Perceived vulnerability for Lyme disease questionnaire: A social science tool for understanding tick-borne disease attitudes
Bibliographic record
Abstract
Lyme disease has emerged as a growing epidemic across the U.S., with tick populations spreading north because of a plethora of human-induced factors. As the scope of this problem grows, there is a need to understand how vulnerable the public perceives themselves to be and how perceived vulnerability as a psychological construct influences public behavior. A growing body of literature has explored individual risk perceptions and individual preventative behaviors toward Lyme disease, but there remains a notable research gap regarding the concept of vulnerability. This empirical study establishes the first questionnaire for perceived vulnerability towards Lyme disease, modified from pre-existing infectious disease literature. This novel instrument was tested and compared with individual factors relating to preventative behaviors and source credibility of major information sources about Lyme disease in the state of Maine. Recent increases in black-legged tick (Ixodes scapularis) populations have affected the state of Maine in dramatic ways. This research specifically surveyed homeowners to explore their perceived vulnerability, source credibility, and individual protective intentions related to ticks and Lyme disease in Maine. Results from this study validate a modified perceived vulnerability scale for Lyme disease and highlight how understanding the relationships between these perceptions of vulnerability, individual behaviors, and sources of information can improve outreach and communication efforts about tick-borne diseases.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.003 | 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".