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. 2019 Dec 6;9(12):1091.
doi: 10.3390/ani9121091.

Using Principles from Applied Behaviour Analysis to Address an Undesired Behaviour: Functional Analysis and Treatment of Jumping Up in Companion Dogs

Nicole Pfaller-Sadovsky  1 , Gareth Arnott  1 , Camilo Hurtado-Parrado  2   3
Affiliations

Using Principles from Applied Behaviour Analysis to Address an Undesired Behaviour: Functional Analysis and Treatment of Jumping Up in Companion Dogs

Nicole Pfaller-Sadovsky et al. Animals (Basel). .

Abstract

The aim of this study was to investigate the feasibility and effectiveness of procedures successfully used in human related applied behaviour analysis practices to the field of clinical animal behaviour. Experiment 1 involved functional analyses to identify the reinforcement contingencies maintaining jumping up behaviour in five dogs. Experiment 2 comprised teaching dog owners a noncontingent reinforcement intervention (i.e., time-based reinforcement) via behavioural skills training. Single-case experimental methods were implemented in both experiments. The results of Experiment 1 showed that access to a tangible (dogs D01, D02, D03, and D04) and owner attention (dog D05) were reliably maintaining the jumping up behaviour. Experiment 2 demonstrated that noncontingent reinforcement effectively reduced jumping in three out of four dogs (Tau -0.59, CI 90% [-1-0.15], p = 0.026, Tau -1, CI 90% [-1--0.55], p = 0.0003, and Tau -0.32, CI 90% [-0.76-0.11], p = 0.22 for dyads D01, D02, and D05, respectively), and that behavioural skills training was successful in teaching owners to perform a dog training intervention with high fidelity. Although the results are promising, more canine-related research into functional analysis and noncontingent reinforcement, as well as implementation of behavioural skills training with animal caregivers, is needed.

Keywords: ABA; behavioural skills training; companion dogs; functional analysis; noncontingent reinforcement.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Counts of jumping up behaviour during functional analysis conditions (i.e., attention, control, demand, ignore, and tangible) are shown for (A) dyad D01; (B) dyad D02; (C) dyad D03; (D) dyad D04; and (E) dyad D05. Each figure displays numbers of weekly cycles (i.e., five sessions; x-axis), and count of jumping up responses (y-axis) for each dyad. The data paths represent the behaviour changes during each condition.
Figure 1
Figure 1
Counts of jumping up behaviour during functional analysis conditions (i.e., attention, control, demand, ignore, and tangible) are shown for (A) dyad D01; (B) dyad D02; (C) dyad D03; (D) dyad D04; and (E) dyad D05. Each figure displays numbers of weekly cycles (i.e., five sessions; x-axis), and count of jumping up responses (y-axis) for each dyad. The data paths represent the behaviour changes during each condition.
Figure 1
Figure 1
Counts of jumping up behaviour during functional analysis conditions (i.e., attention, control, demand, ignore, and tangible) are shown for (A) dyad D01; (B) dyad D02; (C) dyad D03; (D) dyad D04; and (E) dyad D05. Each figure displays numbers of weekly cycles (i.e., five sessions; x-axis), and count of jumping up responses (y-axis) for each dyad. The data paths represent the behaviour changes during each condition.
Figure 2
Figure 2
Count of dogs’ jumping-up responses (left y-axis) and procedural integrity of owners’ implementation of the NCR training, expressed in percentages, during different conditions of BST intervention (right y-axis). Data on owner procedural integrity are not shown during baselines (FA tang and FA attn for dyads 01 to 03 and dyad 05, respectively) because the BST intervention was not provided during these phases. Each horizontally arranged panel displays the indicated dyad’s data throughout weekly sessions. Each of the BST phases are presented in separate columns which are divided by dashed vertical lines. The phases labelled with “GEN” (“generalisation sessions”) were conducted by the experimenter. Respective procedural integrity data are depicted as open circles contrasting owner procedural integrity data points (closed circles). Data on FU probes were collected three weeks after the last GEN session. Note. FA tang/attn = functional analysis tangible/attention condition; OI = oral instruction; MOD = modelling; MOD and FB = modelling and feedback; GEN = generalisation sessions; FU = follow-up probe.
Figure 3
Figure 3
Mean inter-response times (IRT) proportional to baseline measures (FAtang or FAattn) across owner-led BST phases and the generalisation phase, which was carried out by the first author. Values below 1 represent shorter mean IRTs between jumps, when compared to baseline measures (increase in rate of responses). Proportions were calculated by averaging the IRT of each phase and dividing it by the average IRT of baseline. For example, in the case of dog D03 during OI phase, mean IRT of 14 s was divided by mean baseline IRT of 20 s, which resulted in a proportional IRT of 0.70. This value indicates that the length of IRTs dropped 70% when compared to baseline levels.
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