Since the inception of equitation science, there have been many predictions by researchers that this discipline will produce multiple benefits to horses and the humans interacting with them. These predictions fall into five broad categories: Welfare, Safety, Training, Economics, and Relationship. Each of the categories are closely related, and so each of these claims also depend on and support one another. After more than ten years of research in these areas, many of these predictions of the benefits of equitation science remain founded on anecdotal evidence and logic, though some evidence has been garnered from research. The subject of horse welfare has been the most studied in relation to equitation science, consistently showing expected welfare benefits of equitation science. Relationship and economics are the least studied with respect to elucidating the benefits of employing equitation science principles, while the benefits of the most immediately applicable categories of safety and training have received little support from the literature. A review of the equitation science literature, and an evaluation of the claims made, has been undertaken to determine whether the predicted benefits have materialized in practice as well as to identify opportunities for further research that will demonstrate more conclusively the benefits claimed by equitation science practitioners.
Keywords: equitation science, welfare, safety, training, economics, relationship
Measuring interactions between horses and their handlers and riders has been recently popularized by the maturing discipline of equitation science (McGreevy, 2007). Equitation science is based on learning theory and seeks to measure interactions between horses and humans with the goal of determining what practices are useful for improving these interactions (McGreevy and McLean, 2010). It is not, therefore, a horse training method. These human-horse interactions are the subject of a review by Hausberger et al (2008) who suggest that relationships are built upon previous interactions, with an overall positive interaction building a positive step for the relationship, and an overall negative interaction doing the opposite. They posit that understanding learning rules would help to facilitate positive interactions. Having a relationship with a horse tends to produce an interest in the horse’s welfare, which Baragli et al (2015) evaluate in terms of equine learning. The ability of horses to learn affects their usefulness in the horse industry’s economy (Murphy and Arkins, 2007; Olczak et al, 2016) and the safety of the horse and handler during all interactions (Waran et al, 2002).
Since the inception of equitation science, many predictions have been made by researchers that this discipline will produce benefits to horses and the humans interacting with them. These predictions fall into five broad categories: Welfare, Safety, Training, Economics, and Relationship. Much of the support for these claims comes from the researchers’ logical deductions from their study findings and their own experience. After more than ten years of such studies and predictions, it is reasonable to begin investigating whether or not equitation science is fulfilling the roles expected of it. If equitation science indeed improves welfare, the appalling behavioural wastage rate of horses could be reduced. If equitation science improves safety, the unacceptable injury rate to riders could be diminished. If equitation science improves training, horses could be more easily and effectively trained, leading to improved usefulness and better economics. Finally, if equitation science improves human-horse relationships, all other categories could be positively affected. This review examines the equitation science literature regarding the claims made about the benefits of using the principles set forth. The purpose of this review is to determine whether these benefits are being realized in practice, as well as to identify opportunities for further research to elucidate whether or not equitation science has conferred a net benefit on the horse industry.
The most oft-cited claim in the literature discussing equitation science is improved equine welfare. According to Thompson and Haigh (2018), the very aim of equitation science is to improve welfare. Animal welfare is related to the quality of an individual’s life (Waran, 2002), and involves the animal’s caretaker making ethical, moral, and aesthetic decisions (Thompson and Haigh, 2018). It is proposed that when horse handlers understand and use the 10 first principles of equitation science (ISES, 2017), the limitations of the horse will be understood and its behaviour will be interpreted and responded to appropriately by the handler (Ladewig, 2007), resulting in improved welfare (Starling et al, 2016). Equitation science is also said to remove emotiveness from welfare debates (Goodwin et al, 2008), to create standardized methods of research (Pierard et al, 2015), and reduce wastage of horses to abattoirs for behavioural reasons (McGreevy and McLean, 2007; Warren-Smith and McGreevy, 2008; Doherty et al, 2017). Wastage is currently estimated at 6% for the racehorse population, and better foundation training is cited as a way to reduce this rate (Hayek et al, 2005). The concept of ethical equitation, proposed by Jones and McGreevy (2010), is based on an understanding of learning theory which underpins equitation science. All of these claims concerning the relationship between equitation science and welfare follow logically, and the relationship between normal equid behaviour and good welfare has been established (Waran et al, 2007).
