A systematic review of nurse-related social network analysis studies

Social Networks as a Tool for Evidence-Based Health Education: Umbrella Review

BACKGROUND

The number of people who access social networking sites continues to increase at an exponential rate. The use of technology is an essential skill for nursing professionals and its development represents a challenge in improving health education, promotion and care. The objective of this systematic review is to analyse the use of social networking sites by healthcare professionals as an intervention tool for evidence-based public health education.

METHODS

The protocol of this umbrella review was registered in the International Prospective Register of Systematic Reviews (CRD42023407249). Searches were carried out in MEDLINE (PubMed), Web of Science, CINAHL, PsycINFO (EBSCOhost), and Cochrane Library of Systematic Reviews, in February 2023. A narrative synthesis of the results was conducted.

RESULTS

1896 articles were found, of which 15 reviews fulfilled the inclusion criteria. Social networks broadened the profession; they were YouTube, X (formerly Twitter), Facebook, and Instagram. The target population was mainly young professionals, and they came across different topic areas that addressed health education.

CONCLUSIONS

It is important to have information backed by scientific evidence to make health decisions. Health professionals active on social networking sites have a unique opportunity to educate the public about health by sharing scientific evidence in an accessible and clear way, which helps to combat misinformation.

Renewing the Nursing Culture: Sustaining the Professional Community of Practice Through the Role of the Preceptor

Culture is the driving frame within which all human action takes form. This article explores the elements and characteristics of culture and applies them to the nursing professional community of practice. As it drills down to the work in the cultural context, it argues for the central role of the preceptor in evidencing the influence of culture. For onboarding nurses and the nursing community, the preceptor becomes the carrier of culture, demonstrating the impact of culture in a way that exhibits its influence and impact on nursing practice and patient care.

Describing nurses' communication about evidence-based practice change: A social network analysis of hospital nurses

BACKGROUND

Nurses play a critical role in providing evidence-based, high-quality care to optimize patient outcomes. Models from implementation science suggest social networks may influence the adoption of evidence-based practices (EBPs). However, few studies have examined this relationship among hospital nurses. Social network analysis (SNA) mathematically evaluates patterns of communication, a critical step in implementation. Exploring hospital nurses' communication networks may provide insight into influences on the adoption of EBPs.

AIMS

This study aimed to describe complete communication networks of hospital nurses for practice changes on inpatient units, including upper level nursing administrators.

METHODS

This descriptive, exploratory, cross-sectional study used SNA on two inpatient units from one hospital. A sociometric survey was completed by nurses (unit to executive level) regarding communication frequency about practice changes. Network-level density, diameter, average path length, centralization, and arc reciprocity were measured. Attribute data were used to explore subnetworks.

RESULTS

Surveys from 148 nurses on two inpatient adult intensive care units (response rates 90% and 98%) revealed high communication frequency. Network measures were similar across the two units and among subnetworks. Analysis identified central (charge nurses and nurse leaders) and peripheral members of the network (new-to-practice nurses). Subnetworks aligned with the weekend and shift worked.

LINKING EVIDENCE TO ACTION

Established communication channels, including subnetworks and opinion leaders, should be used to maximize and optimize implementation strategies and facilitate the uptake of EBPs. Future work should employ SNA to measure the impact of communication networks on promoting the uptake of EBP and to improve patient outcomes.

Team communication patterns during real and simulated trauma resuscitation-a social network analysis

In trauma teams, coordination can be established through a centralised leader. The team can also use a decentralised strategy. In this descriptive study of video-recorded trauma resuscitations, using quantification of qualitative data, Social Network analysis of all real-time communications of eight in-real-life (IRL) and simulated trauma teams explained team social structure. The communication network structures in the simulated scenarios were more centralised using individually directed speech and had a high proportion of communication to update all team members. Such a structure might be the result of work performed in a complexity-stripped simulation environment where simplified task-executions required less interactions, or from work revolving around a deteriorating patient, imposing high demands on rapid decision-making and taskwork. Communication IRL was mostly decentralised, with more variability between cases, possibly due to unpredictability of the IRL case. The flexibility to act in a decentralised manner potentiates adaptability and seems beneficial in rapidly changing situations.Practitioner summary: Efficient collaboration in trauma teams is essential. Communication in in-real-life and simulated trauma teams was analysed using social network analysis. The simulation teams were overall more centralised compared to the IRL teams. The flexibility to act decentralised seems beneficial for emergency teams as it enables adaptability in unpredictable situations.

