Aplicativos de smartphone para monitorar a atividade física e o comportamento sedentário: Uma revisão sistemática de estudos de validação
DOI:
https://doi.org/10.12820/rbafs.27e0270Palavras-chave:
Acelerometria, Equipamentos de medição, Postura sentada, EpidemiologiaResumo
Aplicativos para smartphones têm sido desenvolvidos e investigados em estudos de validação para rastreamento de comportamento humano, como atividade física (AF) e comportamento sedentário (CS). No entanto, como não está claro se esses aplicativos são válidos para rastrear AF e CS quando comparados a acelerômetros de grau de pesquisa, portanto, essa revisão sistemática teve o objetivo investigar a validade de aplicativos de smartphone para rastreamento de AF e CS usando o acelerômetro como medida de critério. Uma busca sistemática foi realizada em quatro bases de dados. A diferença percentual média (MPD) foi utilizada para avaliar a validade de critério. Dez estudos (n = 662) validando diferentes aplicativos usando acelerômetros ActiGraph como medida de critério (seis foram realizados em condições de vida diária, dois em condições de laboratório e dois em ambas as condições) foram incluídos para análise. Enquanto quatro aplicativos foram considerados válidos para rastreamento de AF, seis não eram válidos ou totalmente válidos. A análise do MPD revelou que os aplicativos não fornecem pontuações válidas para rastrear medidas de AF (MPD = -12,6 – 37,7). A escassez de estudos investigando o CS limita o rastreamento dos resultados sobre esse comportamento. Desenhos de estudo, localização do smartphone e intensidade do exercício tendem a afetar a precisão dos aplicativos que rastreiam AF; assim, a presente revisão mostrou resultados conflitantes entre os estudos. Esta revisão mostra que não é possível generalizar as pontuações válidas para todos os aplicativos.
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Marques A, Santos T, Martins J, Matos MG, Valeiro MG. The association between physical activity and chronic diseases in European adults. Eur J Sport Sci. 2018;18(1):140-49. DOI: https://doi.org/10.1080/17461391.2017.1400109
Lee IM, Skerrett PJ. Physical activity and all-cause mortality: what is the dose-response relation?. Med Sci Sports Exerc. 2001;33(6 Suppl):S459-S94. DOI: https://doi.org/10.1097/00005768-200106001-00016
Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54(24):1451-62. DOI: https://doi.org/10.1136/bjsports-2020-102955
Jones RA, Hinkley T, Okely AD, Salmon J. Tracking physical activity and sedentary behavior in childhood: a systematic review. Am J Prev Med. 2013;44(6):651-58. DOI: https://doi.org/10.1016/j.amepre.2013.03.001
Hayes G, Dowd KP, MacDonncha C, Donnelly AE. Tracking of Physical Activity and Sedentary Behavior From Adolescence to Young Adulthood: A Systematic Literature Review. J Adolesc Health. 2019;65(4):446-54. DOI: https://doi.org/10.1016/j.jadohealth.2019.03.013
Helmerhorst HJ, Brage S, Warren J, Besson H, Ekelund U. A systematic review of reliability and objective criterion-related validity of physical activity questionnaires. Int J Behav Nutr Phys Act. 2012;9:103. DOI: https://doi.org/10.1186/1479-5868-9-103
Chastin SFM, Dontje ML, Skelton DA, Čukić I, Shaw RJ, Gill JMR et al. Systematic comparative validation of self-report measures of sedentary time against an objective measure of postural sitting (activPAL). Int J Behav Nutr Phys Act. 2018;15(1):21. DOI: https://doi.org/10.1186/s12966-018-0652-x
Sylvia LG, Bernstein EE, Hubbard JL, Keating L, Anderson EJ. Practical guide to measuring physical activity. J Acad Nutr Diet. 2014;114(2):199-208. DOI: https://doi.org/10.1016/j.jand.2013.09.018
van der Ploeg HP, Merom D, Chau JY, Bittman M, Trost SG, Bauman AE. Advances in Population Surveillance for Physical Activity and Sedentary Behavior: Reliability and Validity of Time Use Surveys. Am J Epidemiol. 2010;172(10):1199-206. DOI: https://doi.org/10.1093/aje/kwq265
Troiano RP, McClain JJ, Brychta RJ, Chen KY. Evolution of accelerometer methods for physical activity research. Br J Sports Med. 2014;48(13):1019-23. DOI: https://doi.org/10.1136/bjsports-2014-093546
Wong TC, Webster JG, Montoye HJ, Washburn R. Portable Accelerometer Device for Measuring Human Energy Expenditure. IEEE Trans Biomed Eng. 1981;BME-28(6):67-471. DOI: https://doi.org/10.1109/TBME.1981.324820
John D, Freedson P. ActiGraph and Actical physical activity monitors: a peek under the hood. Med Sci Sports Exerc. 2012;44(1 Suppl 1):S86-9. DOI: https://doi.org/10.1249/MSS.0b013e3182399f5e
Matthews CE, Hagstromer M, Pober DM, Bowles HR. Best Practices for Using Physical Activity Monitors in Population-Based Research. Med Sci Sports Exerc. 2012;44(1):S68-S76. DOI: https://doi.org/10.1249/MSS.0b013e3182399e5b
Fitbit Reports $571M Q4’17 and $1.616B FY’17 Revenue. fitbit.com. https://www.webcitation.org/6xuzBvDVV (accessed Mar 14, 2021).