The modified five domains model has been proposed as an accurate measure of equid welfare during common interventions (McGreevy et al, 2018). These five domains––nutrition, environment, health, behaviour, and mental state––are discussed below to demonstrate how equitation science is applied in each welfare domain. A weakness of this assessment tool is that it focusses on the absence of negative events, conditions, and affective states, but while these are often taken as an indication of positive affective states and excellent welfare (Hotzel et al, 2019) this may not necessarily be the case. A further refinement of the modified five domains model to include the presence of positive affective states (McGreevy et al 2018), positive events, and conditions may provide a more complete picture of a horse’s well-being during normal care and management.
Nutrition: Food or water deprivation is still practiced by some horse trainers as a means of punishing a horse or producing desired behaviour (McLean and McGreevy, 2010). Dehydration or hunger can reduce flight responses, causing a horse to become more compliant. However, nutritional deprivation is contraindicated by equitation science principles because there is unlikely to be any lasting training effect. These practices can also cause painful damage to internal organs, as cumulative food deprivation for 72 hours causes gastric ulceration (Murray and Grady, 2002) and the immune system is also negatively affected (Naylor and Kenyon, 1981).
Environment: Assessing the welfare impact of training, housing, and health interventions on the horse is said to be aided by a knowledge of equitation science, and should be the first step in deciding whether or not to apply a specific intervention to a horse (McGreevy et al, 2018). An appropriate environment is one the horse can adapt to, and which influences learning and behaviour positively (Heitor and Vicente, 2007; Sankey et al, 2010). When a horse is unable to adapt to the environment it is in, depressive behaviour can arise from its inability to perform natural behaviour (Baragli et al, 2015).
Health: Animal welfare includes behaviour medicine, in which veterinarians are expected to participate. Training and restraint methods that do not align with learning principles laid out in equitation science negatively affect welfare (Doherty et al, 2017). Good health and welfare are not affected only by disease (Derksen and Clayton, 2007) but other factors including environment and mental state, so it is predicted that veterinarians receiving training in equitation science will improve the welfare and health of their patients (Pierard et al, 2015).
Behaviour: Making learning theory (McCall, 2007), on which equitation science is based, and a knowledge of equine learning processes accessible to horse handlers is claimed to improve welfare (Heitor and Vicente, 2007; Warren-Smith and McGreevy, 2008) by helping people avoid training techniques that do not align with learning (McLean and McGreevy, 2010). These misaligned techniques can cause undesirable behaviour (Fenner et al, 2019a) including conflict and avoidance, which use of the principles of equitation science is said to mitigate (Warren-Smith and McGreevy, 2008; McLean and Christensen, 2017). Interventions that affect learning processes also affect safety and welfare (Fenner et al, 2019b). This is why Hartmann and co-workers (2019) studied the transference of leadership in horse herds to human-horse interactions. They conclude that welfare would be safeguarded through a better understanding of equine social behaviour instead of relying on the currently popular models of leadership and dominance.
The implications of improper training on horse welfare are shown by McLean (2005a) in correlations between poor trained responses and unwelcome behaviours. In-hand responses that were not immediate from a light cue often corresponded with similarly latent responses under saddle. He found that some latent responses were highly predictive of certain unwanted behaviours, for example, all 50 horses in the study with a sometimes incorrect deceleration response under saddle would also bolt. These correlations are also the subject of a review by Baragli et al (2015), who call for increased levels of competence in horse training based on learning theory.
Mental State: The importance of this final category is highlighted by the work of Mendl and Paul (2008) who conclude that understanding animals’ mental experiences is an asset to assessing welfare. According to these scientists, there are grounds to believe that horses may have an emotional memory whereby certain stimuli linked to a past event can trigger an emotional response. Because horse training relies on negative (removal) reinforcement and therefore aversive stimuli (McLean and Christensen, 2017) it is posited that horses trained to respond to light versions of these cues will experience improved welfare as they have perceived control over the amount of pressure used (Fenner et al, 2019b). It is known that horses value safety (McGreevy et al, 2014) and comfort, motivating them to find a way to remove fear or pain-inducing stimuli. When this motivation is constantly thwarted through poor timing of reward or misuse of cues to achieve a response other than the one trained, the horse may become overreactive or apathetic and welfare is affected (McLean, 2005b). Thus, when the principles of equitation science are applied correctly by the handler, improved mental state during training and riding is expected. Only one study has preliminary results demonstrating the correlation between science-based housing, handling, and care, and improved welfare. King et al (2019) cited zero foal injuries during early training while using the principles of equitation science, which is a sign of good welfare, as is the absence of fear and conflict behaviour through an ethologically aligned training program (ISES, 2017). However, welfare is multi-faceted and is difficult to measure accurately (McGreevy et al, 2018), and more data is needed to be able to confirm the welfare implications of certain training and management practices (McLean and McGreevy, 2010).