Nurses are background actors in medical reality television: A character network analysis and call for authentic action

AIM

The aim of this study was to describe how nurses' dialogue compares with that of doctors in the Australian reality television program Emergency and to explain how this dialogue and the use of narration and direct-to-camera monologues contribute to the portrayal of nurses. The final aim was to outline how these findings can inform the actions of nurses, nursing organizations and writers and journalists.

DESIGN

A descriptive study conducted in 2021 and 2022.

METHODS

Character network analysis was used to describe the verbal interaction of nurses and doctors and identify major, minor and background characters. Narration and direct-to-camera monologues were analysed through frequency counts. Cultivation theory was used to interpret the results.

RESULTS

Fifty-four characters were identified, with 19 of these being nurses. Doctors spoke 87.9% of the dialogue. Most of the dialogue (43%) was monologue by doctors directly to the camera. All major characters were doctors, and only one nurse was a minor character. The mean number of mentions by the narrator of a nurse per episode was 4, and 30 for a doctor.

CONCLUSION

The portrayal of nurses in Emergency is inaccurate and the production methods are used to privilege the role of doctors. This finding comes after decades of research showing inaccurate images of nursing in television. Drawing on recent Australian inquiries and the challenges experienced by mental health and aged care nursing, several approaches for collaborative action to improve these images are suggested.

IMPACT

This is the first study of the portrayal of nursing in reality television. These results suggest that much effort is still required even in contemporary reality television to accurately reflect the work and contribution of nurses. It is the shared responsibility of individual nurses, nursing organizations and writers and journalists to accurately portray nurses in the media.

NO PATIENT OR PUBLIC CONTRIBUTION

This network analysis of a postproduction television program did not allow patient or public involvement in the design or analysis.

Comparing workplace violence among nurses and other professionals using online articles: A social network analysis

AIM

To investigate workplace violence in online articles and compare workplace violence-related words characteristics of nurses and other professionals using social network analysis.

BACKGROUND

Workplace violence is a widespread problem across nursing practice. Online articles are useful for the timely identification and management of nurse violence problems.

METHODS

This descriptive exploratory study involved data extraction focused around the search term workplace violence from sources published during January 1990-December 2020 listed in the BIGKinds database, a Korean integrated news database system. The connections between the extracted terms were determined through social network analysis using the programs UCINET and NetDraw.

RESULTS

Our search found 675 articles for nurses and 5,797 articles for other professionals related to workplace violence. Work burden was found to be the primary cause of violence among both nurses and other professionals. Specifically, being a woman was closely related to violence among nurses, and abuse of power was closely related to violence among other professionals.

CONCLUSION

Nurses and other professionals have different vulnerabilities to violence, which require a different approach to addressing violence.

IMPLICATIONS FOR NURSING MANAGEMENT

Nurse managers should provide a healthy work environment, sufficient workforce, and flexible work schedules to protect nurses from workplace violence.

The use of social network analysis in social support and care: a systematic scoping review protocol

BACKGROUND

In recent decades, the literature on Social Network Analysis and health has experienced a significant increase. Disease transmission, health behavior, organizational networks, social capital, and social support are among the different health areas where Social Network Analysis has been applied. The current epidemiological trend is characterized by a progressive increase in the population's ageing and the incidence of long-term conditions. Thus, it seems relevant to highlight the importance of social support and care systems to guarantee the coverage of health and social needs within the context of acute illness, chronic disease, and disability for patients and their carers. Thus, the main aim is to identify, categorize, summarize, synthesize, and map existing knowledge, literature, and evidence about the use of Social Network Analysis to study social support and care in the context of illness and disability.

METHODS

This scoping review will be conducted following Arksey and O'Malley's framework with adaptations from Levac et al. and Joanna Briggs Institute's methodological guidance for conducting scoping reviews. We will search the following databases (from January 2000 onwards): PubMed, MEDLINE, Web of Science Core Collection, SCOPUS, CINAHL, PsycINFO, Cochrane Database of Systematic Reviews, PROSPERO, and DARE. Complementary searches will be conducted in selected relevant journals. Only articles related to social support or care in patients or caregivers in the context of acute illnesses, disabilities or long-term conditions will be considered eligible for inclusion. Two reviewers will screen all the citations, full-text articles, and abstract the data independently. A narrative synthesis will be provided with information presented in the main text and tables.

