Good Interventions That Few Use: Uptake of Insect Bite Precautions in a Group of Canadian Forces Personnel Deployed to Kabul, Afghanistan
Bibliographic record
Abstract
We evaluated use of interventions to prevent insect bites in Canadian personnel deployed to Kabul, Afghanistan. Data were collected through a self-report written survey. The response rate was 92%, and intervention uptake was 11% applied repellent that day, 21% slept under a bednet their last sleep, and 78% wore insecticide-treated clothing. Two associations were usually evident in multivariate analyses: persons perceiving risk of exposure as high were more likely to use bednets and repellent, and individuals reminded to use an intervention had higher odds of doing so. However, even if perception of exposure risk was high and reminders were received, the use of bednets (60%) and repellent (40%) was relatively low. Hence, on the one hand, increased uptake of interventions through targeted messaging might be possible. On the other hand, effectiveness of these interventions might be substantially constrained because of nonuse, even in a motivated and informed population.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".