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Original research article, efficacy of dog training with and without remote electronic collars vs. a focus on positive reinforcement.

• Animal Behaviour, Cognition and Welfare Research Group, School of Life Sciences, University of Lincoln, Lincoln, United Kingdom

We assessed the efficacy of dog training with and without remote electronic collars compared to training with positive reinforcement. A total of 63 dogs with known off-lead behavioral problems such as poor recall were allocated to one of three training groups (each n = 21), receiving up to 150 min of training over 5 days to improve recall and general obedience. The 3 groups were: E-collar—manufacturer-nominated trainers who used electronic stimuli as part of their training program; Control 1—the same trainers following practices they would apply when not using electronic stimuli; and Control 2—independent, professional trainers who focused primarily on positive reinforcement for their training. Data collection focused on dogs' response to two commands: “Come” (recall to trainer) and “Sit” (place hindquarters on ground). These were the two most common commands used during training, with improving recall being the target behavior for the subject dogs. Measures of training efficacy included number of commands given to elicit the response and response latency. Control 2 achieved significantly better responses to both “Sit” and “Come” commands after a single instruction in the allocated time. These dogs also had shorter response latencies than the E-collar group. There was no significant difference in the proportion of command disobeyed between the three groups, although significantly fewer commands were given to the dogs in Control 2. There was no difference in the number of verbal cues used in each group, but Control 2 used fewer hand and lead signals, and Control 1 made more use of these signals than E-collar group. These findings refute the suggestion that training with an E-collar is either more efficient or results in less disobedience, even in the hands of experienced trainers. In many ways, training with positive reinforcement was found to be more effective at addressing the target behavior as well as general obedience training. This method of training also poses fewer risks to dog welfare and quality of the human-dog relationship. Given these results we suggest that there is no evidence to indicate that E-collar training is necessary, even for its most widely cited indication.

Introduction

Successful obedience training of dogs requires effective use and timing of cues (often referred to as “signals”) alongside reinforcement and/or punishment by dog trainers. Where dog training involves aversive or noxious stimuli, this can lead to punishment if dogs do not behave as desired ( 1 , 2 ). A growing understanding of the application of learning theory to dog welfare has led many training organizations, welfare charities and academics to advocate what they consider to be more humane methods, with a greater focus on the use and timing of rewards ( 3 – 9 ).

Electronic training aids take a number of forms, but they commonly involve a collar-born device (E-collar) which can deliver a static electric stimulus to the dog's neck as well as a number of other stimuli, such as auditory or haptic/vibration signals ( 10 ). Collar-born devices include: remote, hand-operated devices; bark- or noise-activated control collars; and containment systems (or invisible fencing) ( 11 ). Generally, collars are designed to allow the auditory/haptic signals to be paired with the delivery of the electric stimulus as a form of “warning” cue. If the dog ignores this, the electric stimulus may be applied until the desired behavior is performed. In this way dogs may learn through a combination of negative reinforcement and classical conditioning to avoid the electric stimulus by performing the desired response, however, if the delivery of electric stimuli is poorly timed or inescapable, then undesirable associations may be formed ( 11 – 13 ). Opponents of E-collars have argued that because these devices use aversive stimuli to deter undesirable behavior, they pose an increased risk of undesirable training outcomes (such as negative changes in affective state or unanticipated associations) compared to reward-focused training, especially in the hands of poorly trained or inexperienced owners ( 14 – 18 ). In contrast, those who advocate the use of remote E-collars have argued that the devices, especially in the hands of experienced trainers, can be used as to modify behavior through negative reinforcement, with limited exposure to noxious stimuli, so are a valuable training aid. Collar manufacturers suggest that an advantage of these systems is that they give handlers control over a dog even at distance ( 19 ), and effectively suppress highly motivated behaviors, such as predatory behavior; a cause of livestock chasing or unintentional killing of wildlife ( 20 – 23 ). It has also been claimed that where E-collars are successful in treating behavioral problems, dogs may avoid unnecessarily euthanasia, an outcome that would be distressing to the owners ( 24 ).

The use of E-collars in dog training appears to be declining in the UK, from an estimate of 6% of all pet dogs in 2012 ( 25 ) to around 1% in 2019 ( 26 ). This decrease may reflect current government policy on the devices in Wales [devices banned under the ( 27 )] and Scotland [not condoned in dog training and use may lead to punishment ( 28 )], with restrictive legislation proposed for England ( 29 ) as well as high-profile campaigns against their use [e.g., by the ( 18 )]. Nevertheless, these figures while appearing relatively low still suggest about 100,000 dogs in the UK are subject to E-collar use, and these devices remain legal in many other countries.

Research studies are cited selectively by both advocates and opponents of E-collars to support their claims, often with insufficient appreciation of the quality of experimental design or with a biased evaluation of evidence, such as the multiple possible interpretations of isolated behavioral indicators of welfare ( 11 ). However, the necessity of these devices [which has been used to justify their continued use e.g. ( 30 )] depends on their efficacy compared to other training approaches ( 11 , 31 ). Efficacy can be assessed objectively using specific target behavioral measures, and the use of professionally designed regimes delivered by experienced trainers can reduce the risk of sampling bias. In the current study we directly assessed the efficacy of the use of electronic collars to improve recall (the target behavior) and general obedience in dogs compared to training without E-collars. Dogs used in this study were referred to experienced, professional trainers as their owners had been experiencing significant obedience problems, including poor recall, but also chasing livestock and/or aggressive behavior to other dogs. The current study focussed on remote, hand-operated devices, as these were the most commonly used form in the UK at time of study ( 25 , 32 ); being primarily used as a means of discouraging chasing behavior and improving recall. We used training records collected during DEFRA funded research ( 33 ) on behalf of the UK government. In contrast to the previously published work ( 31 ), where efficacy was assessed by owner feedback, this study recorded the speed and reliability of response after each command, in order to derive a more rigorous, systematic and objective measure of efficacy.

Materials and Methods

Data were extracted from dog training videos, which were originally recorded as part of a DEFRA funded study ( 33 ) collected over a period of 6 months in 2010/11. Details of the recruitment of dogs, the training regimes and video data collection have previously been published ( 31 , 33 ), so the methods presented here provide an overview with additional details of differences in the approach taken in the current study.