DISCUSSION

The knowledge about the scientific evidence available in the literature, the methodological characteristics of the studies identified based on Social Network Analysis, and its main contributions will highlight the importance of health-related research's social and relational dimensions. These results will shed light on the importance of the structure and composition of social networks to provide social support and care and their impact on other health outcomes. It is anticipated that results may guide future research on network-based interventions that might be considered drivers to provide further knowledge in social support and care from a relational approach at the individual and community levels.

TRIAL REGISTRATION

Open Science Framework https://osf.io/dqkb5 .

Review of social networks of professionals in healthcare settings-where are we and what else is needed?

Background

Social Network Analysis (SNA) demonstrates great potential in exploring health professional relationships and improving care delivery, but there is no comprehensive overview of its utilization in healthcare settings. This review aims to provide an overview of the current state of knowledge regarding the use of SNA in understanding health professional relationships in different countries.

Methods

We conducted an umbrella review by searching eight academic databases and grey literature up to April 30, 2021, enhanced by citation searches. We completed study selection, data extraction and quality assessment using predetermined criteria. The information abstracted from the reviews was synthesized quantitatively, qualitatively and narratively.

Results

Thirteen reviews were included in this review, yielding 330 empirical studies. The degree of overlaps of empirical studies across included reviews was low (4.3 %), indicating a high diversity of included reviews and the necessity of this umbrella review. Evidence from low- and middle-income countries (LMIC), particularly Asian countries, was limited. The earliest review was published in 2010 and the latest in 2019. Six reviews focused on the construction or description of professional networks and seven reviews reported factors or influences of professional networks. We synthesized existing literature on social networks of health care professionals in the light of (i) theoretical frameworks, (ii) study design and data collection, (iii) network nodes, measures and analysis, and (iv) factors of professional networks and related outcomes. From the perspective of methodology, evidence lies mainly in cross-sectional study design and electronic data, especially administrative data showing “patient-sharing” relationships, which has become the dominant data collection method. The results about the impact of health professional networks on health-related consequences were often contradicting and not truly comparable.

Conclusions

Methodological limitations, inconsistent findings, and lack of evidence from LMIC imply an urgent need for further investigations. The potential for broader utilization of SNA among providers remains largely untapped and the findings of this review may contain important value for building optimal healthcare delivery networks.

PROSPERO registration number

The protocol was published and registered with PROSPERO, the International Prospective Register of Systematic Reviews (CRD42020205996).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12992-021-00772-7.

Nursing Students' Subjective Happiness: A Social Network Analysis

Improving nursing students’ subjective happiness is germane for efficiency in the nursing profession. This study examined the subjective happiness of nursing students by applying social network analysis (SNA) and developing a strategy to improve the subjective happiness of nursing. The study adopted a cross sectional survey to measure subjective happiness and social network of 222 nursing students. The results revealed that the centralization index, which is a measure of intragroup interactions from the perspective of an entire network, was higher in the senior year compared with the junior year. Additionally, the indegree, outdegree, and centrality of the social network of students with a high level of subjective happiness were all found to be high. This result suggests that subjective happiness is not just an individual’s psychological perception, but can also be expressed more deeply depending on the subject’s social relationships. Based on the study’s results, to strengthen self-efficacy and resilience, it is necessary to utilize strategies that activate group dynamics, such as team activities, to improve subjective happiness. The findings can serve as basic data for future research focused on improving nursing students’ subjective happiness by consolidating team-learning social networks through a standardized program approach within a curriculum or extracurricular programs.

Implementation of an interprofessional collaboration in practice program: a feasibility study using social network analysis

BACKGROUND

Due to multimorbidity and geriatric problems, older people often require both psychosocial and medical care. Collaboration between medical and social professionals is a prerequisite to deliver high-quality care for community-living older people. Effective, safe, and person-centered care relies on skilled interprofessional collaboration and practice. Little is known about interprofessional education to increase interprofessional collaboration in practice (IPCP) in the context of community care for older people. This study examines the feasibility of the implementation of an IPCP program in three community districts and determines its potential to increase interprofessional collaboration between primary healthcare professionals caring for older people.

METHOD

A feasibility study was conducted to determine the acceptability and feasibility of data collection and analysis regarding interprofessional collaboration in network development. A questionnaire was used to measure the learning experience and the acquisition of knowledge and skills regarding the program. Network development was assessed by distributing a social network survey among professionals attending the program as well as professionals not attending the program at baseline and 5.5 months after. Network development was determined by calculating the number, reciprocity, value, and diversity of contacts between professionals using social network analysis.

