Abstract
The patient-clinician relationship is known to significantly affect the pain experience, as empathy, mutual trust and therapeutic alliance can significantly modulate pain perception and influence clinical therapy outcomes. The aim of the present study was to use an EEG hyperscanning setup to identify brain and behavioral mechanisms supporting the patient-clinician relationship while this clinical dyad is engaged in a therapeutic interaction. Our previous study applied fMRI hyperscanning to investigate whether brain concordance is linked with analgesia experienced by a patient while undergoing treatment by the clinician. In this current hyperscanning project we investigated similar outcomes for the patient-clinician dyad exploiting the high temporal resolution of EEG and the possibility to acquire the signals while patients and clinicians were present in the same room and engaged in a face-to-face interaction under an experimentally-controlled therapeutic context. Advanced source localization methods allowed for integration of spatial and spectral information in order to assess brain correlates of therapeutic alliance and pain perception in different clinical interaction contexts. Preliminary results showed that both behavioral and brain responses across the patient-clinician dyad were significantly affected by the interaction style.
Keywords: Chronic pain, Therapeutic Alliance, EEG Hyperscanning, Brain Source Localization
I. INTRODUCTION
The perception of pain is heavily influenced by psychological factors, such as past experience, mood and social interaction. This is also true for chronic pain patients whose long-standing pain is known to fluctuate in response to various psychosocial variables. Factors such as clinical engagement and expectations can significantly modulate how patients perceive an intervention and its efficacy and therefore influence the overall clinical outcome[1], [2]. The aim of this study was to identify brain and behavioral mechanisms supporting the patient-clinician relationship as a significant factor in pain therapy. Recent advancements in cognitive neuroscience have already allowed investigators to characterize some of the autonomic and neural processes associated with successful, empathetic social communication [3], [4]. However, while most of these neuroimaging studies have employed single-subject experimental designs, it is increasingly recognized that a more effective understanding of the complex dynamics at the basis of the social interaction requires two-person methodologies [5]. Here we recorded simultaneous EEG of patient-clinician dyads during clinical interaction to investigate the brain response associated with therapeutic alliance and pain perception. In order to study the impact of the patient-clinician relationship on pain therapy we modulated two variables of the interaction between an acupuncturist and a chronic low back pain (cLBP) patient: the context of the encounter [6] (augmented vs. limited) and the presence of an actual treatment (treated vs. no treated). An augmented context is thought to emphasize a meaningful, empathic, respectful, and trust-building conversation, supported by appropriate non-verbal behaviors including warmth, attention, empathy, and bodily behaviors. On the contrary, a limited encounter emphasizes strictly clinical information collection for subsequent treatment and a more neutral, impersonal, and narrowly-focused clinician. We hypothesized that an augmented therapeutic encounter would lead to greater experimental and clinical pain reduction compared to a limited therapeutic encounter and would be supported via behavioral data and activation of brain networks implicated in social mirroring, theory-of-mind, and empathy processing (e.g. TPJ, vlPFC).
II. MATERIAL AND METHODS
A. Experimental Design
We enrolled 11 patient/clinician dyads. Patients were suffering from cLBP while clinicians were acupuncturists. We chose to use an acupuncture treatment in order to allow for a clinical intervention amenable to our experimental design, while still maintaining ecological validity within clinicians’ scope of practice. Brain signals were acquired using 64-channel EEG nets (EGI’s Geodesic EEG System), enabling subjects to interact while in the same room, thereby increasing ecological validity compared to our previously reported fMRI hyperscanning setup. The first part of the experiment session was a clinical assessment in which the clinician performed either an augmented (N=5 dyads) or limited (N=6 dyads) semi-scripted and trained intake. The augmented interaction style established a warm and attentive patient-practitioner relationship with active listening and personalized content; the limited style was instead neutral and impersonal, with a distracted clinician. The clinical intake phase was followed by an experimental paradigm in which the patient experienced pressure-evoked pain stimuli, delivered by pressure cuff inflation over the lower leg. The pressure stimuli comprised 20 repeated trials in a pseudorandom order. Trials were separated into two experimental conditions: i) treatment (T), wherein the clinician treated the cuff pain using an Electro-Acupuncture (EA) device with needles inserted proximal to the cuff; ii) no treatment (NT) wherein the clinician observed the patient during the pain stimulation but did not activate the EA device. The block design (Fig.1) started with a resting interval of variable (2–4s) duration followed by a visual cue that indicated whether the upcoming pain stimulus would be treated (green) or not (red) by the clinician. The anticipation cue duration was jittered in order to avoid habituation to oncoming pain. Cuff pain blocks included moderately painful pressure applied to the patient’s lower leg for 10 seconds while the clinician pressed a button to activate the EA device and treat or not treat the pressure pain. After another variable-duration resting period, patients rated the intensity of the pain they felt on the prior pain trial while clinicians rated patients’ pain vicariously using a Visual Analogue Scale (0 to 100).
