Cognitive exertion affects the appraisal of one’s own and other people’s pain

Laura Riontino; Raphaël Fournier; Alexandra Lapteva; Nicolas Silvestrini; Sophie Schwartz; Corrado Corradi-Dell’Acqua

doi:10.1038/s41598-023-35103-w

. 2023 May 19;13:8165. doi: 10.1038/s41598-023-35103-w

Cognitive exertion affects the appraisal of one’s own and other people’s pain

Laura Riontino ^1,^2,^3,^✉, Raphaël Fournier ², Alexandra Lapteva ⁴, Nicolas Silvestrini ¹, Sophie Schwartz ^2,^5,⁶, Corrado Corradi-Dell’Acqua ^1,^2,⁶

PMCID: PMC10199047 PMID: 37208455

Abstract

Correctly evaluating others’ pain is a crucial prosocial ability. In both clinical and private settings, caregivers assess their other people’s pain, sometimes under the effect of poor sleep and high workload and fatigue. However, the effect played by such cognitive strain in the appraisal of others’ pain remains unclear. Fifty participants underwent one of two demanding tasks, involving either working memory (Experiment 1: N-Back task) or cognitive interference (Experiment 2: Stroop task). After each task, participants were exposed to painful laser stimulations at three intensity levels (low, medium, high), or video-clips of patients experiencing three intensity levels of pain (low, medium, high). Participants rated the intensity of each pain event on a visual analogue scale. We found that the two tasks influenced rating of both one’s own and others’ pain, by decreasing the sensitivity to medium and high events. This was observed either when comparing the demanding condition to a control (Stroop), or when modelling linearly the difficulty/performance of each depleting task (N-Back). We provide converging evidence that cognitive exertion affects the subsequent appraisal of one’s own and likewise others’ pain.

Subject terms: Neuroscience, Psychology

Introduction

Identifying and assessing the intensity of pain experienced by others is a crucial ability. This skill is relevant in many clinical and private contexts^1–5, but especially for caregivers (physicians, nurses, lay individuals in full-time charge of family members, etc.) who have to continuosly monitor others’ pain and might be subjected to fatigue, poor sleep and long/irregular work shifts that may overload of their cognitive resources. However, it is still unclear how extensive mental exhaustion might interfere with the assessment of others’ pain.

In this study we sought to investigate pain assessment under the lens of the well-known “ego depletion” task^6,7. This paradigm assumes that continuous exertion of self-control exhausts one’s own cognitive resources, impacting subsequent use of similar regulatory processes in an active task, decision-making or even the reaction to an aversive event. Importantly, these effects are held to occur across domains, thus suggesting that self-control rests in part on common regulatory abilities^6–8. In this perspective, few studies tested the effect played by cognitive exertion in first-hand pain, to get a glimpse on the role played by one’s resources in the subsequent appraisal and reaction to nociceptive stimuli. However, whereas one study revealed that being engaged in a highly demanding Stroop task decreased the sensitivity to subsequent intense stimulations⁹, others found instead increased sensitivity to mild noxious events^10,11. Such mixed findings beg for a systematic investigation of after-effects of cognitive exertion on different pain levels, and across different depleting tasks, to account also for concerns about reliability of such paradigm which have recently been put forward by the research community^12,13.

Furthermore, it is unclear whether cognitive exertion would impact also the assessment of pain of others, and whether this influence is similar to that observed one’s own experiences. Seminal models from social psychology/neuroscience suggest that others’ suffering is partially processed in an embodied fashion, i.e., by recruiting the same mechanisms underlying one’s own first-hand experiences^14–18. Indeed, analgesic manipulations (e.g., acetaminophen, hypnosis, placebo) can similarly influence the sensitivity to self and others’ pain^19–21. Furthermore, neuroimaging studies suggest that self and others’ pain share a partly-common neuronal representation in a widespread network including the middle cingulate cortex^19,22,23, a brain region held to play a key role in the regulation of one’s pain responses^11,24 (but see²⁵). Hence, it is reasonable to assume that such regulatory mechanisms might equally impact the representation of one’s and others’ pain.

