Social network analysis in medical education

Isba, Rachel, Woolf, Katherine and Hanneman, Robert (2016) 'Social network analysis in medical education'. Medical education, Vol 51, Issue 1, pp. 81-88.

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Abstract

Content
Humans are fundamentally social beings. The social systems within which we live our lives (families, schools, workplaces, professions, friendship groups) have a significant influence on our health, success and well-being. These groups can be characterised as networks and analysed using social network analysis.

Social Network Analysis
Social network analysis is a mainly quantitative method for analysing how relationships between individuals form and affect those individuals, but also how individual relationships build up into wider social structures that influence outcomes at a group level. Recent increases in computational power have increased the accessibility of social network analysis methods for application to medical education research.

Application to Medical Education
Social network analysis has been used to explore team-working, social influences on attitudes and behaviours, the influence of social position on individual success, and the relationship between social cohesion and power. This makes social network analysis theories and methods relevant to understanding the social processes underlying academic performance, workplace learning and policy-making and implementation in medical education contexts.

Conclusions
Social network analysis is underused in medical education, yet it is a method that could yield significant insights that would improve experiences and outcomes for medical trainees and educators, and ultimately for patients.

Item Type:	Article
Subjects:	W General Medicine. Health Professions > W 83 Telemedicine (General) W General Medicine. Health Professions > Professional practice > W88 Administrative work. Teaching. Research WA Public Health > WA 19 Schools, colleges, and specialized departments and facilities
Faculty: Department:	Groups (2002 - 2012) > Professional Services
Digital Object Identifer (DOI):	https://doi.org/10.1111/medu.13152
SWORD Depositor:	JISC Pubrouter
Depositing User:	Stacy Murtagh
Date Deposited:	31 Jan 2017 09:55
Last Modified:	09 Apr 2018 14:47
URI:	https://archive.lstmed.ac.uk/id/eprint/6371

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