IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i9p2995-d350518.html
   My bibliography  Save this article

How Could Peers in Online Health Community Help Improve Health Behavior

Author

Listed:
  • Yumei Li

    (Management Science and Engineering, School of Management, Harbin Institute of Technology, 92 Xidazhi Street, Nangang District, Harbin 150001, China)

  • Xiangbin Yan

    (Management Science and Engineering, Dongling School of Economics and Management, University of Science and Technology Beijing, 30 Xueyuan Road, Beijing 100083, China)

Abstract

Human behavior is the largest source of variance in health-related outcomes, and the increasingly popular online health communities (OHC) can be used to promote healthy behavior and outcomes. We explored how the social influence (social integration, descriptive norms and social support) exerted by online social relationships does affect the health behavior of users. Based on an OHC, we considered the effect of three types of social relationships (friendship, mutual support group and competing group) in the OHC. We found that social integration, descriptive norms and social support (information and emotional support) from the OHC had a positive effect on dietary and exercise behavior. Comparing the effects of different social relationships, we found that the stronger social relationship—friendship—had a stronger effect on health behavior than the mutual support group and competing group. Emotional support had a stronger effect on health behavior than informational support. We also found that the effects of social integration and informational support became stronger as membership duration increased, but the effects of the descriptive norms and emotional support became smaller. This study extended the research on health behavior to the online social environment and explored how the social influence exerted by various social relationships in an OHC affected health behavior. The results could be used for guiding users to make use of online social relationships for changing and maintaining healthy behavior, and helping healthcare websites improve their services.

