Animated Videos Based on Food Processing for Guidance of Brazilian Adults: Validation Study
Bibliographic record
Abstract
BACKGROUND: Ultraprocessed foods (UPFs) contribute almost one-fifth of the calories consumed by the Brazilian population. This consumption has been favored by aspects such as the ease of acquisition and low cost of this food group. Initiatives focused on supporting and promoting healthy eating practices have been implemented. Among them, the availability of educational resources is an important strategy to maximize the effectiveness of these actions in the field of food and nutrition education (FNE). OBJECTIVE: This study aims to describe the development and validation process of animated videos based on the NOVA food classification for FNE actions aimed at Brazilian adults. METHODS: This methodological study was developed in the following 4 phases: planning, preproduction, production, and postproduction. In the planning phase, a literature review was con-ducted on the topic and to define the content to be covered. The design of the material was based on the cognitive theory of multimedia learning. In the preproduction phase, video scripts were developed and evaluated by 7 content specialists. In the production phase, videos were developed based on the assessed scripts and then assessed by 3 multimedia production specialists. In the postproduction phase, the videos were evaluated by 15 representatives of the target audience. All results obtained in the evaluation phases were analyzed using the content validity index (CVI). RESULTS: We developed 3 animated videos covering the following themes: food processing levels, food categories according to processing levels, and UPFs and their impact on health. In the evaluation by the content specialists, the scripts of videos 1, 2, and 3 obtained CVIs at the scale level and average method equal to 0.96, 0.98, and 0.98, respectively. When the animated videos were evaluated by multimedia production specialists and representatives of the target audience, these indexes were equal to 1.0. These results attest to the videos' adequacy and quality in communicating the addressed content. CONCLUSIONS: The animated videos developed and validated in this study proved to be adequate for their purpose. Thus, it is expected that they will be an important instrument for FNE actions aimed at an adult audience and for disseminating the Dietary Guidelines for the Brazilian Population.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".