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Giurgiu M, Timm I, Becker M, Schmidt S, Wunsch K, Nissen R, Davidovski D, Bussmann JBJ, Nigg CR, Reichert M, Ebner-Priemer UW, Woll A, von Haaren-Mack B. Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review. JMIR Mhealth Uhealth 2022; 10:e36377. [PMID: 35679106 PMCID: PMC9227659 DOI: 10.2196/36377] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/27/2022] [Accepted: 04/29/2022] [Indexed: 12/13/2022] Open
Abstract
Background Wearable technology is a leading fitness trend in the growing commercial industry and an established method for collecting 24-hour physical behavior data in research studies. High-quality free-living validation studies are required to enable both researchers and consumers to make guided decisions on which study to rely on and which device to use. However, reviews focusing on the quality of free-living validation studies in adults are lacking. Objective This study aimed to raise researchers’ and consumers’ attention to the quality of published validation protocols while aiming to identify and compare specific consistencies or inconsistencies between protocols. We aimed to provide a comprehensive and historical overview of which wearable devices have been validated for which purpose and whether they show promise for use in further studies. Methods Peer-reviewed validation studies from electronic databases, as well as backward and forward citation searches (1970 to July 2021), with the following, required indicators were included: protocol must include real-life conditions, outcome must belong to one dimension of the 24-hour physical behavior construct (intensity, posture or activity type, and biological state), the protocol must include a criterion measure, and study results must be published in English-language journals. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool with 9 questions separated into 4 domains (patient selection or study design, index measure, criterion measure, and flow and time). Results Of the 13,285 unique search results, 222 (1.67%) articles were included. Most studies (153/237, 64.6%) validated an intensity measure outcome such as energy expenditure. However, only 19.8% (47/237) validated biological state and 15.6% (37/237) validated posture or activity-type outcomes. Across all studies, 163 different wearables were identified. Of these, 58.9% (96/163) were validated only once. ActiGraph GT3X/GT3X+ (36/163, 22.1%), Fitbit Flex (20/163, 12.3%), and ActivPAL (12/163, 7.4%) were used most often in the included studies. The percentage of participants meeting the quality criteria ranged from 38.8% (92/237) to 92.4% (219/237). On the basis of our classification tree to evaluate the overall study quality, 4.6% (11/237) of studies were classified as low risk. Furthermore, 16% (38/237) of studies were classified as having some concerns, and 72.9% (173/237) of studies were classified as high risk. Conclusions Overall, free-living validation studies of wearables are characterized by low methodological quality, large variability in design, and focus on intensity. Future research should strongly aim at biological state and posture or activity outcomes and strive for standardized protocols embedded in a validation framework. Standardized protocols for free-living validation embedded in a framework are urgently needed to inform and guide stakeholders (eg, manufacturers, scientists, and consumers) in selecting wearables for self-tracking purposes, applying wearables in health studies, and fostering innovation to achieve improved validity.
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Affiliation(s)
- Marco Giurgiu
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Irina Timm
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Marlissa Becker
- Unit Physiotherapy, Department of Orthopedics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Steffen Schmidt
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Kathrin Wunsch
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Rebecca Nissen
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Denis Davidovski
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Johannes B J Bussmann
- Department of Rehabilitation Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Claudio R Nigg
- Health Science Department, Institute of Sport Science, University of Bern, Bern, Switzerland
| | - Markus Reichert
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Department of eHealth and Sports Analytics, Faculty of Sport Science, Ruhr-University Bochum, Bochum, Germany
| | - Ulrich W Ebner-Priemer
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Alexander Woll
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Birte von Haaren-Mack
- Department of Health and Social Psychology, Institute of Psychology, German Sport University, Cologne, Germany
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Park J. Using physical activity levels to estimate energy requirements of female athletes. J Exerc Nutrition Biochem 2019; 23:1-5. [PMID: 32018339 PMCID: PMC7004509 DOI: 10.20463/jenb.2019.0024] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2019] [Accepted: 11/25/2019] [Indexed: 12/16/2022] Open
Abstract
[Purpose] The goal of this study was to review data on physical activity level (PAL), a crucial index for determining estimated energy requirement (EER), calculated as total energy expenditure (TEE, assessed with doubly labeled water [DLW]) divided by resting metabolic rate (RMR, PAL = TEE/RMR) in female athletes and to understand the methods of assessing athletes’ EERs in the field. [Methods] For the PAL data review among female athletes, we conducted a PubMed search of the available literature related to the DLW method. DLW studies measuring TEE and RMR were included for the present review. [Results] Briefly, the mean PAL was 1.71 for collegiate swimmers with moderate training, which was relatively low, but the mean PAL was 3.0 for elite swimmers during summer training camp. This shows that PAL can largely vary even within the same sport depending on the amount of training, and the differences in PAL were remarkable depending on the sport. Aside from the DLW method, there is currently no research tool related to athletes’ EERs that can be used in the field. [Conclusion] Briefly, the mean PAL was 1.71 for collegiate swimmers with moderate training, which was relatively low, but the mean PAL was 3.0 for elite swimmers during summer training camp. This shows that PAL can largely vary even within the same sport depending on the amount of training, and the differences in PAL were remarkable depending on the sport. Aside from the DLW method, there is currently no research tool related to athletes’ EERs that can be used in the field.
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