IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i16p8603-d614536.html
   My bibliography  Save this article

Are Diverse Media Better than a Single Medium? The Relationship between Mixed Media and Perceived Effect from the Perspective of Online Psychological Counseling

Author

Listed:
  • Jingfang Liu

    (School of Management, Shanghai University, Shanghai 201800, China)

  • Lu Gao

    (School of Management, Shanghai University, Shanghai 201800, China)

Abstract

The progress of new media has promoted the development of online health consultations. Previous research has investigated the impact of media richness on user satisfaction; however, little attention has been given to the mixed effects of the nesting of multiple media. The purpose of this study is to analyze the impact and differences of the use of single or mixed media on users’ perceived effect from the perspectives of social support and satisfaction by mining user reviews on online health platforms. The data were collected from a professional online psychological counseling platform. We collected data on 48,807 reviews from 11,694 users. Text annotation and sentiment analysis were then used to extract variable eigenvalues from the reviews. One-way analysis of variance (ANOVA) and hierarchical regression analysis were used for statistical analysis. The results show that mixed media with different richness has a significant impact on the users’ perceived effects. Among them, compared to “text + audio,” using “text + audio + video/face to face” can significantly improve the users’ perceived social support and satisfaction. However, compared to single medium, mixed media with higher richness may not necessarily achieve a better effect. We found that the inclusion of “video/face to face” mixed media significantly reduced the users’ perceived social support and satisfaction compared to text or audio use alone. These research results complement the blank media richness theory in the field of online health care and provide guidance for improving the personalized customization of online psychological counseling platforms.

Suggested Citation

  • Jingfang Liu & Lu Gao, 2021. "Are Diverse Media Better than a Single Medium? The Relationship between Mixed Media and Perceived Effect from the Perspective of Online Psychological Counseling," IJERPH, MDPI, vol. 18(16), pages 1-16, August.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:16:p:8603-:d:614536
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/16/8603/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/16/8603/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jingfang Liu & Jun Kong & Xin Zhang, 2020. "Study on Differences between Patients with Physiological and Psychological Diseases in Online Health Communities: Topic Analysis and Sentiment Analysis," IJERPH, MDPI, vol. 17(5), pages 1-17, February.
    2. Guo, Yue & Barnes, Stuart J. & Jia, Qiong, 2017. "Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation," Tourism Management, Elsevier, vol. 59(C), pages 467-483.
    3. Yuxin Peng & Pingping Yin & Zhaohua Deng & Ruoxi Wang, 2019. "Patient–Physician Interaction and Trust in Online Health Community: The Role of Perceived Usefulness of Health Information and Services," IJERPH, MDPI, vol. 17(1), pages 1-13, December.
    Full references (including those not matched with items on IDEAS)