Ethical approval was provided by the University of Lincoln Research Ethics Committee. Owners and trainers that participated in the study gave their informed consent for the use of their dogs and video recordings in the study. Home Office Inspectorate were consulted, and indicated that the work did not constitute a procedure and consequently a Home Office License would not be required based on the following conditions: E-collar use was legal in England and Scotland at the time of the study; dogs were being referred for behaviors commonly associated with E-collar use in the UK; the training was being conducted by experienced professional trainers using normal training programmes with the informed consent of owners.

Training Groups

All dogs used in this study had been referred for behavioral concerns including poor recall and livestock worrying and owners had been recommended to seek professional training to resolve those problems. The 63 dogs involved in the study were all older than 9 months of age and had no prior experience with electronic collars. Dogs in E-collar and Control Group 1 were trained in Autumn/Winter 2010 and were randomly allocated to their training group. Dogs in Control Group 2 were trained in Spring 2011, meaning subjects could be recruited to match the dogs trained with E-collars on the basis of referred behavioral problem and owner's assessment of severity. The 3 training groups were as follows:

• E-collar Group (EC: n = 21): dogs were trained using active electronic collars to improve recall and general obedience by experienced, manufacturer-nominated trainers (ECMA) (chosen to represent best-practice use of the E-collar). Trainers followed approved practice as recommended by ECMA, including assessing the dog's sensitivity to electric stimuli prior to training, and pairing vibration cue with the electric signal with the aim of modifying behavior through negative reinforcement. Dogs in this group also experienced positive reinforcement, such as rewarding dogs with food and negative reinforcement such as lead pressure.

• Control Group 1 (C1: n = 21): dogs were trained by the same trainers who worked with the E-collar group, using a mix of food rewarded positive reinforcement and negative reinforcement such as lead pressure to improve recall and general obedience but without use of electronic stimuli;

• Control Group 2 (C2: n = 21): dogs were trained to improve recall and general obedience by experienced professional trainers who were members of Association of Pet Dog Trainers (APDT UK); an organization which does not support the use of E-collars in dog training (chosen to represent best-practice use of positive reinforcement or “reward-based training”).

The dog population used in this study was broadly similar to the populations described by Blackwell et al. ( 25 ) in their survey of use of electronic training aids, and there were no significant differences between the dogs allocated to the three treatments in type of dog or reason for referral ( 31 ). Gundogs (25%), cross-breeds (25%), pastoral (17%) and terriers (13%) were the most commonly represented breed types with similar numbers in each treatment group, whereas there were no dogs from toy or utility breed groups. 34 (54%) dogs were female, with 21 (33%) of these neutered and 13 (21%) entire female dogs. Of the 29 male dogs, there was also a slightly higher number of neutered dogs (19, 30% of total population) than entire male dogs (10 or 16%); however there were no significant gender biases between the treatment groups. Chasing was the most common reason for referral in the study population (51 out of 63 dogs or 81% of population), representing 18 dogs in the E-Collar Group, 17 dogs in Control Group 1 and 16 dogs in Control Group 2. Sheep or lambs were the most commonly cited chase target, where owners reported chasing as a problem behavior, although owners also listed other livestock such as horses and poultry, wildlife such as rabbits or squirrels, as well as cars and joggers as targets for chasing. The remaining dogs had either been referred for poor recall (9 dogs of which 1 was in E-collar Group and 4 each in Control Group) or aggressive interactions with other dogs whilst off lead (3 dogs, 2 of which were in E-collar Group, 1 in Control Group 2 and none in Control Group 1). The majority of owners described their dogs as exhibiting the referred behavior “Always” (31 dogs or 49% of population), or “Frequently” (24 dogs or 38% of population indicating the high severity as perceived by owners. When these two ratings were pooled, there was no difference in owner assessment of severity between the three groups ( 31 ).

All dogs in the study wore an E-collar during training sessions in order for data analyzers to be blind to training group during video observation. Dogs in the Control groups wore a de-activated or “dummy” collar, whilst the e-collars worn by dogs in E-collar group were active and useable by the trainers. Training mainly occurred in field locations, with penned sheep, penned chickens and other (on lead) dogs, as potential distractors during training. Dogs were primarily kept on 10 m long leads throughout training session; however, trainers had the option to drop the lead or remove the lead from the dog when considered appropriate. During training dogs were normally within 1 m of the trainer (around 70% of time in all three groups) with <5% of time spent more than 5 m distant from trainer (in all three groups). Trainers in all groups had access to food rewards and could use them as the trainer deemed appropriate during training. Previous work ( 31 ) had indicated that whilst dogs in Control Group 2 received fewer signals per 15 min training session than dogs in E-collar Group or Control Group 1 (32 signals compared with 59 and 56, respectively), they were much more likely to receive food reward following a successful response, than dogs in Control Group 1 or E-collar group. Preliminary observations prior to this study to determine which commands were most common in the three groups confirmed these previous reports with food estimated to be used about 5 times more frequently as a reward during training by Control Group 2, than E-collar or Control Group 1 ( 34 ). This rate of reward would be consistent with the emphasis on reward based training in Control Group 2, compared to a mix of training approaches in the other treatment groups. Two training sessions were recorded daily (one in the morning and one in the afternoon) for each dog, for up to 5 consecutive days, producing an average of 28.5 ± 4.5 (mean ± SD) minutes of video record per dog per day, and up to 150 min over the 5 training days.

