Food allergy education: teen learning preferences
Bibliographic record
Abstract
Food allergic teens are at increased risk for fatal anaphylaxis[ 1 ]. Food allergy education is needed to address the transition of care from their parents to the teens. Teen input into education approaches is essential in order to effectively develop programs that will modify behavior. Allergy educators will need to be familiar with effective approaches to education for this important population. Teens with food allergy were invited into focus groups in our education centre as a preliminary step to determine their preferred learning styles to begin development of effective educational resources for teens. Semi-structured interviews were conducted, digitally recorded, transcribed and reviewed for themes. 16 teens (mean 16 yr.) participated in three focus groups facilitated by a food allergy educator. Common themes from these interviews highlighted the need for different methods of communication (both from and to the teens) and behavioral approaches to self-advocacy, risk assessment and reduction, reaction recognition and treatment. In-depth information about allergic reactions and on-going research were also of interest. Learning preferences included spatial, auditory, verbal and kinesthetic style examples. All groups emphasized a need for some hands-on classroom experiences, including: practice with auto-injectors, playing out different scenarios, and distance and mobile information. The teens expressed interest in small group participation where they could voice their opinions, have questions answered, and comfortably communicate with others. Many teens said they liked hybrids of different learning styles, such as auditory and visual instruction followed by hands-on experience in the classroom. Most teens preferred a group facilitator expert in food allergies and/or who had food allergies, educator skills, and could relate to younger people. Online and mobile learning was of interest but most had not yet used these resources. Teens are interested in small group interactive education with hands-on experience, as well as mobile-based learning. Food allergy topics must be adapted to teen specific situations, and a teen program needs to include a variety of approaches to connect with teens. These focus groups have led to the deployment of an online survey for teens to acquire a greater breadth of feedback for topics and teens’ learning preferences.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".