Dropout risks of medical students


 Background The moderation of student dropout is an important aim in the medical training that requires significant resources from individual and national economy points of view. Hungarian medical training has high quality and strong international attraction, although students are exposed to significant stress in the extremely selective and strict training at the beginning, and their professional identity is being shaped between crises. Learning progress is often hampered by recurring exams and grade retentions. Methods In our Study we are going to examine the dropout behaviour of medical students. During our research, the national higher education statistics are being analysed based on the data base of medical students who started in 2010 (N = 977). The question of research is how the rate of dropout people who has finished or exceeded the 6-year long training is forming and what kind of factors limit the risk of dropout. Results Our results indicate that only half of the applicants get admitted to medical training. Half of the admitted applicants could continue without failing, but 30% of them could not obtain absulotorium after 14 semesters. Dropout students are characterized by the early slow-up of their credit accumulations and by making their status passive, which is the shorter-longer termination of their studies. 83.6% of students started in 2010 has been studying in state financed course, and 8% of them has been studying in a self-financed course. 9.4% of state-financed students were dropped out while this rate was 50% from the self-financed course of students. Conclusion According to our consequences, dropout risk can be increased by low credit numbers, passive semesters and the tuition-based financing forms, although dormitory placement can be an advantage.


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The field socialisation of future doctors, the process of the shaping of their professional identity and identifying the factors supporting this are important research topics. Another important question is whether the success of identification with the future role of medical students is determined by their social and demographical characteristics or by the circumstances of their medical studies [16]. Insufficient field socialisation can result in dropout in medical training, individual quit of profession or lack of doctors in case of massive presence of it. The difference of student dropout rates between course fields raised attention to the fact that those who are choosing different fields are affected by diverse factors when it comes to deciding on terminating or continuing their studies. The early formation of professional identity is strengthened by attachments to disciplinary values and relationship nets, besides the high level of requirements of admission and the favourable positional possibilities. These factors can limit the rate of dropout students [18,19].
At the turn of the Millenium to the effect of the appearance of doctor shortage, the government of UK increased the number of students admitted and initiated special development and examinations in favour of their retention [5]. In other countries the incline of the dropout of medical students was examined to the effect of the change in the structure of higher education and it was stated that the temporal distortion of studies increases the risk of dropout [6]. High school results, admission scores and admission year were proved to be a good predicator regarding the success of students getting their degree, and the admission score indicated in advance the finish of studies in a curriculum period [7]. However, longitudinal analyses came to the conclusion, that the increase of dropout rate can be explained by admission politics, the structure of higher education curriculum, the rate of theoretical and practical courses and the increasing tuition fees [5,8,9]. Dropout is further influenced by the hardships of educational costs, the negative effects of taking jobs besides studying, and the fear of being in debt due to the school fees financed by loans [10,11,12,13]. The effective ways of limiting dropout were learning organisation support provided for students (often formative rating, learning methodology courses, group studying), the increase of the rate of practice, problem-based studying and counsel of time-management and stress-handling [14].
Although in Hungary higher education was financed by the state and it was free of tuition, still 40% of the BA students leave higher education without degree. A qualitative research of 2018 examined those students who started a course more than 10 years ago but did not get any degree. Three significant groups of reason caused their dropout: most of them were dropped out due to material reasons, because the student and his family could not handle the travel and living costs of higher education. Others stated that learning hardships, the negative attitude of teachers and administrators, the lack of their helping hand and lack of information caused dropout. According to the third group, the reason of dropout was the disillusionment from their major or institution, and the disappointment in experiences in practice as compared to expectations [16].
In the medical training in Hungary no multi-cycle courses were introduced as compared to other areas at the joining of Bolognai procedures at the turn of the Millenium. So, for example while in the course of economist they introduced the BA and MA courses of 3+2 years, then in the medical, legal and theology courses they kept the single-cycled educational structure. Teacher training was changed to be two-cycled in 2006, and in 2013 they re-set the undivided training in this area too. So future doctors are studying for 6 years in order to obtain diploma. They start their internships and resident years after this so that they can take their medical specialist exam at the end of their 3-5 years long medical course. The extremely long studies delay the becoming of self-sufficient of students and the starting of family. Optimistic future expectations are demolished by the high level of requirements, the extremely difficult studies and the high rate of unsuccessful exams. The inadequate tempo of getting diploma causes labour shortage in certain areas, which is swelled by quit, going to abroad and the aging of medical society [1,15]. In the outstandingly costly medical training 20% of dropout counts as a big waste of resource in an individual and international level too [3]. In the medical training in Hungary until now 3 groups of students were studying according to financing. Hungarian nationality students have been studying financed by the state if they reached the adequate scores at admittance and if they have not exceeded their limit of 7 years. Only some students who started their second degrees or who did not reach admittance scores have started their studies in self-financing courses, but these were only wealthy people.
Mostly foreign students coming from European and Asian countries were studying in selffinanced courses in English. The third group of students includes those foreign people who are coming from poor countries out of Europe within Stipenduim Hungaricum scholarship, whose studies are financed by the Hungarian state with scholarships. The actuality of our research is that the system of financing as a condition of scholastic records was introduced in the systems since 2015 amongst Hungarian medical students who were studying free of charge so far. This new system supervises the scholastic development and grades of students, and those whose scholastic average does not reach 3 out of 5 or who do not get 36 credits yearly, then they loose state finance and have to pay 8000 EUR yearly as a refunding of expenses. Regarding the average income of families, this can mean a significant growth in dropout.