Data Collection

Data for the current study were taken from the two training sessions on the first, third and fifth day of training for each dog. Measures focused on indicators of efficacy and reliability of obeying command, including latency to complete response and number of commands required to complete desired response. Data collection focused on the two commands that were most commonly used in all 3 training groups, and could be easily distinguished from video data. These were a “Come” command normally used for recall of dogs when at a distance from the trainer and a “Sit” command normally used to require the dog to place its hind-quarters on ground and remain stationary for brief periods of time (See Table 1 ). “Come” and “Sit” commands were chosen for several reasons. Both commands could be clearly identified and obtained from the videos, across all groups, and could not be confused with other commands. During preliminary analysis of video records, these commands were also found to be the most commonly used in all three training groups. Three forms of signal or mode of delivery of training signals were noted in preliminary observation; verbal, hand and lead, and these are also defined in context in Table 1 . We also recorded: if dogs began the recall response after a single “Come” command (Come); if multiple commands (Come+) were used to initiate the recall response; or if the dog did not initiate the response (disobey; see Table 2 ). Similarly, we recorded: if a sit response was completed after a single signal (Sit); if multiple signals were needed (Sit+); or if the dog did not perform a Sit response to the “Sit” commands (disobey). In preliminary observations, to determine timeframes for these definitions of outcome, most dogs responded within 2 s of initial command, and where dogs were given additional commands, this was normally limited to 2 or occasionally 3 commands within the 10 s of the initial command. Where dogs had not completed the response within 10 s of initial command, trainers normally ceased this sequence of commands and after a brief rest normally longer than 10 s would resume with a new command. This approach was similar across the three training groups, so the definition of successful responses and disobey could be applied to all groups. To control for the different number of commands given, absolute values were converted into % of commands to compare reliability of response between the three groups. Where dogs responded to the “Come” command the latency was recorded as the time from delivery of first command to the dog initiating the recall response, whereas latency to sit was recorded as the time to place hind-quarters on ground following delivery of the first “Sit” command signal.

Table 1 . Descriptions of the mode of delivery (or signals) for the Come and Sit commands.

Table 2 . Description of dogs' responses to “Come” and “Sit” commands.

Data Extraction and Statistical Analysis

Training videos were viewed in a random order and blinded, such that the viewer could not associate dogs with their respective group, using Solomon Coder software (version: beta 17.03.22). Following collection, raw data was extracted from the Solomon Coder files into a Microsoft Excel spreadsheet, separating each dog into their allocated training group. Data for the number of commands ( Table 3 ) were analyzed per training session. A small number of sessions focused on just recall or just sit, so morning and afternoon sessions were aggregated, for analysis of the percentage of dogs responding to the first signal, multiple signals, or disobeying and for the calculation of latencies. This provided a single daily measure for each dog. Previous work Cooper et al. ( 31 ) had indicated no significant differences in dogs' behavior between morning and afternoon sessions, and exploratory comparison of morning and afternoon data in this study was consistent with this.

Table 3 . Mean number of commands given per training session (±SE) for dogs trained with E-collars and the two control groups, including number of verbal, hand, and lead signals, number of times a single “Come” and “Sit” command were given and numbers of times multiple signals were given for each command (Come+ and Sit+) and the number of times dogs obeyed on first comment, obeyed after multiple commands (Obey+) or did not obey.

Statistical analysis of the data was conducted using Minitab 17.0, using General Linear Models (GLMs). Training groups and days (1, 3, and 5) were treated as fixed factors, whilst individual dog IDs were random factors nested within the training groups. As the focus was on efficacy outcomes we focused on main effects and did not include interactions within our models, so as not to unnecessarily inflate the degrees of freedom in the models. Unless stated otherwise data is presented as mean ± standard error, since our focus was on differences between groups and not group variability.

Number of Commands, Signals, and Responses

On average 20.3 ± 0.6 commands were given per training session, of which 15.7 ± 0.6 (77%) were obeyed on first command, 4.1 ± 0.2 (20%) obeyed after multiple commands and only 0.6 ± 0.1 (3%) disobeyed. On average the number of signals per training session was 26.8 ± 0.8. The majority of signals were verbal with 17.8 ± 0.8 verbal signals per session (66% of all signals). There were 5.2 ± 0.3 hand signals per training session (19% of all signals) and 3.8 ± 0.4 lead signals (14%). There was no difference in the number of verbal signals given to dogs in the 3 training groups ( Table 3 ), but Control Group 1 consistently received more hand and lead signals than dogs trained with E-collars, whilst Control Group 2 consistently had fewer hand and lead signals than the other groups. As a consequence, Control Group 1 received most signals during training, whilst Control Group 2 received fewer signals during the training period than the other groups [ F (2, 293) = 30.2, P < 0.001].

Control Group 2 performed fewer “Sit” responses during training than the E-collar group and Control Group 1, following single commands, following use of multiple commands ( Table 3 ) and overall [ F (2, 293) = 74.5, P < 0.001]. Control Group 1 performed the most “Sit” and most “Come” responses following multiple commands, whilst the E-collar Group performed least “Come” responses following a single command and in total [ F (2, 293) = 5.51, P = 0.005].

Control Group 1 exhibited more disobeys than either the E-collar training group or Control Group 2 ( Table 3 ), but also completed more responses after single and multiple commands as they received most commands of the three training groups. When the percentage of responses was analyzed to account for the different number of commands between the training groups, there was no difference in percentage of disobeys between the three training groups ( Table 4 ). Control Group 2, however, had a higher percentage of performing both “Come” and “Sit” responses on first command and lower percentage following multiple commands than either Control Group 1 or the E-collar Group.

Table 4 . Mean percentage of “Come” and “Sit” commands (± SE) obeyed after a single signal, obeyed after multiple signals (Obey+) or not obeyed for dogs trained with E-collars and the two control groups.

Training day had no effect on number of commands or response rate, except for the use of signals ( Figures 1 – 3 ). Use of lead signals declined from day 1 to day 5 [ Figure 3 : F (2, 293) = 17.5, p < 0.001] and use of hands signals was most common on day 3 [ Figure 2 ; F (2, 293) = 4.04, p = 0.018]. There was however no change in number of verbal signals used over the training days, and overall total number of signals used did not differ across training days [ F (2, 293) = 0.16, P = 0.85].

Figure 1 . The mean (with SE) number of verbal commands given to dogs in the E-collar training group and the two Control groups over the 3 training days. See Tables 3 , 4 for analysis of differences between groups; no significant differences between training days.

Figure 2 . The mean (with SE) number of hand commands given to dogs in each training group over the 3 training days. Subscripts (a and b) indicate where training days differed based on Tukey pair-wise comparisons. See Tables 3 , 4 for analysis of differences between groups.

Figure 3 . The mean (with SE) number of lead commands given to dogs in the E-collar training group and the two Control groups over the 3 training days. Subscripts (a, b, and c) indicate where training days differed based on Tukey pair-wise comparisons. See Tables 3 , 4 for analysis of differences between groups.

