Reliability and validity of smartphone applications to measure the spinal range of motion: A systematic review

Author(s):  
Shibili Nuhmani ◽  
Moazzam H Khan ◽  
Shaji J Kachanathu ◽  
Mohd Arshad Bari ◽  
Turki S Abualait ◽  
...  
PLoS ONE ◽  
2019 ◽  
Vol 14 (5) ◽  
pp. e0215806 ◽  
Author(s):  
Justin W. L. Keogh ◽  
Alistair Cox ◽  
Sarah Anderson ◽  
Bernard Liew ◽  
Alicia Olsen ◽  
...  

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Sarah Hahn ◽  
Inga Kröger ◽  
Steffen Willwacher ◽  
Peter Augat

Abstract The aim of this review was to determine whether smartphone applications are reliable and valid to measure range of motion (RoM) in lower extremity joints. A literature search was performed up to October 2020 in the databases PubMed and Cochrane Library. Studies that reported reliability or validity of smartphone applications for RoM measurements were included. The study quality was assessed with the QUADAS-2 tool and baseline information, validity and reliability were extracted. Twenty-five studies were included in the review. Eighteen studies examined knee RoM, whereof two apps were analysed as having good to excellent reliability and validity for knee flexion (“DrGoniometer”, “Angle”) and one app showed good results for knee extension (“DrGoniometer”). Eight studies analysed ankle RoM. One of these apps showed good intra-rater reliability and excellent validity for dorsiflexion RoM (“iHandy level”), another app showed excellent reliability and moderate validity for plantarflexion RoM (“Coach’s Eye”). All other apps concerning lower extremity RoM had either insufficient results, lacked study quality or were no longer available. Some apps are reliable and valid to measure RoM in the knee and ankle joint. No app can be recommended for hip RoM measurement without restrictions.


2021 ◽  
pp. 175857322110102
Author(s):  
Michael D Eckhoff ◽  
Josh C Tadlock ◽  
Tyler C Nicholson ◽  
Matthew E Wells ◽  
EStephan J Garcia ◽  
...  

Introduction Lateral condyle fractures are the second most common pediatric elbow fracture. There exist multiple options for internal fixation including buried K-wires, unburied K-wires, and screw fixation. Our study aims to review the current literature and determine if fixation strategy affects outcomes to include fracture union, postoperative range of motion, and need subsequent surgery. Methods A systematic review of Pubmed, MEDLINE, and EMBASE databases was performed. Included articles involve pediatric patients with displaced lateral condyle fractures treated with internal fixation that reported outcomes to include union rates and complications. Results Thirteen studies met inclusion criteria for a total of 1299 patients (472 buried K-wires, 717 unburied K-wires, and 110 screws). The patients’ average age was 5.8 ± 0.6 years, male (64%), and had 16.3 months of follow-up. No differences in union and infection rates were found. Unburied K-wires had the shortest time to union and the greatest elbow range of motion postoperatively. Conclusions Our systematic review demonstrates similar outcomes with union and infection rates between all fixation techniques. Unburied K-wires demonstrated a shorter time to union and the greatest postoperative range of motion. Additionally, unburied K-wires may be removed in clinic, decreasing the cost on the healthcare system. Evidence Level 3.


Hand ◽  
2021 ◽  
pp. 155894472110146
Author(s):  
Francisco R. Avila ◽  
Rickey E. Carter ◽  
Christopher J. McLeod ◽  
Charles J. Bruce ◽  
Davide Giardi ◽  
...  

Background Wearable devices and sensor technology provide objective, unbiased range of motion measurements that help health care professionals overcome the hindrances of protractor-based goniometry. This review aims to analyze the accuracy of existing wearable sensor technologies for hand range of motion measurement and identify the most accurate one. Methods We performed a systematic review by searching PubMed, CINAHL, and Embase for studies evaluating wearable sensor technology in hand range of motion assessment. Keywords used for the inquiry were related to wearable devices and hand goniometry. Results Of the 71 studies, 11 met the inclusion criteria. Ten studies evaluated gloves and 1 evaluated a wristband. The most common types of sensors used were bend sensors, followed by inertial sensors, Hall effect sensors, and magnetometers. Most studies compared wearable devices with manual goniometry, achieving optimal accuracy. Although most of the devices reached adequate levels of measurement error, accuracy evaluation in the reviewed studies might be subject to bias owing to the use of poorly reliable measurement techniques for comparison of the devices. Conclusion Gloves using inertial sensors were the most accurate. Future studies should use different comparison techniques, such as infrared camera–based goniometry or virtual motion tracking, to evaluate the performance of wearable devices.


2013 ◽  
Vol 21 (02) ◽  
pp. 123-151 ◽  
Author(s):  
MICHAEL LORZ ◽  
SUSAN MUELLER ◽  
THIERRY VOLERY

The majority of studies that analyze the impact of entrepreneurship education on entrepreneurial attitudes, intentions, and venture activities report positive influences. However, several scholars have recently cast doubts about research methods and the generalizability of entrepreneurship education impact studies. In this study, we conducted a systematic literature review of the methods used in entrepreneurship education impact studies. Our results uncover significant methodological deficiencies and question the overwhelmingly positive impact of entrepreneurship education. Based on this evidence, we propose a series of recommendations to improve the reliability and validity of entrepreneurship education impact studies and we outline promising topics which are currently under-researched.


2015 ◽  
Vol 30 (2) ◽  
pp. 199-207 ◽  
Author(s):  
Marloes LJ Lagarde ◽  
Digna MA Kamalski ◽  
Lenie van den Engel-Hoek

2018 ◽  
Vol 18 (3) ◽  
pp. 447-457 ◽  
Author(s):  
Mohammad Reza Pourahmadi ◽  
Rasool Bagheri ◽  
Morteza Taghipour ◽  
Ismail Ebrahimi Takamjani ◽  
Javad Sarrafzadeh ◽  
...  

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