Art & science research
How nurse leaders are connected internationally Benton DC, Ferguson SL (2014) How nurse leaders are connected internationally. Nursing Standard. 29, 16-18, 42-48. Date of submission: April 13 2014; date of acceptance: July 15 2014.
Abstract Aim To determine whether communication networks exist in a diverse and competitively selected cohort of nurse leaders, and to identify variables that explain any patterns of connection. Method Twenty seven nurse leaders completed a form to ascertain the presence and strength of communication between participants. Data were analysed using social network analysis, generating a visualisation of the network and associated quantitative measures. Results Participants were poorly connected. Those connections that did exist centred on geographic proximity and participation in regional and global bodies. Conclusion These results help improve understanding of how nurse leaders are connected internationally, and prompt inquiry in to how connections might be strengthened.
Authors David Charles Benton Chief executive officer, International Council of Nurses, Geneva, Switzerland. Stephanie L Ferguson Director of ICN-Burdett Global Nursing Leadership Institute, International Council of Nurses, Geneva, Switzerland. Correspondence to: [email protected]
Keywords Communication, nursing leadership, social network analysis
Review All articles are subject to external double-blind peer review and checked for plagiarism using automated software.
Online For related articles visit the archive and search using the keywords above. Guidelines on writing for publication are available at: rcnpublishing.com/r/author-guidelines
THIS RESEARCH EVOLVED from the lead author’s long-standing interest in social network analysis, the co-author’s commitment to programme evaluation, and various issues that drew the attention of both when they were reviewing documents on leadership development and its evaluation. A combination of factors challenged our thinking and provided the opportunity to answer a research question that had not previously been addressed within the nursing literature. Reviewing the history of the International Council of Nurses (ICN), it is clear that a focus on leadership development has been a priority demanded by members for more than a century (Quinn 1989, Brush et al 1999). In the past two decades, this demand has been met by delivering three distinct, yet related, programmes: 1. The Leadership in Negotiation programme caters predominantly for nurse leaders with responsibilities relating to the socio-economic welfare of nurses, their conditions of service and the standing of the profession. 2. The Leadership for Change programme aims to develop strong leadership skills that enable nurses to be more effective at the national level (Shaw 2007, Ferguson 2008). 3. The Global Nursing Leadership Institute (GNLI) programme, the most recent addition, celebrated its fifth year in Geneva, Switzerland, in September 2013. The research reported in this article derives from the GNLI programme, and marks the start of a new investigation into the programme’s effect. The philosophy and structure of the GNLI programme has been described by Blaney (2012). Advanced and strategic leadership development is provided to a highly diverse cohort of around 30 leaders who are well established and recognised as influential leaders in their own countries. Therefore, they have extensive knowledge and skills to draw on and share with their peers. The GNLI programme exposes participants to the latest thinking on a range of topics, delivered by international educators who are leaders in their respective fields. Using a range of leadership skills
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assessment techniques, such as self-reflection and 360o feedback, and a mix of learning sessions, the programme is delivered over seven days in a rural, semi-isolated location near Geneva, where the leaders can focus on their development needs. While our research focused on a cohort of leaders from around the world, the social network analysis techniques we used can be applied at institutional, regional or national levels. In today’s rapidly changing healthcare systems, with their ever more complex challenges, this action learning-based approach can assist in developing shared problem solving among nurses in many settings.
are formed and how they change, Kilduff and Tsai (2003) proposed that research is required to investigate person-level data that would offer insights on how participants were connected internationally.
Global Nursing Leadership Institute: social network analysis
Method
It is often difficult to find a peer who can offer critical yet supportive advice and commentary at the highest levels of nursing leadership. The GNLI programme is designed around an action learning-based approach, and this means that participants can work in teams to reflect and develop an in-depth understanding of their roles as well as the challenges they face, the similarities and differences they experience, and what for them constitutes success or failure. In so doing, participants create new insights, build alliances, and formulate or capture innovative solutions from and with their peers. When reviewing an independent evaluation of the first two cohorts of the GNLI programme, conducted by the Center for Creative Leadership (2011), we noted a comment made by a participant that the experience had extended and strengthened their professional networks. Likewise, one of the major findings identified by the researchers who conducted the study was the GNLI programme’s ability to create lasting international networks (Center for Creative Leadership 2011). These observations prompted a search of the literature to see what had already been undertaken regarding this topic in the field of nursing. A structured search of the literature using both CINAHL (Cumulative Index to Nursing and Allied Health Literature) and PubMed with the search terms ((international) AND (social network analysis) AND (nurs*) AND (leader*)) yielded only three articles, none of which focused exclusively on nurses. After broadening the search by dropping the search term nurs*, the work of Novak (2008) was identified. In his review of the literature, he noted that, despite several attempts to investigate the origins of international networks, the phenomenon remains unclear. He concluded that there was no robust and empirically tested evidence available. To understand how networks
Aim The aim of this study was to determine whether networks exist in a diverse and competitively selected cohort of international nurse leaders, and if so, whether variables could be identified to explain the pattern of connection between them.
Social network analysis is a tool that can be used to identify the connections between individuals, organisations or other entities (Kadushin 2012). In our study the entities of interest, referred to as nodes or egos, were the nurse leaders who participated in the GNLI cohort of 2013. The connections between the nodes represent the interactions between the leaders and are referred to as ties.