The prediction of improved safety of horse and human is also commonly found in the equitation science literature (Hawson et al, 2010). This is an important claim, as the dangerous nature of equestrian sport is well documented. A review of equestrian injury rate studies showed that the number of serious injuries per contact hours range from 1 per 350 hours to 1 per 1000 hours (Sorli, 2000). In their own study of hospital admissions and mortality associated with equestrian activities, Sorli (2000) measured a rate of only 0.49 serious injuries per 1000 contact hours, potentially due to the limited geographic area studied. While one retrospective study reported that the injury rate lessened over the 20 year period between 1990–2010 and attributed this to improved safety standards (Hasler et al, 2011), others found no reduction within certain riding populations, particularly rural or ‘cowboy’ cultures (Newton and Nielsen, 2005).
The unpredictability of horses is cited by many authors as a major contributing factor in equestrian injury, with horse behaviour accounting for 25% (Hausberger et al, 2008) to 70% (Finch and Watt, 1996) of accidents. Despite this, most authors propose helmet use as a solution (Winkler et al, 2016) which, while effective in reducing the severity of trauma (Lim et al, 2003), does nothing to modify potentially dangerous horse behaviour. Alternatively, Thompson et al (2015) and O’Connor et al (2018) suggest that training the rider to understand horse behaviour will reduce the injury rate. None of these studies, however, were designed to determine if the suggested preventative measures were effective, as they focused on determining risk factors. In regards to unpredictable behaviour, Ladewig (2019) notes the importance of body language in equine communication and explains how accurate interpretation of body language through an understanding of equine ethology can be used to predict a horse’s intentions with enough time for the handler or rider react appropriately, preventing accident or injury. Zuckerman et al (2015) concur, adding that horses older than 15 years are safer. Nevertheless, based on the large percentage of behaviour related injuries, Hasler et al (2011) propose training riders in safe practices and proper handling, and providing education in horse behaviour as the way forward to reduce handler injury. This proposal is supported by the work of Mayberry et al (2007), who found that risk of injury decreased with level of experience and education about horses, and whose findings were corroborated by Gronqvist et al (2017). Zuckerman and coworkers (2015) also found that most injuries occurred in recreational settings, suggesting that the experience afforded by being a professional equestrian acts as a safeguard. Guyton et al (2013) cite a healthy relationship with the horse as being a preventative strategy, but note: “There is a prominent subjective element to the development of the horse and rider relationship.” The authors do not seem content with this element of subjectivity, and equitation scientists claim this subjective statement is not entirely true (Hausberger et al, 2008; Sankey et al, 2010; Dalla Costa, 2015).
Thompson et al (2015) argue that horses can be made more predictable, and point out that risk is typically viewed as being imposed by the horse on its rider, and that safety is only for humans. This is poignantly clear when Safe Work Australia (2014) listed unpredictable behaviour and poor training as the problem of the horse. Instead, Thompson et al (2015) note it is often the horse’s innate drive for safety that sparks unpredictable behaviour. Mendl and Paul (2008) agree that understanding what is important to horses would improve handler safety, and McGreevy and Murphy (2009) add that this will improve safety for the horse as well. O’Connor et al (2018) see the value of this approach in their study of horse riding injuries in Victoria, Australia, proposing that a refocus on injury prevention should include improvement in the predictability of horses, a goal that proper training using the principles of equitation science could accomplish (McGreevy, 2007).
Trigg et al (2015) posit that when owners assume they have a strong bond with their pet they may be more likely to become complacent regarding safety measures. With a horse owner this behaviour may manifest as a lack of helmet use when there is an assumption of mutual trust between owner and horse; in trainers the perceived bond could influence the method used, particularly if the trainer assumes the horse knows what is required of it. Gielen and Sleet (2003) agree that human behaviours that give rise to injury are preventable using behaviour science. Complacency that ultimately led to human injury has been documented. Newton and Nielsen (2005) studied rider injuries and found that 38% were preventable because they were caused by rider carelessness or inappropriate horse/rider combination. In 69% of the cases studied by Hasler et al (2011), unpredictable horse behaviour such as taking fright, bucking, refusing a jump, or having a nervous disposition were cited by injured participants as the cause of injury.
