Background & Aims
Facial expressions of pain are vital in signaling the need for social support and clinical intervention (Broom, 2001; Kavaliers, 1988). Facial expressions research indicates that feedback significantly enhances the ability to recognize emotional cues (Blanch-Hartigan et al., 2012). Additionally, variation among observed individuals (Dildine et al., 2023) and empathic traits (Ruben and Hall, 2013; Naor et al., 2018) affect pain facial recognition. Despite these findings, the impact of trial-by-trial feedback on pain recognition, and the influence of individual differences in both perceivers and individuals experiencing pain remain largely unexplored. We hypothesized that: 1) trial-by-trial feedback would improve participants’ ability to accurately recognize pain, in comparison to a group that received no feedback, and 2) individuals who report higher empathy would recognize pain with higher accuracy.
Methods
Forty-six healthy participants viewed videos of individuals (“targets”) who had reported their pain after experiencing different heat levels. Participants completed two tasks: identifying if a target was in pain and estimating the pain intensity. They were randomly assigned to two groups: a No-Feedback Group (n=23), which rated targets’ pain without feedback, and a Feedback Group (n=23), which received feedback about the targets’ actual pain rating, post-judgement. Following the task, they filled out the Empathy Components Questionnaire (ECQ) and the Interpersonal Reactivity Index (IRI) among other questionnaires. Multilevel mixed-effects models analyzed group differences in pain recognition and learning. We applied logistic regression for pain/no pain judgments and linear regression for pain intensity ratings, using model comparison to evaluate the effects of Group, Target, Time, and random effects. Linear regressions evaluated whether average performance was related to ECQ and IRI.
Results
In the pain/no pain judgment task, the Feedback Group (Mean = 0.743) demonstrated significantly greater accuracy compared to the No-Feedback Group (Mean = 0.704; p = 0.030). We also observed significant effects of Target (p < 0.001) and an interaction between Target and Trial (p < 0.001). In the pain intensity rating task, Feedback showed smaller differences between targets’ pain (Mean = 20.885) and perceivers’ judgments compared to No Feedback (Mean = 26.165; p = 0.011). Target (p < 0.001), the interaction between Target and Time (p < 0.001), and the interaction between Group, Target, and Time (p < 0.001) were also significant. Linear regressions showed marginal correlations between accuracy of pain intensity ratings and affective ability (? = -0.598, p = 0.065) and affective drive (? = 0.992, p = 0.050) and accuracy of pain/no pain judgment with cognitive ability (? = 0.007, p = 0.076), which did not differ by Group (all p’s > 0.1).
Conclusions
Our findings show that feedback significantly enhances the ability to distinguish between pain and no-pain expressions and to accurately assess pain intensity in others. Participants became more accurate in judging others’ pain over time, and these effects were strongest in participants who received feedback, suggesting feedback enhances learning in pain assessment. Personality traits relevant to affective and cognitive aspects of empathy were associated with pain recognition accuracy, suggesting that more empathic individuals are better at evaluating others’ pain, regardless of whether they receive feedback. This research enhances our understanding of how feedback mechanisms can improve the accuracy of perceiving pain in others, with potential implications for medical professionals in optimizing pain assessment and management strategies.
References
Blanch-Hartigan, D., Andrzejewski, S. A., & Hill, K. M. (2012). The effectiveness of training to improve person perception accuracy: A meta-analysis. Basic and Applied Social Psychology, 34(6), 483-498.
Broom, M. (2001). The evolution of pain. Vlaams Diergeneeskundig Tijdschrift, 70(1).
Dildine, T. C., Brookes, J., Antkiewicz, N. M., Olsson, A., & Atlas, L. Y. (2023, September 13). Video-based acute pain assessment is subject to sociocultural biases.
Kavaliers, M. (1988). Evolutionary and comparative aspects of nociception. Brain research bulletin, 21(6), 923-931.
Naor, N., Shamay-Tsoory, S. G., Sheppes, G., & Okon-Singer, H. (2018). The impact of empathy and reappraisal on emotional intensity recognition. Cognition and Emotion, 32(5), 972-987.
Ruben, M. A., & Hall, J. A. (2013). “I know your pain” proximal and distal predictors of pain detection accuracy. Personality and Social Psychology Bulletin, 39(10), 1346-1358.
Presenting Author
Yili Zhao
Poster Authors
Yili Zhao
PhD
National Institutes of Health (NIH)
Lead Author
Jasdeep Kang
NCCIH
Lead Author
Kai Sherwood
National Institutes of Health (NIH)
Lead Author
Troy Dildine
PhD
National Institutes of Health; Stanford University School of Medicine
Lead Author
Lauren Atlas
PhD
National Institutes of Health
Lead Author
Topics
- Mechanisms: Psychosocial and Biopsychosocial