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Contributing or receiving-the role of social interaction styles in persuasion over a social networking platform

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Abstract

In this paper, the use of the social network platform Twitter is explored in relation to behavior change (BC) for health. We studied the effect of participation style (tweeters vs. non-tweeters) on perceived health behavior change through the constructs “social influence,” “efficacy,” and “pre-test health behavior.” In the experiment (N = 30), participants were given a basic health message, and the tweeters were then asked to actively search, think up, and share tips and guidance with non-tweeters. Results indicate that for both tweeters and non-tweeters, efficacy and social influence were positively related, but that efficacy and perceived health behavior change are only positively related for non-tweeters. From this, we concluded that participation style can impact the effect of efficacy on target behavior. To understand the information processing in the two groups in terms of higher or lower need for cognition, we also studied the participants’ thought elaboration. We found that tweeters were more distracted from elaboration on the health message, in particular those tweeters presenting a higher need for cognition. From this, we concluded that taking an active content creating role in peer-to-peer e-coaching systems may lead (a) to higher efficacy appraisal without a positive impact on BC and (b) to reduced attention on the intended behavior change message. In other words, the position of producing content may not translate into better intake of that content. In conclusion, there is a need for investigating strategies for overcoming the distracting nature of an active sharing role in e-coaching systems presented by a social network platform.

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References

  1. Al-Husain D and Hammo B (2012) The role of mobile technology and social media in mobile learning: a literature review. In Proceedings of The 11th International Conference on eLearning, e-Business, Enterprise Information Systems, and e-Government, EEE'12, Las Vegas Nevada, USA. 204–211

  2. Bandura A (1976) Social learning theory. Prentice Hall, Englewood Cliffs, NJ

    Google Scholar 

  3. Bandura A (1986) Social foundations of thought and action: a social cognitive theory. Prentice-Hall, Englewood Cliffs, NJ

    Google Scholar 

  4. Bandura A (1997) Self-efficacy: the exercise of control. W. H. Freeman, New York

    Google Scholar 

  5. Bandura A (2001) Social cognitive theory of mass communication. Media Psychology 3(3):265–299

    Article  Google Scholar 

  6. Boudreau M, Gefen D, Straub DW (2001) Validation in information systems research: a state-of-the-art assessment. MIS Q 25(1):1–16

    Article  Google Scholar 

  7. Bush V (1967) “Memex revisited” reprinted in WHK Chun and T Keenan (eds) New Media, Old Media: A History and Theory Reader. New York and London: Routledge, Taylor & Francis Group, 2006

  8. Business Insider (2012) http://www.businessinsider.com/these-brands-are-doing-amazing-things-with-instagram-2012-6?r=US&IR=T&IR=T. Accessed 24 November 2016

  9. Cacioppo JT, Petty RE (1981) Social psychological procedures for cognitive response assessment: the thought-listing techniques. In: Merluzzi TV, Glass CR, Genest M (eds) Cognitive assessment. New York University Press, New York, pp 309–342

    Google Scholar 

  10. Cacioppo JT, von Hippel W, Ernst JM (1997) Mapping cognitive structures and processes through verbal content: the thought-listing technique. J Consult Clin Psychol 65(6):928–940

    Article  Google Scholar 

  11. Cacioppo JT, Petty RE, Kao CF (1984) The efficient assessment of need for cognition. J Pers Assess 48(3):306–307. doi:10.1207/s15327752jpa4803_13

    Article  Google Scholar 

  12. Cohen J (1988) Statistical power analysis for the behavioral sciences. Lawrence Erlbaum, Mahwah, NJ

    MATH  Google Scholar 

  13. Cox DN, Anderson AS, Reynolds J, McKellar S, Lean MEJ, Mela DJ (1998) Take five, a nutrition education intervention to increase fruit and vegetable intakes: impact on consumer choice and nutrient intakes. Br J Nutr 80(2):123–131

    Article  Google Scholar 

  14. Epton T, Harris PR (2008) Self-affirmation promotes health behaviour change. Health Psychol 74:746–752

    Article  Google Scholar 

  15. European Commission (2015) Mobile learning and social media in adult learning. Literature review prepared for the ET Working Group on Adult Learning. Europe 2020: Employment policies. Vocational training and adult Education. http://ec.europa.eu/education/policy/strategic-framework/expert-groups/documents/mobile-learning-social-media_en.pdf. Accessed May 20, 2016