McGreevy and McLean (2007) state that adherence to the 10 principles of equitation science (ISES 2017) would improve safety, since all training is based on associative and non-associative learning and, therefore, a knowledge of ethology and learning theory as presented in the principles would improve consistency and predictability in the horse, allowing the trainer to predict its responses (Creighton, 2007). Starling et al (2016) agree, saying that by using equitation science to train horses in alignment with their cognitive and physical abilities human safety will be improved. They discuss how certain training methods that do not align in this way exacerbate unpredictable behaviour. The 10 principles are proposed as the safety solution, particularly those related to minimizing arousal levels and conflict, which is also corroborated by the work of Fenner et al (2019a) in regard to safety during round pen training.
With respect to training, Warren-Smith and McGreevy (2008) add that only 11.9% of riding instructors who responded to their survey were able to correctly explain the use of negative reinforcement in horse training, which is the primary training modality of horses (McCall, 1990). They and DeAraugo et al (2016) argue it is likely that injury rates would decrease with increased understanding of these learning processes amongst those who educate riders. Preshaw et al (2017) see the value of this education for those working in horse rescues, where horses are likely to be in distress and potentially more dangerous, and Baragli et al (2015) foresee the same benefit for owners, breeders, and veterinarians.
While Hawson et al (2010) also look for improved predictability from the use of equitation science, to date there is only one study that comes close to providing evidence of this prediction (King et al, 2019). The study shows a zero injury rate to the horses involved in equitation science-based training, but makes no mention of the injury rate for handlers. With respect to handler injuries, the preventative effect of equitation science is also assumed by Thompson and Haigh (2018), who note that confusion about equitation science in the horse community will hinder its uptake, inhibiting improvement in safety and welfare. McLean and Christensen (2017) point out that interest in ethical training practices that promote safety may be expanding, and now is a good time to establish principles that lessen the unpredictable behaviours of conflict and avoidance.
The ‘evidence-based enlightenment’ (McLean and McGreevy, 2010) of using equitation science is predicted to unify horse training (Goodwin et al, 2009), and create more effective training with better and more predictable outcomes. This arises through a clear understanding of equine learning processes, allowing the trainer to avoid techniques with questionable or detrimental effect while leveraging learning theory to best advantage (McLean and McGreevy, 2010). The principles should, in theory, explain the mechanics behind all training methods, explaining why some training tactics work and why others do not (Goodwin, 2007; Goodwin et al, 2009). Use of equitation science principles is predicted to speed up the training process (King et al, 2019) through application of clear and consistent methods. Preshaw et al (2017) cite a reduction in flight and defence behaviours from an understanding of these principles, which could influence the speed of learning.
Goodwin et al (2009) logically make the point that effective and humane training relies on knowledge, as knowledge of how to communicate consistently leads to fewer misunderstandings, and fewer misunderstandings results in less confusion for the horse (McGreevy, 2007). Effective training improves horse behaviour, creating a safer, more useful animal (Derksen and Clayton, 2007). Humane training involves the avoidance of fear (Preshaw et al, 2017; McGreevy et al, 2014) and conflict (Goodwin et al, 2009). Some training interactions, however, are necessarily aversive, for example, initial training can be stressful for a young horse (McGreevy et al, 2014). Hausberger et al (2008) propose that by using the principles of learning theory to create a better relationship through sensitive communication (Goodwin et al, 2009) these aversive interactions can be balanced with positive ones for an overall positive relationship.
It has also been suggested that the ability to predict horse behaviour may be a trait of those knowledgeable in equitation science (Doherty et al, 2017). Ladewig (2019) claims that these predictions may be made by observing horse body language, or perhaps ideomotoric responses, which he posits may be present in all mammals. Predictions of this sort would allow the trainer to preempt dangerous behaviour and modify techniques (Creighton, 2007) to ensure the horse remains within trainable arousal levels––levels which have yet to be defined (Olczak et al, 2016). Gronqvist et al (2017) note a difference in the ability of veterinary students to predict horse behaviour is correlated to their level of horse-related experience, where those with less experience struggle to foresee dangerous situations and respond accordingly. While they suggest that equitation science is not the only tool that offers these benefits, it may speed up acquisition of this skill.
