Gender differences in attrition rates of hospital-based medical specialty programs: attributable to gender composition of the clinical specialty?


 Background

Since 1999 the Advisory Committee on Medical Manpower Planning (ACMMP) advises the Dutch government on the medical workforce capacity and the intake in training programs, as to achieve or maintain a balance on the labour market. One of the key parameters the ACMMP uses when calculating the required intake in training programs, is the attrition rate.

Methods

In total 11,579 trainees enrolled in hospital-based programs from January 1 st 2003 until 31 st of December 2012, for 26 specialisms. To explore possible explanations for the gender differences in attrition rate per specialty, additional information was gathered: the percentage of males per program, the total number of specialists in training, the duration of the training and the percentage of males currently working in that specialty.

Results

One training program was excluded, due to the small size of that training program (62 trainees) and the large outliers it produced. Regression analyses were done, showing significant explanations of the variation in the difference between male and female attrition rates (Y1), for the proportion of males working in the profession per 01-01-2003 (R 2 : .545, F(27,60), p<.000), the proportion of males in training per 01-01-2003 (R 2 : .417, F(16,01), p<.000) and a small effect for the relationship with the total attrition rate for each training program (R 2 : .163, F(4,46), p<.046). There was also a significant effect for the duration of the specialty training (R 2 : .299, F(9,85), p<.005). A Kruskal-Wallis test was preformed to analyse the difference in attrition by type of specialty. The difference between the types of specialisms were significant (H=6,66, p.0,036).

Conclusions

Attrition rates in Dutch hospital-based specialty programs differ between males and females in a way that more males tend to drop-out from training when the specialty is dominated by women and, importantly, vice versa as well. The relationships found needs to be explored, in particular as the duration and nature of the specialty training seem to interact with gender ratios in the training programs and occupations longer training programs tend to have more males on them. Furthermore, more insight is needed in the selection and identification processes among residents in specialty training.


Abstract Background
Since 1999 the Advisory Committee on Medical Manpower Planning (ACMMP) advises the Dutch government on the medical workforce capacity and the intake in training programs, as to achieve or maintain a balance on the labour market. One of the key parameters the ACMMP uses when calculating the required intake in training programs, is the attrition rate.

Methods
In total 11,579 trainees enrolled in hospital-based programs from January 1st 2003 until 31st of December 2012, for 26 specialisms. To explore possible explanations for the gender differences in attrition rate per specialty, additional information was gathered: the percentage of males per program, the total number of specialists in training, the duration of the training and the percentage of males currently working in that specialty.

Results
One training program was excluded, due to the small size of that training program (62 trainees) and the large outliers it produced. Regression analyses were done, showing signi cant explanations of the variation in the difference between male and female attrition rates (Y1), for the proportion of males working in the profession per 01-01-2003 (R 2 : .545, F(27,60), p < .000), the proportion of males in training per 01-01-2003 (R 2 : .417, F(16,01), p < .000) and a small effect for the relationship with the total attrition rate for each training program (R 2 : .163, F(4,46), p < .046). There was also a signi cant effect for the duration of the specialty training (R 2 : .299, F(9,85), p < .005). A Kruskal-Wallis test was preformed to analyse the difference in attrition by type of specialty. The difference between the types of specialisms were signi cant (H = 6,66, p. 0,036).

Conclusions
Attrition rates in Dutch hospital-based specialty programs differ between males and females in a way that more males tend to drop-out from training when the specialty is dominated by women and, importantly, vice versa as well. The relationships found needs to be explored, in particular as the duration and nature of the specialty training seem to interact with gender ratios in the training programs and occupations longer training programs tend to have more males on them. Furthermore, more insight is needed in the selection and identi cation processes among residents in specialty training.

