Understand the Impact of Technology Feature in Online Health Communities: Why the Representation of Information Matters

References

• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
   Web of Science ®Google Scholar
• Althauser, K. (2015). Job-embedded professional development: Its impact on teacher self-efficacy and student performance. Teacher Development, 19(2), 210–225. https://doi.org/10.1080/13664530.2015.1011346
   Web of Science ®Google Scholar
• Alyousef, B., Carayon, P., Hoonakker, P., Hundt, A. S., Salek, D., & Tomcavage, J. (2017). Obstacles experienced by care managers in managing information for the care of chronically ill patients. International Journal of Human-Computer Interaction, 33(4), 313–321. https://doi.org/10.1080/10447318.2016.1270017
   PubMed Web of Science ®Google Scholar
• Anderson, E. S., Wagstaff, D. A., Heckman, T. G., Winett, R. A., Roffman, R. A., Solomon, L. J., Cargill, V., Kelly, J. A., & Sikkema, K. J. (2006). Information-motivation-behavioral skills (IMB) model: Testing direct and mediated treatment effects on condom use among women in low-income housing. Annals of Behavioral Medicine, 31(1), 70–79. https://doi.org/10.1207/s15324796abm3101_11
   PubMed Web of Science ®Google Scholar
• Azemi, N. A., Zaidi, H., & Hussin, N. (2017). Information quality in organization for better decision-making. International Journal of Academic Research in Business and Social Sciences, 7(12), 429–437. https://doi.org/10.6007/IJARBSS/v7-i12/3624
   Google Scholar
• Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191
   PubMed Web of Science ®Google Scholar
• Bandura, A. (1986). Social foundations of thought and action.
   Google Scholar
• Bandura, A. (2006). Guide for constructing self-efficacy scales. In F. Pajares & T. Urdan (Eds.), Adolescence and education: Self-efficacy and adolescence (pp. 307–337). Information Age.
   Google Scholar
• Bao, Y., Hoque, R., & Wang, S. (2017). Investigating the determinants of Chinese adult children’s intention to use online health information for their aged parents. International Journal of Medical Informatics, 102(1), 12–20. https://doi.org/10.1016/j.ijmedinf.2017.01.003
   PubMedGoogle Scholar
• Bardhan, I., Chen, H., & Karahanna, E. (2020). Connecting systems, data, and people: a multidisciplinary research roadmap for chronic disease management. Management Information Systems Quarterly, 44(1), 185–200. https://doi.org/10.25300/MISQ/2020/14644
   Google Scholar
• Byrd, T. A., Cossick, K. L., & Zmud, R. W. (1992). A synthesis of research on requirements analysis and knowledge acquisition techniques. MIS Quarterly, 16(1), 117–138. https://doi.org/10.2307/249704
   Web of Science ®Google Scholar
• Chang, F.-C., Chiu, C.-H., Chen, P.-H., Miao, N.-F., Lee, C.-M., Chiang, J.-T., & Pan, Y.-C. (2015). Relationship between parental and adolescent eHealth literacy and online health information seeking in Taiwan. Cyberpsychology, Behavior, and Social Networking, 18(10), 618–624. https://doi.org/10.1089/cyber.2015.0110
   PubMed Web of Science ®Google Scholar
• Chen, C. C., & Tseng, Y.-D. (2011). Quality evaluation of product reviews using an information quality framework. Decision Support Systems, 50(4), 755–768. https://doi.org/10.1016/j.dss.2010.08.023
   Web of Science ®Google Scholar
• Chen, D., Zhang, R., Feng, J., & Liu, K. (2020). Fulfilling information needs of patients in online health communities. Health Information and Libraries Journal, 37(1), 48–59. https://doi.org/10.1111/hir.12253
   PubMed Web of Science ®Google Scholar
• Chiu, C.-M., Hsu, M.-H., & Wang, E. T. (2006). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42(3), 1872–1888. https://doi.org/10.1016/j.dss.2006.04.001
   Web of Science ®Google Scholar
• Cohan, A., Young, S., Yates, A., & Goharian, N. (2017). Triaging content severity in online mental health forums. Journal of the Association for Information Science and Technology, 68(11), 2675–2689. https://doi.org/10.1002/asi.23865
