What is the Added Value of Social Network Analysis when Developing and Evaluating Complex Interventions

As the use of social network analysis in evaluation continues to increase, it is important to understand how, when, and under what conditions social network analysis can add value to evaluation work. In this article, we describe how we have used social network analysis in various evaluation projects. Using the experience of one specific project, we highlight, in greater detail, some challenges we encountered in doing this work, relating to the need for stakeholders to understand the added value of social network analysis, the intricacies of data coding and cleaning, and how changes in the size and scope of the project can have great implications. Finally, we offer some practical suggestions for evaluators considering incorporating social network analysis into their work today, and identify opportunities where evaluators might use social network analysis in the future.Avec la croissance de l’utilisation, en évaluation, de l’analyse des réseaux sociaux, il est important de comprendre quand, comment, et dans quelles conditions l’analyse des réseaux sociaux apporte une valeur ajoutée. Dans le présent article, nous décrivons la façon dont nous avons utilisé l’analyse des réseaux sociaux dans le cadre de divers projets d’évaluation. À partir de l’expérience d’un projet particulier, nous décrivons, de façon détaillée, certains des défis auxquels nous avons fait face, notamment en ce qui concerne la nécessité, pour les parties prenantes, de comprendre la valeur ajoutée de l’analyse des réseaux sociaux, les complexités du codage et du nettoyage des données et les implications des changements dans la taille et la portée du projet. Finalement, nous faisons quelques suggestions pratiques pour les évaluateurs qui pensent inclure l’analyse des réseaux sociaux dans leurs travaux actuels et nous identifions des pistes, pour les évaluateurs, pour l’utilisation future de ce type d’analyse.

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

BMJ Open ◽

10.1136/bmjopen-2020-039681 ◽

2020 ◽

Vol 10 (11) ◽

pp. e039681

Author(s):

Linda C Smit ◽

Jeroen Dikken ◽

Marieke J Schuurmans ◽

Niek J de Wit ◽

Nienke Bleijenberg

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Complex Intervention ◽

Scoping Review ◽

Complex Interventions ◽

Intervention Research ◽

Healthcare Intervention ◽

Scoping Reviews ◽

Healthcare Interventions

ObjectivesMost 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.MethodsA 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.ResultsAmong 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.ConclusionSNA 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.

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A mixed methods analysis of Mozambique’s HPV vaccine delivery network actors.

10.21203/rs.3.rs-17473/v3 ◽

2020 ◽

Author(s):

Caroline Soi ◽

Jessica Shearer ◽

Baltazar Chilundo ◽

Vasco Muchanga ◽

Luisa Matsinhe ◽

...

Keyword(s):

Social Network ◽

Mixed Methods ◽

Social Network Analysis ◽

Network Analysis ◽

Hpv Vaccine ◽

Hpv Vaccination ◽

Scale Up ◽

Added Value ◽

Country Ownership ◽

Outcome Scores

Abstract Background: Global health partnerships have expanded exponentially in the last two decades with Gavi, the Vaccine Alliance considered the model’s pioneer and leader because of its vaccination programs’ implementation mechanism. Gavi, relies on diverse domestic and international partners to carry out the programs in low- and middle-income countries under a partnership engagement framework (PEF). In this study, we utilized mixed methods to examine Mozambique’s Gavi driven partnership network which delivered human papillomavirus (HPV) vaccine during the demonstration phase.Methods: Qualitative tools gauged contextual factors, prerequisites, partner performance and practices while a social network analysis (SNA) survey measured the partnership structure and perceived added value in terms of effectiveness, efficiency and country ownership. 40 key informants who were interviewed included frontline Ministry of Health workers, Ministry of Education staff and supporting partner organization members, of whom 34 participated in the social network analysis survey.Results: Partnership structure SNA connectivity measurement scores of reachability (100%) and average distance (2.5), were high, revealing a network of very well-connected HPV vaccination implementation collaborators. Such high scores reflect a network structure favorable for rapid and widespread diffusion of information, features necessary for engaging and handling multiple implementation scales. High SNA effectiveness and efficiency measures for structural holes (85%) and low redundancy (30%) coupled with high mean perceived effectiveness (97.6%) and efficiency (79.5%) network outcome scores were observed. Additionally, the tie strength average score of 4.1 on a scale of 5 denoted high professional trust. These are all markers of a collaborative partnership environment in which disparate institutions and organizations leveraged each entity’s comparative advantage. Lower perceived outcome scores for country ownership (24%) were found, with participants citing the prominent role of several out-of-country partner organizations as a major obstacle.Conclusions: While there is room for improvement on the country ownership aspects of the partnership, the expanded, diverse and inclusive collaboration of institutions and organizations that implemented the Mozambique HPV vaccine demonstration project was effective and efficient. We recommend that the country adapt a similar model during national scale up of HPV vaccination.

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Seven Decades of Chemotherapy Clinical Trials: A Pan-Cancer Social Network Analysis

10.1101/19010603 ◽

2019 ◽

Author(s):

Xuanyi Li ◽

Elizabeth A. Sigworth ◽

Adrianne H. Wu ◽

Jess Behrens ◽

Shervin A. Etemad ◽

...

