Knowledge about pandemic influenza preparedness among vulnerable migrants in Thailand
Bibliographic record
Abstract
This study was designed to assess factors associated with a high level of knowledge about influenza among displaced persons and labor migrants in Thailand. We conducted a cross-sectional study of 797 documented and undocumented migrants thought to be vulnerable to influenza during the early stages of the 2009 H1N1 pandemic. Data were collected on socio-demographic factors, migration status, health information sources, barriers to accessing public healthcare services and influenza-related knowledge using a 201-item interviewer-assisted questionnaire. Among the different types of influenza, participants' awareness of avian influenza was greatest (81%), followed by H1N1 (78%), human influenza (61%) and pandemic influenza (35%). Logistic regression analyses identified 11 factors that significantly predicted a high level of knowledge about influenza. Six or more years of education completed [odds ratio (OR) 6.89 (95% confidence interval (CI) 3.58-13.24)] and recent participation in an influenza prevention activity [OR 5.27 (95% CI 2.78-9.98)] were the strongest predictors. Recommendations to aid public health efforts toward pandemic mitigation and prevention include increasing accessibility of education options for migrants and increasing frequency and accessibility of influenza prevention activities, such as community outreach and meetings. Future research should seek to identify which influenza prevention activities and education materials are most effective.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".