RESULTS

The IPCP program was found to be instructive and the knowledge and skills gained were applicable in practice. Social network analysis was feasible to conduct and revealed a spill-over effect regarding network development. Program participants, as well as non-program participants, had larger, more reciprocal, and more diverse interprofessional networks than they did before the program.

CONCLUSIONS

This study showed the feasibility of implementing an IPCP program in terms of acceptability, feasibility of data collection, and social network analysis to measure network development, and indicated potential to increase interprofessional collaboration between primary healthcare professionals. Both program participants and non-program participants developed a larger, more collaborative, and diverse interprofessional network.

Value of social network analysis for developing and evaluating complex healthcare interventions: a scoping review

OBJECTIVES

Most complex healthcare interventions target a network of healthcare professionals. Social network analysis (SNA) is a powerful technique to study how social relationships within a network are established and evolve. We identified in which phases of complex healthcare intervention research SNA is used and the value of SNA for developing and evaluating complex healthcare interventions.

METHODS

A scoping review was conducted using the Arksey and O'Malley methodological framework. We included complex healthcare intervention studies using SNA to identify the study characteristics, level of complexity of the healthcare interventions, reported strengths and limitations, and reported implications of SNA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews 2018 was used to guide the reporting.

RESULTS

Among 2466 identified studies, 40 studies were selected for analysis. At first, the results showed that SNA seems underused in evaluating complex intervention research. Second, SNA was not used in the development phase of the included studies. Third, the reported implications in the evaluation and implementation phase reflect the value of SNA in addressing the implementation and population complexity. Fourth, pathway complexity and contextual complexity of the included interventions were unclear or unable to access. Fifth, the use of a mixed methods approach was reported as a strength, as the combination and integration of a quantitative and qualitative method clearly establishes the results.

CONCLUSION

SNA is a widely applicable method that can be used in different phases of complex intervention research. SNA can be of value to disentangle and address the level of complexity of complex healthcare interventions. Furthermore, the routine use of SNA within a mixed method approach could yield actionable insights that would be useful in the transactional context of complex interventions.

Identifying integration and differentiation in a Hospital's logistical system: a social network analysis of a case study

Background

Integration, the coordination and alignment of tasks, has been promoted widely in order to improve the performance of hospitals. Both organization theory and social network analysis offer perspectives on integration. This exploratory study research aims to understand how a hospital’s logistical system works, and in particular to what extent there is integration and differentiation. More specifically, it first describes how a hospital organizes logistical processes; second, it identifies the agents and the interactions for organizing logistical processes, and, third, it establishes the extent to which tasks are segmented into subsystems, which is referred to as differentiation, and whether these tasks are coordinated and aligned, thus achieving integration.

Methods

The study is based on case study research carried out in a hospital in the Netherlands. All logistical tasks that are executed for surgery patients were studied. Using a mixed method, data were collected from the Hospital Information System (HIS), documentation, observations and interviews. These data were used to perform a social network analysis and calculate the network metrics of the hospital network.

Results

This paper shows that 23 tasks are executed by 635 different agents who interact through 31,499 interaction links. The social network of the hospital demonstrates both integration and differentiation. The network appears to function differently from what is assumed in literature, as the network does not reflect the formal organizational structure of the hospital, and tasks are mainly executed across functional silos. Nurses and physicians perform integrative tasks and two agents who mainly coordinate the tasks in the network, have no hierarchical position towards other agents. The HIS does not seem to fulfill the interactional needs of agents.

Conclusions

This exploratory study reveals the network structure of a hospital. The cross-functional collaboration, the integration found, and position of managers, coordinators, nurses and doctors suggests a possible gap between organizational perspectives on hospitals and reality. This research sets a basis for further research that should focus on the relation between network structure and performance, on how integration is achieved and in what way organization theory concepts and social network analysis could be used in conjunction with one another.

Exploring the structure of social media application-based information-sharing clinical networks in a community in Japan using a social network analysis approach

OBJECTIVE

Currently, use of social networking services (SNSs) for interprofessional collaboration is increasing. However, few studies have reported on virtual interprofessional interactions in community healthcare services. Revealing such structural characteristics of the networks can provide insight into the functions of the interprofessional information-sharing network and lead to smoother collaboration. Thus, we aimed to explore the structure of SNS-based information-sharing clinical networks.

DESIGN

Social network analysis (SNA).

SETTING

We selected a community in City X in Japan.