Keyword(s):

Clinical Trials ◽

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Medical Oncology ◽

Added Value ◽

Precision Oncology ◽

Cancer Type ◽

Dynamic Social Network ◽

The Social

AbstractBackgroundClinical trials establish the standard of care for cancer and other diseases. While social network analysis has been applied to basic sciences, the social component of clinical trial research is not well characterized. We examined the social network of cancer clinical trialists and its dynamic development over more than 70 years, including the roles of subspecialization and gender in relation to traditional and network-based metrics of productivity.MethodsWe conducted a social network analysis of authors publishing chemotherapy-based prospective trials from 1946-2018, based on the curated knowledge base HemOnc.org, examining: 1) network density; 2) modularity; 3) assortativity; 4) betweenness centrality; 5) PageRank; and 6) the proportion of co-authors sharing the same primary cancer subspecialty designation. Individual author impact and productive period were analyzed as a function of gender and subspecialty.FindingsFrom 1946-2018, the network grew to 29,197 authors and 697,084 co-authors. While 99.4% of authors were directly or indirectly connected as of 2018, the network had very few connections and was very siloed by cancer subspecialty. Small numbers of individuals were highly connected and had disproportionate impact (scale-free effects). Women were under-represented and likelier to have lower impact, shorter productive periods (P<0.001 for both comparisons), less centrality, and a greater proportion of co-authors in their same subspecialty. The past 30 years were characterized by a trend towards increased authorship by women, with new author parity anticipated in 2032. However, women remain a distinct minority of first/last authors, with parity not anticipated for 50+ years.InterpretationThe network of cancer clinical trialists is best characterized as a strategic or “mixed-motive” network, with cooperative and competitive elements influencing its appearance.Network effects e.g., low centrality, which may limit access to high-profile individuals, likely contribute to ongoing disparities.FundingVanderbilt Initiative for Interdisciplinary Research; National Institutes of Health; National Science FoundationResearch in contextEvidence before this studyWe reviewed the literature on social networks from the 1800’s to 2018. Additionally, MEDLINE was searched for (“Social Networking”[Mesh] OR “Social Network Analysis”) AND (“Clinical Trials as Topic”[Mesh] OR “Hematology”[Mesh] OR “Medical Oncology”[Mesh]) without date restriction. The MEDLINE search yielded 43 results, of which 8 were relevant; none considered gender nor temporality in their analyses. To our knowledge, there has not been any similar study of the dynamic social network of clinical trialists from the inception of the fields of medical oncology and hematology to the present.Added value of this studyThis is the first dynamic social network analysis of cancer clinical trialists. We found that the network was sparse and siloed with a small number of authors having disproportionate impact and influence as measured by network metrics such as PageRank; these metrics have become more disproportionate over time. Women were under-represented and likelier to have lower impact, shorter productive periods, less network centrality, and a greater proportion of co-authors in their same cancer subspecialty.Implications of all the available evidenceWhile gender disparities have been demonstrated in many fields including hematology/oncology, our analysis is the first to show that network factors themselves are significantly implicated in gender disparity. The increasing coalescence of the network by traditional cancer type and around a small number of high-impact individuals implies challenges when the field pivots from traditionally disease-oriented subspecialties to a precision oncology paradigm. New mechanisms are needed to ensure diversity of clinical trialists.

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From Complex Interventions to Complex Systems: Using Social Network Analysis to Understand School Engagement with Health and Wellbeing

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16101694 ◽

2019 ◽

Vol 16 (10) ◽

pp. 1694 ◽

Cited By ~ 2

Author(s):

Hannah J. Littlecott ◽

Graham F. Moore ◽

Hugh Colin Gallagher ◽

Simon Murphy

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Distributed Leadership ◽

School System ◽

Complex Interventions ◽

School Staff ◽

Senior Leadership ◽

Health And Wellbeing

Challenges in changing school system functioning to orient them towards health are commonly underestimated. Understanding the social interactions of school staff from a complex systems perspective may provide valuable insight into how system dynamics may impede or facilitate the promotion of health and wellbeing. Ego social network analysis was employed with wellbeing leads within four diverse case study schools to identify variability in embeddedness of health and wellbeing roles. This variation, as well as the broader context, was then explored through semi-structured qualitative interviews with school staff and a Healthy Schools Coordinator, sampled from the wellbeing leads’ ego-networks. Networks varied in terms of perceived importance and frequency of interactions, centrality, brokerage and cliques. Case study schools that showed higher engagement with health and wellbeing had highly organised, distributed leadership structures, dedicated wellbeing roles, senior leadership support and outside agencies embedded within school systems. Allocation of responsibility for wellbeing to a member of the senior leadership team alongside a distributed leadership approach may facilitate the reorientation of school systems towards health and wellbeing. Ego-network analysis to understand variance in complex school system starting points could be replicated on a larger scale and utilised to design complex interventions.

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