  16. Festinger LA (1957) Theory of cognitive dissonance. Stanford University Press, Stanford

    Google Scholar 

  17. Festinger L, Carlsmith JM (1959) Cognitive consequences of forced compliance. J Abnorm Soc Psychol 58:203–211

    Article  Google Scholar 

  18. Fielden A, Sillance L, Little L, and Harris PR (2016). Online self-affirmation increases fruit and vegetable consumption in groups at high risk of low intake. Applied Psychology: Health and well-being, 2016

  19. Floyd DL, Prentice-Dunn S, Rogers RW (2000) A meta-analysis of research on protection motivation theory. J Appl Soc Psychol 30:407–429

    Article  Google Scholar 

  20. Fogg BJ (2003) Persuasive technology: using computers to change what we think and do. Morgan Kaufmann, San Francisco

    Google Scholar 

  21. Fornell C, Larker D (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 1(18):39–50

    Article  Google Scholar 

  22. Fuchs R, Leppin A, Schwarzer R, Wegner RW (1993) Self-efficacy toward healthy eating behavior. In: Schwarzer R (ed) Measurement of perceived self-efficacy: psychometric scales for cross-cultural research. Freie Universität Berlin, Berlin

    Google Scholar 

  23. Gabriele JM, Carpenter BD, Tate DF, Fisher EB (2011) Directive and nondirective e-coach support for weight loss in overweight adults. Ann Behav Med 41:252–263

    Article  Google Scholar 

  24. Gefen D, Ringdon EE, Straub DW (2011) Editor’s comment: an update and extension to SEM guidelines for administrative and social science research. MIS Q 35(2):3–14

    Google Scholar 

  25. Hair JF, Hult GTM, Ringle CM, Sarstedt M (2014) A primer on partial least squares structural equation modeling (PLS-SEM). SAGE Publications, Los Angeles

    MATH  Google Scholar 

  26. Hair JF, Ringle CM, Sarstedt M (2011) PLS-SEM: indeed a silver bullet. The Journal of Marketing Theory and Practice 19(2):139–152

    Article  Google Scholar 

  27. Heppner PP, Wampold BE, Kivlighan DM Jr (2007) Research design in counseling, 3rd edn. Belmont, Thomson Books/Cole

    Google Scholar 

  28. Kang H, and Sundar SS (2016) When self is the source: effects of media customization on message processing. Media Psychology:1–28

  29. Katona Z (2012) How to identify influence leaders on social medeia. Bloomberg View. https://www.bloomberg.com/view/articles/2012-02-27/how-to-identify-influence-leaders-in-social-media-zsolt-katona. Accessed 24 November 2016

  30. Mak V (2008) The emergence of opinion leaders in social networks. http://ssrn.com/abstract=1157285 Accessed 4 May 2016

  31. Markus H (1977) The effect of mere presence on social facilitation: an unobtrusive test. J Exp Soc Psychol 14:389–397

    Article  Google Scholar 

  32. Mullen M, Shami NS, Millen DR, and Feinberg J (2010) We are all Lurkers: consuming behaviors among authors and readers in an enterprise file-sharing service. Proceedings of the 16th ACM international conference on Supporting group work (GROUP’10), 7–10 November 2010, Sanibel Island, Florida, USA: ACM), 201–210

  33. Naismith L, Lonsdale P, Vavoula G, and Sharples M (2004) Literature review in mobile technologies and learning. Futurelab series, Report 11. ISBN: 0–9548594–1-3. https://lra.le.ac.uk/bitstream/2381/8132/4/%5B08%5DMobile_Review%5B1%5D.pdf Accessed 20 May 2016

  34. Nonnecke B, and Preece J (2000) Lurker demographics: counting the silent. Proceedings of CHI 2000. The Hague, The Netherlands (New York: Addison-Wesley/ACM Press), 73–80

  35. Nunally JC, Bernstein I (1994) Psychometric theory. McGraw-Hill, New York

    Google Scholar 

  36. Oduor M and Oinas-Kukkonen H (2015) A system’s self-referential persuasion: understanding the role of persuasive user experiences in committing social Web users. 10th International Conference, PERSUASIVE 2015, Chicago, June 3–5, 2015

  37. Oinas-Kukkonen H (2013) A foundation for the study of behavior change support systems. Pers Ubiquit Comput 17(6):1223–1235

    Article  Google Scholar 

  38. Oinas-Kukkonen H & Harjumaa M (2009) Persuasive systems design : key issues, process model, and system features. Communications of the Association for Information Systems, 24.

