Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 1 of 26
Investigating Pain-Related Avoidance Behavior using a
Robotic Arm-Reaching Paradigm
Eveliina Glogan1,2, Rena Gatzounis1, Kristof Vandael1,3, Mathijs Franssen2, Johan W. S. Vlaeyen1,2, Ann Meulders1,2
1Experimental Health Psychology, Maastricht University 2Research Group Health Psychology, KU Leuven 3Laboratory of Biological Psychology, KU
Glogan, E., Gatzounis, R., Vandael, K.,
Franssen, M., Vlaeyen, J.W.S.,
Meulders, A. Investigating Pain-Related
Avoidance Behavior using a Robotic
Arm-Reaching Paradigm. J. Vis. Exp. (),
e61717, doi:10.3791/61717 (2020).
October 2, 2020
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
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 2 of 26
investigation of avoidance behavior and to further our understanding of its underlying
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
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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
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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
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 .
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 5 of 26
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
1. Preparing the laboratory for a test session
1. Before the test session: Send the participant an e-mail
informing him/her about the delivery of pain stimuli, of
the general outline of the experiment, and the exclusion
criteria. Exclusion criteria for healthy participants
comprise: being under 18 years of age; chronic pain;
analphabetism or diagnosed dyslexia; pregnancy; left-
handedness; current/history of cardiovascular disease,
chronic or acute respiratory disease (e.g., asthma,
bronchitis), neurological disease (e.g., epilepsy), and/
or psychiatric disorder (e.g., clinical depression, panic/
anxiety disorder); uncorrected problems with hearing or
vision; having pain in the dominant hand, wrist, elbow or
shoulder that may hinder performing the reaching task;
presence of implanted electronic medical devices (e.g.,
cardiac pacemaker); and presence of any other severe
2. Due to COVID-19 safety precautions, ask the participant
to wash/disinfect his/her hands upon arrival at the
lab, and do so yourself. Wear a disposable facemask
throughout the duration of the test session, and latex
gloves whenever physical contact with the participant is
3. Use two separate rooms or sections for the experimental
setting: one for the participant and the other for the
4. Use one computer with two separate screens: one
computer screen for the experimenter, and one larger
television screen for the participant.
5. To turn on the robotic arm (e.g., HapticMaster), press
the power switch in the front of the robot (specific to
this robot). Subsequently, turn on the emergency switch,
which may later be used to turn off the robot if necessary.
6. Recalibrate the robotic arm before each test day. This is
done via a direct application programming interface (API)
connection with the robotic arm, and only needs to be
done once, at the beginning of the test day.
1. To establish the API connection, open an internet
browser on the computer, and type in the specific API
address of the robotic arm.
2. On the webpage, select State under HapticMASTER.
Subsequently, press the Start button next to Init (for
NOTE: This is the standard calibration procedure
for this robot. Different robots may require different
7. Use a constant current stimulator, which is connected
to the computer (see step 1.4). During the experiment,
the pain stimulus is delivered via the experimental
script, which runs on the computer. The experiment is
programmed using a cross-platform game engine (see
Table of Materials).
1. For safety reasons, disable the constant current
stimulator output by switching down the orange toggle
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switch in the upper-right corner of the stimulator’s
front control panel.
2. Use the orange toggle switch in the middle of the front
control panel to set the output range to x 10 mA.
3. Use the black rotary knob in the upper-left corner of
the front control panel to set the pulse duration to 2
ms (2000 µs).
4. To switch on the constant current stimulator, press
the power button in the lower-left corner of the front
2. Screening for exclusion criteria and obtaining
1. Position the participant approximately 2.5 m from the
television screen (see step 1.4), at a comfortable distance
(~15 cm) from the handle (sensor) of the robotic arm, in
a chair with arm rests (Figure 1).
2. Screen the participant for exclusion criteria by means of
self-report (see step 1.1 for exclusion criteria).
