Ecological Momentary Assessment of Physical Activity: Validation Study

Gregory Knell, Kelley Pettee Gabriel, Michael S Businelle, Kerem Shuval, David W Wetter, Darla E Kendzor, Gregory Knell, Kelley Pettee Gabriel, Michael S Businelle, Kerem Shuval, David W Wetter, Darla E Kendzor

Abstract

Background: Ecological momentary assessment (EMA) may elicit physical activity (PA) estimates that are less prone to bias than traditional self-report measures while providing context.

Objectives: The objective of this study was to examine the convergent validity of EMA-assessed PA compared with accelerometry.

Methods: The participants self-reported their PA using International Physical Activity Questionnaire (IPAQ) and Behavioral Risk Factor Surveillance System (BRFSS) and wore an accelerometer while completing daily EMAs (delivered through the mobile phone) for 7 days. Weekly summary estimates included sedentary time and moderate-, vigorous-, and moderate-to vigorous-intensity physical activity (MVPA). Spearman coefficients and Lin's concordance correlation coefficients (LCC) examined the linear association and agreement for EMA and the questionnaires as compared with accelerometry.

Results: Participants were aged 43.3 (SD 13.1) years, 51.7% (123/238) were African American, 74.8% (178/238) were overweight or obese, and 63.0% (150/238) were low income. The linear associations of EMA and traditional self-reports with accelerometer estimates were statistically significant (P<.05) for sedentary time (EMA: ρ=.16), moderate-intensity PA (EMA: ρ=.29; BRFSS: ρ=.17; IPAQ: ρ=.24), and MVPA (EMA: ρ=.31; BRFSS: ρ=.17; IPAQ: ρ=.20). Only EMA estimates of PA were statistically significant compared with accelerometer for agreement.

Conclusions: The mobile EMA showed better correlation and agreement to accelerometer estimates than traditional self-report methods. These findings suggest that mobile EMA may be a practical alternative to accelerometers to assess PA in free-living settings.

Keywords: accelerometry; behavioral risk factor surveillance system; data accuracy; ecological momentary assessment; self-report.

Conflict of interest statement

Conflicts of Interest: None declared.

©Gregory Knell, Kelley Pettee Gabriel, Michael S Businelle, Kerem Shuval, David W Wetter, Darla E Kendzor. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.07.2017.

Figures

Figure 1
Figure 1
Lin concordance correlation plots of physical activity measurement devices to evaluate the agreement between the device and accelerometer in measuring moderate-, vigorous-, and moderate-to vigorous-intensity physical activity (MVPA).
Figure 2
Figure 2
Bland-Altman plots (difference plots) of physical activity measurement devices to evaluate the agreement between the device and accelerometer in measuring moderate-, vigorous-, and moderate-to vigorous-intensity physical activity (MVPA).

