Abstract
Abstract. When using Short Message Service (SMS) as a tool for data collection in psychological research, participants can be contacted at any time. This study examined how sampling frequency and time of day of contact impacted on response rates, response completeness, and response delay in repeated measures data collected via SMS. Eighty-five undergraduate students completed a six-item self-report questionnaire via SMS, in response to 20 SMS prompts sent on a random schedule. One group responded across 2 days, the other on a compressed schedule of 1 day. Overall, there was a high response rate. There was no significant difference in response rate, completeness, and delay of those responding across 1 or 2 days. Timing between prompts did not impact on response behavior. Responses were more likely to be complete if prompts were sent during the working day. The shortest time between prompts was 15 min, however, and use of an undergraduate sample limits generalizability. When conducting repeated measures sampling using SMS, researchers should be aware that more frequent sampling can be associated with poorer data quality, and should aim to collect data during the working day rather than mornings or evenings.
References
(2009). Feasibility of collecting diary data from asthma patients through mobile phones and SMS (short message service): Response rate analysis and focus group evaluation from a pilot study. Journal of Medical Internet Research, 6, e42. doi: 10.2196/jmir.6.4.e42
. (2013). ACMA Communications report 2012–2013. Retrieved from http://www.acma.gov.au/theACMA/Library/Corporate-library/Corporate-publications/communications-report-2012-13
(1999). Response rate in academic studies: A comparative analysis. Human Relations, 52, 421–438. doi: 10.1177/001872679905200401
(2008). Survey response rate levels and trends in organizational research. Human Relations, 61, 1139–1160. doi: 10.1177/0018726708094863
(2011). Using SMS text messaging to assess moderators of smoking reduction: Validating a new tool for ecological measurement of health behaviors. Health Psychology, 30, 186–194. doi: 10.1037/a0022201
(2003). Diary methods: Capturing life as it is lived. Annual Review of Psychology, 54, 579–616. doi: 10.1146/annurev.psych.54.101601.145030
(2012). New data collection modes for surveys: A comparative analysis of the influence of survey mode on question-wording effects. Quality and Quantity, 47, 3135–3152. doi: 10.1007/s11135-012-9708-1
(2012). Effects of intensive mobile happiness reporting in daily life. Social Psychological and Personality Science, 3, 315–323.
(2000). A meta-analysis of response rates in Web- or Internet-based surveys. Educational and Psychological Measurement, 60, 821–836. doi: 10.1177/00131640021970934
(2006). A procedure for evaluating sensitivity to within-person change: Can mood measures in diary studies detect change reliably? Personality and Social Psychology Bulletin, 32, 917–929. doi: 10.1177/0146167206287721
(2009). Using field process data to predict best times of contact conditioning on household and interviewer influences. Retrieved from http://eprints.soton.ac.uk/66318/1/s3ri-workingpaper-M09-12.pdf
. (2014). Short messaging services versus instant messaging: Value versus volume. Retrieved from https://www2.deloitte.com/content/dam/Deloitte/au/Documents/technology-media-telecommunications/deloitte-au-tmt-short-messaging-services-versus-instant-messaging-011014.pdf
(2009). Internet, mail, and mixed-mode surveys (3rd ed.). Hoboken, NJ: Wiley.
(2014). A text message based weight management intervention for overweight adults. Journal of Human Nutrition and Dietetics, 27, 90–97. doi: 10.1111/jhn.12096
(2007). Psychological and psychophysiological ambulatory monitoring. European Journal of Psychological Assessment, 23, 214–226. doi: 10.1027/1015-5759.23.4.214
(1988). Managing attrition in clinical research. Clinical Psychology Review, 8, 499–515. doi: 10.1016/0272-7358(88)90076-1
(1988). Mail survey response rate a meta-analysis of selected techniques for inducing response. Public Opinion Quarterly, 52, 467–491. doi: 10.1086/269125
(2011). A randomised controlled trial using mobile advertising to promote safer sex and sun safety to young people. Health Education Research, 26, 782–794. doi: 10.1093/her/cyr020
(2008). The impact of nonresponse rates on nonresponse bias: A meta-analysis. Public Opinion Quarterly, 72, 167–189. doi: 10.1093/poq/nfn011
(2006). R U OK 2 TXT 4 RESEARCH? Feasibility of text message communication in primary care research. Australian Family Physician, 35, 175–176.
(2013). The feasibility of using SMS as a health survey tool: An exploratory study in patients with rheumatoid arthritis. International Journal of Medical Informatics, 82, 427–434. doi: 10.1016/j.ijmedinf.2012.12.003
(2013). Response patterns to interactive SMS health education quizzes at two sites in Uganda: A cohort study. Tropical Medicine and International Health, 18, 1–6. doi: 10.1111/tmi.12059
(1995). Modeling the drop-out mechanism in repeated-measures studies. Journal of the American Statistical Association, 90, 1112–1121. doi: 10.1080/01621459.1995.10476615
(2009). Australian Mobile Phone lifestyle index. Sydney, Australia: Australian Interactive Media Industry Association Mobile Industry Group.
(1963). Item-skipping and right and wrong solutions in a preliminary version of a multiple-choice vocabulary test. Acta Psychologica, 21, 49–54.
(2012). Safety and adherence to intermittent pre-exposure prophylaxis (PrEP) for HIV-1 in African men who have sex with men and female sex workers. PloS One, 7, e33103. doi: 10.1371/journal.pone.0033103
(1987). Recall bias: A proposal for assessment and control. International Journal of Epidemiology, 16, 167–170.
(2009). SMS: Exploiting the interactional characteristics of near-synchrony. Information, Communication & Society, 12, 1131–1148.
(2001). Effects of study duration, frequency of observation, and sample size on power in studies of group differences in polynomial change. Psychological Methods, 6, 387–401.
(2003). Assessing response rates and nonresponse bias in web and paper surveys. Research in Higher Education, 44, 409–432. Retrieved from http://link.springer.com/article/10.1023/A:1024232915870
(2008). Comparing response rates from Web and mail surveys: A meta-analysis. Field Methods, 20, 249–271. doi: 10.1177/1525822X08317085
(2010). Adolescent engagement in additional therapeutic contact for overweight management via short message service and electronic mail: The loozit study. Journal of Adolescent Health, 46, 15–16.
(2009). The use of mobile phones as a data collection tool: A report from a household survey in South Africa. BMC Medical Informatics and Decision Making, 8, 1–8. doi: 10.1186/1472-6947-9-51
(2010). Item imputation without specifying scale structure. Methodology, 6, 31–36. doi: 10.1027/1614-2241/a000004
(2014). As you Likert: Cross-mode equivalence of administering lengthy self-report instruments via text message. Paper presented at the ACSPRI Social Science Methodology Conference, Sydney, Australia.
(1991). Self-recording of everyday life events: Origins, types, and uses. Journal of personality, 59, 339–354. doi: 10.1111/j.1467-6494.1991.tb00252.x/full
(1993). Errors in measuring vote choice in the National Election Studies, 1952–88. American Journal of Political Science, 37, 291–316. doi: 10.3886/ICPSR08475.v14
(1983). A quantitative review of research design effects on response rates to questionnaires. Journal of Marketing Research, 1, 36–44.
(1988). Models for longitudinal data: a generalized estimating equation approach. Biometrics, 1049–1060.