Feehan LM, Geldman J, Sayre EC, Park C, Ezzat A, Yoo JY et al. Accuracy of Fitbit Devices: Systematic Review and Narrative Syntheses of Quantitative Data. JMIR Mhealth Uhealth. 2018;6(8):e10527. DOI: https://doi.org/10.2196/10527
BankMyCell. How many smartphones are in the world? https://www.bankmycell.com/blog/how-many-phones-are-in-the-world (accessed October 20, 2020).
Silva AG, Simões P, Queirós A, Rodrigues M, Rocha NP. Mobile Apps to Quantify Aspects of Physical Activity: A Systematic Review on its Reliability and Validity. J Med Syst. 2020;44(2):51. DOI: https://doi.org/10.1007/s10916-019-1506-z
Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors. Cochrane handbook for systematic reviews of interventions. 2nd ed. Chichester: Wiley; 2019 DOI: https://doi.org/10.1002/9781119536604
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TM, Mulrow CD et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. DOI: https://doi.org/10.1136/bmj.n71
Tacconelli E. Systematic reviews: CRD’s guidance for undertaking reviews in health care. Lancet Infect Dis. 2010;10(4):226. DOI: https://doi.org/10.1016/S1473-3099(10)70065-7
Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928. DOI: https://doi.org/10.1136/bmj.d5928
Brink Y, Louw QA. Clinical instruments: reliability and validity critical appraisal. J Eval Clin Pract. 2012;18(6):1126-32. DOI: https://doi.org/10.1111/j.1365-2753.2011.01707.x
Lombard MJ, Steyn NP, Charlton KE, Senekal M. Application and interpretation of multiple statistical tests to evaluate validity of dietary intake assessment methods. Nutr J. 2015;14:40. DOI: https://doi.org/10.1186/s12937-015-0027-y
Aaronson N, Alonso J, Burnam A, Lohr NK, Patrick DL, Perrin E et al. Assessing health status and quality-of-life instruments: attributes and review criteria. Qual Life Res. 2002;11(3):193-205. DOI: https://doi.org/10.1023/A:1015291021312
Prince SA, Adamo KB, Hamel ME, Hardt J, Gorber SC, Tremblay M. A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review. Int J Behav Nutr Phys Act. 2008;5:56. DOI: https://doi.org/10.1186/1479-5868-5-56
Asimina S, Chapizanis D, Karakitsios S, Kontoroupis P, Asimakopoulos DN, Maggos T et al. Assessing and enhancing the utility of low-cost activity and location sensors for exposure studies. Environ Monit Assess. 2018;190(3):155. DOI: https://doi.org/10.1007/s10661-018-6537-2
Ata R, Gandhi N, Rasmussen H, El-Gabalawy O, Gutierrez S, Ahmad A et al. Clinical validation of smartphone-based activity tracking in peripheral artery disease patients. NPJ Digit Med. 2018;1. DOI: https://doi.org/10.1038/s41746-018-0073-x
Donaire-Gonzalez D, de Nazelle A, Seto E, Mendez M, Nieuwenhuijsen MJ, Jerrett M. Comparison of physical activity measures using mobile phone-based CalFit and Actigraph. J Med Internet Res. 2013;15(6):e111. DOI: https://doi.org/10.2196/jmir.2470
Donaire-Gonzalez D, Valentin A, van Nunen E, Curto A, Rodrigues A, Fernadez-Nieto M et al. ExpoApp: An integrated system to assess multiple personal environmental exposures. Environ Int. 2019;126:494-503. DOI: https://doi.org/10.1016/j.envint.2019.02.054
Douma JAJ, Verheul HMW, Buffart LM. Feasibility, validity and reliability of objective smartphone measurements of physical activity and fitness in patients with cancer. BMC Cancer. 2018;18(1):1052. DOI: https://doi.org/10.1186/s12885-018-4983-4
