Remote, Reliable, Repeatable: Real-World Test–Retest Validation of Hand Grip Strength Assessments

Background Handgrip strength (HGS) is a key indicator of health and functional status. As remote health assessments become more common, it is critical to understand how procedural supervision influences the reliability of remote HGS assessment. Objective To evaluate the test-retest reliability and measurement precision of remote HGS assessment under varying levels of procedural supervision as found in real world use. Methods Seventy-two adults were randomised into six groups reflecting different supervision levels over two sessions. HGS was measured using the GripAble Sensor and Able Assess platform. Test–retest reliability was evaluated using intraclass correlation coefficients (ICC), while measurement precision was quantified using the standard error of measurement (SEM) and minimal detectable change (MDC%). Agreement between sessions was further assessed using Bland–Altman analysis, reporting mean difference and 95% limits of agreement (LoA). Protocol compliance was rated from video recordings. Participants also completed a post-session questionnaire on remote assessment experience. Results All groups demonstrated a good-to-excellent test-retest reliability (ICC ≥ 0.93, ICC lower bounds ≥ 0.73), but measurement precision varied. Fully supervised groups achieved the lowest MDC% (as low as 8.5%), while unsupervised groups often exceeded 20% in the single trial reporting approach, indicating reduced sensitivity to change. Higher supervision corresponded with better protocol compliance. Participant feedback demonstrated high usability during real-world use: 97% rated the test as easy or very easy, > 75% felt comfortable performing it remotely, and > 95% were satisfied with the experience. Conclusion Remote HGS assessment shows high reliability, but measurement precision is shaped by supervision and procedural compliance. Based on these findings, it is recommended that to maximise measurement precision during remote sessions, in-person supervision should be provided during onboarding, possibly followed up with periodic supervision when conducting repeated longitudinal measurements of an individual. Integrating structured features, including standardised instructions, user specified configuration and compliance monitoring will further improve remote measurement performance without undermining usability during real-world use.