Participant selection
The GNLI programme is advertised every December; potential candidates complete a form, describing their achievements to date, their short-term (within one year) and medium-term (within three to five years) goals, and their vision for the future of nursing. Each application undergoes double-blind review by three leadership experts. Typically, the review panel consists of two nurses who are successful, internationally recognised leaders and in some cases have participated in earlier cohorts. The third expert brings a non-nursing perspective, and is a highly regarded and globally renowned business leader. Each expert scores the applications and these scores, along with limits on the numbers of participants from each country to create the most culturally diverse group possible, are used to identify participants for the cohort. Social network analysis terms this type of group, based on membership of a particular phenomenon (participation in the GNLI cohort), as socio-centric; there is a clear boundary to who is in the group and who is not (Kadushin 2012).
Consent
Participants were given a full description of the aim and design of the study. They were advised that no identifying information would be used in any published work, to protect their anonymity. Participants were advised before data collection began that they would be given an opportunity
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Art & science research to review the results. They were also given the option to decline to participate or to withdraw their consent for their data to be used at any point. All participants agreed and gave their informed consent.
Data collection
Data were collected from 27 nurse leaders selected for the GNLI 2013 cohort, by use of a simple two-page self-completion form. The purpose of this form was to ascertain the presence and strength of communication between participants. Its design was based on guidance offered by Wasserman and Faust (1994), who suggested that the format should be simple and easy to complete, to maximise the likelihood of participation. Since the majority of participants did not have English as a first language, illustrative guidance was offered to assist in the completion of the form. It was pilot tested with a group of similar nurse leaders not selected for the programme. One typographical error was identified and corrected. No other changes were made. The names of all participants were listed down the left-hand side of the form. Participants were asked to place a circle around their own name then place an X in the column that best described the interaction or interactions they had had with the other listed members of the cohort. There were six options to choose from, ranging from ‘I have never heard of this person’ to ‘I frequently communicate with this person’ (Table 1). During coding of the data, a numerical score from 0 to 5 was allocated to indicate the strength of the connections between individuals (Table 1). Since terms such as frequent, regularly and occasional can have different meanings to different people, an illustration of the number of times a person connected over a particular time scale was provided to limit potential error. For example, frequently means at least once a week.
TABLE 1 Options and scoring on the self-completion form Score Strength of connection
Frequency of communication
0
‘I have never heard of this person.’
1
‘I have heard of this person.’
2
‘I have communicated directly with this person in the last year.’
Once in the past year.
3
‘I occasionally communicate with this person.’
Two or three times per year.
4
‘I regularly communicate with this person.’
At least once per month.
5
‘I frequently communicate with this person.’
At least once per week.
Data analysis
Data from the completed forms were transferred to a Microsoft Excel file for importing into the specialist social network analysis software. Huisman and van Duijn (2005) reviewed a range of software that could be used for this purpose. Based on this review, and the relative strengths and weaknesses of the various packages, two programs were identified. The relatively small number of nodes and our need to both visualise the data and conduct quantitative analysis resulted in the selection of UCINET 6 (a software package for the analysis of social network data) and NetDraw (a social network visualisation software program), both available as a single download from https:// sites.google.com/site/ucinetsoftware/home (Borgatti et al 2002). NetDraw 2 enabled the visualisation of the network in steps ranging from those that were most connected down to those who had not heard of one another – that is, were not connected at all. The program plots individuals based on how closely they are connected to others. Hence an individual who is central to all other members of the group is located in the middle of the plot. Those that are furthest away from one another are at the periphery and on opposite sides of the plot. Both UCINET and NetDraw 2 were used to generate the quantitative measures. Several quantitative measures were used to examine either features of the individual node-level data (the leader) or the network as a whole (the entire cohort). Table 2 provides a summary of the measures used, as well as a brief definition and a short explanation of the importance of the measures.
Exploring connections (ties)
Ties were explored by giving participants an opportunity to review the social networks generated from data captured in the self-completion form. This enabled participants to identify and discuss with their peers what they felt were the underlying reasons for the existence of the ties. This exploration of results, assisted by the lead author, was designed to encourage the group to challenge and debate the explanations offered by their peers, thereby strengthening the accuracy of interpretation of the underlying connections being proposed.
Results The GNLI 2013 cohort consisted of 22 women and five men, competitively selected from an applicant pool of 76 women and 25 men. Selected individuals included government chief nursing officers, deans, lecturers and professors, as well as presidents and executive officers of national and
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regional professional associations, trade unions and regulatory bodies. Participants had worked in nursing for 13 to 36 years, with an average of 26 years’ experience.
