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Chesney, T. (2006). The effect of communication medium on research participation decisions. Journal of Computer-Mediated Communication, 11(3), article 10. http://jcmc.indiana.edu/vol11/issue3/chesney.html
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Students are often used in research as research subjects or to validate/pilot questionnaires. It is known that response rates to requests to participate in research projects vary as a function of a number of factors. This research brief examines the effect of the communication medium on response rate by comparing an oral request for participation with an email request. Email and oral communication, specifically public oral communication, are the two easiest and presumably most common approaches faculty members have to access students to request their participation in research. Results show that an impersonal email to a mailing list is the worst way researchers can approach students to request participation, with there being no difference between making the request by personalized email or orally.
Students are often used in research as research subjects or to validate/pilot questionnaires. It is known that response rates to requests to participate in research projects vary as a function of a number of factors such as: a letter sent to forewarn that the request is to be made (Brunner & Carroll, 1969), incentives such as money (Singer, Van Hoewyk, Gebler, Raghunathan, & McGonagle, 1999), the questionnaire length, design and the number of difficult questions (Dillman, Sinclair, & Clark, 1993), how interesting the topic is to the respondent (Groves, Singer, & Corning, 2000), and the use of follow up methods (Roscoe, Lang, & Sheth, 1975). Persuasiveness has been found to be dependent on a large number of factors including the vividness of the message (Frey & Eagly, 1993), the attractiveness of the speaker (DeBono & Harnish, 1988) and the mood of the recipient (Raghunathan & Trope, 2002).
It is difficult to predict whether an email communication will have a better or worse response than an oral one. Previous research into response rates has provided mixed and unexpected results. For instance, Yammarino, Skinner, and Childers (1991), in a meta-analysis of 115 studies, found preliminary notification and follow-ups, inclusion of a return envelope with postage, and monetary incentives, were effective in increasing mail survey response rates. However Tuten, Bosnjak, and Bandilla (2000) found that response rate was lower when respondents had a chance to win a prize than when it was pointed out that they were being given the chance to contribute to science. Conventional wisdom says that in surveys, personal questions should be asked last (see for instance: http://www.deakin.edu.au/buslaw/bowater/research/pdf/questionnaire_design.pdf), but Frick, Bächtinger, and Reips (1999) found that when they were asked first in web-based surveys, fewer drop-outs occurred.
H1: There will be a difference in the responses received when a request for participation is made orally and when it is made by email. If this is correct, it will be of interest to examine the email and oral conditions more closely. Latane's (1981) theory also states that the source's request will be diminished according to the size of the target audience. It might be expected, therefore, that a personal email to each individual in the group will have a higher response rate than one email sent to a mailing list: H2: Emails sent to individuals will get a higher response than emails sent to a group. Experiments on conformity such as that conducted by Asch (1955) show that the responses of others in a group have an impact on the response of an individual. It is possible that in a lecture/tutorial, the more people who agree to participate, the more likely an individual will be to participate: H3: Responses to an oral request will be greater when potential respondents perceive that a large number of their peers have already agreed to take part.
282 final year business school undergraduate students taking a strategic management module were used as the sample. The author was not a tutor on this module and did not teach this group of students on any other module. Each student was requested to participate in a research project. The dependent variable was their response, yes or no. For the purposes of teaching, the class was split into 18 tutorial groups. All the students in each tutorial group were randomly assigned to one of four conditions. Those assigned to Condition 1 were sent an individual, personal email with the request shown below. The email began with 'Dear' followed by the student's name. Those in Condition 2 were put into a mailing list which was used to send one, impersonal email with the same request. This email started 'Dear all'. Students in Conditions 1 and 2 were asked to indicate their agreement to participate by emailing back and saying so.
The results are analyzed using a chi-squared test for independence with phi used as a measure of association. The results of testing H1 are shown in Tables 1 and 2. Table 1 is the cross tabs of comparing the oral request with the email request. The results reveal a significant difference between the two media, with the oral request out-performing the email request. However, the email to group condition achieved a very low response rate (less than 1%) and this alone may be contributing to the significance of the relationship. To test this, the analysis was repeated comparing the oral request with just the email to individuals request. The results are shown in Table 2. This time, no significant difference was found.
Table 1. Comparing oral and email request
χ2 = 4.04, df = 1, p = .044**, ψ = .120 n = 282, **significant at .01
Table 2. Comparing oral and email to individuals request
χ2 = 1.81, df = 1, p = .67, ψ = -.30, n = 198
The results of testing H2 are shown in Table 3. The email condition is examined to determine the impact of emails sent to individuals versus one sent to a group. The results show emails to individuals are much more successful at eliciting a positive response than an email to a group.
