Managing immunization stress-related response: A contributor to sustaining trust in vaccines
Bibliographic record
Abstract
Adverse events following immunizations (AEFI) are important to identify and manage effectively so as to sustain trust in vaccines and optimize health.The AEFI category related to "anxiety about the immunization" was considered problematic as it did not adequately capture the range of stress responses that can occur.The currently used term for this category, immunization stress-related responses (ISRR), is broader, including the full spectrum of signs and symptoms that can arise in response to stress.ISRR can include vasovagal reactions (fainting), hyperventilation and functional neurological symptoms (e.g.weakness, nonepileptic seizures).It is based on a biopsychosocial framework in which biological (e.g.age, sex), psychological (e.g.preparedness, previous experiences, anxiety) and social factors (e.g.response by others, social media) interact to create an individual's stress response to the immunization process.New guidance is available on prevention, early detection and management of ISRRs which is summarized in the article.
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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 | 0.005 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".