Visualising the network
Figure 1 provides a visualisation of the social network of the GNLI 2013 cohort on arrival in Geneva, and highlights how the leaders are connected at a step-by-step (strength of connection) level. Each leader is represented by a small square. The program plotted their location, taking into account the strength of the connections between all of the leaders. Relationships between the leaders are represented by straight lines. Figure 1 consists of five plots (a to e) of the same data, ranging from most connected (Figure 1a) to least connected (Figure 1e). Figure 1a displays the most frequent level of communication. There were only two leaders that frequently communicated with each other. The remaining four levels of interaction appear in sequence until Figure 1e, which shows the lowest level of communication, ‘I have heard of this person.’ As the level of connection becomes less strong or frequent, more leaders meet the criteria for connection and form part of the connected
group(s) on the plot. The groups can be referred to as sub-networks and are labelled using the letters A to I. In Figure 1b there are two small sub-networks (B and C) that are relatively far apart. In Figure 1c the same two networks expand (D and E), and in Figure 1d the two existing sub-networks enlarge further and a third sub-network emerges (F-H). It is only at the lowest level of connectivity that the majority of the leaders are connected. Even at this minimal level of connection, there remain six leaders (isolates) who are not connected on the plot. These leaders are individuals who did not know, and were not known by, any of the other participants and are located in the top-left corner of the plots. These plots were presented to the participants, who were asked to explain the pattern of connections that emerged. The participants explored and described the strongest connections, and then worked through the progressively weaker levels of connection. As a result, it was possible to describe the links through the hierarchy illustrated in Figure 2.
Quantitative measures
Individual leader (node level) data were calculated as set out in Table 2. These data are not reported
TABLE 2 Summary of node and network-level quantitative measures of connectedness Individual node level
Network or cohort level
Measure
Definition
Implication
In degree
The number of ties or connections received by a node (Valente 2010).
Helps to identify opinion leaders.
Out degree
The number of ties or connections sent from a node (Valente 2010).
Helps to identify those that are more outgoing and sociable.
Betweenness
The degree to which a node occupies a strategic Nodes with high betweenness scores position where they connect two or more otherwise can play a gatekeeper or liaison role in unconnected subgroups (Garson 2012). a network.
Eigenvector connectedness
A measure of a node’s network importance, which gives greater weight to a node the more it is connected to other highly connected nodes (Garson 2012).
Can identify popular people in a network or individuals who have indirect influence.
Network density
A measure of the number of connections between the nodes compared with the maximum possible number of connections (Kilduff and Tsai 2003).
The higher the proportion, the more dense the network.
Average path length The average number of steps along the shortest paths for all possible connections of pairs of individuals in the network (Scott 2000).
Provides a measure of the efficiency of the information flow.
Network diameter
Provides a measure of the expanse of a network since it gives the number of transmission steps required to communicate fully to all nodes in the network.
The number of links in the shortest path between the furthest pair of nodes (Ahuja et al 1993).
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Art & science research FIGURE 1 Visualisation of networks based on decreasing frequency of interaction (a to e)
here in tabular format, because of space limitations. However, a narrative summary is provided. The majority of participants had low ‘in degree’ and ‘out degree’ scores, indicating that they had few interactions with one another before participating in the GNLI programme (Figure 1a, sub-network A). The exception to this was scores attained by two individuals who had lived and worked in the same country (Nigeria), and a second group of two participants who held leadership roles in countries in the same region, the Caribbean (Figure 1b, sub-network B). The leader with the highest ‘in degree’ score has a voluntary role as the president of a regional nursing body, in addition to her day job. The high score and her position as president are consistent with being an opinion leader. Four participants, all presidents of national nursing associations, had high ‘betweenness’ scores. The participants confirmed that they had developed connections with a range of individuals through their membership of the ICN. Examination of the ‘eigenvector connectedness’ identified three participants with high scores. All three were active in regional nursing groups. In addition, cohort-level results for network density, average path length and network diameter were calculated and showed numerically that, before attending the GNLI programme, the participants were poorly connected. They also show that communication among members had considerable scope for structural improvements which could assist with the quick distribution of messages among group members and the frequency of contact, to reduce delays in dissemination.
Limitation These results are derived from a single cohort and, although such research had not been undertaken before our study, the demographics of the group in relation to age, gender, geographic composition and years of experience are similar to those of previous GNLI cohorts. While no attempt is made to generalise from these findings, the results are most likely to be typical of any internationally selected group of nurse leaders.
Discussion The results presented reinforce the significant role of homophily – the concept that people with similar interests and attributes more frequently engage in common activities and interactions (Feld 1981) – in the structure of networks (Borgatti et al 2013). This is potentially 46 december :: volRCNi.com 29 no 16-18 :: 2014 NURSING STANDARD / RCN Downloaded17from by ${individualUser.displayName} on Feb 03, 2016.©For personal use only. No other usesPUBLISHING without permission. Copyright © 2016 RCNi Ltd. All rights reserved.
problematic in terms of nurse leadership since there is a danger that the solutions needed to address problems may not be found; leaders in regular contact with one another will have similar experiences and tend to offer a limited range of solutions. New, radical and creative solutions to intractable problems are unlikely to emerge from this close group of peers. Therefore ways to access a wider network should be considered. By actively seeking the contributions of individuals who are more distantly or loosely connected to a peer group, more diverse thinking can be accessed (Reagans et al 2004). Parkhe et al (2006) suggested that, within the business community and with the advent of increased globalisation, few topics have been as important as understanding the effect of networks. The same authors added that understanding the structure of networks and the connections between people can provide a means of reshaping global business. Today, we are a long way from understanding the effect of networks on nursing leadership behaviours at the global level, although membership of global and regional groups does seem to have a positive effect on both the size of an individual’s network
and the importance of his or her role. However, before answering the question of how to restructure nursing globally, it might be prudent to address whether the existing connections described in the article can be influenced in both the short and medium term by participating in events such as the GNLI or similar programmes. From our results on network density and the presence of isolates, even at the most superficial
FIGURE 2 Factors influencing connections between the Global Nursing Leadership Institute 2013 cohort Strongest
Weakest
Leaders who work together or have worked with the person in the past. Leaders who come from the same country. Leaders who work in the same region of the world and/or share a common language. Leaders who share common membership of a global organisation or are from the same domain of practice, for example educators or members of the International Council of Nurses. Leaders who: — Are active at national level. — Regularly attend international conferences. — Publish papers.