Latency to Respond

Overall, the mean latency to respond to the “Come” command was 1.24 ± 0.05 s, whereas dogs took a mean of 1.64 ± 0.06 s to complete the “Sit” commands. There were significant differences in latency to respond to both the “Come” [ F (2, 114) = 5.89; p = 0.04] and the “Sit” command [ F (2, 101) = 12.3; P < 0.001] between the training groups ( Table 5 ). For the “Come” command there was a shorter latency to respond by Control Group 2 compared with the E-collar Group. The difference in latency to respond to the “Sit” command was largely similar to that of the “Come” command, however Control Group 2 responded sooner than both the E-collar Group and Control Group 1.

Table 5 . Mean latency to complete response in seconds from initial command (± standard deviation) for those dogs that completed come and sit responses from the E-collar and 2 Control training groups and on different days.

Although the E-collar Group and Control Group 1 appeared to show a decline in latency to respond to the “Come” command over the study period ( Figure 4 ) there was no significant change in latency to come between the 3 training days [ F (2, 114) = 1.82; P = 0.17]. In contrast there was a change in latency to sit [ F (2, 101) = 5.61; P = 0.005] with longer latencies to sit on day 3 and day 5 compared to day 1 ( Table 5 ), which was related to increased latency in the E-collar training group and Control Group 1, as training progressed ( Figure 5 ).

Figure 4 . The mean (with SE) latency to respond to “Come” command by dogs in the E-collar training group and the two Control groups over the 3 training days.

Figure 5 . The mean (with SE) latency to respond to “Sit” command by dogs in the E-collar training group and the two Control groups over the 3 training days.

Each of the three training groups had successful training outcomes to both “Come” and “Sit” commands. The proportion of responses that were performed following first command was high in all three groups, and the proportion of disobeys was low throughout the study and did not differ between training groups. These findings are consistent with owner satisfaction with training outcomes as reported previously ( 31 ) and should be expected as all trainers were professionals, with extensive experience of training dogs to improve recall and general obedience. The reward-based Control Group 2, however, had a higher proportion of obeys after first command to both “Come” and “Sit” commands and required fewer multiple commands to initiate a recall or complete a sit response. This suggests that the reward-based training was the most effective approach not only for recall which was the target behavior in training, but also for other commands, even though the reward based trainers did not spend as much of their time training on sit command as the other two training groups.

Latencies to respond also indicate successful training outcomes in all three groups with dogs beginning to return to the trainer on average 1.24 s after delivery of a “Come” command and dogs completing the sit response on average 1.64 s after a “Sit” command. The slightly longer latency to sit potentially reflected this measure being based on completion of response, whereas latency to “Come” response was determined from the initiation of recall with dogs beginning to return to trainer. Although differences between groups were small, dogs in Control Group 2, showed a shorter latency to begin to return than the E-collar Group, which is consistent with the higher proportion of responses seen following a single command in this group. There were also differences between the groups in time to complete the sit response, with Control Group 2 being faster to complete this response than both the E-collar group and Control Group 1. This was also consistent with a higher proportion of dogs completing this response after a single command. It is noteworthy that there was little difference in latency to sit between the three groups on the first day of training, as dogs in all three groups had a reliable response to the “Sit” command before training, but longer latencies in the E-collar and Control 1 group become apparent as training progressed. These findings are consistent with the reported public perception that E-collars have lower success rates than reward-based training for recall and chase problems ( 25 ), and concerns regarding efficacy of training programs involving potentially aversive stimuli raised by Hiby et al. ( 3 ), Rooney and Cowan ( 4 ), Fernandes et al. ( 5 ), Ziv ( 6 ), and Masson et al. ( 7 , 35 ).

Two factors apart from the use of electric stimuli during training should be explored before drawing conclusions with regard to the efficacy of the three training methods. The first relates to the weather conditions as E-collar Group and Control Group 1 were trained in mid-winter, whereas Control Group 2 were trained 4 months later in early Spring. This was in part due to availability of industry nominated trainers, but also allowed time to select dogs from the larger population available for training without E-collars to best match those referred to E-collar Group. Although there has been no published work on seasonal variation in training outcomes in dogs, there are likely to be variation in environmental conditions, that may impact on these outcomes. Indeed the winter training period in particular featured some extreme weather conditions with lying snow and low daytime temperatures as well as milder periods. For this reason, as part of the exploratory analysis of data during the original project (AW1402a), weekly variation in data were investigated in each group and no differences were found with respect to command use, dog behavior or training outcomes, suggesting weekly changes in environmental had minimal effects, and that trainers maintained consistent approaches to training over the weeks of data collection, despite the challenges of field conditions.

The second relates to differences in the general approaches to training between the three groups and in particular between Control Group 2 trainers and those in E-Collar and Control Group 1. Firstly, Control Group 2 appeared to primarily target recall training, with less time spent on other commands including sit, whereas the E-collar Group and Control Group 1 chose to work on both recall and general obedience including sitting ( Table 3 ), perhaps indicating a greater focus on controlling the dog as well as achieving the target goal behavior. Furthermore, whilst the use of verbal signals was similar between the three groups, hand and in particular lead signals were less frequently used by Control Group 2 than either Control Group 1 or the E-collar Group; with Control Group 1 making more use of hand and lead signals during training than the E-collar Group. The use of multiple signals in training can have variable effects, with, for example, the use of additional contingencies such as lead pressure during a recall command, potentially affecting the rate of learning of the desired response. Improvement in learning would depend to some extent on the multiple signals being delivered consistently, and even then, dogs may form more reliable associations with some stimuli than others due to learning and perceptual biases or the nature of delivery. For example, it has been reported that visual signals during dog training may overshadow verbal ones when used at the same time ( 36 ). The explanation for differences in learning outcome may therefore lie in the degree to which dogs were exposed to rewarding and potentially aversive stimuli in the three groups and the range of signals used to guide the dogs' behavior.

Broadly speaking, dogs in Control Group 2 were asked to complete a recall task in response to verbal signals and normally received food reward(s) on return to trainer. Hand signals were rarely used and even though dogs were often on lead, lead pressure was very rarely recorded. As a consequence a single signal was used to cue the desired behavior and a single contingency (food) associated with successful completion of response. Similarly, training of a sit used a verbal “sit” command, with dogs receiving food reward once response had been completed. In summary, this group appeared to use the simplest and clearest contingencies for associative learning.

