Development and validation of a behavioral index for adaptation to lyme disease
Bibliographic record
Abstract
BACKGROUND: Recent evidence suggests that climate change and other factors are leading to the emergence of Lyme disease in the province of Quebec, where it previously did not exist. As risk areas expand further north, the population can adopt specific preventive behaviors to limit chances of infection. The objectives of this study were to (1) create an index of Lyme disease prevention behaviors (LDPB), and (2) use the theory of planned behavior (TPB) to explain the decision-making process of people who choose to adopt LDPB. METHODS: A sample of 1959 adults living in a Lyme disease risk area completed a questionnaire by phone (n = 1003) or on the Web (n = 956). The questionnaire measured whether they did or did not adopt the LDPB proposed by public health officials. It also measured some TPB variables, including their attitude or perceived social norms regarding LDPB. RESULTS: Our findings led to the creation of a Lyme disease prevention index consisting of 10 behaviors, down from the 19 behaviors initially considered for inclusion in the index. Rates of adoption of each behavior varied tremendously, from 4.30 to 83.80%. All variables of the TPB model (attitude, social norms, and perceived control) were significantly associated with intention to adopt preventive behaviors. Intention itself was significantly associated with adoption of LDPB. Likewise, risk perception was positively correlated with the adoption of LDPB. CONCLUSIONS: This study led to the creation of a Lyme disease prevention index that can be used by public health agencies, researchers, and professionals to monitor the evolution over time of individuals' LDPB adoption rates. It also showed the usefulness of the TPB in understanding the adoption of LDPB and how intention to adopt such behaviors is formed.
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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 | 0.000 | 0.000 |
| 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".