DATA COLLECTION

We analysed SNS-based information-sharing clinical network data linked to patients receiving home medical care or care services between January and December 2018. A network was created for each patient to allow healthcare professionals to post and view messages on the web platform. In the SNA, healthcare professions registered in a patient group were represented as nodes, and message posting/viewing relationships were represented as links in the patient network. We investigated the structural characteristics of the target networks using several measures for SNA, including indegree centrality and outdegree centrality, which reflect the number of incoming and outgoing links to/from a node, respectively. Additionally, the professions forming the most central nodes were investigated based on their ranking to identify those with a central role in the networks. Finally, to compare the networks of nursing care levels 1-3 (lighter care requirement) and those with nursing care levels 4-5 (heavier care requirement), we analysed the structural differences in the networks and investigated the roles of healthcare professionals using centrality measures of nodes.

RESULTS

Among 844 groups, 247 groups with any nursing care level data were available for analysis. Increasing nursing care level showed higher density, reciprocity and lower centralisation. Healthcare professions with high indegree centrality (physicians, care workers and physical therapists) differed from those with high outdegree centrality (home care workers, physical therapists, and registered dieticians). Visiting nurses and nurses in the clinic played a central role, but visiting nurses tended to have higher indegree and outdegree centrality, while nurses in the clinic had higher closeness and betweenness centrality in networks with heavier care requirement.

CONCLUSION

The SNS-based information-sharing clinical network structure showed that different professions played some form of a central role. Associations between network structures and patient outcomes, cost effectiveness and other factors warrant further investigation.

Exploring the Stability of Communication Network Metrics in a Dynamic Nursing Context

Network stability is of increasing interest to researchers as they try to understand the dynamic processes by which social networks form and evolve. Because hospital patient care units (PCUs) need flexibility to adapt to environmental changes (Vardaman, Cornell, & Clancy, 2012), their networks are unlikely to be uniformly stable and will evolve over time. This study aimed to identify a metric (or set of metrics) sufficiently stable to apply to PCU staff information sharing and advice seeking communication networks over time. Using Coefficient of Variation, we assessed both Across Time Stability (ATS) and Global Stability over four data collection times (Baseline and 1, 4, and 7 months later). When metrics were stable using both methods, we considered them "super stable." Nine metrics met that criterion (Node Set Size, Average Distance, Clustering Coefficient, Density, Weighted Density, Diffusion, Total Degree Centrality, Betweenness Centrality, and Eigenvector Centrality). Unstable metrics included Hierarchy, Fragmentation, Isolate Count, and Clique Count. We also examined the effect of staff members' confidence in the information obtained from other staff members. When confidence was high, the "super stable" metrics remained "super stable," but when low, none of the "super stable" metrics persisted as "super stable." Our results suggest that nursing units represent what Barker (1968) termed dynamic behavior settings in which, as is typical, multiple nursing staff must constantly adjust to various circumstances, primarily through communication (e.g., discussing patient care or requesting advice on providing patient care), to preserve the functional integrity (i.e., ability to meet patient care goals) of the units, thus producing the observed stability over time of nine network metrics. The observed metric stability provides support for using network analysis to study communication patterns in dynamic behavior settings such as PCUs.

Satisfaction with Social Support Received from Social Relationships in Cases of Chronic Pain: The Influence of Personal Network Characteristics in Terms of Structure, Composition and Functional Content

The worldwide burden of chronic illnesses, constitutes a major public health concern and a serious challenge for health systems. In addition to the strategies of self-management support developed by nursing and health organizations, an individual’s personal network represents a major resource of social support in the long-term. Adopting a cross-sectional design based on personal network analysis methods, the main aim of this study is to explore the relationship between satisfaction with the social support received by individuals suffering chronic pain and the structure, composition, and functional content in social support of their personal networks. We collected personal and support network data from 30 people with chronic pain (20 person’s contacts (alters) for each individual (ego), 600 relationships in total). Additionally, we examined the level of satisfaction with social support in each of the 600 relationships. Bivariate and multivariate tests were performed to analyze the satisfaction with the social support received. Using cluster analysis, we established a typology of the 600 relationships under study. Results showed that higher satisfaction was associated with a balance between degree centrality and betweenness (i.e., measures of network cohesion and network modularity, respectively). Finally, new lines of research are proposed in order to broaden our understanding of this subject.

Analyzing Nursing Leadership at an Academic Historical Event: A Descriptive Study Based on Social Networks

PURPOSE

To analyze the leadership network structure among nursing leaders in Spain identified through the Grupo40Enfermeras y Universidad event.