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In virtually every country in the world, the demand of health and social workers will increase steadily over the next decade. Projections indicate that the demand will rise to 80 million workers, which is almost double the supply in the base year (2013, 41 million health workers) (Liu et al., 2017). The World Health Organisation estimated that this leads to a healthcare workforce gap of around 14.5 million by 2030 (WHO, 2016). Health workforce planning is crucial in selecting and implementing the correct policy measures to address the issues of future shortages timely (Ono et al, 2013;Kroezen et al., 2018). The Netherlands has a long tradition in health workforce planning for physicians (Van Greuningen, 2016).
Since 1999 the Advisory Committee on Medical Manpower Planning (ACMMP) advises the Dutch government and sector stakeholders on the medical workforce capacity and the intake in training programs. The latest reports, presented to the government in December 2019, encompass 79 professions and 145,000 fte within the health care sector (ACMMP/Capaciteitsorgaan, 2019). Internationally, the planning and policy model governed by the ACMMP is considered as a 'best practice', as there have been relatively low shortages in most of the medical workforce occupations since the system of health workforce planning started in 1999 (Britnell, 2019).
The ACMMP advises, amongst other professions, on the census-based intake in 26 hospital-based specialty programs for doctors of medicine (MD). A MD can apply for a training position within a hospital-based specialty program after obtaining a Master's degree in Medicine, which, in the Netherlands, consists of a 3-year Bachelor followed by a 3-year Master program at medical school.
One of the key parameters the ACMMP take into account when calculating the required intake in training programs to achieve or maintain a balance on the labour market, is the attrition rate. For this article we  (Burgos and Josephson, 2014). While there is research on surgical specialties and the differences in attrition rates due to the lack of female role models, there does not seem to be research on gender differences in attrition rates in specialties where there are more female doctors and hence less male role models.
The empirical bases of this paper is the availability of data on attrition rates since 2003 for all the hospital-based specialties in the Netherlands. In general the last decade, attrition rates vary between 10%-12%, with outliers ranging from 26,4% to 3% (ACMMP/Capaciteitsorgaan, 2010, 2013, 2016 and 2019). Although attrition rates have been published per specialism, for several periods, little attention has been paid so far to their differences by gender. At the beginning of the data time series, the reason for this was lack of statistical power: for some specialties the group of males or females within a particular hospital-based specialty program was too small to calculate the attrition rates by gender. But as the database on attrition rates has expanded over the last two decades, these data limitations are considerably reduced. Based on data that allows analyses on gender differences within attrition rates per specialty in the Netherlands, the aim this paper is to describe these differences and explain them from different perspectives.

Methods
Aim and design: The aim of this study is to gain insight into the differences between attrition of male and female hospital-based specialists in training. The analyses were based on a historical database of attrition rates, calculated and retrieved from the so called "Registratiecommissie Geneeskundig Specialismen" (Registration Committee Medical Specialists). This Committee has extensive, detailed and up to date information on all medical specialists in training in the Netherlands, their planned training program, including all the cases of attrition.
Description of the data set: Although older data sets were available, data from the Registration  Table 1 is based on these 11,579 enrolees of which 4,868 were male and 6,711 were female (58%) and shows the attrition rates per training program for both males and females. An extra column was added, calculating the difference between male and female attrition (male attrition rate minus female attrition rate). To explore possible explanations for the gender differences in attrition rate by specialty, additional information was gathered: the percentage of males per program, the total number of specialists in training, the duration of the training and the percentage of males currently working in that specialty. Outlier analysis: Descriptive analyses based on Table 1 shows one outlier: cardiothoracic surgery. For this specialty the difference in attrition between males and females is -42%, where the average for all specialties is -2,7%. The attrition rate for cardiothoracic surgery is based on a total of 62 trainees in 10 years, while the average for other training programs is 445, ranging from 62 to 1.580 trainees. Including this outlier will skew the distribution of the dependent variable Y1 in the data set (Anderson-Darling value: 1.260), whereas excluding it changes the distribution to a normal distribution (Anderson-Darling value: 0.886). Based on this outlier analysis, depicted by Figures 2 and 3, it was decided to exclude cardiothoracic surgery as a specialty for further analysis.