References Ahuja RK, Magnanti TL, Orlin JB (1993) Network Flows: Theory Algorithms and Applications. Prentice Hall, Upper Saddle River NJ. Blaney P (2012) Senior nursing leadership – capacity building at the global level. International Nursing Review. 59, 1, 40-47. Borgatti SP, Everett MG, Freeman LC (2002) Ucinet for Windows: Software for Social Network Analysis. Analytic Technologies, Harvard MA.
Borgatti SP, Everett MG, Johnson JC (2013) Analyzing Social Networks. Sage Publications, London. Brush B, Lynaugh JE, Boschma G, Rafferty AM, Stuart M, Tomes NJ (1999) Nurses of All Nations: A History of the International Council of Nurses, 1899-1999. Lippincott Williams and Wilkins, Philadelphia PA. Center for Creative Leadership (2011) Global Nursing Leadership Institute. The Evaluation Report for
2009 and 2010 Cohorts. http://leadership.icn.ch/ wp-content/uploads/2014/07/ GNLI_Evaluation_Report.pdf (Last accessed: December 11 2014.) Cross R, Parker A (2004) The Hidden Power of Social Networks: Understanding How Work Really Gets Done. Harvard Business School Press, Boston MA. Effken JA, Gephart SM, Brewer BB, Carley KM (2013) Using *ORA, a network analysis tool, to assess the relationship of handoffs to quality
and safety outcomes. Computers, Informatics, Nursing. 31, 1, 36-44. Feld S (1981) The focused organization of social ties. American Journal of Sociology. 86, 5, 1015-1035. Ferguson SL (2008) Thriving while working on the edge: nurses leading change worldwide. International Nursing Review. 55, 4, 367-368. Garson GD (2012) Network Analysis. Statistical Publishing Associates, Asheboro NC.
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Art & science research levels of connectivity, there is scope for existing national leaders to be more coherently and efficiently connected. We agree with Cross and Parker (2004), who argued that knowing how networks function is important in promoting collaboration across functional, social, demographic and organisational boundaries. Given increased globalisation, the nursing profession needs to be better at learning lessons from others and using the evidence generated by peers worldwide (World Health Organization (WHO) 2013). Reflecting on this point, and based on other studies that have used social network analysis to understand national, local and team-based connections both within the profession and across disciplines, perhaps the time has come for all nurses to understand what social network analysis can offer as a means of improving communication and problem-solving capacity (Effken et al 2013).
Conclusion This article explores how nurses eminent in their own countries are connected internationally and presents baseline information to investigate the effect of the ICN’s GNLI programme.
Huisman M, van Duijn MAJ (2005) Software for social network analysis. In Carrington PJ, Scott J, Wasserman S (Eds) Models and Methods in Social Network Analysis. Cambridge University Press, New York NY, 270-292. Kadushin C (2012) Understanding Social Networks: Theories, Concepts, and Findings. Oxford University Press, Oxford. Kilduff M, Tsai W (2003) Social Networks and Organizations. Sage, Thousand Oaks CA.
Novak D (2008) Leadership of organizational networks: an exploration of the relationship between leadership and social networks in organizations. Unpublished doctoral thesis, School of Global Leadership & Entrepreneurship, Regent University, Virginia Beech VA. http://gradworks. umi.com/3309284.pdf (Last accessed: December 11 2014.) Parkhe A, Wasserman S, Ralston D (2006) New frontiers in network theory development. Academy of Management Review. 31, 3, 560-568.
Novak (2008) contended that international network-building behaviours are complex, elusive and empirically untested. This study is a step towards addressing these issues by providing insights into the importance of geographical proximity and shared membership of international and regional bodies in the formation of communication networks among established nurse leaders. The findings also prompt consideration of whether existing international networks can be restructured in a way that increases network density while avoiding the potential problems caused by homophily. While these results focus on an international group, it is suggested that this approach might also offer valuable insights into how the connections between nurse leaders at national, or even local, levels might be assessed. Such information may prove valuable in determining how new perspectives might exert influence on intractable problems NS Acknowledgement The Global Nursing Leadership Institute is supported by a grant from the Burdett Trust for Nursing.
Quinn S (1989) ICN, Past and Present. Scutari Press, London. Reagans R, Zuckerman E, McEvily B (2004) How to make the team: social networks vs demography as criteria for designing effective teams. Administrative Science Quarterly. 49, 1, 101-133. Scott J (2000) Social Network Analysis: A Handbook. Second edition. Sage Publications, London. Shaw S (2007) International Council of Nurses: Nursing Leadership. Wiley, Oxford.
