Parental Online Information Access and Childhood Vaccination Decisions in North America: Scoping Review
Bibliographic record
Abstract
BACKGROUND: Immunizing children throughout their early years prevents the spread of communicable disease and decreases the morbidity and mortality associated with many vaccine-preventable diseases. Searching online allows individuals rapid access to health information. OBJECTIVE: The purpose of this review was to develop an understanding of the existing literature of parents' online health information-seeking behaviors to inform their vaccination choices for their children and to identify gaps in the literature around parents' use of online health information and their vaccination choices. METHODS: A scoping review of peer-reviewed literature from Canada and the United States was performed. The following databases were utilized to perform the search: PubMed, CINAHL, Nursing & Allied Health Database, Scopus, and PsycINFO. The purpose of this review was to examine parents' use of online information seeking related to vaccine information and to understand how parents utilize this information to inform decisions about vaccinating their children. Of the 34 papers included in the review, 4 relevant themes and subthemes were identified: information seeking, online information resources, online vaccine content, and trust in health care providers. RESULTS: Examination of the literature revealed conflicting information regarding parents' use of social media and online resources to inform decisions around vaccinating their children. There is evidence of significant misinformation regarding vaccine risks online. Parents' digital health literacy levels are unknown and may affect their ability to appraise online vaccination information. CONCLUSIONS: Parents are seeking vaccine information from online sources. However, the influence of online vaccine information on parental vaccine practices remains uncertain.
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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 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".