Avoidance is central to chronic pain disability, yet adequate paradigms for examining pain-related avoidance are lacking. Therefore, we developed a paradigm that allows investigating how pain-related avoidance behavior is learned (acquisition), spreads to other stimuli (generalization), can be mitigated (extinction), and how it may subsequently re-emerge (spontaneous recovery).
Avoidance behavior is a key contributor to the transition from acute pain to chronic pain disability. Yet, there has been a lack of ecologically valid paradigms to experimentally investigate pain-related avoidance. To fill this gap, we developed a paradigm (the robotic arm-reaching paradigm) to investigate the mechanisms underlying the development of pain-related avoidance behavior. Existing avoidance paradigms (mostly in the context of anxiety research) have often operationalized avoidance as an experimenter-instructed, low-cost response, superimposed on stimuli associated with threat during a Pavlovian fear conditioning procedure. In contrast, the current method offers increased ecological validity in terms of instrumental learning (acquisition) of avoidance, and by adding a cost to the avoidance response. In the paradigm, participants perform arm-reaching movements from a starting point to a target using a robotic arm, and freely choose between three different movement trajectories to do so. The movement trajectories differ in probability of being paired with a painful electrocutaneous stimulus, and in required effort in terms of deviation and resistance. Specifically, the painful stimulus can be (partly) avoided at the cost of performing movements requiring increased effort. Avoidance behavior is operationalized as the maximal deviation from the shortest trajectory on each trial. In addition to explaining how the new paradigm can help understand the acquisition of avoidance, we describe adaptations of the robotic arm-reaching paradigm for (1) examining the spread of avoidance to other stimuli (generalization), (2) modeling clinical treatment in the lab (extinction of avoidance using response prevention), as well as (3) modeling relapse, and return of avoidance following extinction (spontaneous recovery). Given the increased ecological validity, and numerous possibilities for extensions and/or adaptations, the robotic arm-reaching paradigm offers a promising tool to facilitate the investigation of avoidance behavior and to further our understanding of its underlying processes.
Avoidance is an adaptive response to pain signaling bodily threat. Yet, when pain becomes chronic, pain and pain-related avoidance lose their adaptive purpose. In line with this, the fear-avoidance model of chronic pain1,2,3,4,5,6,7,8 posits that erroneous interpretations of pain as catastrophic, trigger increases in fear of pain, which motivate avoidance behavior. Excessive avoidance can lead to the development and maintenance of chronic pain disability, due to physical disuse and decreased engagement in daily activities and aspirations1,2,3,4,5,9. Furthermore, given that the absence of pain can be misattributed to avoidance rather than recovery, a self-sustaining cycle of pain-related fear and avoidance can be established10.
Despite recent interest in avoidance in the anxiety literature11,12, research on avoidance in the pain domain is still in its infancy. Previous anxiety research, guided by the influential two-factor theory13, has generally assumed fear to drive avoidance. Correspondingly, traditional avoidance paradigms12 entail two experimental phases, each corresponding to one factor: the first to establish fear (Pavlovian conditioning14 phase), and the second to examine avoidance (Instrumental15 phase). During differential Pavlovian conditioning, a neutral stimulus (conditioned stimulus, CS+; e.g., a circle) is paired with an intrinsically aversive stimulus (unconditioned stimulus, US; e.g., an electric shock), which naturally produces unconditioned responses (URs, e.g., fear). A second control stimulus is never paired with the US (CS-; e.g., a triangle). Following pairings of the CSs with the US, the CS+ will elicit fear in itself (conditioned responses, CRs) in the absence of the US. The CS- comes to signal safety and will not trigger CRs. Afterwards, during instrumental conditioning, participants learn that their own actions (responses, R; e.g., button-press) lead to certain consequences (outcomes; O, e.g., the omission of shock)15,16. If the response prevents a negative outcome, the chance of that response recurring increases; this is referred to as negative reinforcement15. Thus, in the Pavlovian phase of traditional avoidance paradigms, participants first learn the CS-US association. Subsequently, in the instrumental phase, an experimenter-instructed avoidance response (R) is introduced, canceling the US if performed during CS presentation, establishing a R-O association. Thus, the CS becomes a discriminative stimulus (SD), indicating the appropriate moment for, and motivating the performance of, the conditioned R15. Apart from some experiments showing instrumental conditioning of pain reports17 and pain-related facial expressions18, investigations into the instrumental learning mechanisms of pain, in general, are limited.
