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Journal of Medical Systems

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01.02.2020 | Mobile & Wireless Health

Mobile Apps to Quantify Aspects of Physical Activity: a Systematic Review on its Reliability and Validity

verfasst von: Anabela G. Silva, Patrícia Simões, Alexandra Queirós, Mário Rodrigues, Nelson P. Rocha

Erschienen in: Journal of Medical Systems | Ausgabe 2/2020

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Abstract

The purpose of this study was to systematically review and evaluate the evidence on the accuracy (validity) and consistency (reliability) of mobile apps used to quantify physical activity. Systematic literature searches were conducted in Pubmed, Science Direct, Web of Science, Physiotherapy Evidence Database (PEDro), Academic Search Complete and IEEE Xplore. Studies were included if they reported on the validity and/or reliability of a mobile application aiming primarily at measuring physical activity in humans with or without pathology. The reference lists of included articles were also screened for reports not identified through electronic searches. The methodological quality of included studies was assessed by 2 independent reviewers and data extracted by one reviewer and checked for accuracy by a second reviewer. A total of 25 articles were included in this review, of which 18 refer to validity and 7 to both validity and reliability. Mean percentage difference was used as an indicator of validity and varied between 0.1% and 79.3%. Intraclass Correlation Coefficients varied between 0.02 and 0.99 indicating poor to excellent reliability. There is conflicting and insufficient evidence on the validity and reliability, respectively, of apps for measuring physical activity. Nevertheless, velocity and the place where the smartphone is carried seem to have an impact on validity.

Reiner, M., Niermann, C., Jekauc, D., and Woll, A., Long-term health benefits of physical activity-a systematic review of longitudinal studies. BMC Public Health. 13:813, 2013.CrossRef

Jacobs, J. M., Rottenberg, Y., Cohen, A., and Stessman, J., Physical activity and health service utilization among older people. J Am Med Dir Assoc. 14(2):125–129, 2013.CrossRef

Silva AG, Queiros A, Rocha NP. Functioning and primary healthcare utilization in older adults: a 1-year follow-up study. Physiother Theory Pr. 2018;:1–10.

Ekblom-Bak, E., Ekblom, B., Vikström, M., de Faire, U., and Hellénius, M.-L., The importance of non-exercise physical activity for cardiovascular health and longevity. Br J Sport Med. 48:233–238, 2014.CrossRef

World Health Organization, Global recommendations on physical activity for health. Geneve: World Health Organization, 2010.

Tudor-Locke, C., Craig, C. L., Brown, W. J., Clemes, S. A., De Cocker, K., Giles-Corti, B. et al., How many steps/day are enough? For adults. Int J Behav Nutr Phys Act. 8:79, 2011.CrossRef

Tudor-Locke, C., Craig, C. L., Thyfault, J. P., and Spence, J. C., A step-defined sedentary lifestyle index: <5000 steps/day. Appl Physiol Nutr Metab. 38:100–114, 2013.CrossRef

Middelweerd, A., Mollee, J. S., van der Wal, C. N., Brug, J., and Te Velde, S. J., Apps to promote physical activity among adults: A review and content analysis. Int J Behav Nutr Phys Act. 11:97, 2014.CrossRef

Bort-Roig, J., Gilson, N. D., Puig-Ribera, A., Contreras, R. S., and Trost, S. G., Measuring and influencing physical activity with smartphone technology: A systematic review. Sport Med. 44:671–686, 2014.CrossRef

10.

Statistica. Number of smartphone users worldwide from 2014 to 2020 (in billions). Statistica. 2016. https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/. Accessed 5 Mar 2018.

11.

AppBrain. Google Play Stats. AppBrain. 2018. https://www.appbrain.com/stats. Accessed 5 Mar 2018.

12.

PocketGamer.biz. App Store Metrics. PocketGamer.biz. 2018.

13.

Xcertia mHealth App Guidelines. 2019 Board Approved Xcertia Guidelines.

14.

Vanhees, L., Lefevre, J., Philippaerts, R., Martens, M., Huygens, W., Troosters, T., and Beunen, G., How to assess physical activity? How to assess physical fitness? Eur J Cardiovasc Prev Rehabil. 12(2):102–114, 2005.CrossRef

15.

Caspersen CJ, Powell KE, Christenson GM. Physical activity, Exercise , and Physical Fitness: Definitions and Distinctions for Health-Related Research. Public Heal Rep. 1985;100:126–131.

16.

Streiner, D. L., and Norman, G. R., Health measurement scales: A practical guide to their development and use. 3rd edition. Oxford, UK: Oxford University Press, 2003.

17.

Brink, Y., and Louw, Q. A., Clinical instruments: Reliability and validity critical appraisal. J Eval Clin Pr. 18:1126–1132, 2012.CrossRef

18.

Walter, S. D., Eliasziw, M., and Donner, A., Sample size and optimal designs for reliability studies. Stat Med. 17:101–110, 1998.CrossRef

19.

