Social processes of participatory engagement effects: a longitudinal examination with a sample of young women in the United States

References

• Abar, B. W., Turrisi, R., Hillhouse, J., Loken, E., Stapleton, J., & Gunn, H. (2010). Preventing skin cancer in college females: Heterogeneous effects over time. Health Psychology, 29(6), 574–582. https://doi.org/10.1037/a0021236
   PubMed Web of Science ®Google Scholar
• Aufderheide, P. (1993). Media literacy: A report of the national leadership conference on media literacy. Aspen Institute.
   Google Scholar
• Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.
   Google Scholar
• Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman.
   Google Scholar
• Bandura, A. (2000). Exercise of human agency through collective efficacy. Current Directions in Psychological Science, 9(3), 75–78. https://doi.org/10.1111/1467-8721.00064
   Web of Science ®Google Scholar
• Boudet, H. S., & Bell, S. E. (2015). Social movements and risk communication. In H. Cho, T. Reimer, & K. McComas (Eds.), The Sage handbook of risk communication (pp. 304–316). Sage.
   Google Scholar
• Boulianne, S. (2015). Social media use and participation: A meta-analysis of current research. Information, Communication, and Society, 18(5), 524-538. https://doi.org/10.1080/1369118X.2015.1008542
   Web of Science ®Google Scholar
• Chakravartty, P., Kuo, R., Grubbs, V., & McIlwain, C. (2018). #Communicationsowhite. Journal of Communication, 68(2), 254–266. https://doi.org/10.1093/joc/jqy003
   Web of Science ®Google Scholar
• Chen, Y. C. (2013). The effectiveness of different approaches to media literacy in modifying adolescents’ responses to alcohol. Journal of Health Communication, 18(6), 723–739. https://doi.org/10.1080/10810730.2012.757387
   PubMed Web of Science ®Google Scholar
• Chen, Z., Koh, P. W., Ritter, P. L., Lorig, K., Bantum, E. O., & Saria, S. (2015). Dissecting an online intervention for cancer survivors: Four exploratory analyses of internet engagement and its effects on health status and health behaviors. Health Education and Behavior, 42(1), 32–45. https://doi.org/10.1177/1090198114550822
   PubMed Web of Science ®Google Scholar
• Cho, H., Cannon, J., Lopez, R., & Li, W. (2022). Social media literacy: A conceptual framework. New Media & Society, 146144482110685.https://doi.org/10.1177/14614448211068530
   Web of Science ®Google Scholar
• Cho, H., & Kuang, K. (2015). The societal risk reduction motivation model. In H. Cho, T. O. Reimer, & K. A. McComas (Eds.), The SAGE handbook of risk communication (pp. 117–131). Sage.
   Google Scholar
• Cho, H., Oehlkers, P., Mandelbaum, J., Edlund, K., & Zurek, M. (2004). The Healthy Talk Campaign of Massachusetts: A communication-centered approach. Health Education, 104(5), 314–325. https://doi.org/10.1108/09654280410560569
   Google Scholar
• Cho, H., So, J., & Lee, J. (2009). Personal, social, and cultural correlates of self-efficacy beliefs among South Korean college smokers. Health Communication, 24(4), 337–345. https://doi.org/10.1080/10410230902889381
   PubMed Web of Science ®Google Scholar
• Cho, H., Song, C., & Adams, D. (2020). Efficacy and mediators of a web-based media literacy intervention for indoor tanning prevention. Journal of Health Communication, 25(2), 105–114. https://doi.org/10.1080/10810730.2020.1712500
   PubMed Web of Science ®Google Scholar
• Cho, H., Yu, B., Cannon, J., & Zhu, Y. (2018). Efficacy of a media literacy intervention for indoor tanning prevention. Journal of Health Communication, 23(7), 643–651. https://doi.org/10.1080/10810730.2018.1500659
   PubMed Web of Science ®Google Scholar
• Cho, J., Ahmed, S., Keum, H., Choi, Y. J., & Lee, J. H. (2018). Influencing myself: Self-reinforcement through online political expression. Communication Research, 45(1), 83–111. https://doi.org/10.1177/0093650216644020
   Web of Science ®Google Scholar
• Couper, M. P., Alexander, G. L., Zhang, N., Little, R. J. A., Maddy, N., Nowak, M. A., McClure, J. B., Calvi, J. J., Rolnick, S. R., Stopponi, M. A., & Johnson, C. D. (2010). Engagement and retention: Measuring breadth and depth of participant use of an online intervention. Journal of Medical Internet Research, 12(4), e52. https://doi.org/10.2196/jmir.1430
   PubMed Web of Science ®Google Scholar
• Donkin, L., Christensen, H., Naismith, S. L., Neal, B., Hickie, I. B., & Glozier, N. (2011). A systematic review of the impact of adherence on the effectiveness of e-therapies. Journal of Medical Internet Research, 13(3), e52. https://doi.org/10.2196/jmir.1772
   PubMed Web of Science ®Google Scholar
