In:
BMC Nursing, Springer Science and Business Media LLC, Vol. 21, No. 1 ( 2022-10-17)
Abstract:
The recent surge in applications to nursing in the United Kingdom together with the shift towards providing virtual interviews through the use of video platforms has provided an opportunity to review selection methodologies to meet a new set of challenges. However there remains the requirement to use selection methods which are evidence-based valid and reliable even under these new challenges. Method This paper reports an evaluation study of applicants to nursing and midwifery and reports on how to plan and use online interviews for in excess of 3000 applicants to two schools of nursing in Northern Ireland. Data is reported from Participants, Assessors and Administrators who were asked to complete an online evaluation using Microsoft Forms. Results A total of 1559 participants completed the questionnaire. The majority were aged 17–20. The findings provide evidence to support the validity and reliability of the online interview process. Importantly the paper reports on the design and implementation of a fully remote online interview process that involved a collaboration with two schools of nursing without compromising the rigour of the admissions process. The paper provides practical, quantitative, and qualitative reasons for concluding that the online remote selection process generated reliable data to support its use in the selection of candidates to nursing and midwifery. Conclusion There are significant challenges in moving to online interviews and the paper discusses the challenges and reflects on some of the broader issues associated with selection to nursing and midwifery. The aim of the paper is to provide a platform for discussion amongst other nursing schools who might be considering major changes to their admissions processes.
Type of Medium:
Online Resource
ISSN:
1472-6955
DOI:
10.1186/s12912-022-01058-y
Language:
English
Publisher:
Springer Science and Business Media LLC
Publication Date:
2022
detail.hit.zdb_id:
2091496-9