Terwee, C. B., Bot, S. D. M., de Boer, M. R., van der Windt, D. A. W. M., Knol, D. L., Dekker, J., Bouter, L. M., and de Vet, H. C., Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 60(1):34–42, 2007.CrossRef

20.

Prince, S. A., Adamo, K. B., Hamel, M. E., Hardt, J., Connor Gorber, S., and 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. 5:56, 2008.CrossRef

21.

Lombard, M. J., Steyn, N. P., Charlton, K. E., and Senekal, M., Application and interpretation of multiple statistical tests to evaluate validity of dietary intake assessment methods. Nutr J. 14:40, 2015.CrossRef

22.

Aaronson, N., Alonso, J., Burnam, A., Lohr, K. N., Patrick, D. L., Perrin, E., and Stein, R. E., Assessing health status and quality-of-life instruments: Attributes and review criteria. Qual Life Res. 11(3):193–205, 2002.CrossRef

23.

Adamakis, M., Comparing the validity of a GPS monitor and a smartphone application to measure physical activity. J Mob Technol Med. 6:28–38, 2017.CrossRef

24.

Battenberg, A. K., Donohoe, S., Robertson, N., and Schmalzried, T. P., The accuracy of personal activity monitoring devices. Semin Arthroplast. 28:71–75, 2017.CrossRef

25.

Pobiruchin, M., Suleder, J., Zowalla, R., and Wiesner, M., Accuracy and adoption of wearable technology used by active citizens: A Marathon event field study. JMIR mHealth uHealth. 5(2):e24, 2017. https://doi.org/10.2196/mhealth.6395.CrossRefPubMedPubMedCentral

26.

Prieto-Centurion, V., Bracken, N., Norwick, L., Zaidi, F., Mutso, A., Morken, V., Coultas, D. et al., Can commercially available pedometers be used for physical activity monitoring in patients with COPD following exacerbations? Chronic Obs Pulm Dis. 3:636–642, 2016.

27.

Sarwar, A., Mukhtar, H., Maqbool, M., and Belaid, D., SmartFit: A step count based Mobile application for engagement in physical activities. Int J Adv Comput Sci Appl. 6, 2015.

28.

Vorrink, S. N., Kort, H. S., Troosters, T., and Lammers, J.-W. J., A Mobile phone app to stimulate daily physical activity in patients with chronic obstructive pulmonary disease: Development, feasibility, and pilot studies. JMIR mHealth uHealth. 4(1):e11, 2016. https://doi.org/10.2196/mhealth.4741.CrossRefPubMedPubMedCentral

29.

Presset, B., Laurenczy, B., Malatesta, D., and Barral, J., Accuracy of a smartphone pedometer application according to different speeds and mobile phone locations in a laboratory context. J Exerc Sci Fit. 16(2):43–48, 2018. https://doi.org/10.1016/j.jesf.2018.05.001.CrossRefPubMedPubMedCentral

30.

Duncan, M. J., Wunderlich, K., Zhao, Y., and Faulkner, G., Walk this way: Validity evidence of iphone health application step count in laboratory and free-living conditions. J Sports Sci. 36(15):1695–1704, 2018.CrossRef

31.

Höchsmann, C., Knaier, R., Eymann, J., Hintermann, J., Infanger, D., and Schmidt-Trucksäss, A., Validity of activity trackers, smartphones, and phone applications to measure steps in various walking conditions. Scand J Med Sci Sport. 28:1818–1827, 2018.CrossRef

32.

Xie, J., Wen, D., Liang, L., Jia, Y., Gao, L., and Lei, J., Evaluating the validity of current mainstream wearable devices in fitness tracking under various physical activities: Comparative study. JMIR mHealth uHealth. 6, 2018.

33.

Bergman, R., Spellman, J., Hall, M., and Bergman, S., Is there a valid app for that? Validity of a free pedometer iPhone application. J Phys Act Heal Heal. 9:670–676, 2012.CrossRef

34.

Bort-Roig, J., Puig-Ribera, A., Contreras, R. S., Chirveches-Perez, E., Martori, J. C., Gilson, N. D. et al., Monitoring sedentary patterns in office employees: Validity of an m-health tool (walk@work-app) for occupational health. Gac Sanit. 32(6):563–566, 2018.CrossRef

35.

Chinrungrueng J, Sartsatit S, Intarapanich A. My act: an automatic detection of daily physical activity and calorie expenditure using smart phones. J Assist Rehabil Ther Technol. 2AD;2014:1–8.

36.

Dybus, A., Paul, L., Wyke, S., Brewster, S., and Gill, J., Ramsay A, et al. Validation of smartphone step count algorithm used in STARFISH smartphone application. 25:1157–1162, 2017.

37.

