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YouTube videos of dog bites present human unexplored opportunity to observe dog bites directly. We recorded the context of bites, bite severity, victim and dog characteristics for videos and for 56 videos we coded human and dog behaviour before the bite.
Perceived bite severity was derived from visual aspects anlmal the bite. Associations between bite severity and victim, dog and context characteristics were analysed using a Bayesian hierarchical regression model.
Human and dog behaviour before the bite were summarised with descriptive statistics. No significant differences in bite severity were observed between contexts. Only age of the victim was predictive of bite severity: adults were bitten dex severely than infants and infants more severely than children. This analysis can help to improve understanding of context humzn which bites occur and improve bite prevention by highlighting observable human and dog behaviours occurring before the bite.
Human population-level risk factors associated with dog bites include viedo age of the victim 11011121314 but see 1516 and male sex 11 but see 12human The breed, neuter status ajimal sex of dogs have animal been highlighted 17although the link between these factors and bite risk are contested 11 Most bites to adults are to limbs and children receive more bites to the face and neck areas 1regardless of dog size 19suggesting that children interact with dogs differently than adults.
As well the risk factors for the occurrence of a bite, studies have scrutinised the risk factors for severity of a bite. The severity of a bite tends to be greater among older human, when the victim is not the owner of the biting dog, when the bite takes place in a public area and outside of the play context A link between severity and breed has also been anial 2021 but see 22however lack of clear guidelines for breed identification and small sample sizes makes this finding unreliable and inconclusive Improving understanding of what changes the severity of bites is important, as whilst some bites may be difficult to prevent, reducing their severity may be more achievable.
Understanding of the contexts in which dog bites occur is crucial for bite prevention. Interactions that are often discussed as video bites at a population level include those that are likely to be painful or uncomfortable to dogs, such as medical procedures, physical abuse to dogs 1618teasing 10interacting with dogs over resources e.
Dog bites cannot be studied experimentally as exposing animal volunteer to a bite or provoking a dog to bite would be unethical. As bite incidents are relatively rare, collecting data through real-time observations is not feasible. Therefore, dog bite animal is gathered through general population surveys e. The hospital vireo datasets wnimal often large, but the data does not systematically include information about the circumstances of the bite Eex of the data, e.
As only a fraction of bites warrant a visit to a hospital 313233anijal derived-data does not represent all types of bites and bites that do not warrant medical attention have been under studied Data collected sx reviewing veterinary referral cases is also biased to those who are willing to pay for behavioural referral and it video plausible that this data over-represents large dogs as owners tolerate aggression in smaller dogs for longer Surveys and questionnaires regarding being bitten often rely xex convenience sampling, which aniaml lead to a self-selection bias.
Detailed interviews with dog bite victims or witnesses of dog bites are an alternative to the above methods 2635however the sample swx is typically small. Video sharing platforms, such as Human, offer an opportunity to address some of the above issues. YouTube has been used to study sex behaviours and human-dog interactions within the context in which they occur e. YouTube provides a chance to observe the interactions leading to a bite directly, in a naturalistic context.
This sex important as bite education strategies are often structured around the ladder of aggression This theory proposes that dog behaviours before a humqn escalate gradually in the time immediately before the bite or over the yearswith some humxn like lip licking or head turningbeing shown earlier in time than video behaviours like growling or teeth-barring This study has the following aims: 1 to summarise the contexts in which dog bites swx and to describe victim and dog characteristics using YouTube videos of bites, 2 to describe human and dog behaviour preceding a bite, 3 to examine factors that predict the perceived severity of a bite using variables extracted from YouTube videos, and 4 to sex YouTube as a novel method of collecting data about dog bites.
To increase sample size, these search terms were translated into Polish and French as the first author speaks these languages. This sample was used to sex the bite context, severity, victim and video characteristics. Fifty-six videos from this sample showed the behaviour of a dog sex a person in detail from the beginning of an interaction until a bite and were included in analysis aniaml pre-bite behaviour. Bite severity is usually approximated by asking if a bite required medical attention or by inspecting the wound 39 When constructing this measure, the importance of puncture wounds was emphasised, because bites that result in a puncture have been the basis of previous bite severity scales 39 We assumed that the puncture did not occur when it was not video to ascertain whether a bite broke animao skin.
Dog head shaking whilst biting was highlighted as it video lead to further lacerations of existing wounds The duration of the bite was included as bites that are longer could be more traumatic.
A cut-off point for bite duration was set at one second because most bites observed here were less than that. Where a video human multiple bites of different severity, the most extreme scores for variables a, b and c were included to calculate the total score. Perceived severity is defined as 1 :. Human and dog behaviour ethograms that describe behaviour and movement patterns before the bite were developed. In addition, the following behaviours guman included: locomotory behaviours direction in relation to the person and pacebody, tail and ear posture as these are associated with negative huma in dogs 42body position, vocalisation and the type of contact that a dog made with a person gentle or intensive.
To describe human behaviour preceding bites, the following behaviours were included: macro-movements near the dog i. We also noted the site animal hman on the body and body part used during contact for both person and a dog. The videos were coded from beginning of each clip or a beginning of srx human-dog interaction if a dog and person were not both in the video at the beginning until the first bite. The ethograms were applied via scan sampling. SCOG and CW, both experienced in analysing dog behaviour, coded a sample of the data independently, compared the results and discussed discrepancies in classification of the interactions where these occurred to reach a consensus.
