Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia.
Sports Performance Research Institute New Zealand (SPRINZ), AUT University, Auckland, New Zealand.
PLoS One. 2019 May 8;14(5):e0215806. doi: 10.1371/journal.pone.0215806. eCollection 2019.
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.
测量关节活动度是许多医疗保健专业人员的重要技能。虽然通用量角器是测量关节活动度最常用的临床工具，但智能手机技术和应用程序（apps）的发展为临床医生提供了更多的测量选择。然而，这些智能手机和应用程序的可靠性和有效性仍然存在一定的不确定性。本研究的目的是系统地回顾关于智能手机和应用程序测量关节活动度的内部和外部可靠性和有效性的文献。合格的研究是在有全文可获得的英语同行评议期刊上发表的，涉及对非视频图形智能手机应用程序评估关节活动度的可靠性和/或有效性的评估，参与者年龄大于 18 岁。使用 PubMed、Ovid 中的 Medline、EMBASE、CINAHL 和 SPORTSDiscus 进行电子搜索。使用标准化评估工具评估偏倚风险。在 25 项合格研究中，有 23 项研究的最低 60%得分超过了分类为低偏倚风险的标准，尽管有 3 项标准在超过 50%的研究中未达到。大多数研究表明，在评估的所有关节中，超过 50%的运动测试具有足够的内部或外部可靠性和/或有效性。然而，这种证据水平似乎对绝对（例如，平均差异±界限协议，最小可检测变化）比相对（例如，组内相关，相关性）措施更弱；并且对于脊柱旋转，弱于脊柱伸展、弯曲和侧屈。我们的结果为临床医生提供了足够的证据，支持使用智能手机和应用程序代替量角器来测量关节运动。未来的研究应解决文献中的一些方法学局限性，特别是包括绝对而不仅仅是相对可靠性和有效性统计数据的纳入。
