Preparing Young People With Intellectual Disability and on the Autism Spectrum for School Vaccination
Bibliographic record
Abstract
ABSTRACT Adolescents with intellectual disability and/or on the autism spectrum may have significant anxiety about receiving vaccination with an intramuscular injection and report lower vaccine coverage than their typically developing peers. Good preparation and education may help these young people manage these challenges. Limited evidence exists about the type of information and education they receive about vaccines and vaccination, if any. This study aimed to understand whether, how and by whom, young people with intellectual disability and/or on the autism spectrum in New South Wales, Australia, are prepared for school‐based vaccination in special school settings. Semi‐structured interviews and focus groups were conducted with 50 participants, representing four stakeholder groups, including 10 students, 6 parents, 24 education and 10 health staff. Interviews explored the process and experience of vaccination, including student preparation. Accessible methods such as Easy Read resources were used with students. Using thematic analysis, we identified four student preparation themes: (1) students' prior knowledge of vaccination, (2) decisions whether to prepare students for vaccination, (3) preparation strategies and resources, and (4) responsibility for preparation. We found that while students demonstrated understanding of vaccination benefits and expressed preferences for preparation, many parents, teachers, and health staff assumed they lacked the capacity to understand vaccines. Consequently, student preparation was inconsistent—some students were prepared using support materials, while others received no advance notice due to concerns about anxiety. Responsibility for preparation was unclear, with health staff assuming parents handled it, some parents assuming schools were responsible, and teachers viewing preparation as primarily a parental role. The study revealed significant gaps between students' actual capabilities, as well as inconsistent preparation practices and unclear role responsibilities. These findings highlight the need for health communication policies and practices that recognise students' demonstrated understanding and establish clear collaborative frameworks for vaccination preparation.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".