3. Inform the participant about the delivery of pain stimuli
and of the general outline of the experiment. Also, inform
him/her that he/she is free to withdraw participation at any
point during the experiment, without any repercussions.
Obtain written informed consent.
4. To minimize physical contact with the participant, ensure
that the participant section of the lab includes a table on
which exclusion and informed consent forms, as well as a
Tablet for questionnaires (see step 6.2) are placed before
the participant’s arrival. The participant should be able to
access and sign the forms independently using this table.
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).
1. If the participant is wearing long sleeves, ask him/her to
roll up the sleeve on his/her right arm at least 10 cm above
2. Fill the center of the stimulation electrodes with
conductive electrolyte gel and plug the electrode cables to
the emergency switch, which is connected to the constant
current stimulator in the experimenter section of the lab.
3. Attach the stimulation electrodes over the triceps tendon
of the participant’s right arm using a strap. Make sure the
strap is neither too tight nor too loose. Once the electrodes
have been attached, tell the participant to relax his/her
4. Calibrating the pain stimulus
1. Explain the pain calibration procedure and corresponding
scale by presenting it on the television screen (see step
1. Clarify to the participant that he/she may choose
the stimulus which he/she will receive during the
experiment, but explain that for data integrity he/she is
asked to select a stimulus that he/she would describe
as “significantly painful and demanding some effort to
2. Ask the participant to rate each stimulus on the
numerical scale presented on the television screen,
ranging from 0–10, where 0 is labeled as “I feel
nothing”; 1 as “I feel something, but this is not
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unpleasant; it is only a sensation” (i.e., detection
threshold), 2 as “the stimulus is not yet painful, but is
beginning to be unpleasant”; 3 as “the stimulus starts
being painful” (i.e. pain threshold); and 10 as “this is
the worst pain I can imagine”.
2. Enable the constant current stimulator output by switching
up the orange toggle switch (see step 1.7.1).
3. During the pain calibration procedure, manually increase
the intensity of the pain stimuli using the rotary knob on
the front control panel of the constant current stimulator.
The intensity of the pain stimulus can be seen above this
1. Start with an intensity of 1 mA, and gradually increase
the intensity in a stepwise manner, with increases of
1, 2, 3, and 4 mA increments. Use the following order
of stimulus presentations in mA: 1, 2, 4, 6, 8, 11, 14,
17, 20, 24, 28, 32, 36, 40, 44, 48, 52, etc.
4. To deliver the pain stimuli one stimulus at a time, manually
trigger the constant current stimulator by pressing the
orange trigger button on the front control panel.
1. Announce each stimulus to the participant before
triggering the constant current stimulator.
5. Terminate the calibration procedure once the participant
reaches a pain intensity level which he/she would
describe as “significantly painful and demanding some
effort to tolerate”. Ideally, this should correspond to a 7–
8 on the pain calibration rating scale.
6. Document the participant’s final pain intensity in mA and
his/her pain intensity rating (0–10) and maintain this
intensity for the remainder of the experiment.
5. Running the experimental task
1. Verbally inform the participant that he/she will receive
instructions about the robotic arm-reaching paradigm on
the television screen in front of him/her, after which he/
she will be able to practice the task under the supervision
of the experimenter.
2. Provide the participant with standardized written
instructions of the task on-screen.
3. Practice: Via the experimental script, on the television
screen, present three arches (T1–T3) situated midway
through the movement plane. The easiest arm movement
(T1) is paired with no deviation or resistance, the middle
arm movement (T2) is paired with moderate deviation and
resistance, and the furthest arm movement (T3) is paired
with the largest deviation and strongest resistance.
1. Instruct the participant to use his/her dominant hand
to operate the sensor of the robotic arm, represented
by a green ball on the television screen, and to move
the ball/sensor from a starting point at the lower-
left corner of the movement plane, to a target at the
upper-left corner of the movement plane.
2. Instruct the participant that he/she can freely choose
which one of the available movement trajectories to
perform on each trial.