Figure 1.
Timeline of the experimental paradigm.
Following this experimental paradigm, clinicians treated patients’ clinical back pain using acupuncture therapy. Low back pain (Clinical Pain) was rated by the patient before (PRE) and after (POST) acupuncture therapy using a scale from 0 to 10 (most pain imaginable). The Consultation and Relational Empathy Measure (CARE) questionnaire assessed the quality of the patient-clinician relationship and was collected at the end of every session and used as a measure of therapeutic alliance. We compared behavioral responses (Pain Intensity and CARE score) between limited and augmented groups and correlated ΔPerceived-Pain (NT–T, as rated by the patients) with ΔVicarious-Pain (NT-T, as rated by the clinicians (Pearson’s correlation, α=0.05).
B. EEG data analysis
Pre-processing:
EEG scalp data were band-pass filtered (range 1–30 Hz) and ocular artifacts were removed through Independent Component Analysis (ICA). Signals were then segmented in 10-second time windows corresponding to the pain stimulation (cuff ON) and classified in T and NT trials (10 trials per condition). After a further segmentation in one-second epochs, residual artifacts were removed using a semi-automatic procedure based on a threshold criterion (±80 μV).
Source Reconstruction:
Cortical and subcortical brain sources were then reconstructed by applying the algorithm standardized LOw-REsolution brain electromagnetic Tomography (sLORETA [7]) to the high-density EEG signals acquired at scalp level. sLORETA allowed to estimate the current source density distribution on a dense grid of 6239 voxels (5 mm spatial resolution), modeling the whole grey matter.
Brain Maps:
Firstly, we computed the Power Spectral Density (PSD) at single subject level for each voxel in the gray matter and each experimental condition (T/NT). The obtained PSD values were averaged in the typical EEG frequency bands: theta [4 – 8] Hz, alpha [8 – 12] Hz, beta [12 – 30] Hz. Then, in order to determine areas in the patients’ and clinicians’ brain showing significantly different activity in the T Vs NT conditions, we statistically compared these parameters (Permutation Test, α=0.05, FDR corrected) for each voxel and each frequency band, separately for the augmented group and the limited group. sLORETA software was employed to visualize the head volume. Each colored voxel represents the t-value (red if NT>T and blue if T>NT) associated with a statistical significance.
III. RESULTS
A. Behavioral and Clinical outcomes
This preliminary analysis performed on 11 dyads showed that therapeutic alliance (CARE score), was rated as significantly higher for augmented, compared to limited, interaction context (unpaired T-test, p<0.01). As showed in Fig. 2a, this trend appeared even stronger for clinician ratings compared to the patients. Clinical pain (cLBP), assessed at the beginning and at the end of the session, was reduced for both the augmented and limited interaction style, though statistical significance was noted only for the augmented group (Fig. 2b, paired T-test, p<0.01). Consistently, cuff-evoked pain levels after each stimulation was rated as lower by patients experiencing an augmented context compared to a limited context (Fig. 2c), for both T and NT trials. Moreover, patients’ pain rating change for treatment trials (NT-T) was correlated with clinicians’ vicarious pain difference scores (Fig. 2d), suggesting that clinicians could perceive via non-verbal cues when patients experienced greater pain relief (Pearson’s correlation, R=0.67, p=0.03).
Figure 2.
a) The Consultation and Relational Empathy Measure (CARE) score evaluated for patients and clinicians, is significantly higher in the “augmented” group with respect of the “limited” one (**p<0.01). b) Clinical pain assessed before (PRE) and after (POST) acupuncture treatment significantly decreased for the augmented interaction context group (**p<0.01) and showed a similar trend for the limited context group (p=0.054). c) Evoked cuff pressure pain intensity during the EEG hyperscanning experiment was rated by patients as lower during the augmented context (compared to limited) for both treatment (T) and no treatment (NT) trials. d) Patient-rated ΔPain (NT–T) was correlated with clinicians’ vicarious pain ratings (R=0.67, p=0.03).
B. Brain Response
The brain maps obtained from the EEG signals are the result of the statistical contrast between T and NT trials for each group (Fig. 3). As for the clinicians’ brain maps we found significant differences between NT and T in the insula and the anterior cingulate cortex (ACC) but only in the augmented context, suggesting increased empathy processing when clinicians are not allowed to treat patients receiving an evoked cuff pressure pain. Almost no significant differences were found for clinicians in the limited condition. As for the patients, an inverse behavior was found. In fact, in the augmented context, patients’ maps show no significant differences between T and NT trials, suggesting that the established therapeutic alliance plays a significant role in pain perception, regardless of the presence or absence of treatment. In the limited context, nociception related brain areas (superior temporal gyrus, medial temporal gyrus, insula and middle temporal gyrus) were more active in NT trials than T condition. We did not see significantly increased activity in T, compared to NT, condition for the limited context in patients.
