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Dan Med J. 2013 Sep;60(9):A4692.

Semi-structured interview is a reliable and feasible tool for selection of doctors for general practice specialist training.

Author information

1
Postgraduate Deanery and Office of Medical Education, Faculty of Medicine, University of Southern Denmark, Søkildevej 31, Svendborg, Denmark. jesper.isaksen@dadlnet.dk

Abstract

INTRODUCTION:

In order to optimise the selection process for admission to specialist training in family medicine, we developed a new design for structured applications and selection interviews. The design contains semi-structured interviews, which combine individualised elements from the applications with standardised behaviour-based questions. This paper describes the design of the tool, and offers reflections concerning its acceptability, reliability and feasibility.

MATERIAL AND METHODS:

We used a combined quantitative and qualitative evaluation method. Ratings obtained by the applicants in two selection rounds were analysed for reliability and generalisability using the GENOVA programme. Applicants and assessors were randomly selected for individual semi-structured in-depth interviews. The qualitative data were analysed in accordance with the grounded theory method.

RESULTS:

Quantitative analysis yielded a high Cronbach's alpha of 0.97 for the first round and 0.90 for the second round, and a G coefficient of the first round of 0.74 and of the second round of 0.40. Qualitative analysis demonstrated high acceptability and fairness and it improved the assessors' judgment. Applicants reported concerns about loss of personality and some anxiety. The applicants' ability to reflect on their competences was important.

CONCLUSION:

The developed selection tool demonstrated an acceptable level of reliability, but only moderate generalisability. The users found that the tool provided a high degree of acceptability; it is a feasible and useful tool for -selection of doctors for specialist training if combined with work-based assessment. Studies on the benefits and drawbacks of this tool compared with other selection models are relevant.

FUNDING:

not relevant.

TRIAL REGISTRATION:

not relevant.

PMID:
24001460
[Indexed for MEDLINE]

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