Understanding Factors Influencing Dog Owners' Intention to Vaccinate Against Rabies Evaluated Using Health Belief Model Constructs
Bibliographic record
Abstract
Ethiopia has one of the highest incidence levels of human rabies in Africa, with 3-7 deaths per 100,000 people annually. The country has no official rabies control programme, despite the availability of an effective canine vaccine to control rabies. To support effective rabies control, an understanding of the factors affecting dog owners' voluntary intentions to vaccinate their dogs is important. As such, this study examined factors influencing dog owners' intentions to vaccinate their dogs using the constructs of health belief theory. In this cross-sectional study, a questionnaire, designed based on the Health Belief Model constructs was completed by 249 dog owners in 9 randomly selected wards of Bishoftu town in central Ethiopia between October and December 2016. An ordinal regression model was then fitted to explore factors which best predict the likelihood of a dog owner's intention. A classification and regression tree (CART) model was then used for recursive partitioning of the Likert scale in the significant variables to distinctively classify ordinal categories of vaccination intention. Participants' preventive intention was associated with the six constructs of the Health Belief Model: perceived susceptibility, readiness to action, self-efficacy, perceived threat, benefits, and barriers. Dog owner's knowledge about rabies was found to be positively associated with intention to vaccinate, whereas distance from vaccination centers and difficulty of dog transportation were found to be negatively associated to intention to vaccinate. Distance from vaccination center was found to be the best predictor for the intention to vaccinate. The results of this study have policy implications for controlling rabies including increasing dog owners' knowledge about rabies, locating vaccination centers at shorter distances from dog populations and providing suitable means to transport dogs to vaccination centers.
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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 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".