Health students’ knowledge and infectious disease exposure: findings from a cross-sectional study in Namibia
Bibliographic record
Abstract
BACKGROUND: Namibia has recently introduced a number of health training programmes that expose students to infectious disease risks such as human immunodeficiency virus (HIV) and tuberculosis (TB). We explored the knowledge of students in relation to HIV and TB and whether or not there was evidence of exposure. METHODS: We conducted two cross-sectional surveys of Namibian health students (medicine and pharmacy) in 2018. RESULTS: There was a strong association between knowledge and exposure to HIV, but not TB (i.e. explicit exposure versus latent). Regression analysis suggested the time-related risk (age/year of study) to be predictive of knowledge in both studies. The training rotation in the respiratory unit predicted TB knowledge and post-exposure prophylaxis predicted HIV knowledge. CONCLUSIONS: Knowledge of TB and HIV appears mostly related to the duration of study in health students. Exposure or specific experience may enhance knowledge. Future training in infection control may be better focussed on improving knowledge in earlier years.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".