An independent line of research has investigated the role played by cognitive resources in decoding emotional faces. This was chiefly achieved by engaging participants in emotion labelling concurrently to a working memory paradigm requiring high attentional load. The majority of studies report that the processing of emotional states (especially negative) is affected by the task^26–28. Furthermore, neuroimaging investigations has systematically associated the processing of emotional expressions with brain structures such as the amygdala and fusiform gyrus (see²⁹ as meta-analysis), but also found that the activity of these regions was significantly reduced when attentional resources where limited by a competing task^30,31. These studies suggest that emotion recognition is tightly intertwined with higher-order cognitive processes, something that could potentially generalize also to the case of painful expressions. However, this research is grounded in paradigms engaging working memory tasks concurrently to the processing of facial expressions, thus opening the question if the effects observed underlie divided attention (reflecting the cost of being engaged in two activities at once), or cognitive exertion (whose effects instead linger also after the task’s completion).

Here, we engaged participants in one of two demanding paradigms, involving either working memory (Experiment 1: N-Back task) or inhibition (Experiment 2: Stroop task), to investigate the effects of cognitive exertion on the subsequent assessment of one’s and others’ pain (Fig. 1). Although the two tasks underlie different aspects of human executive function, they should both tap a broad regulatory process held to underlie depletion effects. Based on previous research, we expected both demanding tasks to influence intensity ratings of self-pain, albeit with unascertained direction^9,10. The critical question was whether the manipulation would influence also the pain perceived in others in similar fashion to first-hand experiences (as predicted by embodied accounts), or simply by making individuals less sensitive to face-related information.

Experiment 1

Methods

Participants

Recruitment took place through advertisements posted at the University of Geneva buildings and online platforms. We excluded from our experiment all individuals with the following characteristics: history of alcohol or drug abuse, history of neurological or psychiatric illness, history of chronic pain, fever or an ongoing acute medical condition and extreme dark skin colour (because radiation absorption of dark skin is higher for the wavelength of the laser device used for nociceptive stimulations^32,33). No recruitment constraints were applied to gender or age. None of the participants reported using medication. They declared good health and typical cognitive proficiency, they had good (or corrected) visual acuity, and were naïve to the purpose of the study.

Previous studies reported Stroop after-effects on self-pain in an overall cohort of N = 24¹⁰, after excluding those individuals who were not susceptible to the task manipulation (who found the main task easier than its associated control)¹⁰. The same sample size was also sufficiently powerful to show effects on an N-Back task on concurrent pain, after excluding those individuals who were insensitive to the nociceptive stimulation³⁴. As such, we sought to acquire a cohort of similar size which, in addition to the criteria mentioned above, were also filtered for pain insensitivity and task susceptibility. Hence, we recruited a total of 36 participants. Ten were subsequently excluded due to lack of sensitivity to the nociceptive stimulation, whereas 1 was excluded due to the low susceptibility to the task manipulation (see Data Processing subsection below for more details). This led to a final sample of N = 25 (14 females; aged 19 to 37, Mean = 25.16, SD = 5.03 years). This study was approved by the local ethical committee (Commission Cantonale d'Éthique de la Recherche of Geneva, protocol code: CCER N. 2019-01355) and conducted according to the Declaration of Helsinki.

Experimental set-up

In the present study, volunteers assessed their pain sensitivity and judgments of others’ pain after a low or high cognitive demanding N-Back task. Within this framework, we systematically modulated workload (factor Load: low vs high), type of pain (factor Type: self vs other) and pain intensity (factor Intensity: low, medium, high).