4. Do not administer the pain stimulus (see section 3:
Note and step 5.7.6) during the practice phase. However,
ensure that the relationship between deviation and
resistance (see step 5.3) is in place.
5. Provide the participant with verbal feedback while they
perform the practice phase.
1. Ensure the participant does not start moving before
the visual and auditory “start signals”, and that he/she
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releases the robotic arm immediately when the visual
and auditory “stop signals” are presented.
NOTE: Two distinct auditory signals (a “start tone”
and a “scoring tone”) and two distinct visual signals
(the target and a virtual “traffic light” turning green and
red, respectively; Figure 1) have been used as start
and stop signals. Auditory and visual start signals are
presented simultaneously, as are auditory and visual
2. Instruct the participant to provide self-report
measures of pain-expectancy and fear of movement-
related pain on a continuous rating scale, by scrolling
to the left and right on the scale using two respective
foot pedals on a triple foot switch. Instruct him/her to
confirm his/her answer using a third foot pedal.
NOTE: Present self-report questions on fixed,
predetermined trials, for each movement trajectory
separately. Ensure, via the experimental script, that
the robotic arm is immobilized and remains fixed
during the time the participant is responding to the
6. At the end of the practice phase, respond to the
participant’s questions. Leave the experimental section/
room and dim the lights. The participant starts the
experiment himself/herself by pressing the ‘Confirm’ foot
pedal (see step 5.5.2).
7. Acquisition: During avoidance acquisition, similarly to
the practice phase, let the participant choose which
movement trajectory (T1–T3) to perform on each trial.
1. During avoidance acquisition, subject the participant
to the experimental Response-Outcome (movement
trajectory-pain) contingencies, and to the avoidance-
costs, i.e., the tradeoff between pain and effort, via
the experimental script.
2. Specifically, if the participant performs the easiest
movement trajectory (T1), always present the pain
stimulus (100% pain/no deviation or resistance).
3. If he/she performs the middle movement trajectory
(T2), present the pain stimulus with a 50% chance, but
ensure he/she will have to exert more effort (moderate
deviation and resistance).
4. If the participant performs the furthest, most effortful
movement trajectory (T3), do not present the pain
stimulus at all, but ensure that he/she will have to
exert the most effort to reach the target (0% pain/
largest deviation, strongest resistance).
NOTE: If applicable to the design, a Yoked Group
can be used as control. In yoked procedures, each
control participant is paired with a participant in
the experimental group, such that the two receive
the same reinforcement schedules48 . Thus, in the
current paradigm, each Yoked Group participant
receives pain stimuli on the same trials as his/
her Experimental Group counterpart, regardless of
the trajectories he/she chooses. No acquisition of
avoidance behavior is expected in the Yoked Group,
given the lack of manipulated Response-Outcome
(movement trajectory-pain) contingencies.
5. Where applicable, save data from each Experimental
Group participant on the computer (see section 1.4),
and use as reference for the reinforcement schedules
of each Yoked (control) Group participant.
1. If using a Yoked procedure (i.e., each control
participant is paired with a participant in the
experimental group, such that the two receive
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the same reinforcement schedules48 ), allocate
participants to groups using a randomization
schedule with the rule that the first participant
must be in the Experimental Group. Following
this, participants are assigned to either group
randomly, as long as, at each point, the number
of Experimental Group participants exceeds the
number of Yoked Group participants.
6. On trials with a pain stimulus, present the pain
stimulus once two-thirds of the movement has
been performed, i.e., once the participant has
moved through a trajectory arch. The constant
current stimulator is automatically triggered via the
7. Successful trial-completion is indicated by the
presentation of visual and auditory stop signals.
Subsequently, ensure, via the experimental script,
that the robotic arm automatically returns to its starting
position where it remains fixed. After 3,000 ms,
present the visual and auditory start signals, and the
participant can start the next trial.
NOTE: Trial duration differs between trials and
participants, due to differences in movement speeds.