References

    1. Adams SA, Matthews CE, Ebbeling CB, Moore CG, Cunningham JE, Fulton J, Hebert JR. The effect of social desirability and social approval on self-reports of physical activity. Am J Epidemiol. 2005 Feb 15;161(4):389–98. doi: 10.1093/aje/kwi054.
    1. Ferrari P, Friedenreich C, Matthews Ce. The role of measurement error in estimating levels of physical activity. Am J Epidemiol. 2007 Oct 01;166(7):832–40. doi: 10.1093/aje/kwm148.
    1. Prince SA, Adamo KB, Hamel ME, Hardt J, Connor GS, 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 Nov 06;5:56. doi: 10.1186/1479-5868-5-56.
    1. Strath SJ, Kaminsky LA, Ainsworth BE, Ekelund U, Freedson PS, Gary RA, Richardson CR, Smith DT, Swartz AM, American Heart Association Physical Activity Committee of the Council on LifestyleCardiometabolic HealthCardiovascular‚ Exercise‚ Cardiac RehabilitationPrevention Committee of the Council on Clinical Cardiology‚Council Guide to the assessment of physical activity: clinical and research applications: a scientific statement from the American Heart Association. Circulation. 2013 Nov 12;128(20):2259–79. doi: 10.1161/01.cir.0000435708.67487.da.
    1. Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annu Rev Clin Psychol. 2008;4:1–32.
    1. Matthews CE, Moore SC, George SM, Sampson J, Bowles HR. Improving self-reports of active and sedentary behaviors in large epidemiologic studies. Exerc Sport Sci Rev. 2012 Jul;40(3):118–26. doi: 10.1097/JES.0b013e31825b34a0.
    1. Schatzkin A, Subar AF, Moore S, Park Y, Potischman N, Thompson FE, Leitzmann M, Hollenbeck A, Morrissey KG, Kipnis V. Observational epidemiologic studies of nutrition and cancer: the next generation (with better observation) Cancer Epidemiol Biomarkers Prev. 2009 Apr;18(4):1026–32. doi: 10.1158/1055-9965.EPI-08-1129.
    1. Bianchi Sm, Milkie Ma, Sayer Lc, Robinson Jp. Is anyone doing the housework? Trends in the gender division of household labor. Soc Forces. 2000;79(1):191–228. doi: 10.1093/sf/79.1.191.
    1. Bowles HR. Measurement of active and sedentary behaviors: closing the gaps in self-report methods. J Phys Act Health. 2012 Jan;9(s1):S1–S4. doi: 10.1123/jpah.9.s1.s1.
    1. Calabro MA, Welk GJ, Carriquiry AL, Nusser SM, Beyler NK, Mathews CE. Validation of a computerized 24-hour physical activity recall (24PAR) instrument with pattern-recognition activity monitors. J Phys Act Health. 2009 Mar;6(2):211–20.
    1. Thomas JG, Bond DS, Ryder BA, Leahey TM, Vithiananthan S, Roye GD, Wing RR. Ecological momentary assessment of recommended postoperative eating and activity behaviors. Surg Obes Relat Dis. 2011 Mar;7(2):206–12. doi: 10.1016/j.soard.2010.10.007.
    1. Rofey DL, Hull EE, Phillips J, Vogt K, Silk JS, Dahl RE. Utilizing Ecological Momentary Assessment in pediatric obesity to quantify behavior, emotion, and sleep. Obesity (Silver Spring) 2010 Jun;18(6):1270–2. doi: 10.1038/oby.2009.483. doi: 10.1038/oby.2009.483.
    1. Atienza AA, Oliveira B, Fogg B, King AC. Using electronic diaries to examine physical activity and other health behaviors of adults age 50+ J Aging Phys Act. 2006 Apr;14(2):192–202. doi: 10.1123/japa.14.2.192.
    1. U.S. Department of Health and Human Services . 2008. [2017-02-27]. Physical Activity Guidelines Advisory Committee Report
    1. Kendzor DE, Shuval K, Gabriel KP, Businelle MS, Ma P, High RR, Cuate EL, Poonawalla IB, Rios DM, Demark-Wahnefried W, Swartz MD, Wetter DW. Impact of a mobile phone intervention to reduce sedentary behavior in a community sample of adults: a quasi-experimental evaluation. J Med Internet Res. 2016;18(1):e19. doi: 10.2196/jmir.5137.
    1. Yore MM, Ham SA, Ainsworth BE, Kruger J, Reis JP, Kohl HW, Macera CA. Reliability and validity of the instrument used in BRFSS to assess physical activity. Med Sci Sports Exerc. 2007 Aug;39(8):1267–74. doi: 10.1249/mss.0b013e3180618bbe.
    1. Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003 Aug;35(8):1381–95. doi: 10.1249/01.MSS.0000078924.61453.FB.
    1. sites.google. [2017-02-10]. Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire (IPAQ) - Short and Long Forms .
    1. Healy GN, Matthews CE, Dunstan DW, Winkler EA, Owen N. Sedentary time and cardio-metabolic biomarkers in US adults: NHANES 2003-06. Eur Heart J. 2011 Mar;32(5):590–7. doi: 10.1093/eurheartj/ehq451.