N-Back task

We administered an N-Back task³⁵, which was previously used successfully to evaluate the impact of distraction on pain sensitivity³⁴. Participants monitored a series of stimuli written in black appearing one at a time on a grey screen (Fig. 1A). They were required to identify if the stimulus presented was the same as the one presented n previous items by pressing one button (‘yes’) and if not by pressing a different button (‘no’). In the current study, n was set to be 3 (high cognitive load condition) or 0 (low cognitive load condition). In the 3-Back condition, participants were required to constantly update the target letter, by retrieving from working memory the one letter occurring 3 items before. For instance, if we pretend a sequence of letters "RGSR", correct answer to the last would be "yes", as the same letter occurred also three trials before in the sequence "RSGP" but in this case answer is "no". As control, we implemented a low cognitive load condition, in which participants were asked to respond only on the trial that they were currently processing, by pressing “yes” whenever a predefined stimulus (“V” letter) would be presented. In each block, a total of 18 letter stimuli were presented one at a time with 4 target-hits.

Each letter was presented for 500 ms, followed by an inter-trial interval (ITI). The ITI between letters of the 0-Back condition was fixed at 700 ms. Instead, for the 3-Back condition to reduce within-participant variation, the ITI was adapted based on participants’ performance in the previous block (i.e., corresponding to 18 previous trials). This is roughly comparable to a previous study with a similar design (adaptation based on previous 15 trials³⁴), although in that case, the authors tested pain concurrently to the N-Back, and therefore had no need to divide the experimental session into small blocks³⁴. Target sensitivity was assessed with the non-parametric signal detection measure A’^36,37. This parameter is computed from a pair of hit and false alarm rates³⁴: a value near 1 indicates a good discriminability, whereas a value near 0.5 (when hits are equal to false alarm) indicates chance performance. Initial duration of the empty screen was 700 ms. Then based on the previous trial, when discriminability was higher than the targeted level of A’ = 0.75, empty screen interval was reduced, while with a discriminability lower than A’ = 0.75 it was increased.

Prior to the main experiment, participants carried out a brief training session, in which the order of the blocks was fixed: the first block was 0-Back, the second block was 3-Back in which subsequent adjustments were made after each trial. Instead, in the main experiment, the order of blocks was pseudorandomized, and difficulty of the task was calibrated by adapting the interval for each participants’ performance to the previous 3-Back block. Thirteen participants (7 women) started with two blocks 0-Back condition (low cognitive load) and then two blocks with high cognitive load (combined with 2 “Self” and 2 “Other” in a pseudorandomized order) followed by a break of about 5 min and then the same task sequence was repeated (combined with 2 “Self” and 2 “Other” in a pseudorandomized order). With the same procedure, twelve participants (7 women) started with the 3-Back condition (high cognitive load).

Self-pain

Half of the N-Back blocks were followed with painful stimulations on their own body. Self-pain was administered through nociceptive radiant heat stimuli was delivered by an infrared neodymium: yttrium–aluminum-perovskite laser system (Neodinium: Yttrium Aluminium Perovskite; Stimul 1340 El.En®; wavelength 1.34 µm; pulse duration 4 ms, beam diameter 6 mm²). At this short wavelength, the skin is highly transparent to laser stimulation, and consequently, the laser pulses directly and selectively activate Aδ and C fibers nociceptive terminals located in the superficial layers of the skin^38,39. Since these fibers have different conduction velocity, participants experienced a double sensation: an initial pricking pain due to Aδ-fiber stimulation, followed by a C-fiber-related burning pain. Laser pulse was transmitted through an optic fiber of 10-m length, with a diameter of 6 mm by focusing lenses. Laser beam was directed to a rectangular skin area (approximately 4 × 2 cm, main axis mediolateral) on the back of the non-dominant hand. To avoid receptor sensitization, as well as damages from long-term exposure, the laser beam was relocated after each trial within a predefined stimulated skin area (see also⁴⁰).

To ensure protection from adverse effects of the laser, the following procedure were put in place. The experiment was carried out in an ad hoc room, protected with laser safety curtains certified for the wavelength of the stimulator. Furthermore, participants and experimenters wore eye-protection goggles with optical density ≥ 2 at 1.34 µm. Participants were asked to remove all accessories from their non-dominant hand to allow safe stimulation of the skin area.

