An evaluation of the Kinect-Ed presentation, a motivating nutrition and cooking intervention for young adolescents in grades 6–8
Bibliographic record
Abstract
Recently, public health messaging has included having more family meals and involving young adolescents (YAs) with meal preparation to improve healthful diets and family dinner frequency (FDF). Kinect-Ed, a motivational nutrition education presentation was created to encourage YAs (grades 6-8) to help with meal preparation and ultimately improve FDF. The purpose of this study was to evaluate the Kinect-Ed presentation, with the goals of the presentation being to improve self-efficacy for cooking (SE), food preparation techniques (TECH), food preparation frequency (PREP), family meal attitudes and behaviours, and ultimately increase FDF. A sample of YAs (n = 219) from Southern Ontario, Canada, completed pre- and postpresentation surveys, measuring FDF, PREP, SE, and TECH. Kinect-Ed successfully improved participants' FDF (p < 0.01), PREP (p < 0.01), SE (p < 0.01), and TECH (<0.01). Overall, goals of the presentation were met. Encouraging YAs to help prepare meals and get involved in the kitchen may reduce the time needed from parents to prepare meals, and, in turn, allow more time for frequent family dinners.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".