Factors impacting vaccine hesitant parents of young children in Northern British Columbia: a qualitative study from a health care communicator’s lens
Bibliographic record
Abstract
In 2019 the World Health Organization (WHO) declared vaccine hesitancy as a top threat to global health while highlighting the concerning resurgence of vaccine preventable diseases. In the Northern British Columbia region, which is under the jurisdiction of the Northern Health Authority, there are lower routine child vaccination rates than the rest of the province, however, these rates do not tell us why parents may be vaccine hesitant. As a communications professional working in healthcare, I conducted this qualitative research to better understand the local barriers and drivers of vaccination for Northern BC parents. Semi-structured interviews were conducted with two key audiences: parents of young children (five years and younger) and immunizers (nurses) who administer routine child vaccinations. The interview data were analyzed using discourse analysis to develop vaccination-related themes. Unexpected results included the negative impact of the COVID-19 pandemic on increasing parental vaccine hesitancy, the impact of the pandemic on increasing general vaccine awareness, the experience of first-time parents, and the impact of family dynamics in small communities. This research also revealed the extreme difficulty in recruiting participants in the vaccine-hesitant parent population. In accordance with the WHO’s Tailoring Immunization Programmes approach of not guessing why populations may be hesitant but determining the root cause, this research sheds light on several reasons why Northern BC parents may be vaccine-hesitant, and it goes one step further by offering strategic communication recommendations informed by the Behaviour Change Wheel to help increase vaccine uptake for young children in the region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".