Prior to the beginning of the experiment, pain stimulus intensity was individually calibrated for each participant based on a random staircase thresholding session⁴¹ to determine stimulations eliciting three levels of pain that were then used in the main experiment. Each trial started with a flash appearing on the screen for 3 s indicating that the stimulation was about to come, while the laser was preparing to deliver the correct amount of energy. After each stimulation, participants answered on a 10-point visual analogue scale ranging from not at all painful (0) to worst pain imaginable (10). Extreme manikins of the arousal scale of the Self-Assessment Manikin (SAM) were displayed at the extremities of the scale for assessing pain intensity as an economical and straightforward cue⁴². We also included numbers under the rating line, coloured from green (0) to red (10), to visually help participants choosing their answer. In this context, participants were instructed to consider the landmark “4” on the scale as the ideal point where they started to feel the stimulation as painful. The rating was self-paced with no time restrictions. The calibration session lasted about 15 min. At the end of this session, we obtained a pain curve based on which we would then select three different energies that corresponded to three different levels of pain for each participant for low pain (LP), medium pain (MP) and high pain (HP) intensity respectively (medians of about 2, 4 and 6 on the pain rating scale).

In the main experiment, after each corresponding N-Back block, participants were exposed to six stimulation-trials in random order. These were characterized by 2 Low, 2 Medium and 2 High pain stimulations. Each trial started with a flash appearing on the screen for 3 s indicating that a stimulation was about to come. The nociceptive stimulus was followed by a black screen lasting for 1 s and then the visual analogue scale for pain judgement. This was identical to the one used in the calibration session, except for the absence of intermediate tick lines, and a time constraint of 5 s for providing a response.

After the pain intensity rating, a 1 s of black screen was presented, followed by a second rating scale. This was a pain metacognition scale probing for participants’ confidence about their previous rating. In particular, participants had to express their confidence about their previous pain judgment on a 10-point visual analogue scale ranging from no confidence at all (0) to completely confident (10). Extreme manikins of the dominance scale of the Self-Assessment Manikin (SAM) were included at the extremities of the metacognition scale⁴². As for the case of pain intensity ratings, participants had 5 s to provide a rating. This second scale was introduced to assess a secondary hypothesis that cognitive exertion could influence, not only participants’ pain assessment, but also the degree of which they were aware of such potential influence.

Following the confidence assessment, a black screen appeared for a random inter-trial interval ranging between 2.5 and 4.5 s with steps of 200 ms. Overall, each block, and subsequent pain stimulations, lasted about 3 min.

Other-pain

The remaining half of the blocks were followed by saw video-clips describing pain in others. For this purpose, we used stimuli taken from a database of videos of patients faces, which had spontaneous (non-simulated) expressions of pain⁴³. Thirty videos were cut to last 3 s and to show the most salient expressions. For video piloting, 21 independent participants rated these short videos online (14 women; age 22 to 35, Mean = 27.6, SD = 4.7). For the purpose of this experiment, we selected 24 videos based on median ratings of the piloting that could match the three levels of self-pain (8 videos per each level of pain), one characterized by low (3 women, 5 men; Mean = 0.58, SD = 0.50), one characterized by medium (4 women, 4 men; Mean = 3.12, SD = 0.60) and one characterized by high (4 women, 4 men; Mean = 4.70, SD = 0.49) level of painful expression. Furthermore, there was high agreement between the 21 raters in their assessment of the videos of each pain level, as shown by the average inter-rater-correlation (low pain, Spearman’s ρ = 0.40 [95% CI: 0.15, 0.67]; medium, ρ = 0.50 [0.11, 0.70]; high, ρ = 0.65 [0.40, 0.82]) and Cronbach’s α (low, α = 0.81 [0.61, 0.89]; medium, α = 0.91 [0.79, 0.96]; high, α = 0.93 [0.85, 0.96]). Finally, as the people depicted in the videos were also probed to rate their own pain experience⁴³, we could thus check that the videos for the three levels of other’s pain exhibited clear-cut differences in low, medium and high self-reported pain. This insured that the selected clips clearly depicted three distinct intensity levels (Low Pain = LP, Medium Pain = MP, High Pain = HP) from both the point of view of the video-recorded people, and from an independent sample of observers.