Valente TW (2010) Social Networks and Health: Models, Methods, and Applications. Oxford University Press, Oxford. Wasserman S, Faust K (1994) Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge. World Health Organization (2013) The World Health Report 2013: Research for Universal Health Coverage. WHO, Geneva.
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How nurse leaders are connected internationally Benton DC, Ferguson SL (2014) How nurse leaders are connected internationally. Nursing Standard. 29, 16-18, 42-48. Date of submission: April 13 2014; date of acceptance: July 15 2014.
Abstract Aim To determine whether communication networks exist in a diverse and competitively selected cohort of nurse leaders, and to identify variables that explain any patterns of connection. Method Twenty seven nurse leaders completed a form to ascertain the presence and strength of communication between participants. Data were analysed using social network analysis, generating a visualisation of the network and associated quantitative measures. Results Participants were poorly connected. Those connections that did exist centred on geographic proximity and participation in regional and global bodies. Conclusion These results help improve understanding of how nurse leaders are connected internationally, and prompt inquiry in to how connections might be strengthened.
Authors David Charles Benton Chief executive officer, International Council of Nurses, Geneva, Switzerland. Stephanie L Ferguson Director of ICN-Burdett Global Nursing Leadership Institute, International Council of Nurses, Geneva, Switzerland. Correspondence to: [email protected]
Keywords Communication, nursing leadership, social network analysis
Review All articles are subject to external double-blind peer review and checked for plagiarism using automated software.
Online For related articles visit the archive and search using the keywords above. Guidelines on writing for publication are available at: rcnpublishing.com/r/author-guidelines
THIS RESEARCH EVOLVED from the lead author’s long-standing interest in social network analysis, the co-author’s commitment to programme evaluation, and various issues that drew the attention of both when they were reviewing documents on leadership development and its evaluation. A combination of factors challenged our thinking and provided the opportunity to answer a research question that had not previously been addressed within the nursing literature. Reviewing the history of the International Council of Nurses (ICN), it is clear that a focus on leadership development has been a priority demanded by members for more than a century (Quinn 1989, Brush et al 1999). In the past two decades, this demand has been met by delivering three distinct, yet related, programmes: 1. The Leadership in Negotiation programme caters predominantly for nurse leaders with responsibilities relating to the socio-economic welfare of nurses, their conditions of service and the standing of the profession. 2. The Leadership for Change programme aims to develop strong leadership skills that enable nurses to be more effective at the national level (Shaw 2007, Ferguson 2008). 3. The Global Nursing Leadership Institute (GNLI) programme, the most recent addition, celebrated its fifth year in Geneva, Switzerland, in September 2013. The research reported in this article derives from the GNLI programme, and marks the start of a new investigation into the programme’s effect. The philosophy and structure of the GNLI programme has been described by Blaney (2012). Advanced and strategic leadership development is provided to a highly diverse cohort of around 30 leaders who are well established and recognised as influential leaders in their own countries. Therefore, they have extensive knowledge and skills to draw on and share with their peers. The GNLI programme exposes participants to the latest thinking on a range of topics, delivered by international educators who are leaders in their respective fields. Using a range of leadership skills
42 december 17from :: volRCNi.com 29 no 16-18 :: 2014 NURSING STANDARD / RCN Downloaded by ${individualUser.displayName} on Feb 03, 2016.©For personal use only. No other usesPUBLISHING without permission. Copyright © 2016 RCNi Ltd. All rights reserved.
assessment techniques, such as self-reflection and 360o feedback, and a mix of learning sessions, the programme is delivered over seven days in a rural, semi-isolated location near Geneva, where the leaders can focus on their development needs. While our research focused on a cohort of leaders from around the world, the social network analysis techniques we used can be applied at institutional, regional or national levels. In today’s rapidly changing healthcare systems, with their ever more complex challenges, this action learning-based approach can assist in developing shared problem solving among nurses in many settings.
are formed and how they change, Kilduff and Tsai (2003) proposed that research is required to investigate person-level data that would offer insights on how participants were connected internationally.
Global Nursing Leadership Institute: social network analysis
Method
It is often difficult to find a peer who can offer critical yet supportive advice and commentary at the highest levels of nursing leadership. The GNLI programme is designed around an action learning-based approach, and this means that participants can work in teams to reflect and develop an in-depth understanding of their roles as well as the challenges they face, the similarities and differences they experience, and what for them constitutes success or failure. In so doing, participants create new insights, build alliances, and formulate or capture innovative solutions from and with their peers. When reviewing an independent evaluation of the first two cohorts of the GNLI programme, conducted by the Center for Creative Leadership (2011), we noted a comment made by a participant that the experience had extended and strengthened their professional networks. Likewise, one of the major findings identified by the researchers who conducted the study was the GNLI programme’s ability to create lasting international networks (Center for Creative Leadership 2011). These observations prompted a search of the literature to see what had already been undertaken regarding this topic in the field of nursing. A structured search of the literature using both CINAHL (Cumulative Index to Nursing and Allied Health Literature) and PubMed with the search terms ((international) AND (social network analysis) AND (nurs*) AND (leader*)) yielded only three articles, none of which focused exclusively on nurses. After broadening the search by dropping the search term nurs*, the work of Novak (2008) was identified. In his review of the literature, he noted that, despite several attempts to investigate the origins of international networks, the phenomenon remains unclear. He concluded that there was no robust and empirically tested evidence available. To understand how networks
Aim The aim of this study was to determine whether networks exist in a diverse and competitively selected cohort of international nurse leaders, and if so, whether variables could be identified to explain the pattern of connection between them.