Figure 3.
Spectral statistical group maps obtained comparing the brain activations (PSD in theta band) during the T and the NT trials. We reported the same slice (MNI coordinates: X=−42, Y=−15, Z=0) for clinicians’ (top) and for the patients’ (bottom) in the augmented (top) and limited (bottom) interaction. Red codes for the t value when NT>T, blue for T>NT (permutation test, α=0.05, FDR corrected)
IV. DISCUSSION
Patient-clinician behavioral and neurobiological response (including brain and autonomic signals) reflects and supports processes such as mutual empathy and therapeutic alliance, constituting a cornerstone for patient-centered care [8]. We employed advanced technologies to create a hyperscanning experimental setup in which several acquisition devices are synchronized (millisecond precision) in order to collect simultaneously EEG, ECG, GSR data from patient/clinician dyads during a naturalistic clinical interaction and an experimental pain paradigm. The preliminary results obtained for the first 11 dyads demonstrated important behavioral/clinical responses. Patients in the augmented group rated their therapeutic alliance with their clinician higher than patients in the limited group, reflecting a successful experimental design in terms of differentiation of the two interaction contexts.
In the augmented group, the clinical low back pain showed a stronger reduction in the POST vs. PRE and the evoked cuff pressure pain was lower in agreement with the hypothesis that the quality of the clinical encounter contributes to analgesia and clinical outcomes [4], [6]. Interestingly, we found evidence of transfer in pain ratings, as patients who reported greater pain relief, had clinicians who perceived higher treatment efficacy. The main findings of brain signal analysis demonstrated that even with a low spatial resolution acquisition technique as EEG, we were able to identify activation (for no-treatment versus treatment trials) of important regions encoding social cognitive processes, such as mentalizing or Theory of Mind (ToM) [9]. Furthermore, insula cortex and ACC played a more important role in the clinician response during the observation or patients’ (i.e. vicarious) pain, reflecting stronger empathy processing [10], [11]. No specific activation was noted when comparing T versus NT trials for patients during an augmented context, possibly due to the fact that the established positive relationship with the therapist influenced pain regardless of treatment. On the contrary, patients involved in the limited context showed increased brain activity when the clinician did not treat their evoked pain. In agreement with previous studies, the evoked cuff pain activated areas such as superior and middle temporal gyrus, and insula cortex [12]. Limitations of this study included the sample size, which will be increased to allow a more robust statistical analysis between the two sub-groups. We hope our findings will lead to a better understanding of the brain mechanisms by which the patient-provider relationship impacts clinical outcomes.
V. CONCLUSION
Behavioral and brain responses across the patient/clinician dyad reflect the context of the interaction style. Empathy and therapeutic alliance can play a key role in the treatment of chronic pain. Our results suggest that empathetic processing may be stronger in the clinician when forced to passively observe, and not be able to treat, the patient in pain following an augmented intake. As for patients, our results suggest that therapeutic alliance influences the perception of pain more broadly, i.e. with or without applied therapy.
Clinical Relevance—
The context of a clinical intervention can significantly impact the treatment of chronic pain. Effective therapeutic alliance, based on empathy, mutual trust, and warmth can improve treatment adherence and clinical outcomes. A deeper scientific understanding of the brain and behavioral mechanisms underlying an optimal patient-clinician interaction may lead to improved quality of clinical care and physician training, as well as better understanding of the social aspects of the biopsychosocial model mediating analgesia in chronic pain patients.
VI. ACKNOWLEDGMENTS
Research supported by NIH - National Center for Complementary and Integrative Health, NIH-NIBIB National Institute of Biomedical Imaging and Bioengineering and Korea Institute of Oriental Medicine (KIOM) and by Sapienza University- Progetto di Ateneo 2019 RM11916B88C3E2DE.
Footnotes
Ethical permissions: The study was approved by the Massachusetts General Hospital institutional review board. All participants provided written informed consent.
Contributor Information
A. Anzolin, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
K. Isenburg, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
A. Grahl, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
J. Toppi, Dept. of Computer, Control, and Management Engineering, “Sapienza” University of Rome, Italy and Neuroelectrical Imaging and Brain Computer Interface Lab, Fondazione Santa Lucia IRCCS, Rome, Italy.
M. Yücel, Boston University Neurophotonics Center.
D.M. Ellingsen, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. He is now with the Department of Psychology, University of Oslo, Norway
J. Gerber, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
A. Ciaramidaro, Department of Education and Human Sciences, University of Modena and Reggio Emilia, Modena, Italy
L. Astolfi, Dept. of Computer, Control, and Management Engineering, “Sapienza” University of Rome, Italy and Neuroelectrical Imaging and Brain Computer Interface Lab, Fondazione Santa Lucia IRCCS, Rome, Italy..
T.J. Kaptchuk, Program in Placebo Studies, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
V. Napadow, Department of Anesthesiology, Brigham and Women’s Hospital and with Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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