Procedure

The experiment was conducted under the following procedure. On arrival, participants read carefully and signed the informed written consent, then they were reminded that each laser stimulus would be very fast (only 4 ms) and that they could ask to stop the experiment at any time. All tasks and stimuli were coded, managed and presented with Psychophysics Toolbox Version 3 (PTB-3, http://psychtoolbox.org/), a free set of Matlab R2018b (Mathworks, Natick, MA). The experimental session consisted of two parts: (1) pre-test divided in pain thresholding session and training of the N-Back task, and (2) main experiment. Participants had to use a response box with four buttons in their dominant hand to answer. Two experimenters were always present during the experimental session. One experimenter was responsible for technical checks of the equipment before and during acquisition, including physiological measures, laser inputs and behavioural recordings. The other experimenter was responsible for interacting with participants and delivering painful stimulations by directing the laser beam on participants’ hand. Importantly, the latter experimenter was unaware of the level of pain emitted by the laser.

In the main experiment, each participant performed four blocks representing the 3-Back (cognitive exertion) and four blocks of a 0-Back (baseline), presented in a pseudorandom order (Fig. 1A and C). Each block was followed by the delivery of six pain stimulation trials delivered to either the self (through nociceptive laser stimulations) or the other (through video-clips). This led to a 2 (Task: 3-Back vs. 0-Back) × 2 (Type: Self vs. Other) structure of each block, within each which are administered pain events of 3 intensity levels (Low, Medium, and High). Overall, the experiment session lasted 1 h and half and, at the end, participants were refunded for their time and effort.

Questionnaires’ battery

Following the main experimental session, participants were asked to fill some questionnaires. In addition to the general information sheet (including questions about sex, age and hand dominance), participants filled out the Pain Catastrophizing Scale⁴⁴ (PCS) and the Interpersonal Reactivity Index⁴⁵ (IRI), because we hypothesized that these dimensions of personality might modulate the effects of interests. In the PCS, participants were asked to indicate the degree to which they think and feel when they experience pain using a 0 (not at all) to 4 (all the time) scale. A total score is yielded (ranging from 0 to 52), along with three subscale scores assessing rumination (4 questions), helplessness (6 questions) and magnification (3 questions), which respectively report rumination about pain (e.g. "I can´t stop thinking about how much it hurts"), feeling helpless to manage pain (e.g. "There is nothing I can do to reduce the intensity of my pain") and magnification of pain (e.g. "I´m afraid that something serious might happen").

The IRI measures various aspects of empathy including cognitive and emotional empathy. Participants had to answer 28 statements (7 questions per subscale) using a 5-point scale, ranging from “Does not describe me well” to “Describes me very well”. This measure is divided in four seven-item subscales. The perspective taking (PT) scale reports tendency to spontaneously adopt the psychological point of view of others in daily life (e.g., “I sometimes try to understand my friends better by imagining how things look from their perspective”). The empathic concern (EC) scale assesses the tendency to experience feelings of sympathy and compassion for unfortunate others (e.g., “I often have tender, concerned feelings for people less fortunate than me”). The personal distress (PD) scale taps the tendency to experience distress and discomfort in response to extreme distress in others (e.g., “Being in a tense emotional situation scares me”). The fantasy (FS) scale measures the tendency to imaginatively transpose oneself into fictional situations (e.g., “When I am reading an interesting story or novel, I imagine how I would feel if the events in the story were happening to me”).