• Elms, A. C. (1966). Influence of fantasy ability on attitude change through role playing. Journal of Personality and Social Psychology, 4(1), 36–43. https://doi.org/10.1037/h0023509
   PubMed Web of Science ®Google Scholar
• Eveland, W. P. (2004). The effect of political discussion in producing informed citizens: The roles of information, motivation, and elaboration. Political Communication, 21(2), 177–193. https://doi.org/10.1080/10584600490443877
   Web of Science ®Google Scholar
• Eveland, W. P., & Thomson, T. (2006). Is it talking, thinking, or both? A lagged dependent model of discussion effects on political knowledge. Journal of Communication, 56(3), 523–542. https://doi.org/10.1111/j.1460-2466.2006.00299.x
   Web of Science ®Google Scholar
• Fernández-Ballesteros, R., Díez-Nicolás, J., Caprara, G. V., Barbaranelli, C., & Bandura, A. (2002). Structural relation of perceived personal efficacy to perceived collective efficacy. Applied Psychology: An International Review, 51(1), 107–125. https://doi.org/10.1111/1464-0597.00081
   Web of Science ®Google Scholar
• Filho, E., Tenenbaum, G., & Yang, Y. (2015). Cohesion, team mental models, and collective efficacy: Towards an integrated framework of team dynamics in sport. Journal of Sports Science, 33(6), 641–653. https://doi.org/10.1080/02640414.2014.957714
   PubMed Web of Science ®Google Scholar
• Gil de Zúñiga, H., Molyneux, L., & Zheng, P. (2014). Social media, political expression, and political participation: Panel analysis of lagged and concurrent relationships. Journal of Communication, 64(4), 612–634. https://doi.org/10.1111/jcom.12103
   Web of Science ®Google Scholar
• Greene, J. O. (1984). A cognitive approach to human communication: An action assembly theory. Communication Monographs, 51(4), 289–306. https://doi.org/10.1080/03637758409390203
   Web of Science ®Google Scholar
• Greenwald, A. G., & Albert, R. D. (1968). Acceptance and recall of improvised arguments. Journal of Personality and Social Psychology, 8(1), 31–34. https://doi.org/10.1037/h0021237
   PubMedGoogle Scholar
• Hales, S. B., Davidson, C., & Turner-McGrievy, G. M. (2014). Varying social media post types differentially impacts engagement in a behavioral weight loss intervention. Translational Behavioral Medicine, 4(4), 355–362. https://doi.org/10.1007/s13142-014-0274-z
   PubMed Web of Science ®Google Scholar
• Han, J. Y., Shah, D. V., Kim, E., Namkoong, K., Lee, S.-Y. Y., Moon, T. J., Cleland, R., Bu, Q. L., McTavish, F. M., & Gustafson, D. H. (2011). Empathic exchanges in online cancer support groups: Distinguishing message expression and reception effects. Health Communication, 26(2), 185–197. https://doi.org/10.1080/10410236.2010.544283
   PubMed Web of Science ®Google Scholar
• Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford.
   Google Scholar
• Higgins, E. T., Douglas, M. C., & Fondacaro, R. (1982). The “communication game”: Goal-directed encoding and cognitive consequences. Social Cognition, 1(1), 21–37. https://doi.org/10.1521/soco.1982.1.1.21
   Google Scholar
• Hillhouse, J., Turrisi, R., Stapleton, J., & Robinson, J. A. (2008). A randomized controlled trial of an appearance focused intervention to prevent skin cancer. Cancer, 113(11), 3257–3266. https://doi.org/10.1002/cncr.23922
   PubMed Web of Science ®Google Scholar
• Janis, I. L., & King, B. T. (1954). The influence of role-playing on opinion change. Journal of Abnormal and Social Psychology, 49(2), 211–218. https://doi.org/10.1037/h0056957
   PubMed Web of Science ®Google Scholar
• Jeong, M., & Bae, R. E. (2018). The effect of campaign-generated interpersonal communication on campaign-targeted health outcomes: A meta-analysis. Health Communication, 33(8), 988–1003. https://doi.org/10.1080/10410236.2017.1331184
   PubMed Web of Science ®Google Scholar
• Kharroub, T., & Bas, O. (2016). Social media and protests: An examination of Twitter images of the 2011 Egyptian Revolution. New Media & Society, 18(9), 1973–1992. https://doi.org/10.1177/1461444815571914
   Web of Science ®Google Scholar
• Livingstone, S. (2004). Media literacy and the challenge of new information and communication technologies. Communication Review, 7(1), 3–14. https://doi.org/10.1080/10714420490280152
   Google Scholar
• Maio, G. R., & Thomas, G. (2007). The epistemic-teleological model of deliberate self-persuasion. Personality & Social Psychology Review, 11(1), 46–67. https://doi.org/10.1177/1088868306294589
   PubMed Web of Science ®Google Scholar
• McLeod, D. M., Kosicki, G. M., & McLeod, J. M. (2009). Political communication effects. In J. Bryant & M. B. Oliver (Eds.), Media effects: Advances in theory and research (pp. 228–251). Routledge.
