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Record W4417135396 · doi:10.2196/77239

Communication Strategies for Tick-Borne Disease Prevention Among US Cattle Producers: Quasi-Experimental Study on Message Framing and Source Credibility

2025· article· en· W4417135396 on OpenAlexvenueno aff
Cheng-Xian Yang, Lauri M. Baker, Jessica Czipulis

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Relations and Crisis Communication
Canadian institutionsnot available
FundersCenters for Disease Control and Prevention
KeywordsCredibilityFraming (construction)Psychological interventionSource credibilityRisk communicationQualitative researchDisease prevention

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.081
GPT teacher head0.481
Teacher spread0.401 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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