Data processing

Behavioral measures

Despite all 36 participants exhibited good sensitivity to pain during the calibration phase, effects of habituation/desensitization might occur in the main experiment. For this reason, we inspected the average rating of the most intense laser stimulation following those blocks which were not held to induce cognitive exhaustion (i.e., 0-Back). We did not include the difficult condition (3-back) as in those blocks sensitivity could have been dampened due to the main manipulation. For ten participants, rating was < 4 on the 10 points intensity scale, and were therefore excluded.

We then checked whether participants were susceptible to the N-Back task. To this purpose, we considered all participants who displayed good sensitivity to pain (N = 26). In this analysis, trials with reaction times < 100 ms were removed as potentially reflective anticipatory response unrelated to the task. For each participant, each task and each condition, we calculated the average accuracy, median reaction times of correct responses, and combined Inverse Efficiency Score (IES), with $I E S = \frac{ReactionTimes}{AccuracyRate}$ ^46,47. This combined measure refers to Reaction Times of correct responses penalized proportionally to the number of errors performed in the same condition (e.g., if a given condition is associated with an accuracy of 90%, IES corresponds to correct Reaction Times multiplied by ~ 10%), and aims at maximizing the information from those cases in which correct Reaction Times and Accuracy are negatively coupled (i.e., conditions eliciting the slowest correct responses being also the least accurate). Omitted responses were considered as errors. After acquisition, all these measures were fed to a paired-sample t-test assessing effects of task difficulty (3-Back vs. 0-Back). Then, individual data were used to exclude from all subsequent analyses those participants who were not susceptible to the task (final sample N = 25 see Results and Fig. 2, left subplot).

Violin plots and individual inverse efficiency data describing the difference between the two main conditions in (A) the N-Back (Exp. 1) and (B) Stroop task (Exp. 2). *** p < 0.001 for the effect of task difficulty. Inverse Efficiency scores refer to Response Times of correct responses (sec) penalized proportionally to the number of errors performed in the same condition. Red dots/lines refer to those specific participants for whom the difficult condition was associated with comparable/lower scores than the control condition. *Int.* Stroop Interference. *Contr.* Stroop Control.

Having established participants’ susceptibility to the task, we tested its effect on the subsequent pain intensity ratings. This was achieved through a linear mixed model with task condition (3-Back vs 0-Back) and intensity of pain (low, medium, high) as fixed factors. In this case, omitted responses were removed from the analysis. The subject’s identity was modelled as random factor, with random intercept and slope for the two fixed factors and the interaction therefor. Specifically, we ran two models, one for the Self-Pain condition, and the second for the Other-pain conditions. Significance associated with the fixed effects was calculated with a Type III Analysis of Variance using the Satterthwaite approximation of the degrees of freedom, as implemented in the lmerTest package⁴⁸ of R (https://cran.r-project.org/) software. In the analysis of pain ratings, effects were considered significant if associated with p < 0.05. Each statistical test is also reported in tabular form associated with the correspondent effect size (Cohen’s d). Following the main analysis, we also run follow-up models assessing the modulating factor of questionnaires scores. The results of these secondary analyses were considered significant if surviving Bonferroni-correction for multiple comparisons for the number of sub-scores.

Physiologic responses

Since it has been shown that cognitive exertion has a negative carryover effects on physical performance⁴⁹ and that physiological states correlate with cognitive fatigue⁵⁰, physiological measures during pain stimulation were also collected to examine possible subsequent effects. Therefore, during the main experiment, we continuously recorded physiological responses to stimuli from their left hand, such as skin conductance (EDA) and heart rate. Detailed information about the analysis of these measures in provided in Supplements.

Results

Task demands

We first assessed whether participants exhibited higher difficulty in the demanding condition. We focused on all participants who displayed adequate sensitivity to pain (N = 26; see “Methods”) and found that, on average, they displayed significant decrease in accuracy in the 3-Back vs. 0-Back condition (t₍₂₅₎ = − 8.64, p < 0.001; d = − 1.73), but also an increase in reaction times of correct responses (t₍₂₅₎ = 5.45, p < 0.001; d = 1.09), and combined inverse efficiency score (IES, t₍₂₅₎ = 5.83, p < 0.001; d = 1.17). This confirms that the 3-Back condition was considered more difficult than its control on the overall population. However, one participant appeared non-susceptible to the manipulation (Fig. 2, left subplot, red line). As mentioned in the Methods section, data from this participant were excluded from subsequent analysis. We thus obtained a final sample of N = 25.

