Food Allergy Training for Schools and Restaurants (The Food Allergy Community Program): Protocol to Evaluate the Effectiveness of a Web-Based Program
Bibliographic record
Abstract
BACKGROUND: Food allergy is a growing public health concern. The literature suggests that a significant number of reactions occur in community services, such as schools and restaurants. Therefore, suitable training and education for education and catering professionals using viable and practical tools is needed. OBJECTIVE: The objective of this study is to evaluate the effectiveness of a Web-based food allergy training program for professionals working in schools and restaurants, designed to improve knowledge and good practices in the community. METHODS: Free learning programs which contain educational animated videos about food allergy were developed for professionals working at schools and restaurants. The learning programs comprise of nine 5-minute videos, developed in video animation format using GoAnimate, with a total course length of 45-60 minutes. The courses for professionals at both schools and restaurants include contents about food allergy epidemiology, clinical manifestations, diagnosis and treatment, dietary avoidance, emergencies, labelling, and accidental exposure prevention. Additionally, specific topics for work practices at schools and restaurants were provided. Food allergy knowledge survey tools were developed to access the knowledge and management skills about food allergy of school and restaurant staff, at baseline and at the end of the food allergy program. The courses will be provided on the e-learning platform of the University of Porto and professionals from catering and education sectors will be invited to participate. RESULTS: Data collection will take place between September 2017 and October 2017, corresponding to a 2-month intervention. Final results will be disseminated in scientific journals and presented at national and international conferences. CONCLUSIONS: The Food Allergy Community Program intervention may improve school and restaurant professionals' commitment and skills to deal with food allergy in the community. Furthermore, this e-intervention program will provide an innovative contribution to understanding the impact of electronic health technologies on the learning process and the development of strategies for community interventions. REGISTERED REPORT IDENTIFIER: RR1-10.2196/9770.
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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 | 0.018 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.046 | 0.010 |
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".