Starling et al (2013) propose that use of equitation science principles helps avoid negative affective states during training. When a horse’s expectations of the outcome of certain behaviours or events are not met, the difference between expected outcome and actual outcome produces frustration (Olczak et al, 2016). Negative moods can create aggression and long term negative affective states (Dalla Costa et al, 2015), and punishment can contribute to this state as well (Mills, 1998). In these states, the horse is monitoring a perceived threat and is ready to react to protect itself. In contrast, when in a positive affective state, induced in this study with Equine Appeasing Pheromone, horses showed increased attention and better recall of learned behaviours with fewer mistakes (Mengoli et al, 2014). Starling et al (2013) point out that awareness of affective and arousal states will increase effectiveness of training and assist in prediction of behaviour. In addition to increasing effectiveness of training (Ladewig, 2019), predicting behaviour is expected to reduce injury (Creighton, 2007; Hausberger et al, 2008; Ladewig, 2019). Finch and Watt (1996) also claim that predicting behaviour would improve safety, although their evidence is largely anecdotal.
The consequences of not understanding or utilizing the principles of equitation science during training, especially by equestrian coaches, is shown by Warren-Smith and McGreevy (2008). Consequences include misuse of negative reinforcement (McCall et al, 2003), which has been highly correlated with conflict behaviours by McLean (2005a), and increased behavioural wastage, where horses are sent to slaughter because of unsuitable behaviour. Starling et al (2016) add to this the import of understanding the limits of cognitive ability. Without this understanding behaviour is often misinterpreted, an inappropriate training technique is applied, the horse reacts to this inappropriate solution, and the cycle continues with lowered welfare, ineffective training, and increased safety risk. While the correlations between poorly trained basic responses and conflict or fear related behaviours are well documented (McLean, 2005a), and while it follows logically that retraining these basic responses would mitigate the conflict and fear behaviours, this has yet to be conclusively demonstrated in a controlled study.
In all human activity economics can be a motivating factor, and so the financial aspect of some equine industries has also been considered in equitation science research. Baragli et al (2015) claim that increased competence in horse training could reduce behavioural wastage, estimated at 10% in the United States, thereby reducing economic loss in the industry. Factors they identified as causing behaviour that could result in wastage were abnormal management, which creates abnormal behaviour, and incorrect use of negative reinforcement, which results in an unwanted response being trained. These are in accord with psychological rules (i.e. learning theory), which they assert must be applied in training to achieve economic benefit by creating safer, more useful animals.
Doherty et al (2017) say that if veterinarians were to better understand ethology and learning theory, horse performance could be optimized in addition to reducing wastage. Because the symptoms of pain are similar to those of confusion (Derksen and Clayton, 2007), appropriate conditioning, management, and training could be vital in determining what treatment options are most effective and least expensive. The usefulness of horses is determined in part by their behaviour and their ease of learning (Murphy and Arkins, 2007), so making learning theory accessible to horse handlers and owners is considered essential (McCall, 2007). Finally, King et al (2019) assert that foals trained by them using the principles of equitation science had a higher likelihood of being placed on the racetrack and later successfully transitioning to a different career after the track. Thus, applying the principles of equitation science should extend the useful lifespan of the horse and reduce the economic risk undertaken when raising a horse (Derksen and Clayton, 2007).
Relationships are formed through mutual perceptions of one another based on multiple encounters (Sankey et al, 2010) which influence mutual behaviour (Dalla Costa et al, 2015). Attachment can form in a relationship where there is proximity seeking, safety, a base for exploration, and the potential for separation anxiety (DeAraugo et al, 2014). Factors cited as influential in the formation of a strong positive human-horse relationship are: applying learning theory (Warren-Smith and McGreevy, 2008); matching horse and rider carefully (Weeks and Beck, 1996); previous experience; temperament (Hausberger et al, 2008); and training (Dalla Costa et al, 2015). All of these factors are spoken to by equitation science, and human enjoyment of a relationship with horses is also believed to be improved by use of equitation science (Derksen and Clayton, 2007). The attitude held by the caretaker will also affect a horse’s relationship with humans, with a positive attitude toward the horse positively affecting the horse (Dalla Costa et al, 2015), while appropriate conditioning, training, and management is proposed to improve the equine attitude as well (Derksen and Clayton, 2007).
