Momentary assessment of adults' physical activity and sedentary behavior: feasibility and validity

Genevieve Fridlund Dunton, Yue Liao, Keito Kawabata, Stephen Intille, Genevieve Fridlund Dunton, Yue Liao, Keito Kawabata, Stephen Intille

Abstract

Introduction: Mobile phones are ubiquitous and easy to use, and thus have the capacity to collect real-time data from large numbers of people. Research tested the feasibility and validity of an Ecological Momentary Assessment (EMA) self-report protocol using electronic surveys on mobile phones to assess adults' physical activity and sedentary behaviors.

Methods: Adults (N = 110; 73% female, 30% Hispanic, 62% overweight/obese) completed a 4-day signal-contingent EMA protocol (Saturday-Tuesday) with eight surveys randomly spaced throughout each day. EMA items assessed current activity (e.g., Watching TV/Movies, Reading/Computer, Physical Activity/Exercise). EMA responses were time-matched to minutes of moderate-to-vigorous physical activity (MVPA) and sedentary activity (SA) measured by accelerometer immediately before and after each EMA prompt.

Results: Unanswered EMA prompts had greater MVPA (±15 min) than answered EMA prompts (p = 0.029) for under/normal weight participants, indicating that activity level might influence the likelihood of responding. The 15-min. intervals before versus after the EMA-reported physical activity (n = 296 occasions) did not differ in MVPA (p > 0.05), suggesting that prompting did not disrupt physical activity. SA decreased after EMA-reported sedentary behavior (n = 904 occasions; p < 0.05) for overweight and obese participants. As compared with other activities, EMA-reported physical activity and sedentary behavior had significantly greater MVPA and SA, respectively, in the ±15 min of the EMA prompt (ps < 0.001), providing evidence for criterion validity.

Conclusion: Findings generally support the acceptability and validity of a 4-day signal-contingent EMA protocol using mobile phones to measure physical activity and sedentary behavior in adults. However, some MVPA may be missed among underweight and normal weight individuals.

Keywords: accelerometers; adults; ecological momentary assessment; physical activity; sedentary behavior; validity.

Figures

Figure 1
Figure 1
Ecological momentary assessment (EMA) screen shots. Images display how Ecological Momentary Assessment (EMA) items and response choices appeared on the display screen of the mobile phone. Respondents used the key pad to toggle up/down and select their response. Only one response choice could be selected per screen. If a respondent selected “Physical Activity/Exercising” on Screen 1, he/she was automatically directed to Screen 2. If a respondent selected “Other” on Screen 1, he/she was automatically directed to Screen 3. If a respondent selected “Something else” on Screen 3, he/she was automatically directed to Screen 4.
Figure 2
Figure 2
Ecological momentary assessment (EMA) procedure. Each X represents an EMA survey that was prompted at a random time with the specified time interval.
Figure 3
Figure 3
Flow chart of data availability. Level 1 represents the number of electronic Ecological Momentary Assessment (EMA) surveys, and Level 2 represents the number of participants. EMA Surveys Downloaded = the number of EMA surveys successfully downloaded from the mobile phone. Prompted EMA Surveys = the number of EMA surveys with a time and date record of being prompted. Matched EMA Surveys = the number of prompted EMA surveys that could be time-matched to available accelerometer data. EMA Surveys with Worn Accelerometer = the number of prompted EMA surveys that could be time-matched to data indicating accelerometer wear during that period. Accelerometer wear was defined as greater than zero activity counts in the ±15 min window of each electronic EMA survey prompt. Answered EMA Surveys with Worn Accelerometer = the number of answered EMA surveys that could be time-matched to data indicating accelerometer wear during that period.
Figure 4
Figure 4
Mean moderate-to-vigorous physical activity (MVPA) minutes by activity categories self-reported through ecological momentary assessment (EMA). MVPA was recorded by accelerometer in the ±15 min window of each answered EMA survey prompt. Values represent the predicted marginal means generated through multilevel linear regressions, which adjusted for sex, age, race/ethnicity, annual household income, and weight status. Standard error (SE) bars are shown. Non-overlapping SE bars indicate a statistically significant difference between means at p < 0.05.
Figure 5
Figure 5
Mean sedentary activity (SA) minutes by activity categories self-reported through ecological momentary assessment (EMA). SA was recorded by accelerometer in the ±15 min window of each answered EMA survey prompt. Values represent the predicted marginal means generated through multilevel linear regressions, which adjusted for sex, age, race/ethnicity, annual household income, and weight status. Standard error (SE) bars are shown. Non-overlapping SE bars indicate a statistically significant difference between means at p < 0.05.