Dogs in the E-collar group were trained in accordance with industry best practice, with dogs' sensitivity to E-collar settings assessed early in training, and training focussed on associating the pre-warning cue, a collar born vibration, with exposure to the electric stimuli. In this way, the intensity of the electric stimulus could have been moderated to match the dog's tolerance and dogs could learn to modify their behavior to avoid exposure to the electric stimulus; a form of negative reinforcement. This sophisticated use of e-collars contrasts with that of some trainers reported in Cooper et al. ( 31 ), who used e-collars at their maximum settings and applied the electric stimulus after the dogs engaged in undesirable behavior, such as sheep chasing, without the use of the pre-warning cues. As buttons to deliver pre-warning cues were on same handset as the button for electric stimulus, it was not possible to reliably determine when electric stimuli were applied, so we should be cautious about inferring when stimuli were used during training schedules. For example, although one might predict that there would be more use of electric stimuli during early training as sensitivity is determined and an association formed between stimulus and desired response, or that electric stimuli would be more likely to be applied if the dog did not respond to initial command this cannot be verified from our data. For example, in previous published work ( 31 ), where vocalizations and abrupt changes in posture were recorded when dogs were remote from trainers, there was no evidence of change in frequency over 5 days of training. This freedom to adjust application of stimuli as part of the training program, as well as inclusion of other approaches to training the target or other behaviors, was consistent with the ethical approval of our project as well as our aim to assess best practice as advocated by the industry. Therefore, so long as dogs were not exposed to inescapable punishment, and trainers followed industry standards, we could not artificially impose standardized training programs, nor could we preclude trainers from using other signals and/or contingencies during training such as hand and lead signals. As a consequence, although we did not have the control over variables of experimental investigations of e-collar training [e.g., ( 37 – 39 )], we did meet our aim of evaluating professional training of companion dogs with typically referred behaviors in the field.

Dogs in Control Group 1 were trained by the same trainers as the E-collar group and were expected to follow the same training approaches but without use of E-collar stimuli. Dogs in this group wore a de-activated dummy collar (as did dogs in Control Group 2) to control for the wearing of an unfamiliar device as well as part of the process of blinding observers to treatment in video analysis. As a consequence these dogs experienced collar fitting at start of each training session, but were not exposed to electric or vibration stimuli during training. These trainers therefore also used a mix of verbal, hand and lead signals, as the E-collar Group, but relatively few food rewards during training. It was also clear that the dogs received more lead and hand signals than the dogs in the E-collar group. Hand signals, involved not only hand gestures, but were also accompanied in some instances by physical contact with the dogs to gain their attention, stopping of ongoing behavior or pushing the dog into the desired position, whilst lead signals could be accompanied by what appeared to be sharp pulls on the lead. This more physical and potentially aversive use of contact or lead pressure was not observed in any of the videos relating to Control Group 2 but were clearly identified in both the E-collar Group and Control Group 1. These qualitative observations support the suggestion that the trainers involved in both the E-collar training and Control Group 1 were again more focussed on forcing compliance rather than shaping the desired response ( 40 ).

In summary, an important strategy within the reward-focused training of Control Group 2 was the positive reinforcement of successive approximations of the desired behavior, with mainly verbal signals, in order to build a strong contingency between command word and response ( 40 ). In contrast the E-collar group and Control Group 1 used a variety of signals and contingencies, including some potentially aversive handling and lead pressure during training. With good timing, these could result in negative reinforcement, although poor timing or imposition of the noxious stimuli in response to failure to perform the desired behavior would constitute a form of punishment. It has been frequently argued that the use of aversives in dog training results in poorer learning outcomes and poses greater welfare risks compared with largely reward based training ( 3 – 6 ). Our results demonstrate through direct evidence from real life situations, that the reward-focused training was, indeed, more efficient than methods which included potentially aversive stimuli such as electric stimuli or excessive lead pressure. Whilst our results may reflect general differences in training style of the trainer groups involved in the study rather than use of E-collar per se , we would argue that because the trainers who used E-collars were put forward by industry representatives as exemplars of best practice; their data (at least in relation to E-collar use) should be taken to represent a best case scenario for professional E-collar training. It is likely that less experienced trainers and owners would be less skilled and thus less effective in their use of the device [See ( 25 , 35 )].

Overall, the professional use of a reward-focused training regime, as demonstrated by Control Group 2, was superior to E-collar and Control Group 1 in every measure of efficacy where there was a significant difference. In addition, dogs in Control Group 1 showed no better learning outcomes than those in the E-collar group, indicating industry nominated trainers were as effective at modifying undesirable behavior, when they did not use e-collars as one of their training methods. Given the better target behavior response parameters associated with a reward-focused training programme, and the finding that the use of an E-collar did not create a greater deterrent for disobedience; we conclude that an E-collar is unnecessary for effective recall training. Given the additional potential risks to the animal's well-being associated with use of an E-collar ( 7 , 25 , 31 , 38 , 39 ), we conclude that dog training with these devices causes unnecessary suffering, due to the increased risk of a dog's well-being is compromised through their use, without good evidence of improved outcomes.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The animal study was reviewed and approved by University of Lincoln Research Ethics Committee. Written informed consent was obtained from the owners for the participation of their animals in this study.

Author Contributions

LC undertook video observation and behavioral coding of the training videos, as well as initial statistical analysis, and led the writing of the main article. JC and DM were LC's supervisors for her Master's thesis, providing support throughout. All authors made similar contributions to the final manuscript.

We would like to thank DEFRA for funding the original study (AW1402A). We would also like to thank University of Lincoln, who provided an alumni support bursary for LC's Master's by Research thesis.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The authors wish to thank DEFRA for funding of original project (AW1402A) and ECMA and APDT for supporting the nomination of the best trainers available and support in recruitment of dogs through referrals. We would also thank the dog owners for participation in this study and volunteering their dogs. We would also like to acknowledge Hannah Wright and Jessica Hardiman, for working with trainers in the field and recording of the video records and Marie Delpech, Emma Cosby, Rachael Nicklin, and Molly Taylor who previously worked with LC on the development of methods for assessing efficacy of training methods for this study.