    1. Matthew CE. Calibration of accelerometer output for adults. Med Sci Sports Exerc. 2005;37(11 Suppl):16294114. doi: 10.1249/01.mss.0000185659.11982.
    1. Nichols J, Morgan C, Chabot L, Sallis J, Calfas K. Assessment of physical activity with the Computer Science and Applications, Inc., accelerometer: laboratory versus field validation. Res Q Exerc Sport. 2000;71(1):36–43. doi: 10.1080/02701367.2000.10608878.
    1. Troiano RP, Berrigan D, Dodd KW, Mâsse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008 Jan;40(1):181–8. doi: 10.1249/mss.0b013e31815a51b3.
    1. . 2016. Feb 03, [2017-02-10]. SAS Programs for Analyzing NHANES 2003-2004 Accelerometer Data
    1. McBride G. Using statistical methods for water quality management: issues, problems and solutions. Hoboken: John Wiley & Sons; 2005.
    1. Dunton GF, Whalen CK, Jamner LD, Henker B, Floro JN. Using ecologic momentary assessment to measure physical activity during adolescence. Am J Prev Med. 2005 Nov;29(4):281–7. doi: 10.1016/j.amepre.2005.07.020.
    1. Dunton GF, Liao Y, Intille SS, Spruijt-Metz D, Pentz M. Investigating children's physical activity and sedentary behavior using ecological momentary assessment with mobile phones. Obesity (Silver Spring) 2011 Jun;19(6):1205–12. doi: 10.1038/oby.2010.302.
    1. Dunton GF, Liao Y, Kawabata K, Intille S. Momentary assessment of adult's physical activity and sedentary behavior: feasibility and validity. Front Psychology. 2012;3:260–269. doi: 10.3389/fpsyg.2012.00260.
    1. Lin LI. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 1989 Mar;45(1):255. doi: 10.2307/2532051.
    1. Lee PH, Yu Y, McDowell I, Leung GM, Lam T, Stewart SM. Performance of the international physical activity questionnaire (short form) in subgroups of the Hong Kong chinese population. Int J Behav Nutr Phys Act. 2011;8(1):81. doi: 10.1186/1479-5868-8-81.
    1. Kocherginsky M, Huisingh-Scheetz M, Dale W, Lauderdale DS, Waite L. Correction: Measuring physical activity with hip accelerometry among U.S. older adults: how many days are enough? PLoS One. 2017 Jan;12(3):e0174739. doi: 10.1371/journal.pone.0170082. doi: 10.1371/journal.pone.0174739.
    1. Carpineto P, Mastropasqua R, Marchini G, Toto L, Di Nicola M, Di Antonio L. Reproducibility and repeatability of foveal avascular zone measurements in healthy subjects by optical coherence tomography angiography. Br J Ophthalmol. 2016 May;100(5):671–6. doi: 10.1136/bjophthalmol-2015-307330.
    1. Martinez-Martin P, Chaudhuri KR, Rojo-Abuin JM, Rodriguez-Blazquez C, Alvarez-Sanchez M, Arakaki T, Bergareche-Yarza A, Chade A, Garretto N, Gershanik O, Kurtis MM, Martinez-Castrillo JC, Mendoza-Rodriguez A, Moore HP, Rodriguez-Violante M, Singer C, Tilley BC, Huang J, Stebbins GT, Goetz CG. Assessing the non-motor symptoms of Parkinson's disease: MDS-UPDRS and NMS Scale. Eur J Neurol. 2015 Jan;22(1):37–43. doi: 10.1111/ene.12165.
    1. Pérez A, Gabriel K, Nehme EK, Mandell DJ, Hoelscher DM. Measuring the bias, precision, accuracy, and validity of self-reported height and weight in assessing overweight and obesity status among adolescents using a surveillance system. Int J Behav Nutr Phys Act. 2015;12(Suppl 1):S2. doi: 10.1186/1479-5868-12-S1-S2.
    1. Gabriel KP, Morrow JR, Woolsey AT. Framework for physical activity as a complex and multidimensional behavior. J Phys Act Health. 2012 Jan;9(Suppl 1):S11–S18. doi: 10.1123/jpah.9.s1.s11.
    1. Sallis JF, Saelens BE. Assessment of physical activity by self-report: status, limitations, and future directions. Res Q Exerc Sport. 2015 Feb 13;71(sup2):1–14. doi: 10.1080/02701367.2000.11082780.
    1. Baranowski T. Validity and reliability of self report measures of physical activity: an information-processing perspective. Res Q Exerc Sport. 1988;59(4):314–27. doi: 10.1080/02701367.1988.10609379.
    1. van Poppel MN, Chinapaw MJ, Mokkink LB, van Mechelen W, Terwee CB. Physical activity questionnaires for adults: a systematic review of measurement properties. Sports Med. 2010 Jul 01;40(7):565–600. doi: 10.2165/11531930-000000000-00000.
    1. Shuval K, Kohl HW, Bernstein I, Cheng D, Pettee Gabriel K, Barlow CE, Yinghui L, DiPietro L. Sedentary behaviour and physical inactivity assessment in primary care: the Rapid Assessment Disuse Index (RADI) study. Br J Sports Med. 2013 Oct 21;48(3):250–255. doi: 10.1136/bjsports-2013-092901.

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