Duncan MJ, Wunderlich K, Zhao Y, Faulkner G. Walk this way: validity evidence of iphone health application step count in laboratory and free-living conditions. J Sports Sci. 2018;36(15):1695-704. DOI: https://doi.org/10.1080/02640414.2017.1409855
Hekler EB, Buman MP, Grieco L, Rosenberger M, Winter SJ, Haskell W et al. Validation of Physical Activity Tracking via Android Smartphones Compared to ActiGraph Accelerometer: Laboratory-Based and Free-Living Validation Studies. JMIR mHealth uHealth. 2015;3(2):e36. DOI: https://doi.org/10.2196/mhealth.3505
Maddison R, Gemming L, Monedero J, Bolger L, Belton S, Issartel J et al. Quantifying Human Movement Using the Movn Smartphone App: Validation and Field Study. JMIR Mhealth Uhealth. 2017;5(8):e122. DOI: https://doi.org/10.2196/mhealth.7167
Rodriguez VH, Medrano C, Plaza I, Corella C, Abarca A, Julian JA. Comparison of Several Algorithms to Estimate Activity Counts with Smartphones as an Indication of Physical Activity Level. IRBM. 2019;40(2):95-102. DOI: https://doi.org/10.1016/j.irbm.2018.12.001
Zhai Y, Nasseri N, Poettgen J, Gezhelbash E, Heesen C, Stellmann J-P. Smartphone Accelerometry: A Smart and Reliable Measurement of Real-Life Physical Activity in Multiple Sclerosis and Healthy Individuals. Front Neurol. 2020;11:688. DOI: https://doi.org/10.3389/fneur.2020.00688
Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30(5):777-81. DOI: https://doi.org/10.1097/00005768-199805000-00021
Matthews CE, Chen KY, Freedson PS, Buchowski MS, Beech BM, Pate RR et al. Amount of time spent in sedentary behaviors in the United States, 2003-2004. Am J Epidemiol. 2008;167(7):875-81. DOI: https://doi.org/10.1093/aje/kwm390
Sasaki JE, John D, Freedson PS. Validation and comparison of ActiGraph activity monitors. J Sci Med Sport. 2011;14(5):411-16. DOI: https://doi.org/10.1016/j.jsams.2011.04.003
Crouter SE, Kuffel E, Haas JD, Frongillo EA, Bassett DRJ. Refined two-regression model for the ActiGraph accelerometer. Med Sci Sports Exerc. 2010;42(5):1029-37. DOI: https://doi.org/10.1249/MSS.0b013e3181c37458
Bornstein MH, Jager J, Putnick DL. Sampling in Developmental Science: Situations, Shortcomings, Solutions, and Standards. Dev Rev. 2013;33(4):357-70. DOI: https://doi.org/10.1016/j.dr.2013.08.003
Hagströmer M, Ainsworth BE, Kwak L, Bowles HR. A checklist for evaluating the methodological quality of validation studies on self-report instruments for physical activity and sedentary behavior. J Phys Act Health. 2012;9 Suppl 1:S29-S36. DOI: https://doi.org/10.1123/jpah.9.s1.s29
Perry MA, Hendrick PA, Hale L, Baxter GD, Milosavljevic S, Dean SG et al. Utility of the RT3 triaxial accelerometer in free living: An investigation of adherence and data loss. Appl Ergon. 2010;41(3):469-76. DOI: https://doi.org/10.1016/j.apergo.2009.10.001
Belton S, O’Brien W, Wickel EE, Issartel J. Patterns of noncompliance in adolescent field-based accelerometer research. J Phys Act Health. 2013;10(8):1181-5. DOI: https://doi.org/10.1123/jpah.10.8.1181
Wolf A, Gray R, Fazel S. Violence as a public health problem: an ecological study of 169 countries. Soc Sci Med. 2014;104(100):220-27. DOI: https://doi.org/10.1016/j.socscimed.2013.12.006
Mobile Time. Mais de 100 milhões de celulares já foram roubados ou furtados no Brasil. https://www.mobiletime.com.br/noticias/23/07/2020/mais-de-100-milhoes-de-celulares-ja-foram-roubados-ou-furtados-no-brasil/ (accessed Apr 14, 2021).
