Communication Strategies for Tick-Borne Disease Prevention Among US Cattle Producers: Quasi-Experimental Study on Message Framing and Source Credibility
Bibliographic record
Abstract
Background: Haemaphysalis longicornis (Asian longhorned tick) presents a growing threat to cattle health in the United States, causing anemia, weight loss, and even death. Despite the expanding distribution of this tick and the need for prevention, there is limited research on how to effectively communicate tick-borne disease risks to agricultural communities, particularly cattle producers. Social media represents a potentially impactful channel for risk communication; however, its utility and optimal message design for this population remain insufficiently understood. Objective: This study aimed to evaluate the effectiveness of various digital communication strategies in influencing US cattle producers' engagement, risk perceptions, and self-reported preventive intentions regarding tick-borne diseases. Methods: A quasi-experimental study with a 2×3 factorial design was conducted with 116 cattle producers in the United States. Participants were randomly assigned to view simulated Facebook posts that varied by message source (extension agent vs cattle producer) and message framing (prevention-oriented, fear-based, or neutral). Participants reported their likelihood of engaging with the post (using an emoji reaction, commenting, or sharing), their perceptions (fear and attitudes), and their intention to adopt preventive behaviors. Data were analyzed using descriptive statistics, ANOVA, and Spearman rank-order correlations. Results: Across all groups, participants showed a clear preference for low-effort engagement, most frequently using emoji reactions rather than commenting or sharing. Descriptive trends suggested that posts from cattle producers, especially those framed as prevention oriented, elicited higher mean engagement. Prevention-oriented messages were also associated with greater concern about tick risks and more favorable attitudes toward prevention. As reflected in the qualitative feedback, fear-based posts were often viewed as exaggerated or less credible. Social media engagement showed moderate correlations with attitudes (ρ=0.52-0.64) and preventive intentions, with attitudes more strongly associated with behavioral intent than fear. Conclusions: This study provides preliminary evidence that prevention-oriented digital messages, especially when shared by credible sources, may foster more positive attitudes and greater willingness to undertake tick prevention among cattle producers, compared to fear-based or neutral content. The findings highlight the need for balanced, context-rich messaging tailored to the preferences and realities of agricultural audiences. By integrating quantitative and qualitative results, this study informs the design of more effective social media-based interventions for tick-borne disease prevention in agricultural settings.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".