Pain ratings

We then assessed whether sensitivity to nociceptive stimulation on one’s own body was influenced by the preceding task. Table 1 reports results associated with pain intensity ratings, and revealed a significant main effect of stimulation Intensity, confirming that participants rated both MP and HP as more painful than the LP level. No modulation of Task was observed, neither as a main effect, nor in interaction with the Intensity. We also checked whether participants’ sensitivity to one’s pain changed as function of performance of the preceding 3-Back condition. This was achieved by modelling participants’ inverse efficiency score (IES, see Methods) from the previous block as a between-subjects continuous predictor. We chose this measure as it represents an efficient combination of correct Response Times and Accuracy values, which prevents us from running two separate analyses. Table 2 and Fig. 3A report results of the main analysis, confirming the main effect of stimulation Intensity, but also describing a significant IES*Intensity interaction. In particular, the interaction reveals that blocks associated with poorer performance led to significant decreased sensitivity to MP (vs. LP) stimulations, meaning the poorer the performance (high IES) the higher the subsequent hypoalgesia. A similar interaction was observed also for HP (vs. LP), although only at a marginally significant level (Table 2). Finally, as the 3-Back task was adjusted online to stabilize performance across blocks (see “Methods”), IES describes only part of the inter-individual variability in performance, whereas the remaining part of the information is provided by the difficulty parameter (the inter-trial interval, ITI, see “Methods”) of the task and how they changed from block to block. We therefore also modelled responses as function of the median ITI from the preceding block. However, such parameter did not affect participants’ sensitivity to pain, neither as main effect nor in interaction with intensity (see Table 2).

Table 1.

Experiment 1: Analysis of Task-effects on pain.

	Self pain		Other-pain
	t	d	t	d
Intercept	9.43***	1.86	5.00****	1.00
Task	− 1.75	− 0.17	0.37	0.06
Intensity MP	4.72***	0.91	9.29***	1.69
Intensity HP	10.53***	2.11	15.21***	2.92
Task*MP	0.73	0.11	− 0.54	− 0.08
Task*HP	0.30	0.04	0.30	0.04

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We report the t-values and effect sizes (d) associated with parameter estimates from linear mixed model analyses testing effects of task on Self and Others’ pain. Significant effects are highlighted based on the corresponding p-value.

Task contrast 3-back vs. 0-back, MP contrast medium pain vs. low pain, HP contrast high pain vs. low pain.

***, **, * indicate parameters significantly different from 0 at p < 0.001, p < 0.01, p < 0.05, respectively.

Table 2.

Experiment 1: Analysis of task performance.

	Self-pain: IES		Other-pain: IES		Other-pain: ITI
	t	d	t	d	t	d
Intercept	9.33***	1.85	6.11***	1.22	6.22***	1.21
Intensity MP	6.17***	1.07	9.18***	1.57	9.47***	1.43
Intensity HP	10.81***	2.23	13.43***	2.81	14.02***	2.84
Covariate	0.94	0.09	1.90	0.19	1.50	0.10
Cov.MP*	− 2.81**	− 0.20	− 2.89**	− 0.24	− 2.50*	− 0.17
Cov.HP*	− 1.76^	− 0.15	− 0.95	− 0.10	− 1.73	− 0.12

Open in a new tab

We report the t-values and effect sizes (d) associated with parameter estimates from linear mixed model analyses testing effects of task performance and difficulty on Self and Others’ pain. Significant effects are highlighted based on the corresponding p-value.

MP contrast medium pain vs. low pain, HP contrast high pain vs. low pain. Cov. covariate of interest (IES, ITI).

