Determinants of parents' decision to vaccinate their children against rotavirus: results of a longitudinal study
Bibliographic record
Abstract
Rotavirus disease is a common cause of health care utilization and almost all children are affected by the age of 5 years. In Canada, at the time of this survey (2008-09), immunization rates for rotavirus were <20%. We assessed the determinants of a parent's acceptance to have their child immunized against rotavirus. The survey instruments were based on the Theory of Planned Behavior. Data were collected in two phases. In all, 413 and 394 parents completed the first and second interviews, respectively (retention rate 95%). Most parents (67%) intended to immunize their child against rotavirus. Factors significantly associated with parental intentions (Phase 1) were as follows: perception of the moral correctness of having their child immunized (personal normative belief) and perception that significant others will approve of the immunization behavior (subjective norm), perceived capability of having their child immunized (perceived behavioral control) and household income. At Phase 2, 165 parents (42%) reported that their child was immunized against rotavirus. The main determinant of vaccination behavior was parental intention to have their child vaccinated, whereas personal normative beliefs influenced both intention and behavior. The acceptability of the rotavirus vaccine will be higher if health promotion addresses parental knowledge, attitudes and beliefs regarding the disease and 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".