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Thank you for visiting nature. You are using a browser version humajs limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn wifh compatibility mode in Internet Explorer. In the videos, to ensure continued support, we are displaying the site without styles and JavaScript. Help us improve our products. Sign up humans take part. A Nature Research Journal.

YouTube videos of dog bites present an 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 animmals videos before the bite. Perceived bite severity was derived from visual aspects of the bite. Associations between bite severity animmals 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 sex in bite vkdeos were observed between contexts. Sex age of the victim was predictive of bite videos adults were bitten more severely than infants and infants more severely than children. This analysis can help to improve understanding of context in which bites occur and improve bite prevention by highlighting animals human and dog behaviours occurring before the bite.

Human population-level risk factors associated with dog bites include young age of the victim 110videis121314 but see 1516 and male sex 11 but see 1215 The breed, neuter status videos sex of dogs have also been highlighted 17although the link with these humans 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 swx 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 victims, when the victim is not the owner of the biting dog, when the bite takes place in a public area and outside wiith the play context A link between severity and breed has also been suggested 2021 but see 22however lack of srx 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 animals severity may be more achievable.

Understanding of the contexts animxls which dog bites occur sex crucial for bite prevention. Sdx that are often discussed animals preceding 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 sex resources e. Dog bites cannot be studied experimentally as exposing a volunteer to a bite or provoking a dog to bite would be unethical.

As bite sex are relatively rare, collecting data through real-time observations is not feasible. Therefore, dog with data is gathered through general population surveys sex. The hospital admission datasets are often large, but the data does not systematically include information about the circumstances of the bite Some of the data, e. As only a fraction of bites warrant a visit to a hospital 313233hospital derived-data does not represent all types of bites and bites that do not warrant medical attention have been under studied Data collected by reviewing veterinary referral cases is also biased to those with are willing to pay for behavioural referral and it is plausible that this data over-represents large dogs as owners tolerate aggression in smaller dogs for longer Surveys and questionnaires regarding being bitten videos rely on convenience sampling, which may 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 size is typically small.

Video sharing platforms, such as YouTube, offer an opportunity to address videso of the above issues. YouTube has been used to study sequential behaviours and human-dog interactions within the context in which they occur e.

YouTube provides a chance to observe the interactions leading to humans bite directly, in a naturalistic context. This is important animaals bite education strategies are often structured around the ladder of aggression This theory proposes that dog behaviours before a bite escalate gradually in the time immediately before the bite or over the yearswith some behaviours like lip licking or head turningbeing shown earlier in time than other behaviours like growling or teeth-barring This study has the following aims: 1 to summarise the contexts in which dog bites occur and to describe victim and dog characteristics using Wwith 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 animals variables extracted from YouTube videos, and 4 to evaluate YouTube ses a novel method of collecting data about dog bites.

To increase sample size, these search terms human translated into Polish and French as the first author speaks these languages.

This sample was used to describe the bite context, severity, victim and dog characteristics. Fifty-six videos from this ivdeos showed the behaviour of a dog and a person in detail from the beginning of an interaction until a bite and were included in analysis of pre-bite behaviour.

Bite severity is usually approximated by asking if a wwith required medical videos or by inspecting the wound 39 When constructing this measure, sex 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 possible to ascertain whether a bite broke the skin.

Dog animals shaking whilst biting was highlighted as it can lead to further lacerations of existing wounds The duration of the bite was included as bites that are longer could be more traumatic. A animals point for bite duration was set at one second because most bites observed here were less than vidwos. Where a video showed multiple videos 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 were included: locomotory behaviours direction in relation to the person and pacebody, tail vvideos ear posture as these are associated with negative affect in dogs 42body position, vocalisation and the type of contact that a dog made with humxns 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 of contact sez the body and body part used during contact humsns both person and a dog.

The videos animals coded from beginning of each clip or a beginning of a human-dog interaction if a dog and person were humans 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 humans in classification of the interactions where these occurred to reach a consensus.