Gordon BA, Bruce L, Benson AC. Physical activity intensity can be accurately monitored by smartphone global positioning system ‘app.’ Eur J Sport Sci. 2016;16:624–631. doi:https://doi.org/10.1080/17461391.2015.1105299, Physical activity intensity can be accurately monitored by smartphone global positioning system 'app', 5.CrossRef

38.

Khalil A, Glal S. StepUp : A Step Counter Mobile Application to Promote Healthy Lifestyle. In: International Conference on the Current Trends in Information Technology (CTIT). 2009. p. 1–5.

39.

Leong, J., and Wong, J., Accuracy of three android-based pedometer applications in laboratory and free-living settings. J Sport Sci. 35:14–21, 2017.CrossRef

40.

Maddison, R., Gemming, L., Monedero, J., Bolger, L., Belton, S., Issartel, J., Marsh, S., Direito, A., Solenhill, M., Zhao, J., Exeter, D. J., Vathsangam, H., and Rawstorn, J. C., Quantifying human movement using the Movn smartphone app: Validation and field study. JMIR mHealth uHealth. 5(8):e122, 2017. https://doi.org/10.2196/mhealth.7167.CrossRefPubMedPubMedCentral

41.

Åkerberg, A., Söderlund, A., and Lindén, M., Investigation of the validity and reliability of a smartphone pedometer application. Eur J Physiother. 18:185–193, 2016.CrossRef

42.

Benson, A., Bruce, L., and Gordon, B., Reliability and validity of a GPS-enabled iPhone TM “app” to measure physical activity. J Sport Sci. 33:1421–1428, 2015.CrossRef

43.

Fokkema, T., Kooiman, T. J. M., Krijnen, W. P., Van Der Schans, C. P., and De Groot, M., Reliability and validity of ten consumer activity trackers depend on walking speed. Med Sci Sport Exerc. 49:793–800, 2017. https://doi.org/10.1249/MSS.0000000000001146.CrossRef

44.

Konharn, K., Eungpinichpong, W., Promdee, K., Sangpara, P., Nongharnpitak, S., Malila, W., and Karawa, J., Validity and reliability of smartphone applications for the assessment of walking and running in Normal-weight and overweight/obese young adults. J Phys Act Heal. 13(12):1333–1340, 2016. https://doi.org/10.1123/jpah.2015-0544.CrossRef

45.

Kooiman, T. J. M., Dontje, M. L., Sprenger, S. R., Krijnen, W. P., van der Schans, C. P., and de Groot, M., Reliability and validity of ten consumer activity trackers. BMC Sports Sci Med Rehabil. 7:24, 2015. https://doi.org/10.1186/s13102-015-0018-5.CrossRefPubMedPubMedCentral

46.

Orr, K., Howe, H. S., Omran, J., Smith, K. A., Palmateer, T. M., Ma, A. E., and Faulkner, G., Validity of smartphone pedometer applications. BMC Res Notes. 8:733, 2015. https://doi.org/10.1186/s13104-015-1705-8.CrossRefPubMedPubMedCentral

47.

Douma, J. A. J., Verheul, H. M. W., and Buffart, L. M., Feasibility, validity and reliability of objective smartphone measurements of physical activity and fitness in patients with cancer. BMC Cancer. 18, 2018.

48.

World Health Organization. Prevalence of insufficient physical activity. Global Health Observatory (GHO) data. 2010,.

49.

Silva, A. G., Queirós, A., Sá-Couto, P., and Rocha, N. P., Higher pain intensity, depression, and being 75 years or older are associated with lower levels of self-reported physical activity in older adults with pain attending primary care. Clin Gerontol. 39:324–341, 2016.CrossRef

50.

Brink, Y., and Louw, Q., Clinical instruments : Reliability and validity critical appraisal. J Eval Clin Pr. 18:1126–1132, 2012.CrossRef

51.

Mokkink, L. B., Terwee, C. B., and Patrick, D. L., Alonso J. Knol DL, et al. COSMIN checklist manual. Amsterdam: Stratford PW, 2012.

52.

Mokkink, L. B., Terwee, C. B., Knol, D. L., Stratford, P. W., Alonso, J., Patrick, D. L. et al., The COSMIN checklist for evaluating the methodological quality of studies on measurement properties: A clarification of its content. BMC Med Res Methodol. 10:22, 2010.CrossRef

53.

Weir, J. P., Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res. 19(1):231–240, 2005.PubMed

Titel: Mobile Apps to Quantify Aspects of Physical Activity: a Systematic Review on its Reliability and Validity
verfasst von: Anabela G. Silva
Patrícia Simões
Alexandra Queirós
Mário Rodrigues
Nelson P. Rocha
Publikationsdatum: 01.02.2020
Verlag: Springer US
Erschienen in: Journal of Medical Systems / Ausgabe 2/2020
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-019-1506-z

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Mobile Apps to Quantify Aspects of Physical Activity: a Systematic Review on its Reliability and Validity

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