Mapping the evidence-based landscape in Chinese library and information science: a mixed-methods assessment
DOI:
https://doi.org/10.47989/ir31iConf64159Keywords:
Evidence based science, LIS study, Application, Optimization strategy, Interdisciplinary communicationAbstract
Introduction. This study systematically explores the thematic distribution, evolutionary trajectory, and future directions of evidence-based research in the Library and Information Science (LIS) discipline in China.
Method. A mixed-method design was employed, combining quantitative and qualitative approaches. Data were collected from 18 core CSSCI LIS journals (1999–2025). Methods included word frequency analysis, LDA topic modelling, and qualitative content analysis, with independent coding by two researchers to ensure reliability.
Analysis. Thematic and evolutionary analysis was conducted using LDA topic modelling at an optimal k=9, evaluated through perplexity and coherence metrics. Content analysis was performed to identify application dimensions of evidence-based systems in LIS research.
Results. The study identifies nine major research topics and reveals a clear shift from traditional, resource-centered themes to strategic, intelligence-aided, and application-oriented research. Evidence-based systems function through five key dimensions: perspective introduction, theoretical support, methodological innovation, diverse evidence integration and expansion of application scenarios.
Conclusion. Evidence-based research in Chinese LIS has evolved significantly, showing strong local adaptation and interdisciplinary integration. To enhance future development, it is essential to develop a more comprehensive understanding of evidence-based research, give higher-level attention to evidence-based research, and explore wider horizons and application spaces for its implementation.
References
Carlsson, H., & Torngren, T. (2020). Understanding library users via surveys and other methods—best practices for evidence-based library development. Journal of Library Administration, 60(8), 925-944. https://doi.org/10.1080/01930826.2020.1820276
Chen, H. L., Chiu, T. H., & Cline, E. (2023). Academic libraries and research data management: a case study of Dataverse global adoption. Information Discovery and Delivery, 51(2), 166-178. https://doi.org/10.1108/IDD-04-2022-0028
Cox, A. M., & Mazumdar, S. (2024). Defining artificial intelligence for librarians. Journal of librarianship and information science, 56(2), 330-340. https://doi.org/10.1177/09610006221142029
Creswell, J. W., & Clark, V. L. P. (2017). Designing and conducting mixed methods research. Sage publications. https://cdn.bookey.app/files/pdf/book/en/designing-and-conducting-mixed-methods-research.pdf
Fidel, R. (2008). Are we there yet?: Mixed methods research in library and information science. Library & information science research, 30(4), 265-272. https://doi.org/10.1016/j.lisr.2008.04.001
Grbin, L., Nichols, P., Russell, F., et al. (2022). The development of a living knowledge system and implications for future systematic searching. Journal of the Australian Library and Information Association, 71(3), 275–292. https://doi.org/10.1080/24750158.2022.2087954
Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Toward a Conceptual Framework for Mixed-Method Evaluation Designs. Educational Evaluation and Policy Analysis, 11(3), 255–274. https://doi.org/10.2307/1163620
Jelodar, H., Wang, Y., Yuan, C., Feng, X., Jiang, X., Li, Y., & Zhao, L. (2019). Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey. Multimedia tools and applications, 78(11), 15169-15211. https://doi.org/10.1007/s11042-018-6894-4
Kallaher, A., Eldermire, E. R., Fournier, C. T., Ghezzi-Kopel, K., Johnson, K. A., Morris-Knower, J., ... & Young, S. (2020). Library systematic review service supports evidence-based practice outside of medicine. The Journal of Academic Librarianship, 46(6), 102222. https://doi.org/10.1016/j.acalib.2020.102222
Leech, N. L., & Onwuegbuzie, A. J. (2009). A typology of mixed methods research designs. Quality & quantity, 43(2), 265-275. https://doi.org/10.1007/s11135-007-9105-3
Li, L., Liu, M., & Wang, Y. (2023). Evidence-based Library and Information Practice(EBLIP): Historical Evolution and Theoretical Framework. Library Theory and Practice, (5), 41–46. https://doi.org/10.14064/j.cnki.issn1005-8214.2023.05.006
Maibach, E., Roser-Renouf, C., Myers, T., Kotcher, J., & Reed, D. (2024). The “think-and-do tank” model: Action-oriented climate communication research. Environmental Communication, 18(1-2), 68-75. https://doi.org/10.1080/17524032.2024.2304571
Sackett, D. L., Rosenberg, W. M., Gray, J. M., Haynes, R. B., & Richardson, W. S. (1996). Evidence based medicine: what it is and what it isn't. bmj, 312(7023), 71-72. https://doi.org/10.1136/bmj.312.7023.71
Scherrer, C. S., & Dorsch, J. L. (1999). The evolving role of the librarian in evidence-based medicine. Bulletin of the Medical Library Association, 87(3), 322. https://pmc.ncbi.nlm.nih.gov/articles/PMC226592/
Tran, C. Y., & Guo, J. X. (2021). Developing user-centered collections at a research library: An Evidence-Based Acquisition (EBA) pilot in STEM. The Journal of Academic Librarianship, 47(5), 102434. https://doi.org/10.1016/j.acalib.2021.102434
Wang, P., Xu, J., & Yu, B. (2016). A Review on Evidence Based Library and Information Practice. Journal of the China Society for Scientific and Technical Information, 35(1), 98–112. https://kns.cnki.net/kcms2/article/abstract?v=YQFK0XGjx42whxk8w2_hvPKZj_wUYb0WiNMD6ivSKKgC2mQAOqX7t9wLE0AYUrBymQNns9lfBC2evLzLHJSrAfCbLoJokrKzro-bSHXsPhr1bQFlvR3HyvaI-0iojof4Vv3sWb2ih9g2L31RaqR2MW4KevVH8SLY8LafwD9_FNaefsUh8Ebzxg==&uniplatform=NZKPT&language=CHS
Wu, T., & Li, B. (1999). Information research methods in evidence-based medicine. Journal of the Library Science Society of Sichuan, (3), 50–53. https://kns.cnki.net/kcms2/article/abstract?v=YQFK0XGjx41EdBlc6Qq_DYuAOgx_3J5Bm8PgBFThjkgwmRNiKdvxt9IYNrNqrBHzskjKFzKwMcUCgxLGOgn0gPmYca414UEf96Y6uC5NJAmRPjMTyNrtxYr30XmBKX5e4q_fwrGYQ4VMR5VZOIfI-9dhGYMc7ubyhW5FxC0VZDkIwj8IBP7mbg==&uniplatform=NZKPT&language=CHS
Yu, M., & Qu, J. (2018). Research Progress of Evidence-based Science in Library and Information Science (LIS). Library and Information Service, 62(20), 133–141. https://doi.org/10.13266/j.issn.0252-3116.2018.20.015. https://doi.org/10.13266/j.issn.0252-3116.2018.20.015
Zhang, Y., & Yong, S. (2023). Discussion on Evolution and Innovation of Evidence-based Library Science in China. Journal of Jilin Provincial Institute of Education, 39(4), 165–174. https://doi.org/10.16083/j.cnki.1671-1580.2023.04.024
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Copyright (c) 2026 Junling Ye, Xinyu Chen, Siqi Jiang, Yikun Xia
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