Results
Four OLS regression analyses were executed to explain the variation in 'Y1', gender differences in attrition rate, by the dependent variables 'X1' to 'X4' at the level of the 25 (remaining) specialties or training programmes. A Kruskal-Wallis test was done to analyse the gender differences in attrition rate by type specialty training ('X5'), as the number of observations per subgroups (specialty) were relatively small.
Results of the rst regression analysis showed the strongest predictor for X2, the proportion of males working in the profession per 01-01-2003. 55% of the variation in the difference in attrition rates is explained by this dependent variable, a signi cant nding (R 2 : .545, F(27,60), p<.000). Figure 4 depicts this result. The regression model shows that residuals were normally distributed, giving no signs for other outliers. Also, the prediction interval for the regression model equation felt within the 95% boundaries.
The negative and signi cant coe cient implies that the lower the percentage of males working in a speciality, the higher the difference in attrition rate between males and females that are training for that specialty (top left hand of the tted line plot, gure 4). Speci cally, in the specialties with lower percentages of males working, males have higher drop-out rates compared to females in training. The opposite can obviously be concluded as well, as the lower right end of the tted line plot in gure 4 implies: in specialties with more males working in that profession, the drop-out of females in training is signi cantly higher.
Another OLS regression analysis was done for the relationship between Y1 and the 'X1', the proportion of males in training. This analysis showed that 42% of the variation in the gender difference in attrition rates was explained by this predictor, as signi cant nding (R 2 : .417, F(16,01), p<.000), and depicted by Figure  5. Residuals were normally distributed, the prediction interval for this regression equation felt within the 95% boundaries. This negative and signi cant coe cient implies that the lower the percentages of males in training in a specialty, the higher the difference in attrition between males and females in training for that speciality (top left hand of the tted line plot, gure 5). In contrast to the previous regression analysis result however, the speci c result is that less male residents drop-out if the proportion of males is higher in a specialty. And vice versa, shown by the lower right end of the tted line plot ( gure 5): if specialties have more males in training, more females will stop their training before completion, i.e. females have signi cant higher attrition rates.
Third, OLS regression analysis was done to analyse the relationship between difference in male and female attrition rates and the total attrition rate for each training program ('X3'). The result can be summarized as a relative small but signi cant effect (R 2 : .163, F(4,46), p<.046). From Figure 6, it can be derived that for specialty training programs where the overall attrition rates are higher, the difference in attrition between males and females is higher as well (top/right side of gure 6). Likewise, in specialties where the overall drop-out rates in the training program are lower, the difference in attrition between males and females in training for that speciality is lower as well (bottom/left side of gure 6).
A fourth OLS regression analysis was performed to explore the relationship between the difference in attrition between males and females in training, and the duration of the specialty training ('X4'). In sum, it can be showed this relation is negative and signi cant (R 2 : .299, F(9,85), p<.005), see gure 7. Longer specialty training programs thus show larger differences in attrition between males and females in training.
In a nal step, the differences between the specialties as such were explored ('X5'), in particular the distinction between surgical and other specialties. This is partly related to the previous analysis as most surgical specialties also have the highest training duration. A Kruskal-Wallis test was preformed to analyse the difference in attrition between males and females in training by type of specialty. The difference between the types of specialisms were signi cant (H=6,66, p.0,036). The ranking results of the Kruskal-Wallis test implied that the gender differences in attrition rate was negative for 'surgical' specialisms (Z-value -1,98), positive for 'auxillary' specialisms (Z-value 2,29) and ranked in between for the 'non-surgical' specialisms (Z-value -0,11).

