© Borgis - New Medicine 1/2013, s. 21-27
Applying the network research matrix methodology to identify and map the international migration of hungarian nurses
Department of Carrier, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary
Dean of the Faculty: Prof. Judit Meszáros, PhD
Nurse migration (like migration in general) is a complex and dynamic process and there are no simple and painless ways to draw a clear picture about it. In the course of the analysis, however, I have discovered a new linked method of describing the system of the migration of nurses. I realized that many ideas originally elaborated by network theory can be adapted to the research on nurse migration and the relationships among the migrants outline a model, which furthermore is empirically measurable.
The new theory provides a more complete and explicit model of this complex phenomenon to guide policy and research. For example, understanding that the consequences of nurse migration should be examined through the eyes of all stakeholders is important for policy makers. This theory could also guide the development of a predictive model of nurse migration to guide health care human resource planning.
Migrants, according to a definition widely used in the relevant scientific literature, are people who stay outside their usual country of residence for at least one year. Estimates by the UN posit the number of international migrants worldwide around 214 million, while internal migration scales even higher, at an estimated 740 million. Thus cca. 1 billion people (i. e. one in seven) live far from their place of birth (and these figures do not include temporary or short-term migration). According to World Bank estimates, the cash flow of money sent home by migrants comes close to USD 400 billion yearly, and is expected to rise by a further 7-8% between 2012 and 2014 in spite of the economic crisis.
Humans have always been on the move, migrating due to reasons as varied as war, famine and persecution, or in search of better working conditions. In the last four decades, international migration started to rise steeply again and the number of migrants doubled. While the specific outcomes of this process are still being explored by a number of researchers, it has already become clear that on the whole, migration can undermine the stability of, and create additional problems for, national economies. One of the sectors where the impact can be felt is health care, with high numbers of professionals leaving their home countries behind.
The healthcare systems of many countries are in crisis, some of them undergoing a loss of balance due to the ongoing emigration of young doctors and nurses. Both emerging economies and developed countries experience a shortage of professionals, but the odds are not even in the migration race. Developed countries face a significant shortage of registered nurses due to demographic features and an ageing medical profession, which is balanced out however by an influx of young nurses attracted by an open society, good working conditions, as well as the opportunities to gain professional experience and growth. Essentially, however, it is all part of the Brain Drain.
Although the extent of shortage is difficult to assess either today or tomorrow, the phenomenon can be observed to occur at a significant rate in many places around the globe. Almost all European countries are facing a shortage in registered nurses.
Migration theories focus on different levels of analysis: micro-level theories concentrate on individual migration decisions, macro-level analyses provide aggregate explanations, while mid-level theories examine household and community level influences on migration (1). The theory most frequently used to explain the migration of nurses is the push/pull theory (where ‘pull” refers to the forces of attraction and ‘push” denotes the opposite). The micro-level framework offers an explanation of why nurses migrate, but does not concern itself with the motives behind the individual”s decision-making (2). Thus the theory lacks a proper foundation while having no credible systemic embeddedness. Thus the analyses are much more descriptive then fit for use at the strategic levels (3).
Aim of the study
My first aim is to understand the role of decision-making by the individual in the migratory process. The initial step is to explore the individual and community areas of the nursing profession, with reference to education, the clinical sector, administrative and research positions that are involved directly and indirectly with nurse migration. According to my hypothesis, nurse migration (like migration in general) is a complex and dynamic process and there are no simple and painless ways to draw a clear picture about it. In the course of the analysis, however, I have discovered a new linked method of describing the system of the migration of nurses. I realized that many ideas originally elaborated by network theory can be adapted to the research on nurse migration and the relationships among the migrants outline a model which furthermore is empirically measurable.
The identification of the attributes, antecedents and consequences represents a framework for a new theory of nurse migration. Although requiring testing and further development, this theory is much more robust than the push/pull theory, which only focuses on the stimuli influencing the decision to migrate. The new theory provides a more complete and explicit model of this complex phenomenon to guide policy and research. For example, understanding that the consequences of nurse migration should be examined through the eyes of all stakeholders is important for policy makers. This theory could also guide the development of a predictive model of nurse migration to guide health care human resource planning.
The difficulty of migration surveys is to localize the migrants. Database analysis of international migrants demonstrates that the immigration statistics of reception countries are clearer and can be used better than the emigration data from the countries of origin. The concept of usual place of residence is a key element in the question of internal and international migration. Nevertheless, migration as a notion construed as based on this concept is less and less fit for identifying, describing and analysing the new kinds of migration processes. Unfortunately, there is not enough valid information on the phenomenon of network-linked migration processes, that is, on the system of migration (4, 7).
