Research Article: Reliability and validity of clinically accessible smartphone applications to measure joint range of motion: A systematic review

Date Published: May 8, 2019

Publisher: Public Library of Science

Author(s): Justin W. L. Keogh, Alistair Cox, Sarah Anderson, Bernard Liew, Alicia Olsen, Ben Schram, James Furness, Juliane Müller.

http://doi.org/10.1371/journal.pone.0215806

Abstract

Measuring joint range of motion is an important skill for many allied health professionals. While the Universal Goniometer is the most commonly utilised clinical tool for measuring joint range of motion, the evolution of smartphone technology and applications (apps) provides the clinician with more measurement options. However, the reliability and validity of these smartphones and apps is still somewhat uncertain. The aim of this study was to systematically review the literature regarding the intra- and inter-rater reliability and validity of smartphones and apps to measure joint range of motion. Eligible studies were published in English peer-reviewed journals with full text available, involving the assessment of reliability and/or validity of a non-videographic smartphone app to measure joint range of motion in participants >18 years old. An electronic search using PubMed, Medline via Ovid, EMBASE, CINAHL, and SPORTSDiscus was performed. The risk of bias was assessed using a standardised appraisal tool. Twenty-three of the eligible 25 studies exceeded the minimum 60% score to be classified as a low risk of bias, although 3 of the 13 criteria were not achieved in >50% of the studies. Most of the studies demonstrated adequate intra-rater or inter-rater reliability and/or validity for >50% of the range of motion tests across all joints assessed. However, this level of evidence appeared weaker for absolute (e.g. mean difference ± limit of agreement, minimal detectable change) than relative (e.g. intraclass correlation, correlation) measures; and for spinal rotation than spinal extension, flexion and lateral flexion. Our results provide clinicians with sufficient evidence to support the use of smartphones and apps in place of goniometers to measure joint motion. Future research should address some methodological limitations of the literature, especially including the inclusion of absolute and not just relative reliability and validity statistics.

Partial Text

The measurement of joint range of motion (ROM) in static and dynamic, passive and active, human movements is an essential skill in the musculoskeletal assessments commonly performed by physiotherapists, as well as some strength and conditioning coaches, to examine joint function, detect joint asymmetry and evaluate treatment efficacy as an objective outcome measure [1]. In the present study, static ROM is defined as the range of a joint held motionless at either of its limit of movement. Dynamic ROM is the range a joint moved to and from the limits of movement. When a joint is moved passively by an assessor or external device, passive ROM is assessed. When a joint moves as a result of muscular contraction, active ROM is assessed. The universal goniometer has long been the preferred method of clinical ROM measurement (especially static ROM) due to its ease of use, low cost, and demonstrated reasonable levels of reliability and validity in numerous studies [2–4].

This study systematically reviewed the literature for studies which examined the reliability and/or validity of smartphones and apps to quantify joint ROM. Thirty-seven studies were found to be eligible, with the studies assessing joint ROM across most of the body’s major joints. Specifically, the most common joints assessed were the spine/trunk (n = 11), knee (n = 9) and shoulder (n = 6), with a smaller number of studies examining the wrist (n = 4), elbow (n = 3), ankle (n = 3) and hip (n = 1) joints. The primary result of the systematic review was that the apps generally demonstrated adequate intra-rater and inter-rater reliability as well as validity when compared to criterion devices such as goniometers, inclinometers and 3D motion capture. However, there was a trend for the reliability outcomes that these results were somewhat stronger for relative (e.g. ICC, r) than absolute measures (e.g. SEM, MDC).

 

Source:

http://doi.org/10.1371/journal.pone.0215806

 

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