METHODS

A descriptive cross-sectional study using social network analysis was used. Study sample consisted of 210 individuals, of whom 119 received nominations as referents. Structural analysis of the network was conducted using centrality and cohesion.

RESULTS

A network structure was generated in which different leadership strategies were identified through InDegree, Eigenvector, and Betweenness Centrality. Five leaders were identified as bridges to other individuals using Betweenness. The whole network presented little cohesion although two highly cohesive cores were detected by K-core measurements.

CONCLUSION

A strategy is needed to support nursing leaders with high degree of Betweenness to serve as bridges to connect other nursing leaders.

Nurse and midwife researcher collaboration in eastern sub-Saharan Africa: a social network analysis

AIM

To investigate the collaborative networks among expert clinical nurse and midwifery researchers in eastern and southern Africa.

METHODS

Thirty-eight clinical nurse and midwifery researchers completed an online survey to analyse collaboration between respondents. Data were analysed using social network analysis, generating a network map and associated measurements.

RESULTS

Regional collaboration was poor. Those links that did exist centred on geographic proximity and participation in regional and international organizations.

CONCLUSION

These results help us to understand better ways to strengthen and support nursing and midwifery clinical research in eastern and southern Africa.

IMPLICATIONS FOR NURSING POLICY

Clinical nursing and midwifery research capacity building efforts should focus on supporting collaboration networks among individuals and institutions in the region.

Research trends in Korean medicine based on temporal and network analysis

Background

Much research on Korean medicine has been recently published in Korea. The aim of this study was to determine the research trends in Korean medicine by performing a comprehensive analysis of articles that have been published in Korea using temporal and network analysis methods.

Methods

A total of 29,876 articles from 1963 to 2018 were prepared from OASIS (Oriental Medicine Advanced Searching Integrated System), the largest portal for Korean medicine. After the keywords and years were extracted from the metadata of the articles, an annual frequency matrix was obtained for the keywords. By using the matrix, the temporal trends of the keywords were analyzed by comparing the changes in similarity between the lists of keywords by year. Moreover, to analyze the relationship among research topics, a clustered network was constructed in which a node was a keyword and an edge was a similarity between two keywords.

Results

The temporal trend of the keywords was classified into six chronological phases. The appearance frequency of most keywords tended to increase gradually, but only the keywords “mibyeong,” “systems biology” and “korean medicine hospital” appeared in the most recent phase. The network of keywords was clustered and visualized into thirteen groups with the Gephi software. The main keywords in each group were related to effects such as “anti-inflammation” and “antioxidant,” to diseases such as “allergic rhinitis” and “diabetes” and to therapies such as “herbal acupuncture” and “herbal formula.”

Conclusions

The analysis of the trends determined in this study provides a systematic understanding as well as future research directions in Korean medicine to researchers. In the future, an overall analysis of the research trends in Korean medicine will be done by analyzing articles published in Korea and other countries.

Electronic supplementary material

The online version of this article (10.1186/s12906-019-2562-0) contains supplementary material, which is available to authorized users.

How the study of networks informs knowledge translation and implementation: a scoping review

Background

To date, implementation science has focused largely on identifying the individual and organizational barriers, processes, and outcomes of knowledge translation (KT) (including implementation efforts). Social network analysis (SNA) has the potential to augment our understanding of KT success by applying a network lens that examines the influence of relationships and social structures on research use and intervention acceptability by health professionals. The purpose of this review was to comprehensively map the ways in which SNA methodologies have been applied to the study of KT with respect to health professional networks.

Methods

Systematic scoping review methodology involved searching five academic databases for primary research on KT that employed quantitative SNA methods, and inclusion screening using predetermined criteria. Data extraction included information on study aim, population, variables, network properties, theory use, and data collection methods. Descriptive statistics and chronology charting preceded theoretical analysis of findings.

Results

Twenty-seven retained articles describing 19 cross-sectional and 2 longitudinal studies reported on 28 structural properties, with degree centrality, tie characteristics (e.g., homophily, reciprocity), and whole network density being most frequent. Eleven studies examined physician-only networks, 9 focused on interprofessional networks, and 1 reported on a nurse practitioner network. Diffusion of innovation, social contagion, and social influence theories were most commonly applied.