IES = Inverse Efficiency Score; ITI = Inter-trial Interval.

***, **, * indicate parameters significantly different from 0 at p < 0.001, p < 0.01, p < 0.05, respectively.

^ indicate effect at the marginal (0.05 < p < 0.1).

Experiment 1. Analysis of Task Performance. Performance effects on Pain Intensity Stimulation results associated with the N-Back task for Self-Pain **(A)** and Other-Pain data **(B)**. For each pain level, the relationship between IES and pain ratings is described through a linear regression line with 95% confidence interval area. “**”, “*”, “^” refer to simple IES effects for a given pain level, or significant interactions between IES and pain intensity at p < 0.01, p < 0.05, and 0.05 < p < 0.1, respectively. *IES* inverse efficiency score, LP low pain, MP medium pain, HP high pain.

Next, we analysed pain ratings associated with videos of patients displaying painful/painless facial expressions. Results are reported in Table 1 and reveal a significant main effect of pain Intensity, confirming that participants rated both MP and HP as more painful than the LP level. No modulation of Task was observed, neither as a main effect, nor in interaction with Intensity. We also checked whether participants’ sensitivity to one’s pain changed as function of performance of the preceding 3-Back condition, as described by both IES and ITI values. Results are displayed in Table 2 and Fig. 3B, confirming the main effect of stimulation Intensity, but also describing significant IES*Intensity and ITI*Intensity interactions. In particular, blocks associated with poorer performance led to significant decreased sensitivity to MP (vs. LP) stimulations, for both IES and ITI (Table 2 and Fig. 3).

Questionnaire scores

We repeated the analyses of pain ratings by including scores of relevant questionnaires of interest as covariates, in order to identify potential determinants of inter-individual differences in our effects. Specifically, we considered the Pain Catastrophizing Scale⁴⁴, which is expected to tap key components involving attention and cognitive control of pain. As this questionnaire contains three subscales of interest (Rumination, Helplessness and Magnification), each of which could lead to plausible relevant effects, we report effects if associated with an α ≤ 0.0166 (corresponding to Bonferroni-corrected α ≤ 0.05 for three multiple tests). We found no effects associated in any of the three sub-scores in any of the measures of Self- and Other-Pain.

We also tested whether scores of the Interpersonal Reactivity Index⁴⁵, a standardized questionnaire of individual empathic traits, could influence the Other-Pain effects. As this questionnaire contains four subscales of interest (Personal Distress, Perspective Taking, Empathic Concern, Fantasy), we report effects if associated with an α ≤ 0.0125 (Bonferroni-corrected for four tests) for the Other-Pain condition. We found only a significant main effect of Personal Distress in the analysis of Pain intensity ratings, suggesting that individuals with higher scores are more prone to rate others’ expressions as more painful (t_(29.04) = 3.20, p = 0.003; d = 0.59; see Fig. 4). No other main/interaction effects were associated with any of the questionnaire scores.

Experiment 1. Personal distress effect on other-pain data. Individuals with higher scores on the Personal Distress subscale of IRI were more prone to rate others’ expressions as more painful. The relationship is described in terms of a linear regression line, associated with 95% confidence intervals area and data-points.

Additional measures

Supplementary Results report also details about the effects associated with physiological responses, and confidence ratings. Briefly, in the Self-pain condition all physiological measures (skin conductance response and heart rate variability) were significantly associated with a main effect of stimulation Intensity, reflecting a progressing increase of response, the stronger energy levels. We found neither an effect of Task, nor a modulation of participants’ performance (IES, ITI) on pain response. Instead, no significant effect was associated with the Other-pain condition. Finally, the analysis of confidence ratings revealed no significant effects.

Experiment 2

Experiment 2 was carried out as a conceptual replication of Experiment 1, aimed at verifying whether the effects observed could be found also when manipulating cognitive exhaustion through another paradigm. For this reason, we run a new study which was identical to Experiment 1, except that the N-Back task was replaced with Stroop.