   Google Scholar
• Mundt, M., Ross, K., & Burnett, C. M. (2018). Scaling social movements through social media: The case of Black Lives Matter. Social Media + Society, 4(4), 1–14. https://doi.org/10.1177/2056305118807911
   Web of Science ®Google Scholar
• Petty, R., & Cacioppo, J. (1986). The elaboration likelihood model of persuasion. Springer.
   Google Scholar
• Pingree, R. J. (2007). How messages affect their senders: A more general model of message effects and implications for deliberation. Communication Theory, 17(4), 439–461. https://doi.org/10.1111/j.1468-2885.2007.00306.x
   Web of Science ®Google Scholar
• Rojas, H., & Puig-i-Abril, E. (2009). Mobilizers mobilized: Information, expression, mobilization and participation in the digital age. Journal of Computer Mediated Communication, 14(4), 902–927. https://doi.org/10.1111/j.1083-6101.2009.01475.x
   Web of Science ®Google Scholar
• Shefner-Rogers, C. L., Rao, N., Rogers, E. M., & Wayangankar, A. (1998). The empowerment of women dairy farmers in India. Journal of Applied Communication Research, 26(3), 319–337. https://doi.org/10.1080/00909889809365510
   Web of Science ®Google Scholar
• Siegel, R. L., Miller, K. D., & Jemal, A. (2020). Cancer statistics, 2020. CA Cancer Journal for Clinicians, 70(1), 7–30. https://doi.org/10.3322/caac.21590
   PubMed Web of Science ®Google Scholar
• Skoric, M. M., Zhu, Q., Goh, D., & Pang, N. L. S. (2016). Social media and citizen engagement: A meta-analytic review. New Media & Society, 18(9), 1817–1839. https://doi.org/10.1177/1461444815616221
   Web of Science ®Google Scholar
• So, J., Kuang, K., & Cho, H. (2019). Information seeking upon exposure to risk messages: Predictors, outcomes, and mediating roles of health information seeking. Communication Research, 46(5), 663–687. https://doi.org/10.1177/0093650216679536
   Web of Science ®Google Scholar
• Stapleton, J. L., Hillhouse, J., Coups, E. J., & Pagoto, S. (2016). Social media use and indoor tanning among a national sample of young adult non-Hispanic white women: A cross-sectional study. Journal of American Academy of Dermatology, 75(1), 218–220. https://doi.org/10.1016/j.jaad.2016.01.043
   PubMed Web of Science ®Google Scholar
• Thorson, E. (2014). Beyond opinion leaders: How attempts to persuade foster political awareness and campaign learning. Communication Research, 41(3), 353–374. https://doi.org/10.1177/0093650212443824
   Web of Science ®Google Scholar
• Tufekci, Z., & Wilson, C. (2012). Social media and the decision to participate in political protest: Observations from Tahrir square. Journal of Communication, 62(2), 363–379. https://doi.org/10.1111/j.1460-2466.2012.01629.x
   Web of Science ®Google Scholar
• U.S. Centers for Disease Control & Prevention. (2012). Use of indoor tanning devices by adults — United States, 2010. MMWR, 61(18), 323–326.
   Google Scholar
• Vaccari, C., Valeriani, A., Barbera, P., Bonneau, R., Jost, J. T., Nagler, J., & Tucker, J. A. (2015). Political expression and action on social media: Exploring the relationship between lower- and higher-threshold political activities among Twitter users in Italy. Journal of Computer-Mediated Communication, 20(2), 221–239. https://doi.org/10.1111/jcc4.12108
   Web of Science ®Google Scholar
• Velasquez, A., & LaRose, R. (2015). Youth collective activism through social media: The role of collective efficacy. New Media & Society, 17(6), 899–918. https://doi.org/10.1177/1461444813518391
   Web of Science ®Google Scholar
• Wang, S. L., & Lin, S. S. J. (2007). The effects of group composition of self-efficacy and collective efficacy on computer-supported collaborative learning. Computers in Human Behavior, 23(5), 2256–2268. https://doi.org/10.1016/j.chb.2006.03.005
   Web of Science ®Google Scholar
• Watts, W. A. (1967). Relative persistence of opinion change induced by active compared to passive participation. Journal of Personality and Social Psychology, 5(1), 4–15. https://doi.org/10.1037/h0021196
   PubMed Web of Science ®Google Scholar
• Yoon, I. (2011). A case study of low collective efficacy and lack of collective community action. Journal of Human Behavior in the Social Environment, 21(6), 625–643. https://doi.org/10.1080/10911359.2011.583496
   Google Scholar