Journal of Veterinary Behavior-clinical Applications and Research最新文献

Trazodone hydrochloride is a tetracyclic antidepressant commonly used in human, gaining popularity in feline patients as a pre-appointment anxiolytic and sedative medication. However, the oral administration route in cats poses difficulties for owners and limits practicality. This study evaluated the efficacy and safety of transdermal trazodone in cats. At the first visit, the cat stress score (CSS), global sedation score (GSS), behavioral response score (BRS), and owner-assessed overall experience score (OES) were used to observe and record the behavior during transportation and examination. Thereafter, each cat was given 150 mg of transdermal trazodone before the second visit. The respiratory rate, heart rate, pulse rate, systolic blood pressure, blood test, adverse effects, and response time were compared between the two visits. Thirteen cats were enrolled in this study. Transdermal trazodone significantly lowered CSS of outward trip (P = 0.005) and return trip (P = 0.005) (Wilcoxon signed-rank test). No significant differences were observed in CSS and GSS during the examination. Moreover, the BRS was significantly low (P = 0.018), but the significance varied depending on the examination procedure and behavior. The OES questionnaire showed a significant reduction in stress during the outward trip (P = 0.002), return trip (P = 0.005), and examination (P = 0.003) (all Wilcoxin signed ranks test). Physiologic parameters and laboratory values were not significantly affected, and the adverse effects were few and mild. In conclusion, transdermal trazodone was well tolerated at a single dose of 150 mg/cat. It can reduce stress and anxiety before a veterinary visit, resulting in a better patient-owner experience.

Cat personality may influence adoption choices and future guardian-cat relationship. This study aimed to evaluate the relationships between cat personality and guardian-reported undesirable behaviors after adoption. A questionnaire was sent to guardians of recently adopted cats approaching their doubts, details on cats’ physical characteristics, behavioral events, and cat personality, as assessed by the Qualitative Behavior Assessment. Most of the 133 respondents adopted female cats (60.1%), at most 6 months-old (63.9%). Many guardians reported doubts about initial cat care (75.9%), and 34.6% did not have other cats at home. Half of the guardians were unsure how to introduce the new cat to their other animals (50.4%). Common events included meowing and scratching or biting an adult human (39.1% each). Five cat personality dimensions were identified, with correlations to behavioral events: “agreeableness” with hiding (P < 0.005), not allowing touch (P < 0.005), scratching or biting a child (P = 0.049), and skittishness (P < 0.005); “introversion” with meowing (P = 0.034); “soliciting” with inappropriate urination (P = 0.008); and “aggressiveness” with skittishness (P = 0.013). Households where a resident disliked the adopted cat were correlated with the cat’s young age (P = 0.014). The number of cats in the household was associated with vet visits (P = 0.049), inappropriate urination (P = 0.038), skittishness (P = 0.001), and not allowing touch (P = 0.013). Some post-adoption behavioral events are more common in certain cat personality dimensions and household characteristics. Considering these variables may increase successful cat adoptions.

Collar use in cats is a controversial topic. Cat owners do have very different reasons for either deciding to use a collar on their cat or rejecting collar use. We conducted an online survey on cat management, use of and attitudes toward collars. Our survey participants were mainly women (88.8%), mostly came from Germany (88.2%), and owned 2 ± 2 cats. Collar use was reported by 32.9%. Overall, participants showed significantly higher agreement to the subscale risk perception than to the subscale benefit perception (Z = −56.997, P < 0.001, N = 4940). Participants (N = 318) who reported first-time collar fitting on their cat in the past 2 years used most often plastic breakaway buckles (rounded edges: 44.2%; round with edges inwards: 17.9%; rectangular: 10.4%), non-breakaway buckles were used by 14.4% (plastic: 9.4%; metal: 4.9%). The most common objects attached to the collar were ID tags/tubes (32.4%) and bells (22.1%) and tracker (19.7%). Based on lifetime experience, collar users were older, less often first-time owners, more often allowed their cats free roaming, and had less often professional experience with cats. Agreement to risks was lower than in non-users but still higher than agreement to benefits. In contrast, the perception of benefits outweighed perception of risks in recent collar users. Collar use in the past was strongly associated to risks from entrapment. This suggests that owners are willing to try collars but do not continue to use them over time as they may perceive more risks than benefits.

This article explores the novel application of deep learning methods in the analysis of complex cattle behavior patterns using accelerometer data. With the information provided by accelerometer data regarding the movements of cows, valuable insights into their health, behavior, and overall welfare can be understood. Manual deciphering of these patterns presents an overwhelming challenge owing to the intricate and fluctuating nature of cattle behavior. The principal objective of this research is to construct a deep learning framework that can precisely interpret complex cow behavior patterns and enable more precise and efficient surveillance. To achieve this objective, the input accelerometer data collected during various cattle behavioral instances, such as grazing, lying, walking, and other activities, undergo preprocessing and augmentation. The preprocessed data then undergo a deep learning framework comprised of 23 layers, incorporating convolution layers, batch normalization, rectified linear unit (ReLu), and MaxPooling layers. The model demonstrates promising performance in categorizing cow behaviors based on the unique movement signatures captured by the sensors. Through rigorous evaluation using three distinct datasets, each containing a different number of activities, we achieve high accuracy rates of 96.72%, 87.15%, and 98.7%, respectively. It enhances livestock management by automating behavior analysis, enabling real-time monitoring, and informed decision-making. Improved animal welfare is achieved through early detection of stress or illness, leading to prompt interventions.