Social network analysis is a tool that can be used to identify the connections between individuals, organisations or other entities (Kadushin 2012). In our study the entities of interest, referred to as nodes or egos, were the nurse leaders who participated in the GNLI cohort of 2013. The connections between the nodes represent the interactions between the leaders and are referred to as ties.
Participant selection
The GNLI programme is advertised every December; potential candidates complete a form, describing their achievements to date, their short-term (within one year) and medium-term (within three to five years) goals, and their vision for the future of nursing. Each application undergoes double-blind review by three leadership experts. Typically, the review panel consists of two nurses who are successful, internationally recognised leaders and in some cases have participated in earlier cohorts. The third expert brings a non-nursing perspective, and is a highly regarded and globally renowned business leader. Each expert scores the applications and these scores, along with limits on the numbers of participants from each country to create the most culturally diverse group possible, are used to identify participants for the cohort. Social network analysis terms this type of group, based on membership of a particular phenomenon (participation in the GNLI cohort), as socio-centric; there is a clear boundary to who is in the group and who is not (Kadushin 2012).
Consent
Participants were given a full description of the aim and design of the study. They were advised that no identifying information would be used in any published work, to protect their anonymity. Participants were advised before data collection began that they would be given an opportunity
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Art & science research to review the results. They were also given the option to decline to participate or to withdraw their consent for their data to be used at any point. All participants agreed and gave their informed consent.
Data collection
Data were collected from 27 nurse leaders selected for the GNLI 2013 cohort, by use of a simple two-page self-completion form. The purpose of this form was to ascertain the presence and strength of communication between participants. Its design was based on guidance offered by Wasserman and Faust (1994), who suggested that the format should be simple and easy to complete, to maximise the likelihood of participation. Since the majority of participants did not have English as a first language, illustrative guidance was offered to assist in the completion of the form. It was pilot tested with a group of similar nurse leaders not selected for the programme. One typographical error was identified and corrected. No other changes were made. The names of all participants were listed down the left-hand side of the form. Participants were asked to place a circle around their own name then place an X in the column that best described the interaction or interactions they had had with the other listed members of the cohort. There were six options to choose from, ranging from ‘I have never heard of this person’ to ‘I frequently communicate with this person’ (Table 1). During coding of the data, a numerical score from 0 to 5 was allocated to indicate the strength of the connections between individuals (Table 1). Since terms such as frequent, regularly and occasional can have different meanings to different people, an illustration of the number of times a person connected over a particular time scale was provided to limit potential error. For example, frequently means at least once a week.
TABLE 1 Options and scoring on the self-completion form Score Strength of connection
Frequency of communication
0
‘I have never heard of this person.’
1
‘I have heard of this person.’
2
‘I have communicated directly with this person in the last year.’
Once in the past year.
3
‘I occasionally communicate with this person.’
Two or three times per year.
4
‘I regularly communicate with this person.’
At least once per month.
5
‘I frequently communicate with this person.’
At least once per week.
Data analysis
Data from the completed forms were transferred to a Microsoft Excel file for importing into the specialist social network analysis software. Huisman and van Duijn (2005) reviewed a range of software that could be used for this purpose. Based on this review, and the relative strengths and weaknesses of the various packages, two programs were identified. The relatively small number of nodes and our need to both visualise the data and conduct quantitative analysis resulted in the selection of UCINET 6 (a software package for the analysis of social network data) and NetDraw (a social network visualisation software program), both available as a single download from https:// sites.google.com/site/ucinetsoftware/home (Borgatti et al 2002). NetDraw 2 enabled the visualisation of the network in steps ranging from those that were most connected down to those who had not heard of one another – that is, were not connected at all. The program plots individuals based on how closely they are connected to others. Hence an individual who is central to all other members of the group is located in the middle of the plot. Those that are furthest away from one another are at the periphery and on opposite sides of the plot. Both UCINET and NetDraw 2 were used to generate the quantitative measures. Several quantitative measures were used to examine either features of the individual node-level data (the leader) or the network as a whole (the entire cohort). Table 2 provides a summary of the measures used, as well as a brief definition and a short explanation of the importance of the measures.
Exploring connections (ties)
Ties were explored by giving participants an opportunity to review the social networks generated from data captured in the self-completion form. This enabled participants to identify and discuss with their peers what they felt were the underlying reasons for the existence of the ties. This exploration of results, assisted by the lead author, was designed to encourage the group to challenge and debate the explanations offered by their peers, thereby strengthening the accuracy of interpretation of the underlying connections being proposed.
Results The GNLI 2013 cohort consisted of 22 women and five men, competitively selected from an applicant pool of 76 women and 25 men. Selected individuals included government chief nursing officers, deans, lecturers and professors, as well as presidents and executive officers of national and
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regional professional associations, trade unions and regulatory bodies. Participants had worked in nursing for 13 to 36 years, with an average of 26 years’ experience.