Conclusions

Emerging interest in SNA for KT- and implementation-related research is evident. The included articles focused on individual level evidence-based decision-making: we recommend also applying SNA to meso- or macro-level KT activities. SNA research that expands the range of professions under study, examines network dynamics over time, extends the depth of analysis of the role of network structure on KT processes and outcomes, and employs mixed methods to triangulate findings, is needed to advance the field. SNA is a valuable approach for evaluating key network characteristics, structures and positions of relevance to KT, implementation, and evidence informed practice. Examining how network structure influences connections and the implications of those holding prominent network positions can provide insights to improve network-based KT processes.

Team Collaboration Networks and Multidisciplinarity in Diabetes Care: Implications for Patient Outcomes

Prevalence of type 2 diabetes mellitus (T2DM) has almost doubled in recent decades and commonly presents comorbidities and complications. T2DM is a multisystemic disease, requiring multidisciplinary treatment provided by teams working in a coordinated and collaborative manner. The application of social network analysis techniques in the healthcare domain has allowed researchers to analyze interaction between professionals and their roles inside care teams. We studied whether the structure of care teams, modeled as complex social networks, is associated with patient progression. For this, we illustrate a data-driven methodology and use existing social network analysis metrics and metrics proposed for this research. We analyzed appointment and HbA1c blood test result data from patients treated at three primary health care centers, representing six different practices. Patients with good metabolic control during the analyzed period were treated by teams that were more interactive, collaborative and multidisciplinary, whereas patients with worsening or unstable metabolic control were treated by teams with less collaboration and more continuity breakdowns. Results from the proposed metrics were consistent with the previous literature and reveal relevant aspects of collaboration and multidisciplinarity.

Exploring Research Topics and Trends in Nursing-related Communication in Intensive Care Units Using Social Network Analysis

This study used social network analysis to identify the main research topics and trends in nursing-related communication in intensive care units. Keywords from January 1967 to June 2016 were extracted from PubMed using Medical Subject Headings terms. Social network analysis was performed using Gephi software. Research publications and newly emerging topics in nursing-related communication in intensive care units were classified into five chronological phases. After the weighting was adjusted, the top five keyword searches were "conflict," "length of stay," "nursing continuing education," "family," and "nurses." During the most recent phase, research topics included "critical care nursing," "patient handoff," and "quality improvement." The keywords of the top three groups among the 10 groups identified were related to "neonatal nursing and practice guideline," "infant or pediatric and terminal care," and "family, aged, and nurse-patient relations," respectively. This study can promote a systematic understanding of communication in intensive care units by identifying topic networks. Future studies are needed to conduct large prospective cohort studies and randomized controlled trials to verify the effects of patient-centered communication in intensive care units on patient outcomes, such as length of hospital stay and mortality.

Relationship of Staff Information Sharing and Advice Networks to Patient Safety Outcomes

OBJECTIVE

The aim of this study was to compare information sharing and advice networks' relationships with patient safety outcomes.

BACKGROUND

Communication contributes to medical errors, but rarely is it clear what elements of communication are key.

METHODS

We investigated relationships of information-sharing and advice networks to patient safety outcomes in 24 patient care units from 3 hospitals over 7 months. Web-based questionnaires completed via Android tablets provided data to create 2 networks using ORA, a social network analysis application. Each hospital provided nurse-sensitive patient safety outcomes.

RESULTS

In both networks, medication errors correlated positively with node count and average distance and negatively with clustering coefficient. Density and weighted density negatively correlated with medication errors and falls in both networks. Eigenvector and total degree centrality correlated negatively with both safety outcomes, whereas betweenness centrality positively related to falls in the information-sharing network.

CONCLUSION

Technology-enabled social network analysis data collection is feasible and can provide managers actionable system-level information.

[Semantic Network Analysis of Online News and Social Media Text Related to Comprehensive Nursing Care Service]

PURPOSE

As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis.

METHODS

The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network.

RESULTS

A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality.

CONCLUSION

This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.

Exploring the Knowledge Structure of Nursing Care for Older Patients With Delirium: Keyword Network Analysis

Prevention of delirium is considered a critical part of the agenda for patient safety and an indicator of healthcare quality for older patients. As the incidence rate of delirium for older patients has increased in recent years, there has been a significant expansion in knowledge relevant to nursing care. The purposes of this study were to analyze the knowledge structure and trends in nursing care for older adults with delirium based on a keyword network analysis, and to provide a foundation for future research. Data analysis showed that knowledge structure in this area consists of three themes of research: postoperative acute care for older patients with delirium, prevention of delirium for older patients in intensive care units, and safety management for the improvement of outcomes for patients with delirium. Through research trend analysis, we found that research on care for patients with delirium has achieved both quantitative and qualitative improvements over the last decades. Concerning future research, we propose the expansion of patient- and family-centered care, community care, specific nursing interventions, and the integration of new technology into care for patients with delirium. These results provide a reference framework for understanding and developing nursing care for older adults with delirium.