Table 3. Examining email conditions
χ2 = 20.632, df = 1, p = .000**, ψ = .349 n = 282, ** significant at .01
Table 4. Examining oral conditions
χ2 = 3.506, df = 1, p = .061, ψ = .176 n = 282 Support was found for H1 and H2 but not H3. There is a significant difference between the email and oral request, but only because of the poor performance of the email to the group. Emails to individuals are significantly better at eliciting a positive response than one email to a group. There is no statistically significant difference between oral requests when potential respondents perceive a large number of people have already agreed to take part and when they do not. However, as seen in Table 4, the number of yes responses for the full name sheet were much higher than expected and the percentage of yes responses for the full name sheet is nearly twice that for the blank name sheet. Therefore, research to examine this result further would be useful. Overall, the findings show that to achieve the highest response, researchers should avoid asking students to participate in research by sending one impersonal email to the entire group. There is no difference in response if the request is made by personalized email, or orally in tutorials, so this choice may be made based on convenience. Asch, S. E. (1955). Opinions and social pressure. Scientific American, 193 (5), 31-35. Brunner, G. A., & Carroll, S. J. (1969). The effect of prior notification on the refusal rate in fixed address surveys. Journal of Advertising Research, 9 (1), 42-44. Chaikin, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of Personality and Social Psychology, 39, 752-766. DeBono, K. G., & Harnish, R. J. (1988). Source expertise, source attractiveness, and the processing of persuasive information: a functional approach. Journal of Personality & Social Psychology, 55 (4), 541-546. Dillman, D. A., Sinclair, M. D., & Clark, J. R. (1993). Effects of questionnaire length, respondent-friendly design and a difficult question on response rates for occupant-addressed census mail surveys. Public Opinion Quarterly, 57 (3), 289-304. Frey, K. P., & Eagly, A. H. (1993). Vividness can undermine the persuasiveness of messages. Journal of Personality and Social Psychology, 65 (1), 32-44. Frick, A., Bächtinger, M. T., & Reips, U. D. (1999). Financial incentives, personal information and drop-out rate in online studies. In U. D. Reips, B. Batinic, W. Bandilla, M. Bosnjak, L. Gräf, K. Moser, & A.Werner, (Eds.), Current Internet Science - Trends, Techniques, Results. [Aktuelle Online-Forschung - Trends, Techniken, Ergebnisse.] Zürich: Online Press. Retrieved April 10, 2006 from http://dgof.de/tband99/ Groves, R. M., Singer, E., & Corning, A. (2000). Leverage-Saliency theory of survey participation. Public Opinion Quarterly, 64 (3), 299-308. Lana, R. E. (1963). Interest, media, and order effects in persuasive communications. Journal of Psychology, 56 (1), 9-13. Latane, B. (1981). The psychology of social impact. American Psychologist, 36 (4), 343-356. McGinnies, A. (1965). A cross-cultural comparison of printed communication versus spoken communication is persuasion. Journal of Psychology, 60 (1), 1-8. Moon, Y. (1999). The effects of physical distance and response latency on persuasion in computer-mediated communication and human-computer communication. Journal of Experimental Psychology: Applied, 5 (4), 379-392. Pallak, S. R. (1983). Salience of a communicator's physical attractiveness and persuasion: A heuristic versus systematic processing interpretation. Social Cognition, 2 (2), 158-170. Petty, R. E., & Cacioppo, J. T. (1981). Attitudes and Persuasion: Classic and Contemporary Approaches. Dubuque, IA: William C. Brown. Raghunathan, R., & Trope, Y. (2002). Walking the tightrope between feeling good and being accurate: Mood as a resource in processing persuasive messages. Journal of Personality & Social Psychology, 83 (3), 510-525. Roscoe, A. M., Lang, D., & Sheth, J. N. (1975). Follow-up methods, questionnaire length, and market differences in mail surveys. Journal of Marketing, 39 (2), 20-27. Rosnow, R. L., & Robinson, E. J. (Eds.). (1967). Experiments in Persuasion. New York: Academic Press. Singer, E., Van Hoewyk, J., Gebler, N., Raghunathan, T., & McGonagle, K. (1999). The effect of incentives on response rates in interviewer-mediated surveys. Journal of Official Statistics, 15 (2), 217-230. Tuten, T. L., Bosnjak, M., & Bandilla, W. (2000). Banner-advertised web-surveys. Marketing Research, 11 (4), 17-21. Yammarino, F. J., Skinner, S. J., & Childers, T. L. (1991). Understanding mail survey response behaviour: a meta-analysis. Public Opinion Quarterly, 55 (4), 613-639.
is a lecturer in information systems at Nottingham University Business School. He holds a PhD in information systems from Brunel University, an MSc in informatics from Edinburgh University, and a BSc in information management from the Queen's University of Belfast. His research interests are adoption of recreational information systems, use of blogs to share knowledge, and determinants of research participation decisions. For more information, see: http://www.nottingham.ac.uk/~liztc/Personal/index.html
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