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Getting the right balance? A mixed logit analysis of the relationship between UK training doctors’ characteristics and their specialties using the 2013 National Training Survey

OBJECTIVE: To analyse how training doctors’ demographic and socioeconomic characteristics vary according to the specialty that they are training for. DESIGN: Descriptive statistics and mixed logistic regression analysis of cross-sectional survey data to quantify evidence of systematic relationships...

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Autores principales: Rodriguez Santana, Idaira, Chalkley, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5724110/
https://www.ncbi.nlm.nih.gov/pubmed/28801397
http://dx.doi.org/10.1136/bmjopen-2016-015219
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author Rodriguez Santana, Idaira
Chalkley, Martin
author_facet Rodriguez Santana, Idaira
Chalkley, Martin
author_sort Rodriguez Santana, Idaira
collection PubMed
description OBJECTIVE: To analyse how training doctors’ demographic and socioeconomic characteristics vary according to the specialty that they are training for. DESIGN: Descriptive statistics and mixed logistic regression analysis of cross-sectional survey data to quantify evidence of systematic relationships between doctors’ characteristics and their specialty. SETTING: Doctors in training in the United Kingdom in 2013. PARTICIPANTS: 27 530 doctors in training but not in their foundation year who responded to the National Training Survey 2013. MAIN OUTCOME MEASURES: Mixed logit regression estimates and the corresponding odds ratios (calculated separately for all doctors in training and a subsample comprising those educated in the UK), relating gender, age, ethnicity, place of studies, socioeconomic background and parental education to the probability of training for a particular specialty. RESULTS: Being female and being white British increase the chances of being in general practice with respect to any other specialty, while coming from a better-off socioeconomic background and having parents with tertiary education have the opposite effect. Mixed results are found for age and place of studies. For example, the difference between men and women is greatest for surgical specialties for which a man is 12.121 times more likely to be training to a surgical specialty (relative to general practice) than a woman (p-value<0.01). Doctors who attended an independent school which is proxy for doctor’s socioeconomic background are 1.789 and 1.413 times more likely to be training for surgical or medical specialties (relative to general practice) than those who attended a state school (p-value<0.01). CONCLUSIONS: There are systematic and substantial differences between specialties in respect of training doctors’ gender, ethnicity, age and socioeconomic background. The persistent underrepresentation in some specialties of women, minority ethnic groups and of those coming from disadvantaged backgrounds will impact on the representativeness of the profession into the future. Further research is needed to understand how the processes of selection and the self-selection of applicants into specialties gives rise to these observed differences.
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spelling pubmed-57241102017-12-19 Getting the right balance? A mixed logit analysis of the relationship between UK training doctors’ characteristics and their specialties using the 2013 National Training Survey Rodriguez Santana, Idaira Chalkley, Martin BMJ Open Medical Education and Training OBJECTIVE: To analyse how training doctors’ demographic and socioeconomic characteristics vary according to the specialty that they are training for. DESIGN: Descriptive statistics and mixed logistic regression analysis of cross-sectional survey data to quantify evidence of systematic relationships between doctors’ characteristics and their specialty. SETTING: Doctors in training in the United Kingdom in 2013. PARTICIPANTS: 27 530 doctors in training but not in their foundation year who responded to the National Training Survey 2013. MAIN OUTCOME MEASURES: Mixed logit regression estimates and the corresponding odds ratios (calculated separately for all doctors in training and a subsample comprising those educated in the UK), relating gender, age, ethnicity, place of studies, socioeconomic background and parental education to the probability of training for a particular specialty. RESULTS: Being female and being white British increase the chances of being in general practice with respect to any other specialty, while coming from a better-off socioeconomic background and having parents with tertiary education have the opposite effect. Mixed results are found for age and place of studies. For example, the difference between men and women is greatest for surgical specialties for which a man is 12.121 times more likely to be training to a surgical specialty (relative to general practice) than a woman (p-value<0.01). Doctors who attended an independent school which is proxy for doctor’s socioeconomic background are 1.789 and 1.413 times more likely to be training for surgical or medical specialties (relative to general practice) than those who attended a state school (p-value<0.01). CONCLUSIONS: There are systematic and substantial differences between specialties in respect of training doctors’ gender, ethnicity, age and socioeconomic background. The persistent underrepresentation in some specialties of women, minority ethnic groups and of those coming from disadvantaged backgrounds will impact on the representativeness of the profession into the future. Further research is needed to understand how the processes of selection and the self-selection of applicants into specialties gives rise to these observed differences. BMJ Publishing Group 2017-08-11 /pmc/articles/PMC5724110/ /pubmed/28801397 http://dx.doi.org/10.1136/bmjopen-2016-015219 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Medical Education and Training
Rodriguez Santana, Idaira
Chalkley, Martin
Getting the right balance? A mixed logit analysis of the relationship between UK training doctors’ characteristics and their specialties using the 2013 National Training Survey
title Getting the right balance? A mixed logit analysis of the relationship between UK training doctors’ characteristics and their specialties using the 2013 National Training Survey
title_full Getting the right balance? A mixed logit analysis of the relationship between UK training doctors’ characteristics and their specialties using the 2013 National Training Survey
title_fullStr Getting the right balance? A mixed logit analysis of the relationship between UK training doctors’ characteristics and their specialties using the 2013 National Training Survey
title_full_unstemmed Getting the right balance? A mixed logit analysis of the relationship between UK training doctors’ characteristics and their specialties using the 2013 National Training Survey
title_short Getting the right balance? A mixed logit analysis of the relationship between UK training doctors’ characteristics and their specialties using the 2013 National Training Survey
title_sort getting the right balance? a mixed logit analysis of the relationship between uk training doctors’ characteristics and their specialties using the 2013 national training survey
topic Medical Education and Training
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5724110/
https://www.ncbi.nlm.nih.gov/pubmed/28801397
http://dx.doi.org/10.1136/bmjopen-2016-015219
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