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Analysing the opinions of UK veterinarians on practice-based research using corpus linguistic and mathematical methods

Huntley, Selene J.; Mahlberg, Michaela; Wiegand, Viola; van Gennip, Yves; Yang, Hui; Dean, Rachel S.; Brennan, Marnie L.

Authors

Selene J. Huntley

Michaela Mahlberg

Viola Wiegand

Yves van Gennip

Hui Yang

Rachel S. Dean



Abstract

The use of corpus linguistic techniques and other related mathematical analyses have rarely, if ever, been applied to qualitative data collected from the veterinary field. The aim of this study was to explore the use of a combination of corpus linguistic analyses and mathematical methods to investigate a free-text questionnaire dataset collected from 3796 UK veterinarians on evidence-based veterinary medicine, specifically, attitudes towards practice-based research (PBR) and improving the veterinary knowledge base.

The corpus methods of key word, concordance and collocate analyses were used to identify patterns of meanings within the free text responses. Key words were determined by comparing the questionnaire data with a wordlist from the British National Corpus (representing general English text) using cross-tabs and log-likelihood comparisons to identify words that occur significantly more frequently in the questionnaire data. Concordance and collocation analyses were used to account for the contextual patterns in which such key words occurred, involving qualitative analysis and Mutual Information Analysis (MI3). Additionally, a mathematical topic modelling approach was used as a comparative analysis; words within the free text responses were grouped into topics based on their weight or importance within each response to find starting points for analysis of textual patterns.

Results generated from using both qualitative and quantitative techniques identified that the perceived advantages of taking part in PBR centred on the themes of improving knowledge of both individuals and of the veterinary profession as a whole (illustrated by patterns around the words learning, improving, contributing). Time constraints (lack of time, time issues, time commitments) were the main concern of respondents in relation to taking part in PBR. Opinions of what vets could do to improve the veterinary knowledge base focussed on the collecting and sharing of information (record, report), particularly recording and discussing clinical cases (interesting cases), and undertaking relevant continuing professional development activities. The approach employed here demonstrated how corpus linguistics and mathematical methods can help to both identify and contextualise relevant linguistic patterns in the questionnaire responses. The results of the study inform those seeking to coordinate PBR initiatives about the motivators of veterinarians to participate in such initiatives and what concerns need to be addressed. The approach used in this study demonstrates a novel way of analysing textual data in veterinary research.

Citation

Huntley, S. J., Mahlberg, M., Wiegand, V., van Gennip, Y., Yang, H., Dean, R. S., & Brennan, M. L. (2018). Analysing the opinions of UK veterinarians on practice-based research using corpus linguistic and mathematical methods. Preventive Veterinary Medicine, 150, https://doi.org/10.1016/j.prevetmed.2017.11.020

Journal Article Type Article
Acceptance Date Nov 21, 2017
Online Publication Date Dec 5, 2017
Publication Date Feb 1, 2018
Deposit Date Jan 3, 2018
Publicly Available Date Jan 3, 2018
Journal Preventive Veterinary Medicine
Print ISSN 0167-5877
Electronic ISSN 1873-1716
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 150
DOI https://doi.org/10.1016/j.prevetmed.2017.11.020
Keywords Evidence-based veterinary medicine; Practice-based research; Veterinarian; Veterinary surgeon; Topic modelling; Corpus linguistic analysis; Corpus linguistics; Survey; Questionnaire
Public URL http://eprints.nottingham.ac.uk/id/eprint/48917
Publisher URL https://www.sciencedirect.com/science/article/pii/S0167587717300223
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0





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