Accuracy, validity, and reliability of an electronic visual analog scale for pain on a touch screen tablet in healthy older adults: A clinical trial
Background: New technology for clinical data collection is rapidly evolving and may be useful for both researchers and clinicians; however, this new technology has not been tested for accuracy, reliability, or validity.
Objective: This study aims to test the accuracy of visual analog scale (VAS) for pain on a newly designed application on the iPad (iPadVAS) and measure the reliability and validity of iPadVAS compared to a paper copy (paperVAS).
Methods: Accuracy was determined by physically measuring an iPad scale on screen and comparing it to the results from the program, with a researcher collecting 101 data points. A total of 22 healthy community dwelling older adults were then recruited to test reliability and validity. Each participant completed 8 VAS (4 using each tool) in a randomized order. Reliability was measured using interclass correlation coefficient (ICC) and validity measured using Bland-Altman graphs and correlations.
Results: Of the measurements for accuracy, 64 results were identical, 2 results were manually measured as being 1 mm higher than the program, and 35 as 1 mm lower. Reliability for the iPadVAS was excellent with individual ICC 0.90 (95% CI 0.82-0.95) and averaged ICC 0.97 (95% CI 0.95-1.0) observed. Linear regression demonstrated a strong relationship with a small negative bias towards the iPad (-2.6, SD 5.0) with limits of agreement from -12.4 to 7.1.
Conclusions: The iPadVAS provides a convenient, user-friendly, and efficient way of collecting data from participants in measuring their current pain levels. It has potential use in documentation management and may encourage participatory healthcare.
National Stroke Foundation
Publication titleInteractive Journal of Medical Research
Department/SchoolSchool of Health Sciences
Place of publicationCanada
Rights statement©Marie-Louise Bird, Michele L Callisaya, John Cannell, Timothy Gibbons, Stuart T Smith, Kiran DK Ahuja. Licensed under Creative Commons Attribution 2.0 Generic (CC BY 2.0) https://creativecommons.org/licenses/by/2.0/