   Web of Science ®Google Scholar
• Connelly, N. A., & Knuth, B. A. (1998). Evaluating risk communication: Examining target audience perceptions about four presentation formats for fish consumption health advisory information. Risk Analysis, 18(5), 649–659. https://doi.org/10.1111/j.1539-6924.1998.tb00377.x
   PubMed Web of Science ®Google Scholar
• Crossler, R. E., & Bélanger, F. (2019). Why would I use location-protective settings on my smartphone? Motivating protective behaviors and the existence of the privacy knowledge–belief gap. Information Systems Research, 30(3), 995–1006. https://doi.org/10.1287/isre.2019.0846
   Web of Science ®Google Scholar
• Dadgar, M., & Joshi, K. D. (2018). The role of information and communication technology in self-management of chronic diseases: an empirical investigation through value sensitive design. Journal of the Association for Information Systems, 19(2), 86–112. https://doi.org/10.17705/jais1.00485
   Web of Science ®Google Scholar
• Demoulin, N. T., & Coussement, K. (2020). Acceptance of text-mining systems: The signaling role of information quality. Information & Management, 57(1), 103120. https://doi.org/10.1016/j.im.2018.10.006
   Web of Science ®Google Scholar
• Esmaeilzadeh, P., Mirzaei, T., & Maddah, M. (2020). The effects of data entry structure on patients’ perceptions of information quality in Health Information Exchange (HIE). International Journal of Medical Informatics, 135(1), 104058. https://doi.org/10.1016/j.ijmedinf.2019.104058
   PubMed Web of Science ®Google Scholar
• Fan, J., Huang, X., Li, Y. (2019). The effect of features on information quality and knowledge acquisition in online health communities. In Proceedings of the Americas Conference on Information Systems, Cancun, Mexico.
   Google Scholar
• Fisher, J. D., Fisher, W. A., Williams, S. S., & Malloy, T. E. (1994). Empirical tests of an information-motivation-behavioral skills model of AIDS-preventive behavior with gay men and heterosexual university students. Health Psychology, 13(3), 238–250. https://doi.org/10.1037/0278-6133.13.3.238
   PubMed Web of Science ®Google Scholar
• Fisher, W. A., Fisher, J. D., & Harman, J. (2003). The information-motivation-behavioral skills model: A general social psychological approach to understanding and promoting health behavior. Social Psychological Foundations of Health and Illness, 22(1), 82–106. https://doi.org/10.1002/9780470753552.ch4
   Google Scholar
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
   Web of Science ®Google Scholar
• Frost, J. H., & Massagli, M. P. (2008). Social uses of personal health information within PatientsLikeMe, an online patient community: What can happen when patients have access to one another’s data. Journal of Medical Internet Research, 10(3), e15. https://doi.org/10.2196/jmir.1053
   PubMed Web of Science ®Google Scholar
• Gao, J., Wang, J., Zhu, Y., & Yu, J. (2013). Validation of an information–motivation–behavioral skills model of self-care among Chinese adults with type 2 diabetes. BMC Public Health, 13(1), 1–6. https://doi.org/10.1186/1471-2458-13-100
   PubMedGoogle Scholar
• Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-Graph: Tutorial and annotated example. Communications of the Association for Information Systems, 16(1), 91–109. https://doi.org/10.17705/1CAIS.01605
   Google Scholar
• Gutierrez, J., & Long, J. A. (2011). Reliability and validity of diabetes specific health beliefs model scales in patients with diabetes and serious mental illness. Diabetes Research and Clinical Practice, 92(3), 342–347. https://doi.org/10.1016/j.diabres.2011.02.018
   PubMed Web of Science ®Google Scholar
• Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate data analysis: A global perspective (7th ed.). Pearson Education.
   Google Scholar
• Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128
   Google Scholar
• Harman, H. H. (1976). Modern factor analysis (3rd ed.). The University of Chicago Press.