    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. Wang, Binni & Wang, Pong & Tu, Yiliu, 2021. "Customer satisfaction service match and service quality-based blockchain cloud manufacturing," International Journal of Production Economics, Elsevier, vol. 240(C).
    2. M. Narciso, 2022. "The Unreliability of Online Review Mechanisms," Journal of Consumer Policy, Springer, vol. 45(3), pages 349-368, September.
    3. Jiacong Wu & Yu Wang & Ru Zhang & Jing Cai, 2018. "An Approach to Discovering Product/Service Improvement Priorities: Using Dynamic Importance-Performance Analysis," Sustainability, MDPI, vol. 10(10), pages 1-26, October.
    4. Shuyue Huang & Lena Jingen Liang & Hwansuk Chris Choi, 2022. "How We Failed in Context: A Text-Mining Approach to Understanding Hotel Service Failures," Sustainability, MDPI, vol. 14(5), pages 1-18, February.
    5. Carmela Iorio & Giuseppe Pandolfo & Antonio D’Ambrosio & Roberta Siciliano, 2020. "Mining big data in tourism," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(5), pages 1655-1669, December.
    6. Mohamed M. Mostafa, 2023. "A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3905-3935, August.
    7. Ian Sutherland & Kiattipoom Kiatkawsin, 2020. "Determinants of Guest Experience in Airbnb: A Topic Modeling Approach Using LDA," Sustainability, MDPI, vol. 12(8), pages 1-16, April.
    8. Boccali, Filippo & Mariani, Marcello M. & Visani, Franco & Mora-Cruz, Alexandra, 2022. "Innovative value-based price assessment in data-rich environments: Leveraging online review analytics through Data Envelopment Analysis to empower managers and entrepreneurs," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    9. Ahani, Ali & Nilashi, Mehrbakhsh & Yadegaridehkordi, Elaheh & Sanzogni, Louis & Tarik, A. Rashid & Knox, Kathy & Samad, Sarminah & Ibrahim, Othman, 2019. "Revealing customers’ satisfaction and preferences through online review analysis: The case of Canary Islands hotels," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 331-343.
    10. Xue, Lan & Leung, Xi Y. & Ma, Shihan (David), 2022. "What makes a good “guest”: Evidence from Airbnb hosts' reviews," Annals of Tourism Research, Elsevier, vol. 95(C).
    11. Xiao-kang Wang & Sheng-hui Wang & Hong-yu Zhang & Jian-qiang Wang & Lin Li, 2021. "The Recommendation Method for Hotel Selection Under Traveller Preference Characteristics: A Cloud-Based Multi-Criteria Group Decision Support Model," Group Decision and Negotiation, Springer, vol. 30(6), pages 1433-1469, December.
    12. Zhizhen Yao & Zhenni Ni & Bin Zhang & Jian Du, 2022. "Do Informational and Emotional Elements Differ between Online Psychological and Physiological Disease Communities in China? A Comparative Study of Depression and Diabetes," IJERPH, MDPI, vol. 19(4), pages 1-21, February.
    13. Liu, Yuqing & Schuberth, Florian & Liu, Yide & Henseler, Jörg, 2022. "Modeling and assessing forged concepts in tourism and hospitality using confirmatory composite analysis," Journal of Business Research, Elsevier, vol. 152(C), pages 221-230.
    14. Gang Ren & Taeho Hong, 2017. "Investigating Online Destination Images Using a Topic-Based Sentiment Analysis Approach," Sustainability, MDPI, vol. 9(10), pages 1-18, September.
    15. Yang Song & Jessica Fernandez & Tong Wang, 2020. "Understanding Perceived Site Qualities and Experiences of Urban Public Spaces: A Case Study of Social Media Reviews in Bryant Park, New York City," Sustainability, MDPI, vol. 12(19), pages 1-15, September.
    16. Wen-Kuo Chen & Dalianus Riantama & Long-Sheng Chen, 2020. "Using a Text Mining Approach to Hear Voices of Customers from Social Media toward the Fast-Food Restaurant Industry," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
    17. Junegak Joung & Ki-Hun Kim & Kwangsoo Kim, 2021. "Data-Driven Approach to Dual Service Failure Monitoring From Negative Online Reviews: Managerial Perspective," SAGE Open, , vol. 11(1), pages 21582440209, January.
    18. Pengxia Zhang & Mingzheng Liu & Dandan Li & Yue Dong, 2021. "The Audience’s Perspective: Decline of Mythical Elements in Films," SAGE Open, , vol. 11(3), pages 21582440211, August.
    19. Lee, Carmen Kar Hang & Tse, Ying Kei & Leung, Eric Ka Ho & Wang, Yichuan, 2024. "Causal recipes of customer loyalty in a sharing economy: Integrating social media analytics and fsQCA," Journal of Business Research, Elsevier, vol. 181(C).
    20. Tong Yang & Yanzhong Dang & Jiangning Wu, 2025. "How to prioritize perceived quality attributes from consumers' perspective? Analysis through social media data," Electronic Commerce Research, Springer, vol. 25(1), pages 39-67, February.

    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:18:y:2021:i:16:p:8603-:d:614536. 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.