Although the standard avoidance paradigm, described above, has elucidated many of the processes underlying avoidance, it also has several limitations5,19. First, it does not allow examining the learning, or acquisition, of avoidance itself, because the experimenter instructs the avoidance response. Having participants freely choose between multiple trajectories, and, therefore, learn which responses are painful/safe and which trajectories to avoid/not avoid, more accurately models real-life, where avoidance emerges as a natural response to pain9. Second, in traditional avoidance paradigms, the button-press avoidance response comes at no cost. However, in real life, avoidance can become extremely costly for the individual. Indeed, high-cost avoidance especially disrupts daily functioning5. For example, avoidance in chronic pain can severely limit people’s social and working lives9. Third, dichotomous responses such as pressing/not pressing a button also do not very well represent real life, where different degrees of avoidance occur. In the following sections, we describe how the robotic arm-reaching paradigm20 addresses these limitations, and how the basic paradigm can be extended to multiple novel research questions.
Acquisition of avoidance
In the paradigm, participants use a robotic arm to perform arm-reaching movements from a starting point to a target. Movements are employed as the instrumental response because they closely resemble pain-specific, fear-evoking stimuli. A ball virtually represents participants’ movements on-screen (Figure 1), allowing participants to follow their own movements in real-time. During each trial, participants freely choose between three movement trajectories, represented on-screen by three arches (T1–T3), differing from each other in terms of how effortful they are, and in the likelihood that they are paired with a painful electrocutaneous stimulus (i.e., pain stimulus). Effort is manipulated as deviation from the shortest possible trajectory and increased resistance from the robotic arm. Specifically, the robot is programmed such that resistance increases linearly with deviation, meaning that the more participants deviate, the more force they need to exert on the robot. Furthermore, pain administration is programmed such that the shortest, easiest trajectory (T1) is always paired with the pain stimulus (100% pain/no deviation or resistance). A middle trajectory (T2) is paired with a 50% chance of receiving the pain stimulus, but more effort is required (moderate deviation and resistance). The longest, most effortful trajectory (T3) is never paired with the pain stimulus but requires the most effort to reach the target (0% pain/largest deviation, strongest resistance). Avoidance behavior is operationalized as the maximum deviation from the shortest trajectory (T1) per trial, which is a more continuous measure of avoidance, than for example, pressing or not pressing a button. Furthermore, the avoidance response comes at the cost of increased effort. Moreover, given that participants freely choose between the movement trajectories, and are not explicitly informed about the experimental R-O (movement trajectory-pain) contingencies, avoidance behavior is instrumentally acquired. Online self-reported fear of movement-related pain and pain-expectancy have been collected as measures of conditioned fear toward the different movement trajectories. Pain-expectancy is also an index of contingency awareness and threat appraisal21. This combination of variables allows scrutinizing the interplay between fear, threat appraisals, and avoidance behavior. Using this paradigm, we have consistently demonstrated the experimental acquisition of avoidance20,22,23,24.
Generalization of avoidance
We have extended the paradigm to investigate generalization of avoidance23—a possible mechanism leading to excessive avoidance. Pavlovian fear generalization refers to the spreading of fear to stimuli or situations (generalization stimuli, GSs) resembling the original CS+, with fear declining with decreasing similarity to the CS+ (generalization gradient)25,26,27,28. Fear generalization minimizes the need to learn relationships between stimuli anew, allowing swift detection of novel threats in ever-changing environments25,26,27,28. However, excessive generalization leads to fear of safe stimuli (GSs similar to CS-), thus causing unnecessary distress28,29. In line with this, studies using Pavlovian fear generalization consistently show that chronic pain patients excessively generalize pain-related fear30,31,32,33,34, whereas healthy controls show selective fear generalization. Yet, where excessive fear causes discomfort, excessive avoidance can culminate in functional disability, due to avoidance of safe movements and activities, and increased daily activity disengagement1,2,3,4,9. Despite its key role in chronic pain disability, research on the generalization of avoidance is scarce. In the paradigm adapted for studying generalization of avoidance, participants first acquire avoidance, following the procedure described above20. In a subsequent generalization phase, three novel movement trajectories are introduced in the absence of the pain stimulus. These generalization trajectories (G1–G3) lie on the same continuum as the acquisition trajectories, resembling each of these trajectories, respectively. Specifically, generalization trajectory G1 is situated between T1 and T2, G2 between T2 and T3, and G3 to the right of T3. In this way, generalization of avoidance to novel safe trajectories can be examined. In a previous study, we showed generalization of self-reports, but not avoidance, possibly suggesting different underlying processes for pain-related fear- and avoidance generalization23.