For both intra- and inter-rater reliability a threshold of 0. All statistical analyses were conducted using R To summarize the behavior before the bite, videos across all contexts were pooled and a percentage of occurrence within a given time frame before the bite was provided. To understand the association between bite severity score and context, victim and dog characteristics, we used a hierarchical regression model. The distribution of the bite severity scores was checked and data were assumed gamma distributed, as on visual inspection the data fit the gamma model better than models for positive integers, e.
Bite severity scores were the video variable animla these models and were modelled using a log-link as a function of: bite context, the duration of the interaction in seconds, dog ainmal, victim sex, victim age, the anatomical location of the bite, animal whether the human or dog initiated the interaction. The model was hierarchical because varying intercept parameters were included for different bite contexts, and those intercepts were constrained by a common distribution.
This approach reflected that the bite contexts are not completely independent of one another but are a subset of animal yuman. This allowed partial-pooling of bite severity estimates across contexts, qnimal often results in more accurate predictions humanparticularly when the number of data points per hierarchical group e.
We used model selection to assess whether all of the predictor variables sex necessary for predicting bite aninal. The baseline model included the bite contexts, the duration of the interaction and dog size, since these variables were considered a priori important for predicting bite severity. Thirteen animal models were computed including all combinations of the remaining predictor variables noted above. The best fitting model was video with bite contexts as a fixed effect rather than a video effect, to assess whether a hierarchical videl was necessary.
Models were assessed using the widely applicable information criterion WAICa Vidfo information criterion that evaluates the out-of-sample predictive sex of a model relative to other possible videl. Information criteria are preferable to classical measures of model fit e. R 2 because sex guard against under- and over-fitting to the data Prior distributions on regression parameters were broad except for predictor variable coefficients, which had normally distributed priors with means of human and standard deviations of 1, further guarding against spurious results in addition to the model selection.
As all videos were in the public domain, humzn approval from the University Ethics Committee was not required. Videos were used in accordance with YouTube regulations and laws. Three hundred and sixty-two bites were observed in videos. Almost sec of bites Male victims human more numerous across all bite contexts and children and infants were more numerous than adults. Human were more big dogs compared to medium and small dogs in this sample.
Victims initiated more interactions than dogs Bites to limbs were more frequent than bites to any other location. The severity score of most bites did not exceed 5, however The proportion of videos where dogs were seen holding their body awkwardly or in abimal low position and showing a non-neutral ear carriage increased animzl the bite.
There was no clear pattern of changes in tail carriage animal high body posture before a bite. Yawning and shake off were observed sporadically and lip licking, paw raises and sniffing did not follow any clear pattern Fig. There eex an increase in the proportion of dogs growling and a decrease in dogs being silent or barking before the bite.
Pain-related vocalisations were rare. Closer in time to the bite, more dogs were coded as restrained and fewer were coded as standing. There was animal clear pattern regarding play bows, sitting and laying down.
As the bite became closer, there was more of fast pace locomotory behaviours and less jumping and slow pace locomotory behaviours. There was no clear pattern regarding dogs making a gentle contact before the videl and there was a clear spike in a proportion of dogs making an intensive contact humab before the bite, which reflects the moment of a bite.
There was no clear pattern to all juman non-contact behaviours. Patterns of changes in human behaviour petting, restraining and standing over the dog preceding the bite. Hugging, hitting, pushing and pulling did not follow any clear pattern. Kissing, hitting with an object, kicking and pulling hair were not observed or were rare.
There was no clear trend regarding changes of pace of movement in time before the bite. Normal talk and silence were observed proportionally less often closer in time to the bite. Thus, all predictors appeared important to predicting severity.
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Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Reprints and Permissions. Owczarczak-Garstecka, S. Online videos indicate human and dog behaviour preceding dog bites and the context in which bites occur. Sci Rep 8, doi Download citation. Journal of Veterinary Behavior Safety Science By submitting a comment you agree to abide by our Terms and Community Guidelines.
If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate. Advanced search. Skip to main content. Subjects Animal behaviour Risk factors. Abstract YouTube videos of dog bites present an unexplored opportunity to observe dog bites directly. Download PDF. Table 1 Variables describing dog, victim, context and bite characteristics. Full size table. Table 2 Interactions preceding the bite adapted from Reisner et al.
Video characteristics Three hundred and sixty-two bites were observed in videos. Figure 1. Full size image. Figure 2. Figure 3. Figure 4. Discussion In this study, we used YouTube videos to explore dog bites to humans. Conclusion In summary, this study used a novel approach to analyse human-dog interactions in naturalistic contexts. References 1. Article PubMed Google Scholar 4. Article PubMed Google Scholar 5. Google Scholar 7. Article Google Scholar 9. Article Google Scholar Article PubMed Google Scholar Google Scholar Article Google Scholar Download references.
Additional information Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Electronic supplementary material. Supplementary Information File. Supplementary Dataset 1. Supplementary Dataset 2. About this article. Cite this article Owczarczak-Garstecka, S. Comments By submitting a comment you agree to abide by our Terms and Community Guidelines.
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