Abstract
We evaluated the validity of the use of an SMS text messaging survey for measuring daily life activity in a sample of emerging adults. Short Message Service (SMS) text messaging is a prevalent form of everyday communication in the lives of emerging adults, yet there is limited research on the use of automated text messaging as a data collection method in clinical research. Study participants were 274 ethnically diverse emerging adults (54.4% female, baseline age = 17–21 years), and constructs included alcohol use, substance use, school activity, peer interaction, mood, and interaction with parents. Participants responded to “bursts” that included multiple surveys during the course of 2 weeks, 6 months apart (a total of 13 texting surveys). Most of the questions were strongly associated across bursts. Findings revealed response stability for participating subjects across the 6 months and across the texting and self-report survey methodologies. Paired sample t-tests indicated that participants reported differently across data methodologies, which suggests that some data collection methodologies are best suited for certain types of constructs, such as alcohol consumption. Study results encapsulate the daily life of emerging adults and highlight the importance of evaluating the validity of SMS text messaging as a potential data collection device in future research.
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References
Achenbach, T. M. (2003). Adult self-report for ages. Burlington, VT: University of Vermont 18–59.
Arnett, J. J. (2007). Emerging adulthood: What is it, and what is it good for? Child Development Perspectives, 1(2), 68–73. https://doi.org/10.1111/j.1750-8606.2007.00016.x.
Berkman, E. T., Dickenson, J., Falk, E. B., & Lieberman, M. D. (2011). Using SMS text messaging to assess moderators of smoking reduction: Validating a new tool for ecological measurement of health behaviors. Health Psychology, 30(2), 186–194. https://doi.org/10.1037/a0022201.
Child and Family Center. (2001a). CFC Youth Questionnaire. Eugene, OR: Child and Family Center. Unpublished instrument.
Child and Family Center. (2001b). Teen Interview (CINT). Eugene, OR: Child and Family Center, University of Oregon. Unpublished instrument.
Dishion, T. J., & Caruthers, A. (2007). Time Allocation Measure of Social Adaptation (TAMSA). Eugene, OR: Child and Family Center, University of Oregon. Unpublished instrument.
Ferguson, S. G., & Shiffman, S. (2011). Using the methods of ecological momentary assessment in substance dependence research—smoking cessation as a case study. Substance Use & Misuse, 46(1), 87–95. https://doi.org/10.3109/10826084.2011.521399.
Hadley, E. K., Smith, C., Gallo, A. M., Angst, D. B., & Knafl, K. A. (2008). Parents’ perspectives on having their children interviewed for research. Research in Nursing & Health, 31(1), 4–11. https://doi.org/10.1002/nur.
Harris, K. M., Griffin, B. A., McCaffrey, D. F., & Morral, A. R. (2008). Inconsistencies in self-reported drug use by adolescents in substance abuse treatment: Implications for outcome and performance measurements. Journal of Substance Abuse Treatment, 34(3), 347–355. https://doi.org/10.1016/j.jsat.2007.05.004.
Hedden, S. L. (2015). Behavioral health trends in the United States: Results from the 2014 National Survey on Drug Use and Health. Substance Abuse and Mental Health Services Administration, Department of Health & Human Services: Rockville, MD.
Johansen, B., & Wedderkopp, N. (2010). Comparison between data obtained through real-time data capture by SMS and a retrospective telephone interview. Chiropractic & Manual Therapies, 18(10), 1–7. https://doi.org/10.1186/1746-1340-18-10.
Johnston, L. D, O’Malley, P. M, Bachman, J. G, Schulenberg, J. E., & Miech, R. A. (2016). Monitoring the Future national survey results on drug use, 1975–2015: Volume 2, college students and adults ages. 19–55. Ann Arbor: Institute for Social Research, The University of Michigan. http://monitoringthefuture.org/pubs.html#monographs.
Kuntsche, E., & Labhart, F. (2014). The future is now—using personal cellphones to gather data on substance use and related factors. Addiction, 109(7), 1052–1053. https://doi.org/10.1111/add.12540.
Kuntsche, E., & Robert, B. (2009). Short Message Service (SMS) technology in alcohol research—a feasibility study. Alcohol & Alcoholism, 44(4), 423–428. https://doi.org/10.1093/alcalc/agp033.
Lim, M. S. C., Sacks-Davis, R., Aitken, C. K., Hocking, J. S., & Hellard, E. (2010). Randomised controlled trial of paper, online and SMS diaries for collecting sexual behaviour information from young people. Journal of Epidemiology & Community Health, 64(10), 885–889. https://doi.org/10.1136/jech.2008.085316.
Margolis, K. L., Fosco, G. M., & Stormshak, E. A. (2016). Circle of care: Extending beyond primary caregivers to examine collaborative caretaking in adolescent development. Journal of Family Issues, 37(9), 1179–1202. https://doi.org/10.1177/0192513X14536565.