Extinction of avoidance with response prevention
The primary method of treating high fear of movement in chronic musculoskeletal pain is exposure therapy35—the clinical counterpart to Pavlovian extinction36, i.e., the reduction of CRs through repeated experience with the CS+ in the absence of the US36. During exposure for chronic pain, patients perform feared activities or movements in order to disconfirm catastrophic beliefs and expectations of harm34,37. Since these beliefs do not necessarily concern pain per se, but rather underlying pathology, movements are not always carried out pain-free in the clinic34. According to inhibitory learning theory38,39, extinction learning does not erase the original fear memory (e.g., movement trajectory-pain); rather, it creates a novel inhibitory extinction memory (e.g., movement trajectory-no pain), which competes with the original fear memory for retrieval40,41. The novel inhibitory memory is more context-dependent than the original fear memory40, deeming the extinguished fear memory susceptible to re-emergence (return of fear)40,41,42. Patients are often prevented from performing even subtle avoidance behaviors during exposure treatment (extinction with response prevention, RPE), to establish genuine fear extinction by preventing the misattribution of safety to avoidance10,43.
Return of avoidance
Relapse in terms of return of avoidance is still common in clinical populations, even after extinction of fear43,44,45,46. Although multiple mechanisms have been found to result in the return of fear47, little is known about those relating to avoidance22. In this manuscript, we specifically describe spontaneous recovery, i.e., return of fear and avoidance due to the passage of time40,47. The robotic arm-reaching paradigm has been implemented in a 2-day protocol to investigate return of avoidance. During day 1, participants first receive acquisition training in the paradigm, as described above20. In a subsequent RPE phase, participants are prevented from performing the avoidance response, i.e., they can only perform the pain-associated trajectory (T1) under extinction. During day 2, to test for spontaneous recovery, all trajectories are available again, but in the absence of pain stimuli. Using this paradigm, we showed that, one day after successful extinction, avoidance returned22.
The protocols presented here meet the requirements of the Social and Societal Ethics committee of the KU Leuven (registration number: S-56505), and the Ethics Review Committee Psychology and Neuroscience of Maastricht University (registration numbers: 185_09_11_2017_S1 and 185_09_11_2017_S2_A1).
1. Preparing the laboratory for a test session
2. Screening for exclusion criteria and obtaining informed consent
3. Attaching the stimulation electrodes
NOTE: The pain stimulus is a 2 ms square-wave electrical stimulus delivered cutaneously through two stainless steel bar stimulation electrodes (electrode diameter 8 mm, interelectrode distance 30 mm).
4. Calibrating the pain stimulus
5. Running the experimental task
6. Concluding the experiment
Acquisition of avoidance behavior is demonstrated by participants avoiding more (showing larger maximal deviations from the shortest trajectory) at the end of an acquisition phase, compared to the beginning of the acquisition phase (Figure 2, indicated by A)20, or as compared to a Yoked control group (Figure 3)23,48.
Acquisition of fear and pain-expectancy is evidenced by participants reporting lower fear for T3 compared to T1 and T2, and expecting the pain stimulus less during T3 compared to T1 and T220. Differential self-reports between T1 and T3 are of primary interest, because T2 is ambiguous. Non-differential self-reports between T1 and T2 have also been found, with both differing from T323 (Figure 4A, Figure 5A, Figure 6A, and Figure 7A).
Acquisition is a prerequisite for generalization. Generalization of avoidance behavior is indicated by participants in the Experimental Group avoiding (deviating) more than the Yoked Group48 at the beginning of the generalization phase. Given that generalization is tested in the absence of pain stimuli, avoidance behavior may decrease throughout the generalization phase. Furthermore, a general decrease in avoidance behavior between the end of the acquisition phase and the beginning of the generalization phase (generalization decrement) can be expected. This is a result of the introduction of novel movement trajectories, which may constitute a context-switch49,50. In a previous study, we did not find generalization of avoidance, possibly due to specific parameters of the paradigm23.