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Keywords: dog training, dog welfare, electronic collar, reinforcement, punishment

Citation: China L, Mills DS and Cooper JJ (2020) Efficacy of Dog Training With and Without Remote Electronic Collars vs. a Focus on Positive Reinforcement. Front. Vet. Sci. 7:508. doi: 10.3389/fvets.2020.00508

Received: 31 March 2020; Accepted: 03 July 2020; Published: 22 July 2020.

Reviewed by:

Copyright © 2020 China, Mills and Cooper. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jonathan J. Cooper, jcooper@lincoln.ac.uk

This article is part of the Research Topic

Working Dogs: Form and Function, Volume II

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Improving dog training methods: Efficacy and efficiency of reward and mixed training methods

Roles Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Visualization, Writing – original draft

* E-mail: [email protected]

Affiliations Instituto de Biologia Molecular e Celular, Universidade do Porto, Porto, Portugal, i3S –Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal

Roles Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing

Affiliation Polícia de Segurança Pública, Lisbon, Portugal

Roles Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources

Affiliation CINAMIL, The Military Academy Research Center of the Portuguese Army, Lisbon, Portugal

Roles Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – review & editing

• Ana Catarina Vieira de Castro, 
• Ângelo Araújo, 
• André Fonseca, 
• I. Anna S. Olsson

• Published: February 19, 2021
• https://doi.org/10.1371/journal.pone.0247321
• Peer Review
• Reader Comments

Dogs play an important role in our society as companions and work partners, and proper training of these dogs is pivotal. For companion dogs, training helps preventing or managing dog behavioral problems—the most frequently cited reason for relinquishing and euthanasia, and it promotes successful dog-human relationships and thus maximizes benefits humans derive from bonding with dogs. For working dogs, training is crucial for them to successfully accomplish their jobs. Dog training methods range widely from those using predominantly aversive stimuli (aversive methods), to those combining aversive and rewarding stimuli (mixed methods) and those focusing on the use of rewards (reward methods). The use of aversive stimuli in training is highly controversial and several veterinary and animal protection organizations have recommended a ban on pinch collars, e-collars and other techniques that induce fear or pain in dogs, on the grounds that such methods compromise dog welfare. At the same time, training methods based on the use of rewards are claimed to be more humane and equally or more effective than aversive or mixed methods. This important discussion, however, has not always been based in solid scientific evidence. Although there is growing scientific evidence that training with aversive stimuli has a negative impact on dog welfare, the scientific literature on the efficacy and efficiency of the different methodologies is scarce and inconsistent. Hence, the goal of the current study is to investigate the efficacy and efficiency of different dog training methods. To that end, we will apply different dog training methods in a population of working dogs and evaluate the outcome after a period of training. The use of working dogs will allow for a rigorous experimental design and control, with randomization of treatments. Military (n = 10) and police (n = 20) dogs will be pseudo-randomly allocated to two groups. One group will be trained to perform a set of tasks (food refusal, interrupted recall, dumbbell retrieval and placing items in a basket) using reward methods and the other group will be trained for the same tasks using mixed methods. Later, the dogs will perform a standardized test where they will be required to perform the trained behaviors. The reliability of the behaviors and the time taken to learn them will be assessed in order to evaluate the efficacy and efficiency, respectively, of the different training methods. This study will be performed in collaboration with the Portuguese Army and with the Portuguese Public Security Police (PSP) and integrated with their dog training programs.

Citation: Vieira de Castro AC, Araújo Â, Fonseca A, Olsson IAS (2021) Improving dog training methods: Efficacy and efficiency of reward and mixed training methods. PLoS ONE 16(2): e0247321. https://doi.org/10.1371/journal.pone.0247321

Editor: Simon Clegg, University of Lincoln, UNITED KINGDOM

Received: July 31, 2020; Accepted: February 4, 2021; Published: February 19, 2021

Copyright: © 2021 de Castro et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data from this study will be made available upon study completion.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

The methods used to train dogs range broadly with some using rewards and other non-invasive techniques (reward methods), others using mainly aversive stimuli (aversive methods) and still others using a combination of both (mixed methods). Strong claims have been made for the negative effect of the use of aversive stimuli in training on dog welfare and dog-owner bond. However, the scientific evidence for this has been limited as most studies lack objective welfare measures, investigation of the entire range of aversive techniques and companion dog-focused research [ 1 ]. Recently, in the first large-scale quasi-experimental study of companion dog training (n = 92), Vieira de Castro et al (2020) [ 2 ] found that dogs trained with aversive stimuli displayed more stress behaviors during training, showed higher elevations in cortisol levels after training and, if trained exclusively with aversive methods, were more ‘pessimistic’ in a cognitive bias task than dogs trained with either reward and mixed methods. These findings strongly suggest that using aversive stimuli in training compromises companion dog welfare both within and outside the training context. In parallel, in a study aimed at assessing the relationship between training methods and dog-owner bond, Vieira de Castro el al (2019) [ 3 ] found that a secure attachment tended to be more consistent in dogs trained with reward methods, as revealed by behaviors displayed during a Strange Situation Procedure. These results suggest that the choice of training methods may also affect dog attachment to owner.

In addition to the effects on welfare, efficacy and efficiency are also relevant aspects to consider for the choice of training methods. Although claims have been made that reward and aversive/mixed methods are, at least, equally effective, the existing scientific literature is inconsistent. Some studies examined the efficacy (reliability of trained behaviors) of specific training methods but without directly comparing reward and aversive/mixed methods. Dale et al (2017) [ 4 ] found that dogs learned to avoid native birds after training using e-collars, an aversive technique, and that learning was retained for most dogs following one year. On the other hand, Yin et al (2008) [ 5 ] demonstrated that dogs could be trained with a remote-controlled food reward dispenser not to bark excessively, jump and crowd around the door when people arrived. Also, three proof-of-concept studies have shown that clicker training (a reward technique) is effective for training dogs for scent detection tasks [ 6 , 7 ] and service dog tasks [ 8 ]. Other studies have directly compared the efficacy of aversive and reward methods in both dogs and horses and these have produced conflicting results. Among these, five studies suggest a higher efficacy of reward methods [ 9 – 13 ], whereas one points in the opposite direction [ 14 ] and three show no differences between methods [ 15 – 17 ]. To our knowledge, only one study addressed the efficiency (speed of learning) of different methods and suggests a higher efficiency of reward over aversive methods [ 18 ].