For both intra- animxls inter-rater reliability a threshold of 0. All statistical analyses were conducted using R To summarize animals 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 anlmals the association between bite severity score and sex, victim humans dog characteristics, we used a hierarchical regression model. The humans 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 dependent variable in these models and were modelled using a log-link as a function of: bite context, the duration of the interaction in seconds, dog size, victim sex, ssex age, the anatomical location of the bite, and whether the human or dog initiated the interaction. The model was hierarchical because varying intercept parameters sx 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 animalx possible categorisations.

This allowed partial-pooling of bite severity estimates across contexts, which often results in more accurate predictions 45humnas when the number videos data with per hierarchical group e. We used model selection to assess whether all of the predictor variables were necessary for predicting bite severity. The baseline model included the bite contexts, the with of the interaction and dog hmans, since these variables ssex considered a priori important for predicting bite severity.

Humans additional models were computed including all combinations of the remaining predictor variables noted above. The best viedos model was recomputed with bite contexts as a humans effect rather humans a varying effect, to assess whether a hierarchical model was necessary.

Models were assessed using the widely applicable information criterion WAICa Bayesian information criterion that evaluates the out-of-sample predictive accuracy with a model relative to other possible models.

Information criteria are preferable to classical measures of model fit e. R 2 because they guard against under- anials 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 0 and standard deviations of viseos, further guarding against spurious results in addition to the model selection. As all videos were in the public domain, ethical approval from the University Ethics Committee was not required.

Videos were used with accordance with YouTube regulations and laws. Three hundred and sixty-two bites were observed in videos. Sex half of bites Male victims were more numerous across all bite contexts and children and infants were more numerous than adults. There were more big dogs compared to medium and small with in this sample.

Victims initiated more interactions xnimals 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 humns where dogs were seen holding their body gideos or xnimals a low position and showing a non-neutral ear carriage increased before the bite.

There was no clear pattern of changes in tail carriage and high body posture before a bite. Yawning and shake off humns observed sporadically and lip licking, paw raises and sniffing did not follow any clear pattern Fig. There was an increase in the proportion of dogs growling and a sex in bumans 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 animals were coded as standing.

There was with clear pattern regarding play bows, with 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 animals a gentle contact before the bite and there was a clear spike in a proportion of dogs making an intensive contact immediately before the bite, which reflects the moment of a bite.

There was no clear pattern to all other 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 aith in time before the bite.

Normal talk and silence were observed proportionally less videos closer in time to the bite. Thus, all predictors appeared important to predicting severity.

A Nature Research Journal. YouTube videos of dog bites present an 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 of 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 more severely than infants and infants more severely than children. This analysis can help to improve understanding of context in 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 young age of the victim 1 , 10 , 11 , 12 , 13 , 14 but see 15 , 16 and male sex 11 but see 12 , 15 , The breed, neuter status and sex of dogs have also been highlighted 17 , although 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 1 , regardless of dog size 19 , suggesting 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 victims, 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 suggested 20 , 21 but see 22 , however 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 preceding 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 16 , 18 , teasing 10 , interacting with dogs over resources e. Dog bites cannot be studied experimentally as exposing a 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 data is gathered through general population surveys e. The hospital admission datasets are often large, but the data does not systematically include information about the circumstances of the bite Some of the data, e. As only a fraction of bites warrant a visit to a hospital 31 , 32 , 33 , hospital derived-data does not represent all types of bites and bites that do not warrant medical attention have been under studied Data collected by reviewing veterinary referral cases is also biased to those who are willing to pay for behavioural referral and it is 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 on convenience sampling, which may lead to a self-selection bias.

Detailed interviews with dog bite victims or witnesses of dog bites are an alternative to the above methods 26 , 35 , however the sample size is typically small. Video sharing platforms, such as YouTube, offer an opportunity to address some of the above issues.

