highly satisfied with the intervention. Overall, the intervention was feasible and well-accepted by parents and children. 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 diets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".