Metzler, C. W., Biglan, A., Ary, D. V., & Li, F. (1998). The stability and validity of early adolescents’ reports of parenting constructs. Journal of Family Psychology, 12(4), 600–619. https://doi.org/10.1037/0893-3200.12.4.600.
Phillips, M. M., Phillips, K. T., Lalonde, T. L., & Dykema, K. R. (2014). Feasibility of text messaging for ecological momentary assessment of marijuana use in college students. Psychological Assessment, 26(3), 947–957. https://doi.org/10.1037/a0036612.
Ram, N., Conroy, D. E., Pincus, A. L., Lorek, A., Rebar, A., Roche, M. J., & Gerstorf, D. (2014). Examining the interplay of processes across multiple time-scales: Illustration with the Intraindividual Study of Affect, Health, and Interpersonal Behavior (iSAHIB). Research in Human Development, 11(2), 142–160. https://doi.org/10.1080/15427609.2014.906739.
Ram, N., & Gerstorf, D. (2009). Time-structured and net intraindividual variability: tools for examining the development of dynamic characteristics and processes. Psychology and Aging, 24(4), 778–791. https://doi.org/10.1037/a0017915.
Richmond, S. J., Keding, A., Hover, M., Gabe, R., Cross, B., Torgerson, D., & MacPherson, H. (2015). Feasibility, acceptability and validity of SMS text messaging for measuring change in depression during a randomised controlled trial. BMC Psychiatry, 15(68). Online only. https://doi.org/10.1186/s12888-015-0456-3
Schwarz, N., Strack, F., Hippler, H.-J., & Bishop, G. (1991). The impact of administration mode on response effects in survey measurement. Applied Cognitive Psychology, 5, 193–212. https://doi.org/10.1002/acp.2350050304.
Shapiro, J. R., Bauer, S., Andrews, E., Pisetsky, E., Bulik-Sullivan, B., Hamer, R. M., & Bulik, C. M. (2010). Mobile therapy: Use of text-messaging in the treatment of bulimia nervosa. International Journal of Eating Disorders, 43(6), 513–520. https://doi.org/10.1002/eat.20744.
Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological momentary assessment. Annual Review of Clinical Psychology, 4, 1–32. https://doi.org/10.1146/annurev.clinpsy.3.022806.091415.
Smith, A. (2010). Americans and their gadgets. Retrieved from http://www.pewinternet.org/2010/10/14/americans-and-their-gadgets/.
Smith, A. (2011). How Americans use text messaging. Retrieved from http://www.pewinternet.org/2011/09/19/how-americans-use-text-messaging/.
Smith, T. W., Marsden, P. V., & Hout, M. (2015). General Social Surveys, 1972-2014: Cumulative codebook. Principal Investigator, Tom W. Smith; Co-Principal Investigators, Peter V. Marsden and Michael Hout. Chicago: National Opinion Research Center. (National Data Program for the Social Sciences Series, No. 23).
Spohr, S. A., Nandy, R., Gandhiraj, D., Vemulapalli, A., Anne, S., & Walters, S. T. (2015). Efficacy of SMS text message interventions for smoking cessation: A meta-analysis. Journal of Substance Abuse Treatment, 56, 1–10. https://doi.org/10.1016/j.jsat.2015.01.011.
Stone, A. A., & Shiffman, S. (1994). Ecological momentary assessment (EMA) in behavioral medicine. Annals of Behavioral Medicine, 16(3), 199–202.
Stormshak, E. A., DeGarmo, D. D., Chronister, K. M., & Caruthers, A. (2017). The impact of family-centered prevention on self-regulation and subsequent long-term risk in emerging adults. Prevention Science. Advance online publication. https://doi.org/10.1007/s11121-017-0852-7
van Heerden, A. C., Norris, S. A., Tollman, S. M., Stein, A. D., & Richter, L. M. (2013). Field lessons from the delivery of questionnaires to young adults using mobile phones. Social Science Computer Review, 32(1), 105–112. https://doi.org/10.1177/089.
Author Contributions
L.C.: Designed the study using extant data, ran the data analyses, analyzed the data, wrote the paper. E.S.: Originally collected extant data, collaborated in designing the study and in writing and editing the final manuscript.
Funding
This research was supported by grants from NICHD (HD075150) and NIDA (DA018374). This work was also funded by a minority supplement grant from NIDA (HD3R01DA037628).
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The authors declare that they have no conflict of interest.
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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee of the University of Oregon and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.
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Informed consent was obtained from all individual participants included in the study.Conflict of interest
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Cárdenas, L.E., Stormshak, E.A. Measuring Daily Activity of Emerging Adults: Text Messaging for Assessing Risk Behavior. J Child Fam Stud 28, 315–324 (2019). https://doi.org/10.1007/s10826-018-1267-1
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DOI: https://doi.org/10.1007/s10826-018-1267-1