Therefore, the aim of the current study is to evaluate the efficacy and efficiency of different dog training methods. This will be investigated in the context of working dogs, as working dogs allow a rigorous experimental design and control, with randomization of treatments. Namely, military and police dogs will be trained using either reward (Group Reward) or mixed methods (Group Mixed, dogs pseudo-randomly allocated to groups) to perform a set of behaviors. The efficiency of training methods will be evaluated by measuring the number of sessions required for the dogs to learn the tasks, and efficacy will be assessed using a standardized test in which dogs will be required to perform the trained behaviors.

Dogs play an important role in our society both as companion and working animals. Owning a dog for companionship has been shown to bring several physical and psychological benefits to humans [ 19 , 20 ], and working dogs are of invaluable help when, for example, they fulfil tasks for disabled people or help in the detection of drugs or explosives. Dog training plays a pivotal role here. First, by preventing or managing dog behavioral problems—the most frequently cited reason for relinquishing and euthanasia [ 21 ], it helps to promote successful dog-human relationships and thus maximize the benefits humans derive from bonding with dogs [ 22 ]. Secondly, because it is required for working dogs to successfully accomplish their jobs.

2. Material and methods

2.1. ethics statement.

The planned study includes an experimental training protocol in which working dogs are trained with either reward or mixed methods. The mixed methods will be based on the training method presently used for training these dogs outside the experimental protocol, thus no dog will be subjected to pain, suffering, distress or lasting harm as a result of being recruited for the study. Shock collars and pinch collars, which can cause physical harm, will not be used.

Dogs and handlers will be video recorded for further analysis of behavior. Individual handlers will be identifiable from the video footage. Material in which individuals can be identified will only be used by the research team for research purposes (i.e., to control for the training techniques and for data analysis).

All handlers will be briefed that the purpose of the study is “to investigate different training methods and measure the behavior of the dog-handler dyad”, and sign an informed consent form that they agree to participate in the study and to be video recorded for research purposes. Each handler will be instructed about which tools and techniques are included in the treatment assigned to them, but will not be informed about the overall experimental design.

Applications for approval are submitted to the Committee for Ethics and Responsible Conduct in Research (human subjects research) and from the Animal Welfare and Ethics Body (animal research) of i3S, University of Porto. The study will only start after approval has been obtained.

2.2. Subjects

Military (n = 10) and police dogs (n = 20), housed at the facilities of the Military Working Dog Platoon in the Portuguese Paratroopers Regiment (RPara) and Portuguese Public Security Police (PSP) K9 unit, respectively will be allocated to Group Reward (trained with reward methods) and Group Mixed (trained with mixed methods). All dogs have previous mixed methods training experience, a stratified randomization method [ 23 ] will be used to assign animals to the two groups. This method allows for balancing in terms of subjects’ baseline characteristics (covariates) that may potentially affect the dependent variables under study. In the present study the following covariates will be taken into account: dog sex, age, breed and previous training experience (obedience, odor detection, protection work). This will be done for each institution, meaning that five dogs from RPara and 10 dogs from the PSP K9 unit will be allocated to each group.

As part of their certification process as working dogs, all the animals had to perform and pass the obedience component of a BH test [ 24 ]. Despite all dogs being naïve to the specific exercises included in the present study (food refusal, interrupted recall, dumbbell retrieval and placing items in basket–the detailed description of the exercises is presented below), two similar behaviors are trained as part of the training programs of PSP and RPara. Namely, dogs are trained to retrieve a motivator (e.g., a tug or bite pad), although not to the formality and precision that is going to be required in the ‘dumbbell retrieve’ exercise, and they are also usually trained to interrupt a send away (i.e., they are trained to run forward to a motivator and interrupt the running when instructed). The ‘food refusal’ and ‘place items in the basket’ exercises are not part of the training programs and are thus new or near to completely new for all the animals. Because previous training on similar behaviors may have carryover effects on the training planned for the study, at the time of the beginning of the study, each participating dog’s training history will be thoroughly evaluated and, if needed, this will also be included as a covariate in the randomization process.

2.3. Training methods

All dogs will be trained through associative learning (classical and operant conditioning) [ 25 , 26 ], however, the principles used for each group will differ. Whereas all four quadrants of operant conditioning will be allowed for Group Mixed (positive punishment, negative reinforcement, positive reinforcement and negative punishment), only the quadrants of positive reinforcement and negative punishment will be permitted for Group Reward. Regarding classical conditioning, the use of both conditioned reinforcers and punishers will be allowed for Group Mixed, but only conditioned reinforcers will be allowed for Group Reward. Table 1 displays the detailed definitions for all the conditioning procedures and includes some practical examples.

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https://doi.org/10.1371/journal.pone.0247321.t001

As for training equipment, no pinch nor e-collars will be allowed in the study and choke chains will only be allowed for Group Mixed. Apart from this, the handlers will be free to decide which other equipment to use among leashes, flat collars and harnesses. The use of a clicker will also be optional, as it has been reported not to affect efficiency and efficacy as compared to the use of a verbal marker or food alone [ 27 – 29 ]. In order to ensure that the instructions regarding the training procedures and tools permitted for each group are being followed, checkpoints will be done at the fifth and tenth days of training for each dyad, when the research team will review the video recordings of the training sessions.

Some flexibility for choosing training equipment and procedures will thus be allowed (as opposed to have the handlers following previously defined and detailed training protocols). The reason for this decision is that this study aims to reflect a real-life situation of dog training, where different handlers use different approaches (within the same training method–reward or mixed) and, especially, where the individual dog and its natural tendencies and behaviors usually dictate the training pathway.

2.4. Data collection

2.4.1. training..

Dogs will be trained by their handlers to perform four exercises: ‘food refusal, ‘interrupted recall’, ‘dumbbell retrieval’ and ‘placing items in basket’. The exercises were chosen in order to resemble real working dog tasks, while not interfering with the dogs’ daily working duties. Prior to training commencement, the handlers will be instructed on the exercises that they will train the dogs to perform and on the tools and techniques they are allowed to use during training (as explained in detail in the previous section). The handlers will be free to decide whether to train the exercises in parallel or in a sequence, as well as the order in which to train the different exercises. Training sessions will be conducted two days per week, with a gap between training days no longer than three days. Each training session will have a maximum duration of 10 minutes and up to six training sessions can be conducted per day. Within each training day, a break of at least 30 minutes between training sessions will be required.