Generalization of fear and pain-expectancy is indicated by a similar pattern to that of the acquisition phase, i.e., by participants in the Experimental Group reporting lower fear to G3 compared to G1 and G2, and expecting the pain stimulus less during G3 compared to G1 and G2, at the beginning of the generalization phase. As in the acquisition phase, differential self-reports between G1 and G3 are of primary interest (Figure 4B and Figure 5B). Non-differential self-reports between G1 and G2 have been reported so far, with both differing from G323. Furthermore, given that generalization is tested in the absence of pain stimuli, participants may report less fear and pain-expectancies throughout the generalization phase. Furthermore, a general decrease in fear and pain-expectancies toward the novel generalization trajectories, compared to the acquisition trajectories (generalization decrement) can be expected. In a previous study, we found generalization of fear and pain-expectancies, despite avoidance not generalizing23.
Acquisition is a prerequisite for extinction. During extinction of avoidance behavior with response prevention, participants are only allowed to perform the previously painful movement trajectory (T1), whereas the other two trajectories (T2 and T3) are prohibited. Therefore, given that participants only have the option of performing T1, and thus the observed data pattern does not reflect their own choices, i.e., genuine extinction of avoidance behavior, extinction of avoidance is not included in the analyses (Figure 2).
Extinction of fear and pain-expectancies is evident when participants report lower fear for T1 and expect the pain stimulus less when performing T1, at the end of the RPE phase, compared to the end of the acquisition phase. (Figure 6B and Figure 7B).
Extinction of self-report measures is a prerequisite for spontaneous recovery. Spontaneous recovery of avoidance behavior is indicated by participants avoiding more at the beginning of the test of spontaneous recovery, compared to the end of the RPE phase (Figure 2B).
Spontaneous recovery of fear and pain-expectancy is indicated by participants reporting higher fear and pain-expectancy for T1, during the beginning of the test of spontaneous recovery, compared to the end of the RPE phase (Figure 6C and Figure 7C).
Figure 1: The experimental set-up and outlook of the experimental task. The participant is seated in front of the television screen, at reaching distance from the sensor of the robotic arm. The electrodes are placed on the triceps tendon of the right arm, where the pain stimuli are delivered (red circle), and the triple foot switch is used to give fear of movement-related pain and pain-expectancy ratings. The acquisition phase of the experimental task is shown on the television screen and magnified in the white box. The ball is situated in the lower-left corner, and the target in the upper-left corner (green arch). T1–T3 are situated midway through the movement-plane, from left to right, respectively. Spaces are left between T1–T3 specifically in avoidance generalization protocols, in order to leave room for the subsequent generalization trajectory arches (G1–G3). Please click here to view a larger version of this figure.
Figure 2: Representative data of avoidance behavior during the acquisition, extinction with response prevention, and test of spontaneous recovery phases22. Mean maximum deviation (in centimeters) from the shortest trajectory to the target during acquisition (ACQ1–2), extinction with response prevention (RPE1–4), and spontaneous recovery (TEST1–2). Note that, participants are only allowed to perform the shortest trajectory (T1) during the RPE phase. Error bars represent standard error of the mean (SEM). Data in this figure are from 30 participants (9 men, 21 women; mean age = 21.90)22. This figure is modified with permission from ref.22. Please click here to view a larger version of this figure.
Figure 3: Representative data of avoidance behavior during the acquisition phase20. Relative proportions of movements between the Experimental and Yoked48 Groups, within the experimental movement plane. Top, yellow patterns represent movements predominantly performed by the Experimental Group, and bottom, blue patterns represent movements predominantly performed by the Yoked Group. “Direction from starting point to target” indicates the shortest possible trajectory from the starting point to the target. “Horizontal deviation” indicates deviation from the shortest possible movement trajectory. Data in this figure are from 50 participants (36 men, 14 women; mean age = 24.92)20. This figure is reprinted with permission from ref.20. Please click here to view a larger version of this figure.
Figure 4: Representative data of fear of movement-related pain during the acquisition and generalization phases23. Mean fear of movement-related pain toward the acquisition trajectories in the Experimental and Yoked48 groups during the acquisition blocks (ACQ1–3), and generalization blocks (GEN1–3). Note that during the acquisition phase, self-reports are provided for trajectories T1–T3 and during the generalization phase, for G1–G3. Error bars represent SEM. Data in this figure are from 64 participants (32 per group; Experimental Group: 10 men, 22 women, mean age = 22.88; Yoked Group: 12 men, 20 women; mean age = 23.44)23. This figure is modified with permission from ref.23. Please click here to view a larger version of this figure.
