Comparative validity assessment of three android step counter applications; a semi-structured laboratory-based study.

BMC digital health Pub Date : 2025-01-01 Epub Date: 2025-07-08 DOI:10.1186/s44247-025-00159-3
Uchechukwu Martha Chukwuemeka, Arinze Damian Nnalue, Sochima Johnmark Obiekwe, Fatai Adesina Maruf, Anthony Chinedu Anakor, Monday Omoniyi Moses, Chinedum Amaechi, Uchenna Prosper Okonkwo, Ifeoma Adaigwe Amaechi
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Abstract

Background: Step counting stands out as a highly practical and widely utilised method for assessing an individual's level of physical activity (PA). Although the progress of step counting has undergone a significant transformation in recent times, the need to validate PA applications (apps) is even more pressing to ensure their accuracy. This study aimed to compare the criterion validity of Pacer, Pedometer by ITO Technologies Inc., and Google Fit in measuring step counts in semi-structured laboratory-based conditions.

Method: This comparative experimental study involved 50 students who were fitted with Android phones running the three step counting applications (Pedometer, Pacer and Google Fit) simultaneously while they walked a 30-m walkway at a normal and fast pace during which a video of their walking was recorded with Techno Pouvoir 4 Pro running Android version 11. The steps in the recorded videos served as the criterion compared with the steps recorded by the apps and were counted only when the foot is lifted off the ground and placed in a new location. They were counted independently by two reviewers, who recounted where their level of agreement was more than 3 steps until their report was not more than 2 steps different. The Spearman's correlation was used for a relationship, while Mean Absolute Percentage Error (MAPE) and Bland plot were for validity testing at an Alpha level of 0.05.

Result: While there was no significant difference in step counts among the three apps, a significant difference was found between the steps recorded by the apps and those counted by the video criterion during normal-paced walking but not for fast-paced walking (p > 0.05). The MAPEs for the three applications were moderate, with Google Fit showing 6.6% for normal pace walking and Pedometer and Pacer showing 9.2%. For fast-paced walking, the MAPE was lower at 5.4% across all three applications.

Conclusion: Our findings suggest that a pedometer, Pacer and Google Fit could be used as outcome measures in a general population for counting steps, but Google Fit might be a better step counter when normal pace walking is assessed. However, the study's relatively short duration may have overlooked variations in the applications'performance across different conditions over a longer period; hence, future studies should consider comparing the validity of these applications for a longer duration and among diverse populations.

三种android计步器应用的效度比较评估半结构化的实验室研究。
背景:步数作为一种高度实用和广泛使用的评估个人身体活动水平(PA)的方法。尽管近年来步数计数的进展经历了重大转变,但验证PA应用程序(应用程序)的需求更加迫切,以确保其准确性。本研究旨在比较Pacer、ITO Technologies Inc.的Pedometer和谷歌Fit在半结构化实验室条件下测量步数的效度。方法:这项比较实验研究涉及50名学生,他们配备了同时运行三种步数计算应用程序(Pedometer, Pacer和b谷歌Fit)的Android手机,同时以正常和快速的速度走30米的人行道,期间用运行Android版本11的Techno Pouvoir 4 Pro录制他们的行走视频。视频记录的步数是与应用程序记录的步数进行比较的标准,只有当脚离开地面并放在新的位置时才会被计算。他们由两名评论者独立计算,他们叙述他们的一致程度超过3个步骤,直到他们的报告不超过2个步骤。关系采用Spearman’s相关,效度检验采用Mean Absolute Percentage Error (MAPE)和Bland plot, Alpha水平为0.05。结果:虽然三个应用程序之间的步数没有显著差异,但在正常节奏行走时,应用程序记录的步数与视频标准计算的步数之间存在显著差异,而在快节奏行走时,应用程序记录的步数与视频标准计算的步数之间没有显著差异(p > 0.05)。三种应用程序的mape都是中等的,b谷歌Fit显示正常步速行走的6.6%,Pedometer and Pacer显示9.2%。对于快节奏行走,MAPE在所有三种应用程序中都较低,为5.4%。结论:我们的研究结果表明,计步器、Pacer和谷歌Fit可以作为一般人群计算步数的结果指标,但谷歌Fit可能是评估正常步数时更好的计步器。然而,研究相对较短的持续时间可能忽略了应用程序在不同条件下在较长时间内的性能变化;因此,未来的研究应该考虑比较这些应用在更长的时间和不同人群中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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