Acceptability of tick control interventions to prevent Lyme disease in Switzerland and Canada: a mixed-method study
Bibliographic record
Abstract
BACKGROUND: Lyme disease control strategies may include tick control interventions in high risk areas. Public authorities may be interested to assess how these types of interventions are perceived by the public which may then impact their acceptability. The aims of this paper are to compare socio-cognitive factors associated with high acceptability of tick control interventions and to describe perceived issues that may explain their low acceptability in populations living in two different regions, one being an endemic region for LD since the last 30 years, the Neuchâtel canton, in Switzerland, and another where the disease is emerging, the Montérégie region, in Canada. METHODS: A mixed methods' design was chosen. Quantitative data were collected using web-surveys conducted in both regions (n = 814). Multivariable logistic regressions were used to compare socio-cognitive factors associated with high acceptability of selected interventions. Qualitative data were collected using focus group's discussions to describe perceived issues relative to these interventions. RESULTS: Levels of acceptability in the studied populations were the lowest for the use of acaricides and landscaping and were under 50 % in both regions for six out of eight interventions, but were higher overall in Montérégie. High perceived efficacy of the intervention was strongly associated with high acceptability of tick control interventions. A high perceived risk about LD was also associated with a high acceptability of intervention under some models. High level of knowledge about LD was negatively associated with high acceptability of the use of acaricides in Neuchâtel. Perceived issues explaining low acceptability included environmental impacts, high costs to the public system, danger of individual disempowerment and perceptions that tick control interventions were disproportionate options for the level of LD risk. CONCLUSION: This study suggests that the perceived efficacy and LD risk perception may be key factors to target to increase the acceptability of tick control interventions. Community-level issues seem to be important considerations driving low acceptability of public health interventions. Results of this study highlight the importance for decision-makers to account for socio-cognitive factors and perceived issues that may affect the acceptability of public health interventions in order to maximize the efficacy of actions to prevent and control LD.
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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 | 0.002 |
| 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".