This study aimed to develop and validate the Human-Animal Interaction at Work Scale (HAI@WS). This instrument is designed to measure human-animal interactions during work time. We conducted four studies to achieve this goal. First, we developed the scale, followed by a study to explore its factorial structure (N = 1013). The third study analyzed the scale's internal validity and reliability (N = 253). The fourth study was a daily-diary investigation that assessed the criterion validity of the HAI@WS by examining its within-person correlations with measures of performance, satisfaction, and work engagement (N = 145 × 5 = 725). The findings revealed that the three-item scale represented a single factor and is a reliable measure of human-animal interactions in the work context. Additionally, the results indicated that the scale was significantly related to measures of performance, satisfaction, and work engagement at the within-person level. This study fills a research gap by providing a validated measure for assessing human-animal interactions in the workplace, an area previously lacking such tools. The HAI@WS is valuable for managers seeking to evaluate how the presence of pets at work—whether during teleworking or in the office—and the resulting interactions with employees can satisfy biological and psychological needs, thereby promoting positive outcomes such as work engagement and positive affective work-related experiences. This research advances our understanding of human-animal interactions and their impact on individuals and organizations.

The aims of this study were to examine the relationship between lamb and ewe behaviors in postnatal 3-hour and lamb survival using machine learning (ML) algorithms and to determine the best ML classifier to predict lamb survival. The research data consisted of postnatal 3-hour behavior records of 43 Kivircik ewes and their 65 lambs, along with preweaning survival information of lambs. The prediction of lamb survival was performed on three datasets containing different features using decision tree, support vector machine (SVM), multilayer perceptron, logistic regression, random forest (RF), K-nearest neighbors, and boosting (B) ML algorithms. The accuracy, precision, recall, and F1 score values of the RF algorithm were 0.931, and the area under curve value was 0.966 for dataset 1, which included parity of dam, birth type and sex of lamb, and birth weight predictors, as well as postnatal lamb and ewe behaviors as features. In dataset 2, which includes principal component scores instead of lamb and ewe behaviors, the RF approach made classification with an accuracy of 0.909. In dataset 3, which includes the maternal behavior score as a feature, the RF and SVM algorithms showed similar performance (0.909 accuracy). These results indicate that, by using lamb and ewe behaviors in the postnatal 3-hour with ML methods, it is possible to classify lambs as either surviving or dying before weaning with high accuracy. In addition, it was determined that the ML algorithm that best adapted to the current study data was the RF classifier.

The objective was to evaluate the consumption and behavior of recently weaned foals receiving different sources of roughage. Twenty recently weaned foals of the Mangalarga Marchador breed, with an average of 6 months and 135.9kg, were distributed into four groups: corn silage (CS), conventional hay (HAY), pelleted hay (PELET), and haylage (HL). The diets were formulated to meet the requirements of the category and were isoproteic and isoenergetic. The experimental period lasted 110 days, with the first 35 days of adaptation. The dry matter intake was manually measured at the beginning, middle, and end of the twenty foals experiment, and the ingestion and ingestive behavior of ten foals were also evaluated in an automated way (Intergado®). Two behavioral assessments were also performed (START and END) through visual observations at 5-minute intervals for 24 hours. Ingestion and behavior results were analyzed in a randomized block design (RBD) with split plots, and the results recorded by the Intergado® electronic feeder were analyzed in RBD, and the means were compared by Tukey test at 5% of significance. The lowest forage dry matter (FDMI) and total (TDMI) intakes throughout the experiment were from the CS treatment and the highest was from the HAY Similar results were found for FDMI measured by the Intergado® feeder (FDMIi). At the START, the CS and PELET treatments provided the lowest times consuming roughage and the longest times standing idle and performing stereotypical behavior. At the END, the same treatments provided the shortest times in social interaction and the longest times performing stereotypic behavior. PELET continued to be the treatment with the shortest time-consuming roughage. Thus, CS should not be used as a roughage base in diets for recently weaned foals, as it results in lower FDMI and lower TDMI, resulting in longer idle times and higher frequency of stereotypic behavior. The pelleted hay should be used with caution, because in addition to causing less consumption time, longer idle time, and greater frequency of stereotypic behavior, it can cause colic.

Habituation indicates a decrement in response to a specific stimulus by repeated exposure to that stimulus. Responding to or ignoring sound stimuli, which are common background distractors, is important for the undisturbed functioning of the organism, efficient animal management and safe handling. We habituated 20 warmblood horses to a set of distracting sounds and assessed the possibility of reversing this process through simple modifications in sound playback. The study involved three stages: habituation (Stage 1) and two trials of dishabituation (Stage 2, 3). In Stage 1, five different sounds of animals, each on a separate day, were repeatedly (every 20 minutes (min)) played during a stay on an experimental paddock. The sounds were selected out of 40 sounds of different origin based on their distracting effect on the horses (e.g., interruption of previous activity, increase in emotional arousal) during the first exposure to them three months earlier. In Stage 2, four new and unknown sounds (futuristic characteristics) were additionally introduced to the set of habituated sounds, whereas in Stage 3, habituated sounds (from Stage 1) were played from an altered location. Behavioral (e.g., disruption of feeding, duration of feeding, locomotion and standing alert) and cardiac (heart rate and heart rate variability) variables were assessed. Generally, horses quickly habituated to the initially distracting sounds, but great variability was observed in the number of needed playbacks (1–7) for each horse. After completion of Stage 1, the horses responded with an increase in vigilance, locomotion, refeeding frequency and a 1-minute increase in mean heart rate to novel but not to known sounds. None of the modifications resulted in a recovery of previously habituated reactions. After introduction of playback modifications, only maximum heart rate (in Stage 2, Stage 3) and time of standing alert (in Stage 3) increased after re-exposure to sounds horses had been habituated to, suggesting some level of vigilance. However, this response was too weak to conclude about dishabituation. The results of the study confirm sound recognition and the fast and persistent audio habituation in horses.