Knowledge, Attitudes and Perceptions of Immigrant Parents Towards Human Papillomavirus (HPV) Vaccination: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Our understanding about knowledge, attitudes and perceptions (KAP) of immigrants regarding human papillomavirus (HPV) vaccine is poor. We present the first systematic review on KAP of immigrant parents towards HPV vaccine offered to their children. METHODS: Major bio-medical databases (Medline, Embase, Scopus and PsycINFO) were searched using a combination of keyword and database-specific terms. Following identification of studies, data were extracted, checked for accuracy, and synthesised. Quality of the studies was assessed using the Newcastle Ottawa Scale and the Joanna Briggs Institute Qualitative Assessment tool. RESULTS: A total of 311 titles were screened against eligibility criteria; after excluding 292 titles/full texts, 19 studies were included. The included studies contained data on 2206 adults. Participants' knowledge was explored in 16 studies and ranged from none to limited knowledge. Attitudes about HPV vaccination were assessed in 13 studies and were mixed: four reported negative attitudes fearing it would encourage sexual activity; however, this attitude often changed once parents were given vaccine information. Perceptions were reported in 10 studies; most had misconceptions and concerns regarding HPV vaccination mostly influenced by cultural values. CONCLUSION: The knowledge of HPV-related diseases and its vaccine among immigrant parents in this study was generally low and often had negative attitude or perception. A well-designed HPV vaccine health educational program on safety and efficacy of HPV vaccination targeting immigrant parents is recommended.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".