   Google Scholar
• Heilman, J. M., Kemmann, E., Bonert, M., Chatterjee, A., Ragar, B., Beards, G. M., Iberri, D. J., Harvey, M., Thomas, B., Stomp, W., Martone, M. F., Lodge, D. J., Vondracek, A., de Wolff, J. F., Liber, C., Grover, S. C., Vickers, T. J., Meskó, B., & Laurent, M. R. (2011). Wikipedia: A key tool for global public health promotion. Journal of Medical Internet Research, 13(1), e14. https://doi.org/10.2196/jmir.1589
   PubMed Web of Science ®Google Scholar
• Jeon, E., & Park, H.-A. (2018). Development of the IMB model and an evidence-based diabetes self-management mobile application. Healthcare Informatics Research, 24(2), 125–138. https://doi.org/10.4258/hir.2018.24.2.125
   PubMed Web of Science ®Google Scholar
• Jeon, E., & Park, H.-A. (2019). Experiences of patients with a diabetes self-care app developed based on the information-motivation-behavioral skills model: before-and-after study. JMIR Diabetes, 4(2), e11590. https://doi.org/10.2196/11590
   PubMedGoogle Scholar
• Jiang, H., Chen, X., Li, J., Tan, Z., Cheng, W., & Yang, Y. (2019). Predictors of condom use behavior among men who have sex with men in China using a modified information-motivation-behavioral skills (IMB) model. BMC Public Health, 19(1), 1–12. https://doi.org/10.1186/s12889-019-6593-8
   PubMed Web of Science ®Google Scholar
• Jones, T. L., & Prinz, R. J. (2005). Potential roles of parental self-efficacy in parent and child adjustment: A review. Clinical Psychology Review, 25(3), 341–363. https://doi.org/10.1016/j.cpr.2004.12.004
   PubMed Web of Science ®Google Scholar
• Kang, N., Ding, D., Van Riemsdijk, M. B., Morina, N., Neerincx, M. A., & Brinkman, W.-P. (2021). Self-identification with a virtual experience and its moderating effect on self-efficacy and presence. International Journal of Human–Computer Interaction, 37(2), 181–196. https://doi.org/10.1080/10447318.2020.1812909
   Web of Science ®Google Scholar
• Katayama, A. D., & Crooks, S. M. (2003). Online notes: Differential effects of studying complete or partial graphically organized notes. The Journal of Experimental Education, 71(4), 293–312. https://doi.org/10.1080/00220970309602067
   Web of Science ®Google Scholar
• Kim, H.-S., & Mrotek, A. (2016). A functional and structural diagnosis of online health communities sustainability: A focus on resource richness and site design features. Computers in Human Behavior, 63(11), 362–372. https://doi.org/10.1016/j.chb.2016.05.004
   Google Scholar
• Lindsay, S., Smith, S., Bellaby, P., & Baker, R. (2009). The health impact of an online heart disease support group: a comparison of moderated versus unmoderated support. Health Education Research, 24(4), 646–654. https://doi.org/10.1093/her/cyp001
   PubMed Web of Science ®Google Scholar
• Liu, S., Xiao, W., Fang, C., Zhang, X., & Lin, J. (2020). Social support, belongingness, and value co-creation behaviors in online health communities. Telematics and Informatics, 50(1), 101398. https://doi.org/10.1016/j.tele.2020.101398
   Web of Science ®Google Scholar
• Liu, X., Zhang, B., Susarlia, A., & Padman, R. (2020). Go to YouTube and Call Me in the morning: Use of social media for chronic conditions. MIS Quarterly, 44(1), 257–283. https://doi.org/10.25300/MISQ/2020/15107
   Web of Science ®Google Scholar
• Lu, Y., & Yang, D. (2011). Information exchange in virtual communities under extreme disaster conditions. Decision Support Systems, 50(2), 529–538. https://doi.org/10.1016/j.dss.2010.11.011
   Web of Science ®Google Scholar
• Malinen, S. (2015). Understanding user participation in online communities: A systematic literature review of empirical studies. Computers in Human Behavior, 46, 228–238. https://doi.org/10.1016/j.chb.2015.01.004
   Web of Science ®Google Scholar
• Manzano, W. (2015). How Blood Pressure Works [Video]. YouTube. https://www.youtube.com/watch?v=Ab9OZsDECZw
   Google Scholar
• McAfee, A., & Brynjolfsson, E. (2017). Machine, platform, crowd: Harnessing our digital future. W. W. Norton & Company.