Several empirical surveys and research projects have explored the role of the migrant network and the role of social capital in different periods of the migratory process. These research studies revealed that the influence of networks is also discoverable in the selection of migrants: the flows of information through them and the accessible resources affect the migratory decision-making and migration itself. Over the long run, it is these networks of contacts that keep the migration process going. The impact of network connections was proven on two levels: on the individual level, people with connections in the target country will be more likely to migrate, while at the community level, migration will be more frequent where many people have already emigrated from the community or have gained migration experience (5).
Despite their diversity, most real networks share an essential common feature: growth. Pick any network you can think of, the following will be true of it: starting with a few nodes, it grows incrementally through the addition of new nodes, gradually reaching its current size. If we can describe the migratory phenomenon as a network, its growth will be predictable (6).
Formerly, the theory of networks was based on the assumption that networks are created randomly. This was, however, systematically refuted by mathematician Albert-László Barabási, who proved that this assumption does not hold for complex networks: neither the social network nor the biochemical system of living matter is random. Based on the classical network model, every member of the social network would have around the same number of acquaintances, and every Website would be linked to about the same number of page in the World Wide Web. This is not the case however: on the Net, a smaller number of strongly interlinked pages are linked to by millions of connections. Furthermore, these connections show a scale independent as opposed to random distribution. The greatest difference between random and scale independent networks are that the latter contains so-called strongly connected nodes or hubs, with a high number of links (6).
Migration is a process that both depends on, and creates, social networks. The effective units of migration are neither individuals nor households but sets of people linked by acquaintance, kinship, and work experience. Networks connect migrants across time and space. Once begun, migration flows often become self-sustaining, reflecting the establishment of networks of information, assistance and obligations, which develop between migrants in the host society and friends and relatives in the sending area. These networks link populations in origin and receiving countries and ensure that movements are not necessarily limited in time, unidirectional or permanent (8).
On the basis of the above, I wish to map the migration of Hungarian nurses in three network-dependent steps:
1. The description of the connected network medium of the country of origin – the study of the willingness to emigrate of at least two relevant groups.
2. The study of the international migration network of Hungarian nurses through the domestic network of connections.
3. The description of Hungarian migrant nurses” domestic and international network of contacts through the Hungarian non-migrant nurse network.
MATERIAL AND METHODS
I. The assessment of first-year students was carried out in September 2012th on a sample of 571 full-time BSc students at the Semmelweis University Faculty of Health Sciences (the head of the research: Attila Matiscsák). The survey sample distribution was determined proportionally with number of students at the respective departments of the University (nurses, n = 48) (tab. 1), but we considered the distribution by age groups as well. Weighing the data proved to be an important step due to the presence of a higher population of physiotherapist students within the sample.
The differentiation of the sample by specialization is justified because there are measurable and valid differences amongst the students from different fields of health sciences programmes. The differences are exemplified by their age, social background, and their attitude towards labour mobility. The employment of nurses in Hungary is linked essentially to the public health sector (public medical centres, public hospitals); therefore these nurses have confidence in the demands of the Hungarian public sector. This attitude is shared by the auditors of public health, health visitors and also (in some ways) paramedics who have participated in health care training programmes under specific Hungarian regulations. Significant differences in attitude have been recognised amongst physiotherapists, dieticians and midwifes. The willingness of these professionals to migrate is much higher than the others. But the growing number (and desire) of migrating Hungarian nurses, whose reasons to migrate are less obvious, is what makes this research project relevant and timely.
Table 1. Distribution by Training Programmes.
|Training programme ||N ||% |
|Auditor of Public Health||65||11.4|
|Diagnostic Imaging Specialist||53||9.3|
|Total ||571 ||100.0 |
Issues investigated in structural order:
– demographic indicators,
– family background, as a factor determining the choice of career and professional orientation,
– mobility readiness,
– career plans,
– individuals and factors influencing the decision,
– other factors influencing career choice.
Surveying first year students provides highly significant data on what input parameters characterize the profession at the career choice stage, what motivating factors could have affected young people in their choice of profession and what environmental factors might have influenced them. The data may also illuminate whether the educational system may have played the role of shaping motivations and attitudes which the sectoral development strategy could rely on.
The research confirms the results of previous youth studies to the effect that the life strategies and value patterns of the young are fundamentally different from those characterizing adult generation supposedly „in control” (note: also from those of the investigator/author of the present study) and there is a generation gap which it would be necessary to bridge not only in public discourse, but also when adopting the definitions used to describe the target group.
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