Figure 5: Representative data of pain-expectancy during the acquisition and generalization phases23. Mean pain-expectancy toward the acquisition trajectories in the Experimental and Yoked48 groups during the acquisition blocks (ACQ1–3), and generalization blocks (GEN1–3). Note that during the acquisition phase, self-reports are provided for trajectories T1–T3 and during the generalization phase, for G1–G3. Error bars represent SEM. Data in this figure are from 64 participants (32 per group; Experimental Group: 10 men, 22 women, mean age = 22.88; Yoked Group: 12 men, 20 women; mean age = 23.44)23. This figure is modified with permission from ref.23. Please click here to view a larger version of this figure.
Figure 6: Representative data of fear of movement-related pain during the acquisition, extinction with response prevention, and test of spontaneous recovery phases22. Mean fear of movement-related pain toward the different trajectories (T1–T3) during acquisition (ACQ1–2), extinction with response prevention (RPE1–4), and spontaneous recovery (TEST1–2). Error bars represent SEM. Data in this figure are from 30 participants (9 men, 21 women; mean age = 21.90)22. This figure is modified with permission from ref.22. Please click here to view a larger version of this figure.
Figure 7: Representative data of pain-expectancy during the acquisition, extinction with response prevention, and test of spontaneous recovery phases22. Mean pain-expectancy toward the different trajectories (T1–T3) during acquisition (ACQ1–2), extinction with response prevention (RPE1–4), and spontaneous recovery (TEST1–2). Error bars represent SEM. Data in this figure are from 30 participants (9 men, 21 women; mean age = 21.90)22. This figure is modified with permission from ref.22. Please click here to view a larger version of this figure.
Given the key role of avoidance in chronic pain disability1,2,3,4,5, and the limitations faced by traditional avoidance paradigms19, there is a need for methods to investigate (pain-related) avoidance behavior. The robotic arm-reaching paradigm presented here addresses a number of these limitations. We have employed the paradigm in a series of studies, which have consistently demonstrated acquisition of avoidance, and these effects have extended to our self-report measures of pain-expectancy and fear of movement-related pain20,22,23,24. However, we have also found dissociations between fear and avoidance23 that may be genuine and informative, suggesting that the two do not always share a one-to-one relationship5,12,43,44,45. Additionally, the paradigm presents multiple opportunities for investigating different aspects of avoidance behavior, such as generalization23, extinction with response prevention22, and post-extinction return of avoidance22, as described in the current manuscript.
The current method offers many advantages over traditional avoidance paradigms. First, instead of performing an experimenter-instructed avoidance response, participants in the robotic arm-reaching paradigm acquire avoidance behavior themselves. The paradigm thus better models real life situations, where avoidance behavior emerges naturally as a response to pain9. Understanding the processes underlying how avoidance is acquired, can provide insight into how avoidance can subsequently become pathological, and inspire ways in which these processes can be directly targeted during treatment51. For example, methodological modifications, such as manipulating experimental reward to increase approach and reduce avoidance tendencies52,53, can allow closer investigation of the behavioral and cognitive processes underlying the acquisition of maladaptive avoidance. With regard to this, the acquisition of avoidance demonstrated with the robotic arm-reaching paradigm can be easily applied to investigate excessive generalization of avoidance to safe stimuli23. A second advantage is that the continuous nature of the avoidance response in the current paradigm allows us to examine for whom avoidance might become excessive, as it provides more detailed data than a dichotomous measure. This increased detail in the data allows heightened sensitivity for picking up individual differences, by means of comparing deviation scores between participants. Such a continuous measure is also more ecologically valid, as avoidance in real life can occur at varying degrees. For example, pain-related avoidance can range from subtle (e.g., postural changes or changed breathing when performing a movement) to complete avoidance (e.g., being bedridden). Furthermore, in addition to incorporating a cost to avoidance, the current avoidance response demands some physical effort, meaning that costs increase with time throughout the task. This accurately models real life, where avoidance can become increasingly costly for the individual over a period of time9. For example, prolonged or regular absenteeism becomes costly from a financial point of view54,55. Finally, given the low cost associated with the previously used instructed button-press response, it is hard to disentangle whether participants in traditional avoidance paradigms avoid due to genuine fear, or simply due to automatic following of task instructions. In contrast, given the high-effort and uninstructed nature of the avoidance response in the current paradigm, it seems likely that any avoidance behavior observed models genuine self-motivated avoidance.
