Farm animal careers and perception of 'fit' in undergraduate veterinary students: A mixed methods study

Vet Rec. 2023 Feb;192(4):e2339. doi: 10.1002/vetr.2339. Epub 2022 Nov 7.

Abstract

Background: Recruitment and retention of farm veterinarians have been the focus of recent research. Previous work suggests that a feeling of 'fit' is important for students to consider a farm career. The aim of this study was to identify whether students feel that they 'fit' in farm practice and reasons for their answer.

Methods: An online survey was distributed to students at all British and Irish veterinary schools. A mixed methods approach was considered, with thematic analysis on free text answers and regression analysis on demographic variables.

Results: Thematic analysis identified six themes: career opportunities, nature of farm veterinary work, relationships and interactions, individual experiences, expectations and perceptions, and no perceived barriers. Females, marginalised ethnic groups and those from an urban/suburban background were all identified as having significantly (p < 0.05) less agreement with the statement 'I feel able to pursue a career in farm practice'.

Limitations: Survey limitations include those with a clear bias being likely to respond. However, alignment of the qualitative and quantitative results increased confidence in the findings of this mixed methods approach.

Conclusion: This study confirms that biases that exist within wider society do have an influence on veterinary undergraduates' intentions to pursue a farm animal career. This is vital to consider both at a university level and when considering students' experiences on placements. Urgent action is required to improve inclusivity in the farm animal veterinary sector.

Keywords: inclusivity; mixed methods; recruitment; thematic analysis; veterinary education.

MeSH terms

  • Career Choice*
  • Ethnic and Racial Minorities / statistics & numerical data
  • Farms
  • Female
  • Humans
  • Perception
  • Schools, Veterinary* / statistics & numerical data
  • Students* / statistics & numerical data
  • Surveys and Questionnaires
  • Veterinary Medicine* / classification
  • Veterinary Medicine* / statistics & numerical data