Visualising the network
Figure 1 provides a visualisation of the social network of the GNLI 2013 cohort on arrival in Geneva, and highlights how the leaders are connected at a step-by-step (strength of connection) level. Each leader is represented by a small square. The program plotted their location, taking into account the strength of the connections between all of the leaders. Relationships between the leaders are represented by straight lines. Figure 1 consists of five plots (a to e) of the same data, ranging from most connected (Figure 1a) to least connected (Figure 1e). Figure 1a displays the most frequent level of communication. There were only two leaders that frequently communicated with each other. The remaining four levels of interaction appear in sequence until Figure 1e, which shows the lowest level of communication, ‘I have heard of this person.’ As the level of connection becomes less strong or frequent, more leaders meet the criteria for connection and form part of the connected
group(s) on the plot. The groups can be referred to as sub-networks and are labelled using the letters A to I. In Figure 1b there are two small sub-networks (B and C) that are relatively far apart. In Figure 1c the same two networks expand (D and E), and in Figure 1d the two existing sub-networks enlarge further and a third sub-network emerges (F-H). It is only at the lowest level of connectivity that the majority of the leaders are connected. Even at this minimal level of connection, there remain six leaders (isolates) who are not connected on the plot. These leaders are individuals who did not know, and were not known by, any of the other participants and are located in the top-left corner of the plots. These plots were presented to the participants, who were asked to explain the pattern of connections that emerged. The participants explored and described the strongest connections, and then worked through the progressively weaker levels of connection. As a result, it was possible to describe the links through the hierarchy illustrated in Figure 2.
Quantitative measures
Individual leader (node level) data were calculated as set out in Table 2. These data are not reported
TABLE 2 Summary of node and network-level quantitative measures of connectedness Individual node level
Network or cohort level
Measure
Definition
Implication
In degree
The number of ties or connections received by a node (Valente 2010).
Helps to identify opinion leaders.
Out degree
The number of ties or connections sent from a node (Valente 2010).
Helps to identify those that are more outgoing and sociable.
Betweenness
The degree to which a node occupies a strategic Nodes with high betweenness scores position where they connect two or more otherwise can play a gatekeeper or liaison role in unconnected subgroups (Garson 2012). a network.
Eigenvector connectedness
A measure of a node’s network importance, which gives greater weight to a node the more it is connected to other highly connected nodes (Garson 2012).
Can identify popular people in a network or individuals who have indirect influence.
Network density
A measure of the number of connections between the nodes compared with the maximum possible number of connections (Kilduff and Tsai 2003).
The higher the proportion, the more dense the network.
Average path length The average number of steps along the shortest paths for all possible connections of pairs of individuals in the network (Scott 2000).
Provides a measure of the efficiency of the information flow.
Network diameter
Provides a measure of the expanse of a network since it gives the number of transmission steps required to communicate fully to all nodes in the network.
The number of links in the shortest path between the furthest pair of nodes (Ahuja et al 1993).
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Art & science research FIGURE 1 Visualisation of networks based on decreasing frequency of interaction (a to e)
here in tabular format, because of space limitations. However, a narrative summary is provided. The majority of participants had low ‘in degree’ and ‘out degree’ scores, indicating that they had few interactions with one another before participating in the GNLI programme (Figure 1a, sub-network A). The exception to this was scores attained by two individuals who had lived and worked in the same country (Nigeria), and a second group of two participants who held leadership roles in countries in the same region, the Caribbean (Figure 1b, sub-network B). The leader with the highest ‘in degree’ score has a voluntary role as the president of a regional nursing body, in addition to her day job. The high score and her position as president are consistent with being an opinion leader. Four participants, all presidents of national nursing associations, had high ‘betweenness’ scores. The participants confirmed that they had developed connections with a range of individuals through their membership of the ICN. Examination of the ‘eigenvector connectedness’ identified three participants with high scores. All three were active in regional nursing groups. In addition, cohort-level results for network density, average path length and network diameter were calculated and showed numerically that, before attending the GNLI programme, the participants were poorly connected. They also show that communication among members had considerable scope for structural improvements which could assist with the quick distribution of messages among group members and the frequency of contact, to reduce delays in dissemination.
Limitation These results are derived from a single cohort and, although such research had not been undertaken before our study, the demographics of the group in relation to age, gender, geographic composition and years of experience are similar to those of previous GNLI cohorts. While no attempt is made to generalise from these findings, the results are most likely to be typical of any internationally selected group of nurse leaders.
