From Lyme disease emergence to endemicity: a cross sectional comparative study of risk perceptions in different populations
Bibliographic record
Abstract
BACKGROUND: Lyme disease (LD) is a tick-borne emerging disease in Canada that has been endemic in many temperate countries for decades. Currently, one of the main approaches for LD prevention is the promotion of individual-level preventive behaviors against ticks. Health behaviors are influenced by individual and social factors, one important of which is risk perception. This study aims to describe and compare risk perception of LD, within and between general populations and experts living in two different regions: the Neuchâtel canton in Switzerland, where LD is endemic, and the Montérégie region in Québec (Canada), where LD is emerging. METHOD: A web-based survey was conducted in both study regions (814 respondents) in 2012, and a questionnaire was administered to 16 experts. Comparative analyses of knowledge, risk exposure and different components of LD risk perception were performed. Multivariate analyses were used to calculate a global risk perception score and to identify determinants of risk perception in both regions. RESULTS: In Montérégie, only 15% of the survey respondents had a good level of knowledge of LD compared to Neuchâtel where 51% of survey respondents had good levels of knowledge. In Montérégie, 24% of respondents perceived themselves as being at high or very high risk of contracting LD vs 54% in Neuchâtel; however, a higher percentage of respondents from this region believed that personal protection was simple to carry out (73% vs 58% in Montérégie). Based on the population surveys, almost all of the identified determinants of risk perception were different between both populations except for gender. A good level of knowledge, living in the risk zone and knowing someone who has had LD increased risk perception, while a high level of education and being 18-34 years of age decreased this perception. The majority of the studied components of risk perception were different between populations and their regional experts. CONCLUSION: This study suggests that risk perception of LD differs between populations and regional experts living in different epidemiological situations. Monitoring of knowledge and risk perception in local populations may help to better target LD communication efforts in accordance with population specific attributes thereby enhancing prevention efficacy.
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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 | 0.002 |
| 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) | 0.001 | 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".