  39. Oinas-Kukkonen H, Oinas-Kukkonen H (2013) Humanizing the web: change and social innovation. Palgrave Macmillan, Basingstoke

    Book  MATH  Google Scholar 

  40. Pechman C, Delucchi K, Lakon CM, and Prochaska, JJ (2016) Randomised controlled trial evaluation of Tweet2Quit: a social network quit-smoking intervention. Tobacco Control, 2016: http://tobaccocontrol.bmj.com/content/early/2016/02/29/tobaccocontrol-2015-052768.full Accessed 17 April, 2016

  41. Petty RE, Barden J, and Wheeler CS (2002) The elaboration likelihood model of persuasion: health promotions that yield sustained behavioural change. Emerging theories in health promotion practice and research, pp. 71–99- Jossey-Bass

  42. Petty RE, Briñol P, Tormala ZL (2002) Thought confidence as a determinant of persuasion: the self-validation hypothesis. J Pers Soc Psychol 5(82):722–741

    Article  Google Scholar 

  43. Petty RE and Cacioppo JT (1986) The elaboration likelihood model of persuasion. Advances in Experimental Social Psychology, Vol 19

  44. Ravitsemusneuvottelukunta (National Nutrition Council) n.d. http://www.ravitsemusneuvottelukunta.fi/portal/fi/ravitsemussuositukset/suomalaiset+ravitsemussuositukset/ Accessed 15 April 2016

  45. Ringle CM, Wende S, Becker J-M (2015) SmartPLS 3. SmartPLS GmbH, Boenningstedt http://www.smartpls.com

    Google Scholar 

  46. Rogers RW (1975) A protection motivation theory of fear appraisals and attitude change. J Psychol 19:93–114

    Article  Google Scholar 

  47. Rogers RW (1983) Cognitive and physiological processes in fear appeals and attitude change: a revised theory of protection motivation. In: Cacioppo JT, Petty RE (eds) Social psychophysiology: a sourcebook. The Guildford Press, New York, pp 153–176

    Google Scholar 

  48. Rosset A and Marino G (2005) If coaching is good, then e-coaching is… T+D, Vol. 59 Issue 11, pp. 46–49

  49. Statista.com (2016) Twitter: number of monthly active users 2010–2016 http://www.statista.com/statistics/282087/number-of-monthly-active-twitter-users/ Accessed 1 May, 2016

  50. Stibe A, Oinas-Kukkonen H, and Lehto T (2013) Exploring social influence on customer engagement: a pilot study on the effects of social learning, social comparison, and normative influence. 2013 46th Hawaii International Conference on System Sciences

  51. Stibe A and Oinas-Kukkonen H (2014) Using social influence for motivating customers to generate and share feedback. In: A Spagnolli et al. (Eds.): PERSUASIVE 2014, LNCS 8462, pp. 224–235, 2014. Springer International Publishing Switzerland

  52. Zajonc RB (1965) Social Facilitation. Science 149:269–274

    Article  Google Scholar 

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Authors and Affiliations

  1. Oulu Advanced Research on Service and Information Systems, University of Oulu, P.O. Box 3000, 90014, Oulu, Finland

    Piiastiina Tikka & Harri Oinas-Kukkonen

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  1. Piiastiina Tikka
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  2. Harri Oinas-Kukkonen
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Correspondence to Piiastiina Tikka.

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Table 12 The questionnaire items and their loadings
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Tikka, P., Oinas-Kukkonen, H. Contributing or receiving-the role of social interaction styles in persuasion over a social networking platform. Pers Ubiquit Comput 21, 705–721 (2017). https://doi.org/10.1007/s00779-017-1027-z

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