Methods
The aim of the research is to examine the dropout behaviour of Hungarian medical students in the educational structure before the reform. The majority of researches dealing with medical students are built on examinations with less case numbers and with questionnaires, and many times they are analysing samples relating to one or more institutions. In this study we are analysing data from anonym individual higher education data base [3,4]. These anonymised data collected with statistic aim are accumulated and stored by a higher education information system. In this analysis we were focusing on the progress of students of 4 Hungarian universities who started in 2010. The examination of the anonymised individual higher education data base provided us valid information in some samples about the progress of students. During the analysis we were working with the following variants: gender of the student, age of the student, whether the student lived in dormitory, the categorised variant of the number of passive years, finance form and acquired credit numbers.
During our research we used description analysis, where we were examining rate in case of continuous variants, while in case of discrete variants we were examining and comparing frequency. In order to explore the reason of dropout, we have carried out binary logistic regressive analysis, during which we applied the Forward Wald method.
We regarded p<0.05 as a significant result. Analyses were done with the IBM SPSS Statistics 25.0 program package) SPSS, Chicago, IL).

Results
In the general medical course in Hungary the number of applicants and participants is quite stable. We can state that the chance of being applied considering the rate of first applicants and participants is quite low comparing to other undivided courses, as it is usually around 50%. The peculiarity of the 6-year undivided course is that it has dedicated applicants. In case of unsuccessful application, 75-76% of the applicants apply for this same course on the first place when it comes to re-application. In the undivided dentist major this rate is 40-45%. 2/3 of the applicant in the first place apply for this course on the second place also. What is more, every second applicants chose this course on the third place too -only in a different institution. Selection can basically be diverse in institution preferences knowing that the major can only be carried out in full-time course and the majority of applicants and applied will start their studies in state-financed courses (Chart 1). There is a significant relationship between dropout and finance forms, and their change (Pearson Chi 2 p<0,001). The dropout was 63.4% as compared to the average 15.5% amongst those students who remained in self-financed courses, while it was 9.4% amongst those who remained in state-financed course. The dropout is bigger in case of those students who are put from state-financed courses to self-financed courses. Although the coherence between the two variants does not necessarily mean reason-effect relation as there can be financial and educational hardships in the background as well.
The examination of success of students is very interesting based on our data base (Chart 1). We can see that dropout is the lowest (8% and 9%) in state-finances courses while it is the highest (56% and 63%) in self-financed courses.

Chart 1: Scholastic success of students belonging to certain finance groups
In order to test our hypothesis, we used such a binary logistic regressive model on our data, in which the dependent variant was if someone is dropped out or not, while the background variants were those which were in significant relationship with dropout. We were considering the following: gender of student, age of student, whether he lived in dormitory, the categorised variants of the number of passive semesters and finance form.
Besides, we used credit number as a continuous covariant variant.
By applying the Forward Wald method, we got such a model in which the finance form and its change did not increase the chance of dropout. Scholastic factors (number of credits and passive semesters) proved to be a significant model forming variant: the higher value of the formal decreased, while the latter increased the chance of dropout. Our model was tested in the way too that we did not put credit number in the system. In this case besides the number of passive semesters, the self-financed status and the transferring to it (except for 'self-finance then state-finance status too' p=0.197) had a great chance in dropout. In this model dormitory appeared as a preventive factor: those who lived in dormitory during the course had less chance to dropout. Dropout is characterised by the early and fierce slow of credit accumulation and the application of passive semesters. Slow credit accumulation indicates hardships in scholastic performance, since after failed subjects it is not possible in medical training curriculum to take up the next subject that is based on the failed one. Due to scholastic hardships and the slow of credit accumulation, during the first 2 years students are further selected, and 1/3 of dropouts leave the course at this point. In our samples, dropout is really low amongst students with state-financed course in all active semesters, and it was only 9.4% who ceased their studies. In spite of this, 63% of those who had selffinanced courses and 56% of those who were transformed into self-financed courses were dropped out.

Chart 4: Model 2. Result of binary logistic regression
Based on the student data in the data base we carried out a multi-variant analysis in order to identify the factors that influence the chance of dropout the most. The logistic regressive models confirmed that the dynamically collected credit numbers in the examined sample decreased, while the higher number of passive semesters increased the chance of dropout. These two are not fully independent from each other, since the application of passive semester basically means failed exam, so the system could filter those who have scholastic hardships. Finishing studies in state-financed form was itself a factor that increased the possibility of dropout in the sample of 2010 despite that it affected very few students.

Conclusions
Hungarian medical students enter the course with high point numbers and dedication, but still every second students get their diploma out of course time, and 1/3 of them is not able to obtain absulotorium by the end of the course. In medical training dropout is increased by low credit numbers and passive semesters and the self-financed form.
Although dormitory can be an advantage, as it limits the educational costs and the student can gain social capital that can support him in better scholastic performance.
The obstacle of our examination is that after examining significant data base we only get information relating to pass on of only one sample. One-third of them still continued their studies after the closure of data base, which result is unknown. We could have further important connections by examining scholastic rates but based on the data base we can only conclude on unsuccessful course performance, and we do not have data about the formation of scholastic rate in present higher education. Since the filter with scholastic rates means a new selection and the amount of cost is really high, the restrictions for those who enter after reform can bring radical changes. It is important to examine the effect of change in the future as well.

Ethics approval and consent to participate
Not applicable.

Consent to Publish
Not applicable.

Availability of data and material
The datasets used and analysed during the current study are available from the corresponding author on reasonable request.
All data generated and analysed during this study are included in this published article and its supplementary information files.

Competing interests
The authors declare that they have no competing interests.

Figure 1
Scholastic success of students belonging to certain finance groups