The number of trials per experimental phase can
also change between experiments. We recommend a
minimum of 2 x 12 trials for successful acquisition of
avoidance. Including the steps described above, the
acquisition protocol lasts approximately 45 min.
8. Generalization: In the generalization protocol, test for
generalization of avoidance after the acquisition phase
(see section 5.7).
NOTE: When testing for generalization of avoidance,
the on-screen trajectory arches are separated during
acquisition, to leave room for the generalization trajectory
arches, which are positioned between the acquisition
trajectory arches (see Figure 1).
1. On the television screen, present three novel
movement trajectories instead of the acquisition
trajectories T1–T3. Ensure that these “generalization
trajectories” (G1–G3) are located adjacent to the
acquisition trajectories. Specifically, G1 is situated
between T1 and T2, G2 between T2 and T3, and
G3 to the right of T3 (see Figure 1). Do not pair
generalization trajectories with the pain stimulus.
NOTE: Including the steps described above, with a
generalization phase of 3 x 12 trials, the avoidance
generalization protocol lasts approximately 1.5 h. A
Yoked Group48 is required for testing generalization
of avoidance (see step 5.7.5). However, different
controls can be used depending on the specific
research question (cf. context modulation of
avoidance in a within-subjects design24 ).
9. Extinction with response prevention (RPE): In the
RPE protocol, after the acquisition phase (see section
5.7), provide the participants with standardized written
instructions stating that in the upcoming phase they are
only allowed to perform T1.
1. During the RPE phase, via the experimental script,
visually (e.g., blocking the trajectory arches with a
gate) and/or haptically (e.g., block participant’s arm
movement with a haptic wall) block T2 and T3, so
that only T1 is available. T1 is not paired with the
pain stimulus during this phase. Including the steps
described above, with an RPE phase of 4 x 12 trials,
this session lasts approximately 60 min.
10. Test of spontaneous recovery: For testing spontaneous
recovery of avoidance, administer a 2-day protocol with
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24 h ± 3 h in between sessions. On day 1, administer the
RPE protocol (see section 5.9).
1. On day 2, attach the stimulation electrodes
(see section 3). Provide brief on-screen refresher
instructions of the task. Do not include any information
regarding the pain stimuli.
2. Present the three acquisition trajectories (T1–T3, cf.
acquisition phase, see section 5.7), in the absence
of the pain stimulus. Including the post-experimental
questionnaire (see section 6.2), and a spontaneous
recovery phase of 4 x 12 trials, this session lasts
approximately 45 min.
NOTE: To prevent reinstatement of fear (i.e., return
of fear following unexpected encounters with the pain
stimulus42 ; see discussion), do not recalibrate the
pain stimulus on day 2.
6. Concluding the experiment
1. Once the participant has completed the experiment,
detach the stimulation electrodes.
2. Provide the participant with a Tablet located on the table
in the participant’s section of the lab (see section 2.4),
for responding to an exit questionnaire inquiring about
the intensity and unpleasantness of the pain stimulus
and avoidance-costs, as well as awareness of the
experimental Response-Outcome (movement trajectory-
3. While the participant completes the psychological trait
questionnaires, clean off the electrolyte gel from the
4. Once the participant has finished completing the
psychological trait questionnaires, provide him/her with a
debriefing and reimbursement.
5. Clean the stimulation electrodes thoroughly with a
disinfectant solution appropriate for cleaning medical
instruments; remove all the gel inside and around the
electrodes. Dry the electrodes with soft tissue paper.
Clean the sensor of the robotic arm with disinfectant wipes
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
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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).
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 12 of 26
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.
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 13 of 26
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.
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 14 of 26
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.
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 15 of 26
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.
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 16 of 26
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.
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 17 of 26
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.
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 18 of 26
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
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
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 19 of 26
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.
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 20 of 26
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
Copyright © 2020 JoVE Journal of Visualized Experiments jove.com October 2020 • • e61717 • Page 21 of 26
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
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
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