Discussion The results presented reinforce the significant role of homophily – the concept that people with similar interests and attributes more frequently engage in common activities and interactions (Feld 1981) – in the structure of networks (Borgatti et al 2013). This is potentially 46 december :: volRCNi.com 29 no 16-18 :: 2014 NURSING STANDARD / RCN Downloaded17from by ${individualUser.displayName} on Feb 03, 2016.©For personal use only. No other usesPUBLISHING without permission. Copyright © 2016 RCNi Ltd. All rights reserved.
problematic in terms of nurse leadership since there is a danger that the solutions needed to address problems may not be found; leaders in regular contact with one another will have similar experiences and tend to offer a limited range of solutions. New, radical and creative solutions to intractable problems are unlikely to emerge from this close group of peers. Therefore ways to access a wider network should be considered. By actively seeking the contributions of individuals who are more distantly or loosely connected to a peer group, more diverse thinking can be accessed (Reagans et al 2004). Parkhe et al (2006) suggested that, within the business community and with the advent of increased globalisation, few topics have been as important as understanding the effect of networks. The same authors added that understanding the structure of networks and the connections between people can provide a means of reshaping global business. Today, we are a long way from understanding the effect of networks on nursing leadership behaviours at the global level, although membership of global and regional groups does seem to have a positive effect on both the size of an individual’s network
and the importance of his or her role. However, before answering the question of how to restructure nursing globally, it might be prudent to address whether the existing connections described in the article can be influenced in both the short and medium term by participating in events such as the GNLI or similar programmes. From our results on network density and the presence of isolates, even at the most superficial
FIGURE 2 Factors influencing connections between the Global Nursing Leadership Institute 2013 cohort Strongest
Weakest
Leaders who work together or have worked with the person in the past. Leaders who come from the same country. Leaders who work in the same region of the world and/or share a common language. Leaders who share common membership of a global organisation or are from the same domain of practice, for example educators or members of the International Council of Nurses. Leaders who: — Are active at national level. — Regularly attend international conferences. — Publish papers.
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Borgatti SP, Everett MG, Johnson JC (2013) Analyzing Social Networks. Sage Publications, London. Brush B, Lynaugh JE, Boschma G, Rafferty AM, Stuart M, Tomes NJ (1999) Nurses of All Nations: A History of the International Council of Nurses, 1899-1999. Lippincott Williams and Wilkins, Philadelphia PA. Center for Creative Leadership (2011) Global Nursing Leadership Institute. The Evaluation Report for
2009 and 2010 Cohorts. http://leadership.icn.ch/ wp-content/uploads/2014/07/ GNLI_Evaluation_Report.pdf (Last accessed: December 11 2014.) Cross R, Parker A (2004) The Hidden Power of Social Networks: Understanding How Work Really Gets Done. Harvard Business School Press, Boston MA. Effken JA, Gephart SM, Brewer BB, Carley KM (2013) Using *ORA, a network analysis tool, to assess the relationship of handoffs to quality
and safety outcomes. Computers, Informatics, Nursing. 31, 1, 36-44. Feld S (1981) The focused organization of social ties. American Journal of Sociology. 86, 5, 1015-1035. Ferguson SL (2008) Thriving while working on the edge: nurses leading change worldwide. International Nursing Review. 55, 4, 367-368. Garson GD (2012) Network Analysis. Statistical Publishing Associates, Asheboro NC.
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Art & science research levels of connectivity, there is scope for existing national leaders to be more coherently and efficiently connected. We agree with Cross and Parker (2004), who argued that knowing how networks function is important in promoting collaboration across functional, social, demographic and organisational boundaries. Given increased globalisation, the nursing profession needs to be better at learning lessons from others and using the evidence generated by peers worldwide (World Health Organization (WHO) 2013). Reflecting on this point, and based on other studies that have used social network analysis to understand national, local and team-based connections both within the profession and across disciplines, perhaps the time has come for all nurses to understand what social network analysis can offer as a means of improving communication and problem-solving capacity (Effken et al 2013).
Conclusion This article explores how nurses eminent in their own countries are connected internationally and presents baseline information to investigate the effect of the ICN’s GNLI programme.
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Novak D (2008) Leadership of organizational networks: an exploration of the relationship between leadership and social networks in organizations. Unpublished doctoral thesis, School of Global Leadership & Entrepreneurship, Regent University, Virginia Beech VA. http://gradworks. umi.com/3309284.pdf (Last accessed: December 11 2014.) Parkhe A, Wasserman S, Ralston D (2006) New frontiers in network theory development. Academy of Management Review. 31, 3, 560-568.
Novak (2008) contended that international network-building behaviours are complex, elusive and empirically untested. This study is a step towards addressing these issues by providing insights into the importance of geographical proximity and shared membership of international and regional bodies in the formation of communication networks among established nurse leaders. The findings also prompt consideration of whether existing international networks can be restructured in a way that increases network density while avoiding the potential problems caused by homophily. While these results focus on an international group, it is suggested that this approach might also offer valuable insights into how the connections between nurse leaders at national, or even local, levels might be assessed. Such information may prove valuable in determining how new perspectives might exert influence on intractable problems NS Acknowledgement The Global Nursing Leadership Institute is supported by a grant from the Burdett Trust for Nursing.
Quinn S (1989) ICN, Past and Present. Scutari Press, London. Reagans R, Zuckerman E, McEvily B (2004) How to make the team: social networks vs demography as criteria for designing effective teams. Administrative Science Quarterly. 49, 1, 101-133. Scott J (2000) Social Network Analysis: A Handbook. Second edition. Sage Publications, London. Shaw S (2007) International Council of Nurses: Nursing Leadership. Wiley, Oxford.
Valente TW (2010) Social Networks and Health: Models, Methods, and Applications. Oxford University Press, Oxford. Wasserman S, Faust K (1994) Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge. World Health Organization (2013) The World Health Report 2013: Research for Universal Health Coverage. WHO, Geneva.
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