Discussion
Historical data (2003-2013) on attrition from 25 Dutch hospital-based medical specialty training programs were analysed, to gain insight in the differences between male and female residents and their attrition rate by specialty. Signi cant relationships were found between gender differences in attrition rate on the one hand, and the gender composition of both the specialism and the training program on the other. There is also a relationships between gender differences in attrition rate, the duration of the program, the overall attrition rates and the surgical versus non-surgical type of specialties. These latter relationships can be interactive as male dominated training programs tend to be surgical and thus longer in duration whereas female dominated programs are non-surgical and shorter in duration.
Although there have been publications on higher attrition rates for females in surgical training programs where males are the majority in training and occupation (Khoushhal et al., 2017), to our knowledge, no previous outcome has been reported that similarly more males tend to drop-out from training programs where women outnumber men. This highly interesting result might by explained from social identity theory. Social identity theory "refers to an individual's self-concept in relation to his or her membership of social groups" (Burford, 2012, p.144). This concept of self-categorisation, e.g. whether or not an individual identi es his or herself with other members of the group, might explain our results. It implies that male and female residents differ in whether or not he/she identi es him or herself with the speci c speciality, depending on their t with this 'accessible group'. It requires further study how and why male and female specialists in training either match with in-group differences versus out-group differences depending on the gender composition and other characteristics of the specialty (Burford, 2012). While a male student in training in a female 'dominated' profession might (subconsciously) not identify as easily with the group identity as his female counterpart in training, the opposite can also be the case. Selection and segregation theory might shed further light on the roots of this identi cation process (Gerber and Cheung, 2008). These theories point at persistent gender differences in job values and aspirations that shape choices about what types of skills to seek in the course of education. Young men are held to emphasize economic wealth, status, and prestige in their de nition of an ideal job, whereas for women the social and altruistic opportunities offered by the job are more important (Marini et al., 1996;Jonsson, 1999; Van de Werfhorst and Kraaykamp, 2001). These 'social expectations' regarding job-related gender roles become internalized as preferences (Halaby, 2003), and can be reinforced by 'intergenerational transmission of eld choices', i.e. that youngsters are likely to follow their parents' footsteps (Van de Werfhorst et al. (2001). According to Hearn and Olzak (1981) women also place more weight on supportive departmental culture and positive personal interactions with teaching staff, whereas men on the external rewards. Another relevant nding by Solnick (1995) in line with segregation theory, is that women at women's colleges were more likely to switch into traditionally male-dominated elds during college, than are women enrolled at coeducational institutions because of the supportive cultural and academic environments in women's colleges.
The implications of our ndings is that in trying to resolve attrition issues it is relevant to zoom out and further analyse data from larger groups to understand trends in attrition and factors that could possibly be of in uence.

Conclusions
Attrition rates in Dutch hospital-based specialty programs differ between males and females in a way that more males tend to drop-out from training when the specialty is dominated by women and vice versa. These results were based on a complete nation-wide database, with historical data of over 11,000 trainees from 1st of January 2003 until the 31st of December 2013. Still, the relationships found needs to be explored, in particular how the duration and nature of the specialty training interacts with the gender ratios in the medical training programs and occupations -as these factors are also related to gender differences in attrition rates. Furthermore, more insight is needed in the selection and identi cation processes among residents in specialty training.

Declarations
Ethics approval and consent to participate Not applicable.

Consent for publication
Not applicable.

Availability of data
The datasets generated during and/or analysed during the current study are not publicly available due the contractual agreement with Registration Commissie Geneeskundig Specialismen but are available from the corresponding author on reasonable request. Figure 1 Difference between male and female total attrition rate, 2003-2013, per speciality (including % of female trainees, excluding cardiothoracic surgery).   Linear regression analysis for the difference in attrition between males and females in training, and the proportion of males working within the specialty (n=25) Figure 5 Linear regression analysis for the difference in attrition between males and females in training and the proportion of males in training for the specialty (n=25). Linear regression analysis for the difference in attrition between males and females in training and the total attrition rate of the specialty training (n=25) Figure 7 Linear regression analysis for difference in attrition between males and females in training and the duration of specialty training.