   Google Scholar
• Misovich, S. J., Martinez, T., Fisher, J. D., Bryan, A., & Catapano, N. (2003). Predicting breast self‐examination: A test of the information‐motivation‐behavioral skills model. Journal of Applied Social Psychology, 33(4), 775–790. https://doi.org/10.1111/j.1559-1816.2003.tb01924.x
   Web of Science ®Google Scholar
• Mo, P. K., & Coulson, N. S. (2014). Are online support groups always beneficial? A qualitative exploration of the empowering and disempowering processes of participation within HIV/AIDS-related online support groups. International Journal of Nursing Studies, 51(7), 983–993. https://doi.org/10.1016/j.ijnurstu.2013.11.006
   PubMed Web of Science ®Google Scholar
• Nath, C., Huh, J., Adupa, A. K., & Jonnalagadda, S. R. (2016). Website sharing in online health communities: A descriptive analysis. Journal of Medical Internet Research, 18(1), e11. https://doi.org/10.2196/jmir.5237
   PubMed Web of Science ®Google Scholar
• Nunes, F., & Fitzpatrick, G. (2015). Self-care technologies and collaboration. International Journal of Human-Computer Interaction, 31(12), 869–881. https://doi.org/10.1080/10447318.2015.1067498
   Web of Science ®Google Scholar
• Orlikowski, W. J., & Iacono, C. S. (2001). Research commentary: Desperately seeking the “IT” in IT research—A call to theorizing the IT artifact. Information Systems Research, 12(2), 121–134. https://doi.org/10.1287/isre.12.2.121.9700
   Web of Science ®Google Scholar
• Pellegrini, D., Torlasco, C., Ochoa, J. E., & Parati, G. (2020). Contribution of telemedicine and information technology to hypertension control. Hypertension Research, 43(7), 621–628. https://doi.org/10.1038/s41440-020-0422-4
   PubMed Web of Science ®Google Scholar
• Petter, S., Straub, D. W., & Rai, A. (2007). Specifying formative constructs in information systems research. MIS Quarterly, 31(4), 623–656. https://doi.org/10.2307/25148814
   Web of Science ®Google Scholar
• Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
   PubMed Web of Science ®Google Scholar
• Raver, S. A., & Maydosz, A. S. (2010). Impact of the provision and timing of instructor-provided notes on university students’ learning. Active Learning in Higher Education, 11(3), 189–200. https://doi.org/10.1177/1469787410379682
   Google Scholar
• Richey, J. E., Andres-Bray, J. M. L., Mogessie, M., Scruggs, R., Andres, J. M., Star, J. R., Baker, R. S., & McLaren, B. M. (2019). More confusion and frustration, better learning: The impact of erroneous examples. Computers & Education, 139(1), 173–190. https://doi.org/10.1016/j.compedu.2019.05.012
   Web of Science ®Google Scholar
• Rieder, A., Eseryel, U. Y., Lehrer, C., & Jung, R. (2021). Why users comply with Wearables: The role of contextual self-efficacy in behavioral change. International Journal of Human–Computer Interaction, 37(3), 281–294. https://doi.org/10.1080/10447318.2020.1819669
   Web of Science ®Google Scholar
• Rueger, J., Dolfsma, W., & Aalbers, R. (2021). Perception of peer advice in online health communities: Access to lay expertise. Social Science & Medicine, 277(1), 113117. https://doi.org/10.1016/j.socscimed.2020.113117
   PubMed Web of Science ®Google Scholar
• Ryu, C., Kim, Y. J., Chaudhury, A., & Rao, H. R. (2005). Knowledge acquisition via three learning processes in enterprise information portals: learning-by-investment, learning-by-doing, and learning-from-others. MIS Quarterly, 29(2), 245–278. https://doi.org/10.2307/25148679
   Web of Science ®Google Scholar
• Schneider, B., Krajcik, J., Lavonen, J., Salmela‐Aro, K., Broda, M., Spicer, J., Bruner, J., Moeller, J., Linnansaari, J., Juuti, K., & Viljaranta, J. (2016). Investigating optimal learning moments in US and Finnish science classes. Journal of Research in Science Teaching, 53(3), 400–421. https://doi.org/10.1002/tea.21306
   Web of Science ®Google Scholar
• Silver, L., Huang, C. (2019). Social activities, information seeking on subjects like health and education top the list of mobile activities. https://www.pewresearch.org/internet/2019/08/22/social-activities-information-seeking-on-subjects-like-health-and-education-top-the-list-of-mobile-activities/
   Google Scholar
• Sinan, O., Kaplan, S., Sahin, S., & Peksoy, S. (2020). Assessment of the effectiveness of genital infection awareness training provided to women based on the IMB model. Nigerian Journal of Clinical Practice, 23(3), 408–415. https://doi.org/10.4103/njcp.njcp_205_18
   PubMed Web of Science ®Google Scholar
• Sun, N., Rau, P. P.-L., & Ma, L. (2014). Understanding lurkers in online communities: A literature review. Computers in Human Behavior, 38, 110–117. https://doi.org/10.1016/j.chb.2014.05.022
   Web of Science ®Google Scholar