Training for each exercise will end when the dog reaches the learning criterion (i.e., adequately performs the behavior as determined by the handler) or after a maximum of 45 sessions. Information regarding the number of training sessions, their duration and the behaviors being trained will be annotated by each handler in a notebook (specifically designed for the study) for each training day. In addition, all training sessions will be video recorded.

2.4.2. Evaluating performance.

The efficiency of the different training methods will be evaluated through the number of training sessions necessary to reach the learning criterion (as determined by the handlers), and the efficacy will be assessed through a standardized test where the dogs will be asked to perform the trained behaviors. The test will be conducted in a fenced enclosure and will include the following exercises:

1. Food refusal: The handler asks the dog to ‘stay’ (the position in which the dog is left can be either a sit, a down or a stand, according to the handler’s choice), walks 10 meters away to a pre-defined/marked location within the field of vision of the dog, and stops with his/her back facing the dog. Afterwards, a helper comes near the dog and throws two pieces of food next to the dog’s front legs, one to right side and one to the left side. The handler can use the verbal cue for the dog not to eat before starting the exercise or while the helper is coming within the field.

Cues: ‘Sit’/’Down’/‘Stand’, ‘Stay’, ‘Don’t eat’

2. Interrupted recall: The handler asks the dog to ‘stay’ (the position in which the dog is left can be either a sit, a down or a stand, according to the handler’s choice), walks 30 meters away to a pre-defined/marked location, turns to face the dog and recalls the dog, instructing it to stop after roughly half the distance is covered (the position is which the dog stops can be either a sit, a down or a stand, according to the handler’s choice).

Cues: ‘Sit’/’Down’/‘Stand’, ‘Stay’, ‘Come’, ‘Stop’

3. Dumbbell retrieval: With the dog sitting at his/her side, the handler throws the dumbbell to a distance of roughly 10 meters (marked in the floor in order to help) and then instructs the dog to retrieve it. The dog should move towards the dumbbell, pick it up and bring it to the handler, sit in front of him and only release on cue.

Cues: ‘Sit’, ‘Get it’, ‘Out’

4. Placing items in basket: A basket will be placed in the field and three items will be placed in pre-defined positions in the floor, around the basket, by a helper. The handler will then instruct the dog to place the items in the basket.

Cues: ‘Place’ (only one cue is allowed for the entire exercise, the handler is not allowed to give additional cues after each item is retrieved)

5. Surprise exercise: The dog will have to perform a dumbbell retrieval with two pieces of food being thrown to the floor next to the dog by a helper before the exercise starts. This exercise will be included in order to test for training generalization.

Cues: ‘Sit’, ‘Don’t eat’, ‘Get it’, ‘Out’

The starting points for the exercises will be the same for all dogs and will be marked in the floor with a spray. Only verbal cues will be allowed during the test. The aforementioned words/expressions are, however, purely indicative—each handler will be free to choose his or her own cues. During the test, the dogs will not wear any collar or leash and no treats, toys or punishments will be allowed. Handlers will only be allowed to use social reinforcement (praise) between exercises. Additionally, in order to ensure that all dogs perform the test with similar motivation levels, dogs will be fed 12 hours previously to the conduction of the tests and no play or physical exercise will be allowed during this period.

The designs of Exercises 1, 2 and 3 were inspired on the Federation Cynologique International (FCI) dog sports of IGP, Obedience and Mondioring [ 24 , 30 , 31 ]. Exercise 4 is not part of any recognized dog sport, but its core behavior is (retrieve).

The test will be performed twice, the day after the learning criterion is achieved for all behaviors and 6 months later, to assess short- and long-term efficacy. No formal training will be performed between the two evaluations for ‘Food refusal’ and ‘Placing items in basket’. ‘Interrupted Recall’ and ‘Retrieve dumbbell’ will be trained once a month for maintenance. This will be done in order to evaluate the impact of maintenance training on long-term efficacy. The tests will be recorded using two video cameras, set in order to cover the entire field.

A pilot study using two dog-handler dyads that will not participate in the main study will be performed in order to test and, if needed, refine the methodology.

2.5. Data analysis

Two different approaches will be used to analyze the performance of the dogs in the test. Three international experts on working dog training will be invited to assess dog performance in situ on the test days. The experts, who will be blind to the experimental groups and to the goals of the study, will be instructed to use a qualitative scoring system, according to which the dog performance for each exercise should be classified as ‘insufficient’, ‘sufficient’ or ‘outstanding’ (see S1 Annex for full details). Moreover, two researchers blind to the experimental groups and to the goals of the study will analyze the videos of the tests using a quantitative scoring system, following which the dog performance for each exercise will receive a score ranging from 0 to 10 (see S2 Annex for full details). Inter-observer reliability will be calculated for each exercise. The quantitative scoring system was developed based on FCI rules and guidelines for Obedience, Mondioring and IGP trials [ 24 , 30 , 31 ].

The video recordings of the training sessions and the tests will also be used to assess dog welfare through the analysis of stress behaviors as in Vieira de Castro et al (2020). These will also allow for the analysis of handler behavior and other aspects of training such as the frequency, type and timing of the stimuli applied. This will be used to generate a list of all the conditioning procedures actually used by each handler during training.

2.5.1. Statistical analysis.

Data will be analyzed using a Generalized Linear Mixed Model (GLMM), to account for repeated measures and to investigate the effects of multiple subject variables. Subject ID will be included as the repeated measure. Age (years), sex (M/F), breed and training experience will be included as covariates and Training Method (Mixed vs Reward) and Training Unit (PSP, RPara) as factors. One model will be run for each response variable: 1) number of training sessions necessary to reach the learning criterion, 2) qualitative score obtained in the test and 3) quantitative score obtained in the test.

Supporting information

S1 annex. qualitative scoring system for the test for efficacy evaluation..

https://doi.org/10.1371/journal.pone.0247321.s001

S2 Annex. Quantitative scoring system for the test for efficacy evaluation.

https://doi.org/10.1371/journal.pone.0247321.s002

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