In addition to addressing limitations of previous methodologies, the robotic arm-reaching paradigm offers many opportunities for investigating further aspects of avoidance behavior, as demonstrated in the current manuscript by the avoidance generalization and RPE protocols. It is noteworthy that, we previously observed a dissociation between self-reports and avoidance, with fear and pain-expectancies generalizing to the novel movement trajectories, while avoidance did not. There are several plausible explanations for the observed discrepancy between fear and avoidance23, which we are currently investigating. However, this dissociation may also be a genuine and informative finding, which in fact adds to previous literature suggesting that fear and avoidance do not always occur in synchrony5,12,43,44,45, especially when the avoidance response is costly56,57. This finding emphasizes the importance of experimentally investigating avoidance behavior itself, as distinct processes most likely contribute to different aspects of fear learning58,59, and these processes would be difficult to uncover by solely measuring self-reports and psychophysiological indices of fear. In addition to generalization of avoidance to novel movements, the robotic arm-reaching paradigm has also been applied to study generalization of avoidance to novel contexts24. So far, context-based generalization of avoidance has been investigated using different colored screens as contextual cues24. However, Virtual Reality (VR) could be easily implemented with the current paradigm to increase the ecological validity of the experimental contexts. VR could also be applied to study category-based avoidance generalization, such as generalization of avoidance between different action categories60,61. Additional adaptations may also be implemented in the RPE protocol. Besides using a 2-day protocol for the investigation of spontaneous recovery22, we have also investigated whether pain-related avoidance behavior returns not with the passage of time, but after unexpected encounters with the pain stimulus (reinstatement)42 in a 1-day protocol. Furthermore, to examine the proprioceptive underpinnings of pain-related avoidance behavior more closely, the paradigm can be modified to include less or no visual information. This is something we are currently investigating in our lab. Finally, given that physically moving away from an aversive stimulus represents a species-specific defensive response62, not unique to fear and pain, this type of operationalization of avoidance permits investigation of many different types of avoidance as well. For example, the paradigm can potentially be applied to examine, not only avoidance of painful stimuli, but also avoidance of other types of aversive stimuli, such as those inducing disgust or embarrassment63,64.
The described protocol can also be easily extended to include psychophysiological fear measures. Although not described here, we have incorporated eye-blink startle responses, as well as electroencephalography (EEG), into the robotic arm-reaching paradigm. The eye-blink startle measure offers a fear-specific measure of reflexive defensive responses65,66, which can provide additional insight into the mechanisms underlying avoidance behavior and its relationship to fear, whereas implementing EEG to the paradigm enables investigation into specific neural correlates of avoidance behavior67. Additionally, the skin-conductance response (SCR)68, as well as online self-report ratings of relief-pleasantness69,70 could be included as measures of relief71. SCRs have been previously found to correlate with relief72—a proposed reinforcer of avoidance69,70 given its inherent positive valence in response to the omission of negative events73,74. Finally, heart rate (HR) and heart rate variability (HRV) are easily implementable measures that have been linked to multiple aversive emotions associated with avoidance, such as fear, disgust, and embarrassment75.
