Influenza vaccine uptake in Tunisia from two high-risk groups’ perception and attitudes: a qualitative study
Bibliographic record
Abstract
Background: Pregnant women (PW) and older adult with chronic diseases (ECD) are priority groups for the influenza vaccination. This study was designed to have a better insight into the influenza perceptions and barriers of the vaccine uptake from these groups' perspectives. Methods: This qualitative study consisted of 20 focus group discussions (FGDs) enrolled from five governorates across the country (north, center, and south) between March 18 and July 10, 2019, in urban and rural areas. FGDs were conducted in Arabic (Tunisian dialect) and following the topic guide. Data were transcribed in the local language then translated into English and analyzed using Nvivo12 Software. This permitted the analysis thematic approach, using codes determined by the focus groups. Results: A total of 170 individuals participated in the FGDs (84 ECD and 86 PW). Both groups recognized the weakness of the immune system as key determinant for severity. While PW raised the lack of information about the vaccine, the ECD emphasized accessibility problems. Five main barriers to influenza vaccination were identified: cultural barriers and use of traditional medicine, misleading or lack of information about influenza and the vaccine, advice against its uptake, problems of availability and accessibility of the vaccine as well as mistrust towards the vaccine including adverse effects, vaccine composition and effectiveness. Conclusion: The study provided refined information from the perspectives of users to orient the policies regarding the promotion of influenza vaccine by decision makers among these two high risk groups.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".