PREFERENCES OF INFORMATION SOURCES IN VETERINARY SCIENCE IN INDIA: BEST-WORST SCALING ANALYSIS
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Keywords:
Information sources, veterinary science, India, best-worst scaling, internet, gender disparityAbstract
This study examines the preferences of information sources among veterinary science professionals in India, employing a Best-Worst Scaling analysis to identify the most and least favoured sources, as well as the constraints faced in accessing these resources. Conducted through an online survey in 2024, the research gathered responses from 142 veterinary professionals, predominantly male (88.73%). Key findings reveal that the internet and training courses are the most preferred information sources, while traditional resources like CD databases are least favoured. Constraints such as information overload and inadequate infrastructure significantly hinder effective information access. The study highlights gender disparities in information source preferences and emphasizes the need for improved access to information and resources in the veterinary field.
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Anagaw, T.F. and Guadie, H.A. (2023). Coronavirus disease 2019 information-seeking behavior globally: a systematic review. SAGE Open Medicine, 11, 20503121231153510. https://doi. org/10.1177/20503121231153510
Antonio, A. and Tuffley, D. (2014). The gender digital divide in developing countries. Future Internet, 6:673–687. https://doi.org/10.3390/fi6040673
Beres, L.K., Campoamor, N.B., Hawthorn, R., Mugambi, M.L., Mulabe, M., Vhlakis, N., Kabongo, M., Schuster, A. and Bridges, J.F.P. (2024). Using best-worst scaling to inform policy decisions in Africa: a literature review. BMC Public Health, 24:2607. https://doi.org/10.1186/s12889-024-20068-w
Garner, B.C., Hartle, D.Y. and Creevy, K.E. (2019). The educational resource preferences and information-seeking behaviors of veterinary medical students and practitioners. Journal of Veterinary. Medical Education, 46:470–480. https://doi.org/10.3138/jvme.1017-150r1
Giacomazzo, M., Cian, F., Castagnaro, M., Gelain, M.E. and Bonsembiante, F. (2024). Digital cytology in veterinary education: a comprehensive survey of its application and perception among undergraduate and postgraduate students. Animals, 14:1561. https://doi.org/10.3390/ani14111561
Hendricks, W. and Olawale, B. (2022). Bridging the gender-based digital divide: empowerment of women through ICT, in: Tenth Pan- commonwealth forum on open learning. Commonwealth of Learning. https://doi.org/10.56059/ pcf10.9136
Huntley, S.J., Dean, R.S., Massey, A. and Brennan, M.L. (2016). International evidence-based medicine survey of the veterinary profession: information sources used by veterinarians. PLOS ONE, 11, e0159732. https://doi. org/10.1371/journal.pone.0159732
Louviere, J.J., Flynn, T.N. and Marley, A.A.J. (2015). Best-worst scaling: theory, methods and applications, 1st ed. Cambridge University Press. https://doi.org/10.1017/ CBO9781107337855
Muca, E., Cavallini, D., Odore, R., Baratta, M., Bergero, D. and Valle, E. (2022). Are veterinary students using technologies and online learning resources for didactic training? a mini-meta analysis. Education of Science, 12:573. https://doi.org/10.3390/educsci12080573
Schuster, A.L.R., Crossnohere, N.L., Campoamor, N.B., Hollin, I.L. and Bridges, J.F.P. (2024). The rise of best-worst scaling for prioritization: a transdisciplinary literature review. Journal of Choice Modelling,50:100466. https://doi.org/10.1016/j. jocm.2023.100466
Van Deursen, A.J. and Van Dijk, J.A., (2019). The first-level digital divide shifts from inequalities in physical access to inequalities in material access. New Media and Society, 21:354–375. https://doi. org/10.1177/1461444818797082
White, C., Moberly, H.K., Fausak, E.D., Boulton, C., Shrubb, J., McGillycuddy, L., Everitt, S.M., Nunn, S.D. and Brennan, M.L. (2023). Searching for veterinary evidence: A guide for equine professionals. Equine Veterinary Education, 35: 45–55. https://doi.org/10.1111/eve.13634
Wittenberg, E., Bharel, M., Bridges, J.F.P., Ward, Z. and Weinreb, L. (2016). Using best-worst scaling to understand patient priorities: a case example of papanicolaou tests for homeless women. Annals Family Medicine, 14:359–364. https://doi. org/10.1370/afm.1937
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