Chronic pain is common and disabling. Researchers need robust methods to collect pain data in large populations to enhance knowledge on pain prevalence, causes and treatment. Digital pain manikins address this by enabling self-reporting of location-specific pain. However, it is unknown to what extent pain studies adopted digital manikins for data collection. Therefore, we systematically searched the literature. We included 17 studies. Most were published after 2017, collected pain data cross-sectionally in ≥50 participants, and reported pain distribution and pain extent as manikin-derived summary metrics. Across the studies, 13 unique manikins were used, of which four had been evaluated. Our review shows that adoption of digital pain manikins in research settings has been slow. Harnessing the digital nature of manikins, enabling use of personal devices, and assessing and improving the reliability, validity and responsiveness of digital manikins will expedite their adoption as digital data collection tools for pain research.
Keywords: Pain measurement; patient-generated health data; systematic review.