Swine veterinarians' awareness, attitudes, and intention to recommend precision livestock farming technologies to clients

Engineering notes

Veterinarians intending to recommend PLF reported significantly higher Expected PLF Impact, PLF Cost Perception, PLF Subjective Norms, and PLF Help Wanted scores than those who did not recommend (all p < 0.05).

Chinese explanation / 中文解读

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Original abstract

Introduction Precision Livestock Farming (PLF) technologies offer substantial promise for enhancing animal welfare, productivity, and disease detection in commercial swine production. Swine veterinarians hold a critical advisory role in bridging the gap between the technical evidence base for PLF and on-farm adoption decisions. Yet, the psychological and contextual factors that predict veterinarians' intention to recommend PLF to their clients remain poorly understood in the literature. Methods Using survey data from a convenience sample of 61 U.S. swine veterinarians recruited across four professional meetings (July 2022–July 2023), we used a TPB-informed framework to model PLF recommendation intention and veterinarian-reported current client PLF use. Because perceived behavioral control was not directly measured, the analysis represents a partial rather than full operationalization of TPB. Five TPB-aligned constructs—PLF Awareness, Expected PLF Impact, PLF Cost Perception, PLF Subjective Norms, and PLF Help Wanted—underwent preliminary construct validation using exploratory factor analysis (EFA) with Kaiser–Meyer–Olkin (KMO) and Bartlett's sphericity diagnostics, supplemented by Cronbach's α and McDonald's ω (all α ≥ 0.70). Hierarchical binary logistic regression models were estimated for two outcomes: (A) veterinarian intention to recommend more PLF to clients, and (B) whether any of the veterinarian's clients currently use any PLF technology. Mann–Whitney U -tests examined construct differences between outcome groups; given the modest n , results are reported as exploratory and uncorrected p -values are flagged for caution against multiple testing. Results PLF Help Wanted ( M = 3.91) and Expected PLF Impact ( M = 3.78) received the highest mean scores; PLF Cost Perception ( M = 2.95) was near the scale midpoint, reflecting ambivalence about financial investment. Of 55 respondents who answered the recommendation question, 74.5% intended to recommend more PLF. Veterinarians intending to recommend PLF reported significantly higher Expected PLF Impact, PLF Cost Perception, PLF Subjective Norms, and PLF Help Wanted scores than those who did not recommend (all p < 0.05). The full logistic regression model for recommendation intention (Model A3) explained 51.0% of variance (Nagelkerke R 2 = 0.510). Adding current client PLF use provided no incremental predictive value (Model A4 vs. A3: AIC 44.0 vs. 44.1; lower AIC = better fit; ΔAIC = 0.1 is negligible). For Outcome B (veterinarian-reported current client PLF use), PLF Awareness was the only psychological predictor reaching statistical significance under conventional maximum-likelihood standard errors (Model B2: OR = 3.07, 95% CI: 1.09–8.62, p = 0.034); however, this association was not robust to HC3 heteroscedasticity-consistent standard errors ( z = 1.43, p _robust = 0.153) and is therefore presented as an exploratory association requiring confirmation in larger samples. Discussion U.S. swine veterinarians in this convenience sample show heterogeneous engagement with PLF. Evaluative beliefs about PLF impact and cost-effectiveness, perceived norms, and recognition of client need for PLF emerge as candidate modifiable targets for extension and professional development. Cost perception was near the scale midpoint and warrants explicit attention in PLF outreach. As an exploratory, partially TPB-grounded study with limited statistical power, these findings should be interpreted as hypothesis-generating and require confirmation in larger, nationally representative samples.

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