Despite its strengths, we acknowledge that the robotic arm-reaching paradigm also has its limitations. For example, the paradigm is not easily transferable to other laboratories, as the equipment used in, and required for the paradigm (e.g., robot and constant current stimulator) are expensive, limiting the widespread use of the paradigm and its implementation by other laboratories. However, note that similar robots, which are relatively common in rehabilitation clinics, can be programmed in the same way, and more affordable constant current stimulators are available as well. It is also noteworthy that, in the current method the discriminative stimulus (SD) and the instrumental response are intertwined. This is in contrast to traditional avoidance paradigms, where fear is first acquired towards the CS during the Pavlovian phase, and avoidance is examined in a subsequent instrumental phase. However, the temporal relationship between fear and avoidance is not strictly unidirectional51. Although the current paradigm allows closer investigation of the temporal dynamics of avoidance-emergence in relation to fear-emergence, the measures we have employed so far do not allow us to accurately disentangle the temporal dynamics of fear and avoidance. Currently, avoidance behavior in the paradigm can be examined at a trial-by-trial basis, whereas fear and expectancy ratings are only collected at discrete, specific time points during the task, to not interfere with task flow. However, to allow precise comparisons between fear and avoidance, a future study could use a more continuous measure of fear, for example, by means of a dial76, single-sensor EEG77, or fear-potentiated startle, to allow a detailed understanding of fear-emergence towards the different trajectories, in relation to avoidance. Finally, only electrocutaneous stimuli have so far been used in the robotic arm-reaching paradigm as pain stimuli, for reasons of consistency and comparability with previous studies of pain-related fear78,79,80. However, electrocutaneous stimuli may not fully mimic the more tonic pain experienced by chronic pain patients, given that they produce a relatively phasic, uncommon, and unnatural pain experience81. Other pain-induction methods, such as ischemic stimulation82 and exercise-induced (e.g., delayed onset muscle soreness, DOMS)83,84 pain have been argued to be better experimental analogues of musculoskeletal pain, given their natural and endogenous nature81. These pain-induction methods could be employed in the robotic arm-reaching paradigm in the future. Despite these limitations, the ability of the current paradigm to consistently demonstrate acquisition of fear and avoidance using such entwined SDs and Rs is in itself interesting and novel. Furthermore, we believe that the robotic arm-reaching paradigm can in and of itself further the discussion of the need for more ecologically valid avoidance paradigms19. In addition, the paradigm has the potential to pave the way for developing better avoidance paradigms in general, by providing an example of how problems in the field can be tackled in an innovative manner.
In conclusion, the robotic arm-reaching paradigm offers a promising route to improving the ecological validity of investigations into avoidance behavior, and to furthering our understanding of the underlying processes. Using the paradigm, we have already obtained interesting results, which may not have been uncovered by solely assessing passive correlates of fear such as verbal reports and physiological arousal. Yet, extensions to the paradigm have provided some inconclusive results, which require further investigation and refinement of the procedure. Despite this, the robotic arm-reaching paradigm is a huge leap forward with respect to ecological validity in the paradigms used to study avoidance behavior.
The authors have nothing to disclose.
This research was supported by a Vidi grant from the Netherlands Organization for Scientific Research (NWO), The Netherlands (grant ID 452-17-002) and a Senior Research Fellowship of the Research Foundation Flanders (FWO-Vlaanderen), Belgium (grant ID: 12E3717N) granted to Ann Meulders. The contribution of Johan Vlaeyen was supported by the “Asthenes” long-term structural funding Methusalem grant by the Flemish Government, Belgium.
The authors wish to thank Jacco Ronner and Richard Benning from Maastricht University, for programming the experimental tasks, and designing and creating the graphics for the described experiments.
1 computer and computer screen | Intel Corporation | 64-bit Intel Core | Running the experimental script |
40 inch LCD screen | Samsung Group | Presenting the experimental script | |
Blender 2.79 | Blender Foundation | 3D graphics software for programming the graphics of the experiment | |
C# | Programming language used to program the experimental task | ||
Conductive gel | Reckitt Benckiser | K-Y Gel | Facilitates conduction from the skin to the stimulation electrodes |
Constant current stimulator | Digitimer Ltd | DS7A | Generates electrical stimulation |
HapticMaster | Motekforce Link | Robotic arm | |
Matlab | MathWorks | For writing scripts for participant randomization schedule, and for extracting maximum deviation from shortest trajectory per trial | |
Qualtrics | Qualtrics | Web survey tool for psychological questionnaires | |
Rstudio | Rstudio Inc. | Statistical analyses | |
Sekusept Plus | Ecolab | Disinfectant solution for cleaning medical instruments | |
Stimulation electrodes | Digitimer Ltd | Bar stimulating electrode | Two reusable stainless steel disk electrodes; 8mm diameter with 30mm spacing |
Tablet | AsusTek Computer Inc. | ASUS ZenPad 8.0 | For providing responses to psychological trait questinnaires |
Triple foot switch | Scythe | USB-3FS-2 | For providing self-report measures on VAS scale |
Unity 2017 | Unity Technologies | Cross-platform game engine for writing the experimental script including presentations of electrocutaneous stimuli |