Analysing the opinions of UK veterinarians on practice-based research using corpus linguistic and mathematical methods
Autor: | Hui Yang, Selene J. Huntley, Marnie L. Brennan, Michaela Mahlberg, Viola Wiegand, Yves van Gennip, Rachel Dean |
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Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
Topic model
Veterinary Medicine Veterinary surgeon Relation (database) 040301 veterinary sciences Attitude of Health Personnel Concordance Knowledge Bases Qualitative property Veterinarians Practice-based research 0403 veterinary science Corpus linguistic analysis Food Animals Corpus linguistics British National Corpus Surveys and Questionnaires Survey Evidence-based veterinary medicine 060201 languages & linguistics Veterinarian Collocation Evidence-Based Medicine business.industry Questionnaire Linguistics 06 humanities and the arts 04 agricultural and veterinary sciences Models Theoretical United Kingdom Knowledge base 0602 languages and literature Animal Science and Zoology business Psychology Topic modelling |
ISSN: | 0167-5877 1873-1716 |
Popis: | 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. |
Databáze: | OpenAIRE |
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