Research and Innovation in Pain Measurement Approaches
Pain is a complex, multidimensional experience that is shaped by biological, psychological, and social factors. This perspective was formally reflected by the International Association for the Study of Pain in a 2020 update to their terminology, in which pain was redefined as both a sensory and emotional experience and key principles, such as the distinction between pain and nociception, were emphasized.1 These changes reinforced a growing consensus that pain is inherently multifactorial and deeply personal.
However, it is difficult for research and clinical practice to capture the full complexity of pain. This disconnect has become more pressing with growing inequities in pain management.2-4 Concurrently, rapid advances in digital health technologies and the increasing use of machine learning and large-scale data systems are transforming how pain is studied. These developments suggest an urgent need to rethink how pain research is conducted and translated into practice.5 Innovation in pain measurement approaches is urgently needed in both clinical and research settings.
Patient-reported outcomes (PROs) have been—and continue to be—the foundation of assessing pain, as they can capture the subjective experience of pain through tools like numeric rating scales, visual analogue scales, and condition-specific questionnaires.5 However, traditional PROs are often collected infrequently in clinical or research settings and tend to focus on limited dimensions, such as intensity or location. In addition, self-reports are vulnerable to biases related to memory, context, and social expectations, and they often force patients to simplify complex, non-linear pain experiences into fixed numerical scales.
To address these limitations, recent innovation includes expansions in how and when pain is reported, with digital tools expanding measurement capabilities across a wider variety of settings. Ecological momentary assessments, enabled by smartphones and digital platforms, allow patients to report pain more frequently in their everyday environments, offering richer and more context-sensitive data.6 These methods can better capture how pain changes over time and interacts with factors like mood, sleep, and daily activities, while also reducing the burden of in-person visits.
At the same time, innovations such as digital body maps and pictorial tools aim to make reporting more accessible and expressive, particularly for diverse patient populations. Despite these advancements in the field, persistent challenges include issues of accessibility, reporting fatigue, and the continued influence of psychological and social biases.
Pain can also be studied with environmental sensors that continuously collect data about the body and surroundings, usually collected through connected “smart” devices. These tools provide detailed and real-time insights into pain by tracking things like heart rate variability, movement, sleep, and daily activities, often without requiring active input from patients.
By combining sensor data with self-reports, researchers can better understand how pain changes over time and affects quality of life through dual approaches of objective and subjective metrics, while also making research and care more accessible through at-home monitoring.7 However, these systems still come with significant challenges, including technical complexity, data accuracy issues, and the need to ensure accessibility, comfort, and usability for a wide range of patients. There are also concerns about privacy and bias, among other ethical issues.5
Advancing pain measurement will require integrating subjective and objective approaches to more fully capture the complexity of the total pain experience and support innovation in the field. Combining patient-reported outcomes with emerging digital and sensor-based methods can create a more comprehensive, continuous, and context-aware understanding of pain. Interdisciplinary collaboration and patient-centered design will be essential to ensure that innovations in pain research can effectively translate into more accurate assessments and more equitable and effective care.
References
- International Association for the Study of Pain. Terminology. International Association for the Study of Pain (IASP). Published 2020. https://www.iasp-pain.org/resources/terminology/
- Nieto R, Pardo R, Sora B, Feliu-Soler A, Luciano JV. Impact of COVID-19 Lockdown Measures on Spanish People with Chronic Pain: An Online Study Survey. Journal of Clinical Medicine. 2020;9(11):3558. https://doi.org/10.3390/jcm9113558
- Puntillo F, Giglio M, Brienza N, et al. Impact of COVID-19 pandemic on chronic pain management: Looking for the best way to deliver care. Best Practice & Research Clinical Anaesthesiology. 2020;34(3):529-537. https://doi.org/10.1016/j.bpa.2020.07.001
- Shanthanna H, Strand NH, Provenzano DA, et al. Caring for patients with pain during the COVID ‐19 pandemic: consensus recommendations from an international expert panel. Anaesthesia. 2020;75(7):935-944. https://doi.org/10.1111/anae.15076
- Berger SE, Baria AT. Assessing Pain Research: A Narrative Review of Emerging Pain Methods, Their Technosocial Implications, and Opportunities for Multidisciplinary Approaches. Frontiers in Pain Research. 2022;3. https://doi.org/10.3389/fpain.2022.896276
- Doherty K, Balaskas A, Doherty G. The Design of Ecological Momentary Assessment Technologies. Interacting with Computers. 2020;32(3). https://doi.org/10.1093/iwcomp/iwaa019
- Byrom B, McCarthy M, Schueler P, Muehlhausen W. Brain Monitoring Devices in Neuroscience Clinical Research: The Potential of Remote Monitoring Using Sensors, Wearables, and Mobile Devices. Clinical Pharmacology & Therapeutics. 2018;104(1):59-71. https://doi.org/10.1002/cpt.1077