References

    1. Belcher B. R., Berrigan D., Dodd K. W., Emken B. A., Chou C. P., Spruijt-Metz D. (2010). Physical activity in US youth: effect of race/ethnicity, age, gender, and weight status. Med. Sci. Sports Exerc. 42, 2211–222110.1249/MSS.0b013e3181e1fba9
    1. Colley R., Gorber S. C., Tremblay M. S. (2010). Quality control and data reduction procedures for accelerometry-derived measures of physical activity. Health Rep. 21, 63–69
    1. Conroy D. E., Elavsky S., Hyde A. L., Doerksen S. E. (2011). The dynamic nature of physical activity intentions: a within-person perspective on intention-behavior coupling. J. Sport Exerc. Psychol. 33, 807–827
    1. Dunton G. F., Atienza A. A. (2009). The need for time-intensive information in healthful eating and physical activity research: a timely topic. J. Am. Diet. Assoc. 109, 30–3510.1016/j.jada.2009.06.084
    1. Dunton G. F., Atienza A. A., Castro C. M., King A. C. (2009). Using ecological momentary assessment to examine antecedents and correlates of physical activity bouts in adults age 50+ years: a pilot study. Ann. Behav. Med. 38, 249–25510.1007/s12160-009-9141-4
    1. Dunton G. F., Liao Y., Intille S. S., Spruijt-Metz D., Pentz M. (2011). Investigating children’s physical activity and sedentary behavior using ecological momentary assessment with mobile phones. Obesity (Silver Spring) 19, 1205–121210.1038/oby.2010.302
    1. Froehlich J., Chen M. Y., Consolvo S., Harrison B., Landay J. A. (2007). “Myexperience: a system for in situ tracing and capturing of user feedback on mobile phones,” in Proceedings of the 5th International Conference on Mobile Systems, Applications and Services, San Juan, 57–70
    1. Godin G., Sheeran P., Conner M., Germain M. (2008). Asking questions changes behavior: mere measurement effects on frequency of blood donation. Health Psychol. 27, 179–18410.1037/0278-6133.27.2.179
    1. Haskell W. L. (2012). Physical activity by self-report: a brief history and future issues. J. Phys. Act. Health 9(Suppl. 1), S5–S10
    1. Hawkins M. S., Storti K. L., Richardson C. R., King W. C., Strath S. J., Holleman R. G., Kriskariska A. M. (2009). Objectively measured physical activity of USA adults by sex, age, and racial/ethnic groups: a cross-sectional study. Int. J. Behav. Nutr. Phys. Act. 6, 31.10.1186/1479-5868-6-31
    1. Healy G. N., Dunstan D. W., Salmon J., Cerin E., Shaw J. E., Zimmet P. Z., Owen N. (2008). Breaks in sedentary time: beneficial associations with metabolic risk. Diabetes Care 31, 661–66610.2337/dc07-2046
    1. Hufford M. R., Shields A. L., Shiffman S., Paty J., Balabanis M. (2002). Reactivity to ecological momentary assessment: an example using undergraduate problem drinkers. Psychol. Addict. Behav. S16, 205–21110.1037/0893-164X.16.3.205
    1. Intille S. S., Lester J., Sallis J. F., Duncan G. (2012). New horizons in sensor development. Med. Sci. Sports Exerc. 44(Suppl. 1), S24–S3110.1249/MSS.0b013e3182399c7d
    1. Kanning M., Schlicht W. (2010). Be active and become happy: an ecological momentary assessment of physical activity and mood. J. Sport Exerc. Psychol. 32, 253–261
    1. Kaplan W. A. (2006). Can the ubiquitous power of mobile phones be used to improve health outcomes in developing countries? Global Health 2, 9.
    1. Korn E. L., Graubard B. I. (1999). Analysis of Health Surveys. New York: Wiley
    1. Kosaraju A., Barrigan C. R., Poropatich R. K., Casscells S. W. (2010). Use of mobile phones as a tool for United States health diplomacy abroad. Telemed. J. E. Health 16, 218–22210.1089/tmj.2009.0095
    1. Loney T., Standage M., Thompson D., Sebire S. J., Cumming S. (2011). Self-report vs. objectively assessed physical activity: which is right for public health? J. Phys. Act. Health 8, 62–70
    1. Merom D., Bowles H., Bauman A. (2009). Measuring walking for physical activity surveillance – the effect of prompts and respondents’ interpretation of walking in a leisure-time survey. J. Phys. Act. Health 6(Suppl. 1), S81–S88
    1. Nicaise V., Marshall S., Ainsworth B. E. (2011). Domain-specific physical activity and self-report bias among low-income Latinas living in San Diego County. J. Phys. Act. Health 8, 881–890,
    1. Patrick K., Griswold W. G., Raab F., Intille S. S. (2008). Health and the mobile phone. Am. J. Prev. Med. 35, 177–18110.1016/j.amepre.2008.05.001
    1. Physical Activity Guidelines Advisory Committee (2008). Physical Activity Guidelines Advisory Committee Report Washington, DC: U.S. Department of Health and Human Services
    1. Rofey D. L., Hull E. E., Phillips J., Vogt K., Silk J. S., Dahl R. E. (2010). Utilizing ecological momentary assessment in pediatric obesity to quantify behavior, emotion, and sleep. Obesity (Silver Spring) 18, 1270–127210.1038/oby.2009.483
    1. Spees C. K., Scott J. M., Taylor C. A. (2012). Differences in amounts and types of physical activity by obesity status in US adults. Am. J. Health Behav. 36, 56–6510.5993/AJHB.36.1.6
    1. Thomas J. G., Bond D. S., Ryder B. A., Leahey T. M., Vithiananthan S., Roye G. D., Wing R. R. (2011). Ecological momentary assessment of recommended postoperative eating and activity behaviors. Surg. Obes. Relat. Dis. 7, 206–21210.1016/j.soard.2010.10.007
    1. Troiano R. P., Berrigan D., Dodd K. W., Masse L. C., Tilert T., McDowell M. (2008). Physical activity in the United States measured by accelerometer. Med. Sci. Sports Exerc. 40, 181–18810.1249/01.mss.0000322246.48549.fc
    1. Troiano R. P., Pettee Gabriele K. K., Welk G. J., Owen N., Sternfeld B. (2012). Reported physical activity and sedentary behavior: why do you ask? J. Phys. Act. Health 9(Suppl. 1), S68–S75
    1. Tucker J. M., Welk G. J., Beyler N. K. (2011). Physical activity in U.S.: adults compliance with the physical activity guidelines for Americans. Am. J. Prev. Med. 40, 454–46110.1016/j.amepre.2010.12.016

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