Weighing the risks and benefits: Parental perspectives on COVID-19 vaccines for 5- to 11-year-old children
Bibliographic record
Abstract
BACKGROUND: Parents are the primary decision makers for their children's vaccination, yet, we have limited knowledge on what influences their decision making related to COVID-19 vaccination. The study aimed to understand these different considerations that shape the decisions of parents of children aged 5-11 years old. METHODS: We conducted a qualitative study that included online focus group discussions (FGDs) with parents of children aged 5-11 years old. Data was collected between July 26th, 2022, and February 15th, 2023. A total of eight FGDs were conducted, audio-recorded and transcribed verbatim. Thematic analysis was conducted, and peer debriefing was used to ensure methodological rigor. RESULTS: Findings revealed that parents of vaccinated and unvaccinated children employed language of risk-benefit analysis to inform their decision-making. Parents of vaccinated children highlighted concerns about spreading COVID-19, family member's health, and long COVID-19. For parents of unvaccinated children, they perceived potential vaccine side effects as more harmful than the risks associated with COVID-19. Participants contended that there was a lack of transparency from the government and public health agencies, highlighting inconsistent messaging which had fractured their trust in COVID-19-related recommendations and mandates. CONCLUSIONS: Our results indicate that improved transparency on how evidence is developed and why recommendations and mandates shift during the pandemic would foster trust in the government and public health agencies. Open communication with health providers on the potential risks and benefits would also improve caregivers confidence in the vaccine.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".