Measuring intra-individual physical activity variability using consumer-grade activity devices
Many existing sedentary behavior and physical activity studies focus on primary outcomes that assess change by comparing participants' activity from baseline to post-intervention. With the widespread availability of consumer-grade devices that track activity daily, researchers do not need to re...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Digital Health |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2023.1239759/full |
| _version_ | 1797691158109880320 |
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| author | Vered Lev Marily A. Oppezzo |
| author_facet | Vered Lev Marily A. Oppezzo |
| author_sort | Vered Lev |
| collection | DOAJ |
| description | Many existing sedentary behavior and physical activity studies focus on primary outcomes that assess change by comparing participants' activity from baseline to post-intervention. With the widespread availability of consumer-grade devices that track activity daily, researchers do not need to rely on those endpoint measurements alone. Using activity trackers, researchers can collect remote data about the process of behavior change and future maintenance of the change by measuring participants’ intra-individual physical activity variability. Measuring intra-individual physical activity variability can enable researchers to create tailored and dynamic interventions that account for different physical activity behavior change trajectories, and by that, improve participants' program adherence, enhance intervention design and management, and advance interventions measurements' reliability. We propose an application of intra-individual physical activity variability as a measurement and provide three use cases within interventions. Intra-individual physical activity variability can be used: prior to the intervention period, where relationships between participants' intra-individual physical activity variability and individual characteristics can be used to predict adherence and subsequently tailor interventions; during the intervention period, to assess progress and subsequently boost interventions; and after the intervention, to obtain a reliable representation of the change in primary outcome. |
| first_indexed | 2024-03-12T02:09:19Z |
| format | Article |
| id | doaj.art-8bc2e7ca48914bce9752fe1cfd284b5d |
| institution | Directory Open Access Journal |
| issn | 2673-253X |
| language | English |
| last_indexed | 2024-03-12T02:09:19Z |
| publishDate | 2023-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Digital Health |
| spelling | doaj.art-8bc2e7ca48914bce9752fe1cfd284b5d2023-09-06T17:04:13ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2023-09-01510.3389/fdgth.2023.12397591239759Measuring intra-individual physical activity variability using consumer-grade activity devicesVered Lev0Marily A. Oppezzo1Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA, United StatesDepartment of Medicine, Stanford Prevention Research Center, Stanford University, Stanford, CA, United StatesMany existing sedentary behavior and physical activity studies focus on primary outcomes that assess change by comparing participants' activity from baseline to post-intervention. With the widespread availability of consumer-grade devices that track activity daily, researchers do not need to rely on those endpoint measurements alone. Using activity trackers, researchers can collect remote data about the process of behavior change and future maintenance of the change by measuring participants’ intra-individual physical activity variability. Measuring intra-individual physical activity variability can enable researchers to create tailored and dynamic interventions that account for different physical activity behavior change trajectories, and by that, improve participants' program adherence, enhance intervention design and management, and advance interventions measurements' reliability. We propose an application of intra-individual physical activity variability as a measurement and provide three use cases within interventions. Intra-individual physical activity variability can be used: prior to the intervention period, where relationships between participants' intra-individual physical activity variability and individual characteristics can be used to predict adherence and subsequently tailor interventions; during the intervention period, to assess progress and subsequently boost interventions; and after the intervention, to obtain a reliable representation of the change in primary outcome.https://www.frontiersin.org/articles/10.3389/fdgth.2023.1239759/fullbehavior changesedentary behaviorsphysical activity interventionactivity trackersintra-individualwearables |
| spellingShingle | Vered Lev Marily A. Oppezzo Measuring intra-individual physical activity variability using consumer-grade activity devices Frontiers in Digital Health behavior change sedentary behaviors physical activity intervention activity trackers intra-individual wearables |
| title | Measuring intra-individual physical activity variability using consumer-grade activity devices |
| title_full | Measuring intra-individual physical activity variability using consumer-grade activity devices |
| title_fullStr | Measuring intra-individual physical activity variability using consumer-grade activity devices |
| title_full_unstemmed | Measuring intra-individual physical activity variability using consumer-grade activity devices |
| title_short | Measuring intra-individual physical activity variability using consumer-grade activity devices |
| title_sort | measuring intra individual physical activity variability using consumer grade activity devices |
| topic | behavior change sedentary behaviors physical activity intervention activity trackers intra-individual wearables |
| url | https://www.frontiersin.org/articles/10.3389/fdgth.2023.1239759/full |
| work_keys_str_mv | AT veredlev measuringintraindividualphysicalactivityvariabilityusingconsumergradeactivitydevices AT marilyaoppezzo measuringintraindividualphysicalactivityvariabilityusingconsumergradeactivitydevices |