It is proposed by some people in the horse industry that a human can use equine body language to be perceived by the horse as another horse with a higher social ranking, developing a dominance based relationship and earning respect (Fenner et al, 2019a). McGreevy et al (2009) examined this aspect of the human-horse relationship and found that the possibility of aligning interactions with the equid social ethogram is very limited, and similarities cease as soon as the horse is ridden. They propose instead that use of equitation science will build a positive relationship and a compliant horse.
When naive horses have positive experiences with humans, their subsequent positive behaviour towards humans has been demonstrated to be robust and to be generalized to unfamiliar humans (Sankey et al, 2010). Dalla Costa et al (2015) also report a correlation between good relationships with humans and positive equine welfare. Their study showed significant differences in the latency of voluntary approach to a human between horses kept in stables that were assessed by local authority to have excellent welfare versus those with sub-optimal welfare. These differences extended also to expressions of aggression towards humans and avoidance behaviour. Unfortunately, the study did not discuss what criteria were used to rate the stables as either ‘excellent’ or ‘sub-optimal’, so the factors affecting human-horse relationships could not be discussed. The longitudinal Equine Assessment and Research Questionnaire (E-BARQ) survey currently underway will measure management and training, and how these affect horse behaviour and welfare (Fenner et al, 2019c). The results of this study are eagerly anticipated because they are expected to elucidate best practices in management and training for optimal relationship.
Murphy and Arkins (2007) conclude that having better definitions for and use of learning processes would reveal horses’ intelligence, further developing and enhancing our appreciation and relationship. The preliminary results from DeAraugo et al (2014) build on this knowledge of human-horse attachment showing differences between level and kind of attachment and the training methods employed. Interestingly, respondents subscribing to behavioural methods of training tended to see their relationship with their horse in reverse of those in all other methodologies, viewing it as the trainer’s responsibility to support the horse rather than the other way around. Studying how this view affects the horse’s attachment to the trainer would be an informative next step.
After over ten years of predicting what benefits will come to students of equitation science and their horses, and much anecdotal evidence, it seems there may finally be enough equitation science practitioners to gather preliminary data and put some of these claims to the test. King et al (2019) and Dalla Costa et al (2015) have begun practical field tests, the preliminary results of which, when combined with previous claims and research, seem to lend support for some of the claims made by equitation science researchers. However, much of this support remains anecdotal (Finch and Watt, 1996; King et al, 2019) or intellectual in that the claims have been experienced first-hand by many practitioners in addition to making logical sense.
There is difficulty in selecting adequate test subjects for studies due to differences in the skill level of those applying learning theory (Starling et al, 2016). Yet, Dalla Costa et al (2015) have successfully conducted on-farm tests with consistent results, indicating that it may be possible to determine if differences exist in welfare, safety, training, economics, and relationships between stables actively practicing equitation science and those that are not. While this is a sensitive topic, Dalla Costa et al (2015) were able to tactfully navigate the delicate subject of their study, providing much needed insight.
The topic of welfare has arguably been the most studied and is most conclusive regarding the positive benefits arising from the use of equitation science, though it could certainly use more study. Relationship and economics are the least studied with respect to the differences between employing and not employing equitation science principles. However, the most immediately applicable research would be in the safety and training categories. Whether or not adherence to equitation science principles actually acts as a safeguard is urgently needed information and, if demonstrated, could begin to accelerate the positive change we all wish to see, with governing bodies leading the change. Furthermore, if training is more efficient, more humane, safer, faster, and produces more reliable and competitive horses, it is likely that acceptance and incorporation of these findings amongst trainers and laypeople would increase. Thus the base of equitation science support can be built from the top down and from the bottom up. The benefits, if any, to relationships and economics will also naturally follow from such studies, as will benefits in welfare as these are intrinsically linked to all of the other categories.
Goodwin (2007) encourages more research into the measurable aspects of horse training. With the further refinement of technology such as pressure sensors that are available to measure interactions between horses and riders/handlers, Holmes and Jeffcott (2010) are confident answers can be found to specific questions. Measuring whether equitation science makes the difference it has been promoted to have, particularly in the training, welfare, and relationship categories where there is much public interest, are specific, measurable questions that will help to encourage positive change throughout the industry.
The author would like to thank Dr. Mark Sandercock for his constructive comments and helpful suggestions during the preparation of this manuscript.
The idea for the paper, the research, and the writing, were conducted by Claire Sandercock.
Conflict of Interest Statement
No conflict of interest has been declared by the author.
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