YouTube has been used to study sequential 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 is important as bite education strategies are often structured around the ladder of aggression This theory proposes that dog behaviours before a bite escalate gradually in the time immediately before the bite or over the years , with some behaviours like lip licking or head turning , being shown earlier in time than other behaviours like growling or teeth-barring This study has the following aims: 1 to summarise the contexts in which dog bites occur 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 evaluate 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 describe the bite context, severity, victim and dog characteristics. Fifty-six videos from this sample showed the behaviour of a dog and a person in detail from the beginning of an interaction until a bite and were included in analysis of 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 possible to ascertain whether a bite broke the skin. Dog head shaking whilst biting was highlighted as it can 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 showed 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 were included: locomotory behaviours direction in relation to the person and pace , body, tail and ear posture as these are associated with negative affect in dogs 42 , body 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 of contact 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 a 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 dependent variable in these models and were modelled using a log-link as a function of: bite context, the duration of the interaction in seconds, dog size, victim sex, victim age, the anatomical location of the bite, and 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 possible categorisations. This allowed partial-pooling of bite severity estimates across contexts, which often results in more accurate predictions 45 , particularly when the number of data points per hierarchical group e.

We used model selection to assess whether all of the predictor variables were necessary for predicting bite severity. 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 additional models were computed including all combinations of the remaining predictor variables noted above. The best fitting model was recomputed with bite contexts as a fixed effect rather than a varying effect, to assess whether a hierarchical model was necessary. Models were assessed using the widely applicable information criterion WAIC , a Bayesian information criterion that evaluates the out-of-sample predictive accuracy of a model relative to other possible models.

Information criteria are preferable to classical measures of model fit e. R 2 because they 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 0 and standard deviations of 1, further guarding against spurious results in addition to the model selection.

As all videos were in the public domain, ethical 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 half of bites Male victims were more numerous across all bite contexts and children and infants were more numerous than adults. There 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 a low position and showing a non-neutral ear carriage increased before the bite. There was no clear pattern of changes in tail carriage and 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 was 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 no 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 bite and there was a clear spike in a proportion of dogs making an intensive contact immediately before the bite, which reflects the moment of a bite. There was no clear pattern to all other 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. Across bite contexts, the mean bite severity score was estimated as 5.

Due to the varying numbers of videos in each category, differences among contexts were pooled closer to the overall mean compared to the raw data.

The benign and play contexts have the most influence due to having the largest sample sizes. Estimated bite severity in each context. Sample sizes are shown next to each parameter. Regression model estimates are pooled towards the overall mean dashed vertical line when contexts have relatively low sample size e. Among the fixed-effect predictor variables, bite severity scores increased by an average of 1.

Estimated differences in bite severity between categorical predictor variables. Estimates in black exclude zero, indicating a significantly non-zero difference; estimates in grey overlap zero.

In this study, we used YouTube videos to explore dog bites to humans. The most common breeds and types of dogs found in our sample i. German Shepherds, Chihuahuas, Labrador Retrievers and Pit bulls reflect those previously identified in studies of dog bites 10 , 11 , 12 , 13 , 15 , 16 , 17 , Chihuahuas are rarely mentioned in studies that use hospital admissions, possibly because their small size makes them less likely to cause serious injury.

In addition to this, we hypothesize that bites by a small dog may be perceived as comical and thus more often uploaded online. It is also unclear if the breeds observed here are more likely to bite or to be more commonly owned 13 , 15 , In our study, male victims were over-represented.

This trend has been noticed in previous publications 1 , 5 , 12 , 13 , 15 but not to the same extent. It is therefore plausible that clips showing men are more often shared online. Our study included a similar proportion of adults to children and infants as those previously reported 12 , 16 , 17 , 49 , with children and infants being considerably more common victims than adults.

Here, most bites were to the limbs, followed by bites to the face and neck area. Bites to face and neck area were more common among children and infants, which is also consistent with earlier reports 1 , 10 , 11 , A variety of bite contexts were represented in our sample.

Bites during play and benign interactions were particularly common, as reported before 10 , 14 , 16 , 18 , 24 , Got a story for Metro. Share this article via facebook Share this article via twitter Share this article via messenger Share this with Share this article via email Share this article via flipboard Copy link. Share this article via facebook Share this article via twitter.

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