{"title":"Comparative validity assessment of three android step counter applications; a semi-structured laboratory-based study.","authors":"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","doi":"10.1186/s44247-025-00159-3","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Method: </strong>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.</p><p><strong>Result: </strong>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 (<i>p</i> > 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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":72426,"journal":{"name":"BMC digital health","volume":"3 1","pages":"20"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12234585/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC digital health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s44247-025-00159-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/8 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.