van Hees VT, Sabia S, Anderson KN, Denton SJ, Oliver J, Catt M et al. A Novel, Open access method to assess sleep duration using a wrist-worn accelerometer. PLoS One. 2015;10(11):e0142533. DOI: https://doi.org/10.1371/journal.pone.0142533
Pavey TG, Gilson ND, Gomersall SR, Clark B, Trost SG. Field evaluation of a random forest activity classifier for wrist-worn accelerometer data. J Sci Med Sport. 2017;20(1):75-80. DOI: https://doi.org/10.1016/j.jsams.2016.06.003
Evenson KR, Goto MM, Furberg RD. Systematic review of the validity and reliability of consumer-wearable activity trackers. Int J Behav Nutr Phys Act. 2015;12:159. DOI: https://doi.org/10.1186/s12966-015-0314-1
Santos-Lozano A, Santín-Medeiros F, Cardon G, Torres-Luque G, Bailón R, Bergmeir C et al. Actigraph GT3X: validation and determination of physical activity intensity cut points. Int J Sports Med. 2013;34(11):975-82. DOI: https://doi.org/10.1055/s-0033-1337945
Kelly LA, McMillan DG, Anderson A, Fippinger M, Fillerup G, Rider J. Validity of actigraphs uniaxial and triaxial accelerometers for assessment of physical activity in adults in laboratory conditions. BMC Med Phys. 2013;13(1):5. DOI: https://doi.org/10.1186/1756-6649-13-5
Steenbock B, Wright MN, Wirsik N, Brandes M. Accelerometry-Based Prediction of Energy Expenditure in Preschoolers. J Meas Phys Behav. 2(2):94-102. DOI: https://doi.org/10.1123/jmpb.2018-0032
Hall KS, Howe CA, Rana SR, Martin CL, Morey MC. METs and accelerometry of walking in older adults: standard versus measured energy cost. Med Sci Sports Exerc. 2013;45(3):574-82. DOI: https://doi.org/10.1249/MSS.0b013e318276c73c
McClain JJ, Sisson SB, Tudor-Locke C. Actigraph accelerometer interinstrument reliability during free-living in adults. Med Sci Sports Exerc. 2007;39(9):1509-14. DOI: https://doi.org/10.1249/mss.0b013e3180dc9954
Vanhelst J, Béghin L, Turck D, Gottrand F. New validated thresholds for various intensities of physical activity in adolescents using the Actigraph accelerometer. Int J Rehabil Res. 2011;34(2):175-7. DOI: https://doi.org/10.1097/MRR.0b013e328340129e
O’Driscoll R, Turicchi J, Beaulieu K, Scott S, Matu J, Deighton K et al. How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies. Br J Sports Med. 2020;54(6):332-40.
Lee RS, Hanage WP. Reproducibility in science: important or incremental? The Lancet Microbe. 2020;1(2):e59-60. DOI: https://doi.org/10.1016/S2666-5247(20)30028-8
Google. COVID-19 Community Mobility Reports. https://www.google.com/covid19/mobility?hl=en (accessed Apr 21, 2021).
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Copyright (c) 2023 Raul Cosme Ramos Prado, Margarethe Thaisi Garro Knebel, Evelyn Helena Corgosinho Ribeiro, Inaian Pignatti Teixeira, Jeffer Eidi Sasaki, Luciano Vieira de Araújo, Paulo Henrique Guerra, Alex Antonio Florindo
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