• Sun, Y., Zhang, Y., Gwizdka, J., & Trace, C. B. (2019). Consumer evaluation of the quality of online health information: Systematic literature review of relevant criteria and indicators. Journal of Medical Internet Research, 21(5), e12522. https://doi.org/10.2196/12522
   PubMed Web of Science ®Google Scholar
• Tsamlag, L., Wang, H., Shen, Q., Shi, Y., Zhang, S., Chang, R., Liu, X., Shen, T., & Cai, Y. (2020). Applying the information–motivation–behavioral model to explore the influencing factors of self-management behavior among osteoporosis patients. BMC Public Health, 20(1), 1–8. https://doi.org/10.1186/s12889-020-8292-x
   PubMed Web of Science ®Google Scholar
• van Eenbergen, M. C., van de Poll-Franse, L. V., Heine, P., & Mols, F. (2017). The impact of participation in online cancer communities on patient reported outcomes: systematic review. JMIR Cancer, 3(2), e15. https://doi.org/10.2196/cancer.7312
   PubMed Web of Science ®Google Scholar
• Vennik, F. D., Adams, S. A., Faber, M. J., & Putters, K. (2014). Expert and experiential knowledge in the same place: Patients’ experiences with online communities connecting patients and health professionals. Patient Education and Counseling, 95(2), 265–270. https://doi.org/10.1016/j.pec.2014.02.003
   PubMed Web of Science ®Google Scholar
• Wang, C.-Y., Lee, H.-C., Wu, L.-W., & Liu, C.-C. (2017). Quality dimensions in online communities influence purchase intentions. Management Decision, 55(9), 1984–1998. https://doi.org/10.1108/MD-11-2016-0822
   Web of Science ®Google Scholar
• Wang, J., Wang, X., Wang, L., & Peng, Y. (2021). Health information needs of young Chinese people based on an online health community: Topic and statistical analysis. JMIR Medical Informatics, 9(11), e30356. https://doi.org/10.2196/30356
   PubMed Web of Science ®Google Scholar
• Wang, K., & Lin, C. L. (2012). The adoption of mobile value‐added services: Investigating the influence of IS quality and perceived playfulness. Managing Service Quality: An International Journal, 22(2), 184–208. https://doi.org/10.1108/09604521211219007
   Google Scholar
• Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5–33. https://doi.org/10.1080/07421222.1996.11518099
   Google Scholar
• World Health Organization (2020). The top 10 Causes of Death. https://www.who.int/en/news-room/fact-sheets/detail/the-top-10-causes-of-death
   Google Scholar
• Wu, H., & Deng, Z. (2019). Knowledge collaboration among physicians in online health communities: A transactive memory perspective. International Journal of Information Management, 49, 13–33. https://doi.org/10.1016/j.ijinfomgt.2019.01.003
   Web of Science ®Google Scholar
• Yan, L., & Tan, Y. (2014). Feeling blue? Go online: An empirical study of social support among patients. Information Systems Research, 25(4), 690–709. https://doi.org/10.1287/isre.2014.0538
   Web of Science ®Google Scholar
• Yan, L., Peng, J., & Tan, Y. (2015). Network dynamics: How can we find patients like us? Information Systems Research, 26(3), 496–512. https://doi.org/10.1287/isre.2015.0585
   Web of Science ®Google Scholar
• Yates, T., Davies, M. J., & Khunti, K. (2012). Obesity and chronic disease in younger people: an unfolding crisis. British Journal of General Practice, 62(594), 4–5. https://doi.org/10.3399/bjgp12X616201
   PubMed Web of Science ®Google Scholar
• Zhang, J., Luo, B., & Cao, F. (2019). The antecedent and consequence of users' satisfaction and dissatisfaction with information seeking in online health communities. Proceedings of the Association for Information Science and Technology, 56(1), 836–837. https://doi.org/10.1002/pra2.200
   Google Scholar
• Zhang, X., Liu, S., Chen, X., Wang, L., Gao, B., & Zhu, Q. (2018). Health information privacy concerns, antecedents, and information disclosure intention in online health communities. Information & Management, 55(4), 482–493. https://doi.org/10.1016/j.im.2017.11.003
   Web of Science ®Google Scholar
• Zhang, X., Liu, S., Deng, Z., & Chen, X. (2017). Knowledge sharing motivations in online health communities: A comparative study of health professionals and normal users. Computers in Human Behavior, 75(10), 797–810. https://doi.org/10.1016/j.chb.2017.06.028
   Google Scholar
• Zhang, Y., Li, X., & Fan, W. (2020). User adoption of physician's replies in an online health community: An empirical study. Journal of the Association for Information Science and Technology, 71(10), 1179–1191. https://doi.org/10.1002/asi.24319
   Web of Science ®Google Scholar
• Zhang, Y., Sun, Y., & Xie, B. (2015). Quality of health information for consumers on the web: a systematic review of indicators, criteria, tools, and evaluation results. Journal of the Association for Information Science and Technology, 66(10), 2071–2084. https://doi.org/10.1002/asi.23311
   Web of Science ®Google Scholar