Social network analysis: Presenting an underused method for nursing research

AIM

This paper introduces social network analysis as a versatile method with many applications in nursing research.

BACKGROUND

Social networks have been studied for years in many social science fields. The methods continue to advance but remain unknown to most nursing scholars.

DESIGN

Discussion paper.

DATA SOURCES

English language and interpreted literature was searched from Ovid Healthstar, CINAHL, PubMed Central, Scopus and hard copy texts from 1965 - 2017.

DISCUSSION

Social network analysis first emerged in nursing literature in 1995 and appears minimally through present day. To convey the versatility and applicability of social network analysis in nursing, hypothetical scenarios are presented. The scenarios are illustrative of three approaches to social network analysis and include key elements of social network research design.

IMPLICATIONS FOR NURSING

The methods of social network analysis are underused in nursing research, primarily because they are unknown to most scholars. However, there is methodological flexibility and epistemological versatility capable of supporting quantitative and qualitative research. The analytic techniques of social network analysis can add new insight into many areas of nursing inquiry, especially those influenced by cultural norms. Furthermore, visualization techniques associated with social network analysis can be used to generate new hypotheses.

CONCLUSION

Social network analysis can potentially uncover findings not accessible through methods commonly used in nursing research. Social networks can be analysed based on individual-level attributes, whole networks and subgroups within networks. Computations derived from social network analysis may stand alone to answer a research question or incorporated as variables into robust statistical models.

Social Network Analysis of peer-specific safety support and ergonomic behaviors: An application to safe patient handling

This study applied Social Network Analysis (SNA) to test whether advice-seeking interactions among peers about safe patient handling correlate with a higher frequency of equipment use. Patient-care workers (n=38) at a community hospital in Oregon nominated peers they would consult for advice regarding safe patient handling. Results show a positive correlation between identifying more peers for safe patient handling advice and using equipment more frequently. Moreover, nurses with more reciprocal advice seeking nominations used safe patient handling equipment more frequently. However, employees who would be more consulted about safe patient handling by their peers did not use equipment more frequently than nurses with fewer nominations. Despite the small sample size, the magnitude of the adjusted regressions coefficients ranged between 3 to 4 standard deviations. These results suggest that having more or reciprocal sources of peer-based support may trigger ergonomic related behaviors such as frequent utilization of equipment.

Use of social network analysis methods to study professional advice and performance among healthcare providers: a systematic review

BACKGROUND

Social network analysis quantifies and visualizes relationships between and among individuals or organizations. Applications in the health sector remain underutilized. This systematic review seeks to analyze what social network methods have been used to study professional communication and performance among healthcare providers.

METHODS

Ten databases were searched from 1990 through April 2016, yielding 5970 articles screened for inclusion by two independent reviewers who extracted data and critically appraised each study. Inclusion criteria were study of health care worker professional communication, network methods used, and patient outcomes measured. The search identified 10 systematic reviews. The final set of articles had their citations prospectively and retrospectively screened. We used narrative synthesis to summarize the findings.

RESULTS

The six articles meeting our inclusion criteria described unique health sectors: one at primary healthcare level and five at tertiary level; five conducted in the USA, one in Australia. Four studies looked at multidisciplinary healthcare workers, while two focused on nurses. Two studies used mixed methods, four quantitative methods only, and one involved an experimental design. Four administered network surveys, one coded observations, and one used an existing survey to extract network data. Density and centrality were the most common network metrics although one study did not calculate any network properties and only visualized the network. Four studies involved tests of significance, and two used modeling methods. Social network analysis software preferences were evenly split between ORA and UCINET. All articles meeting our criteria were published in the past 5 years, suggesting that this remains in clinical care a nascent but emergent research area. There was marked diversity across all six studies in terms of research questions, health sector area, patient outcomes, and network analysis methods.

CONCLUSION

Network methods are underutilized for the purposes of understanding professional communication and performance among healthcare providers. The paucity of articles meeting our search criteria, lack of studies in middle- and low-income contexts, limited number in non-tertiary settings, and few longitudinal, experimental designs, or network interventions present clear research gaps.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42015019328.