Digital approaches to pain assessment across older adults: a scoping review

Abstract

Background: Effectively managing pain in adults remains challenging, particularly in individuals with cognitive impairment or communication difficulties. Digital technologies, including artificial intelligence (AI)-enabled facial recognition and mobile applications, are emerging as innovative tools to improve the objectivity and consistency of pain evaluation. This scoping review aimed to map the current evidence on digital pain-assessment tools used with adult and older populations, focusing on validity, reliability, usability, and contributions to person-centred care. Methods: The review followed the Joanna Briggs Institute methodology and Arksey and O’Malley framework and was reported in accordance with PRISMA-ScR guidelines. Systematic searches were conducted in PubMed, CINAHL Complete, Medline (ALL), and PsycINFO for English-language studies published from 2010 onwards. Eligible studies included adults (≥18 years) using digital tools for pain assessment. Data extraction and synthesis were performed using Covidence, and findings were analyzed thematically.Results: Of 1160 records screened, ten studies met inclusion criteria. Most research was quantitative and conducted in high-income clinical settings. Five tools were identified: ePAT/PainChek®, Painimation, PainCAS, Pain Clinical Assessment System, and Active Appearance Model. Four key themes emerged: (1) Validity and Reliability of Digital Pain Assessment Tools; (2) Comprehensive Pain Evaluation Across Contexts (Rest vs. Movement); (3) Usability and Integration into Clinical Practice; (4) Enabling Person-Centred Pain Management and Future Directions. Conclusions: Emerging evidence suggests that facial-recognition-based digital pain-assessment tools may demonstrate acceptable psychometric performance and usability within dementia care settings in high-income countries. However, evidence relating to broader adult populations, diverse care contexts, and low-resource settings remains limited, highlighting important gaps for future research