Suggested Citation

  • Yumei Li & Xiangbin Yan, 2020. "How Could Peers in Online Health Community Help Improve Health Behavior," IJERPH, MDPI, vol. 17(9), pages 1-17, April.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:9:p:2995-:d:350518
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/9/2995/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/9/2995/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Melanie Swan, 2009. "Emerging Patient-Driven Health Care Models: An Examination of Health Social Networks, Consumer Personalized Medicine and Quantified Self-Tracking," IJERPH, MDPI, vol. 6(2), pages 1-34, February.
    2. Vishwali Mhasawade & Anas Elghafari & Dustin T. Duncan & Rumi Chunara, 2020. "Role of the Built and Online Social Environments on Expression of Dining on Instagram," IJERPH, MDPI, vol. 17(3), pages 1-20, January.
    3. Lu Yan & Yong Tan, 2014. "Feeling Blue? Go Online: An Empirical Study of Social Support Among Patients," Information Systems Research, INFORMS, vol. 25(4), pages 690-709, December.
    4. Tutz, Gerhard & Hennevogl, Wolfgang, 1996. "Random effects in ordinal regression models," Computational Statistics & Data Analysis, Elsevier, vol. 22(5), pages 537-557, September.
    5. Young-Jin Lee & Kartik Hosanagar & Yong Tan, 2015. "Do I Follow My Friends or the Crowd? Information Cascades in Online Movie Ratings," Management Science, INFORMS, vol. 61(9), pages 2241-2258, September.
    6. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    7. Cobb, N.K. & Graham, A.L. & Abrams, D.B., 2010. "Social network structure of a large online community for smoking cessation," American Journal of Public Health, American Public Health Association, vol. 100(7), pages 1282-1289.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yingjie Lu & Xinwei Wang & Lin Su & Han Zhao, 2023. "Multiplex Social Network Analysis to Understand the Social Engagement of Patients in Online Health Communities," Mathematics, MDPI, vol. 11(21), pages 1-20, October.
    2. Liyue Gong & Hao Jiang & Xusheng Wu & Yi Kong & Yunyun Gao & Hao Liu & Yi Guo & Dehua Hu, 2022. "Exploring Users’ Health Behavior Changes in Online Health Communities: Heuristic-Systematic Perspective Study," IJERPH, MDPI, vol. 19(18), pages 1-14, September.
    3. Brian M. Green & Casey A. Hribar & Sara Hayes & Amrita Bhowmick & Leslie Beth Herbert, 2021. "Come for Information, Stay for Support: Harnessing the Power of Online Health Communities for Social Connectedness during the COVID-19 Pandemic," IJERPH, MDPI, vol. 18(23), pages 1-12, December.
    4. Qiuju Yin & Haoyue Fan & Yijie Wang & Chenxi Guo & Xingzhi Cui, 2022. "Exploring the Peer Effect of Physicians’ and Patients’ Participation Behavior: Evidence from Online Health Communities," IJERPH, MDPI, vol. 19(5), pages 1-16, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Agnieszka Rusinowska & Vassili Vergopoulos, 2020. "Ingratiation and Favoritism in Organizations," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 176(3), pages 413-445.
    2. Carlos de las Heras-Pedrosa & Dolores Rando-Cueto & Carmen Jambrino-Maldonado & Francisco J. Paniagua-Rojano, 2020. "Exploring the Social Media on the Communication Professionals in Public Health. Spanish Official Medical Colleges Case Study," IJERPH, MDPI, vol. 17(13), pages 1-17, July.
    3. Ni Huang & Zhijun Yan & Haonan Yin, 2021. "Effects of Online–Offline Service Integration on e‐Healthcare Providers: A Quasi‐Natural Experiment," Production and Operations Management, Production and Operations Management Society, vol. 30(8), pages 2359-2378, August.
    4. Eyring, Henry, 2020. "Disclosing physician ratings: performance effects and the difficulty of altering rating consensus," LSE Research Online Documents on Economics 105779, London School of Economics and Political Science, LSE Library.
    5. Zhou, Shasha & Tu, Le, 2022. "The effect of social dynamics in online review voting behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 69(C).
    6. Kim, Da Yeon & Kim, Sang Yong, 2023. "Investigating the effect of customer-generated content on performance in online platform-based experience goods market," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    7. Moldovan, Sarit & Shoham, Meyrav & Steinhart, Yael, 2023. "Sending mixed signals: How congruent versus incongruent signals of popularity affect product appeal," International Journal of Research in Marketing, Elsevier, vol. 40(4), pages 881-897.
    8. Boto-García, David & Baños-Pino, José Francisco, 2022. "Social influence and bandwagon effects in tourism travel," Annals of Tourism Research, Elsevier, vol. 93(C).
    9. Gu, Chen & Guo, Xu & Zhang, Chengping, 2022. "Analyst target price revisions and institutional herding," International Review of Financial Analysis, Elsevier, vol. 82(C).
    10. Ruomeng Cui & Dennis J. Zhang & Achal Bassamboo, 2019. "Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon," Management Science, INFORMS, vol. 65(3), pages 1216-1235, March.
    11. Jonas Hedlund & Carlos Oyarzun, 2018. "Imitation in heterogeneous populations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(4), pages 937-973, June.
    12. Cao, Melanie & Shi, Shouyong, 2006. "Signaling in the Internet craze of initial public offerings," Journal of Corporate Finance, Elsevier, vol. 12(4), pages 818-833, September.
    13. Wei He & Qian Wang, 2020. "The peer effect of corporate financial decisions around split share structure reform in China," Review of Financial Economics, John Wiley & Sons, vol. 38(3), pages 474-493, July.
    14. Kraemer, Carlo & Noth, Markus & Weber, Martin, 2006. "Information aggregation with costly information and random ordering: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 59(3), pages 423-432, March.
    15. Fishman, Arthur & Fishman, Ram & Gneezy, Uri, 2019. "A tale of two food stands: Observational learning in the field," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 101-108.
    16. Tomasz Lenartowicz & Henryk Bujak & Marcin Przystalski & Inna Mashevska & Kamila Nowosad & Krzysztof Jończyk & Beata Feledyn-Szewczyk, 2024. "Assessment of Resistance of Barley Varieties to Diseases in Polish Organic Field Trials," Agriculture, MDPI, vol. 14(5), pages 1-11, May.
    17. Edgardo Arturo Ayala Gaytán, 2009. "Social network externalities and price dispersion in online markets," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 1-28, November.
    18. Jacob K. Goeree & Leeat Yariv, 2015. "Conformity in the lab," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 15-28, July.
    19. Buechel, Berno & Hellmann, Tim & Klößner, Stefan, 2015. "Opinion dynamics and wisdom under conformity," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 240-257.
    20. Boğaçhan Çelen & Kyle Hyndman, 2012. "An experiment of social learning with endogenous timing," Review of Economic Design, Springer;Society for Economic Design, vol. 16(2), pages 251-268, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:9:p:2995-:d:350518. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.