Wfsp2200. Medical sociology II : course outline


Goal: The course aims to train the student in the use of social network research for analysing a health issue.

Learning outcomes

·         To understand key societal challenges of current medical sociology.

·         To  analyse health or medical issues with social network research.

·         To use UCINET to explore and analyse social graphs.

·         To communicate about a paper in social network analysis as applied to health.



·         Introduction to Medical sociology and the relevance of social network analysis

·         Key concepts in social network analysis

·         Design of social network analysis

·         Exploring the network: graphs

·         Ego-level Metrics

·         Network-level metrics

·         Contagion and peer-effects


Agenda (from 9am to 12am)

Lecture 1. 5/2.  Introduction to medical sociology and network research; UCINET overall presentation, data entry and management; essay planning;

Lecture 2. 19/2. Design of social network research; matrices transformation and manipulation: questionnaire content and delivery ;

Lecture 3. 5/3. Exploration; netdraw;

Lecture 4. 19/3. Ego-level metrics;

Lecture 5. 26/3. Network-level  metrics; results exploration and analysis;


Room : Computing room Paré, under the medical library, Louvain-en-Woluwe. 

Teaching activities

·         Lecture

·         Practice of UCINET.

·         Paper presentation and discussion: read and prepare the paper in advance !

·         Organisation of the data collection and analysis



Assessment is based on an essay (see below, 80%) and discussion of one of the  2 papers (20%, references #2,4, 11,12). 


The essay aims to confront the student to the practice of social network research in a topic presented by the lecturer. In the essay the student shows he is able to formulate a research question, design a method, collect and analyse data and conclude about the relevance of the work done. The essay has the following outline: introduction (issue, literature review, research question); method (population, setting, sample, who-what-when; measures);  results (descriptives stats, exploratory graphs; statistical analysis); Discussion-conclusion (main findings; consistency with the literature; limits; conclusion).  The essay is assessed against 5 criteria: relevance of the research question; data collection effectiveness; graph exploration; data analysis; conclusion and reflexivity; the essay has a maximum of 10 pages, is delivered to the lecturer pigeon hole one week before the exam session begins and is discussed face-to-face with the lecturer the 8th of june between 2PM and 6PM.

Topic in 2017-18

The essay will perform a 2-mode network analysis of the publications of the Faculty in Public Health and the Doctoral School in Public Health –Health and Society. A tentative and non-exhaustive list of questions includes: who’s working with who; what is the core of the Faculty and of the Phd School; what are the components or the subgroups ?  Are teaching activities related to master supervision or to Phd supervision; are some master thesis topics (i.e.,health care versus health issues) or some methodological approaches (qual, quant) more associated with some groups ?  Who are the brokers ?   


Textbooks or key papers to read:

The lectures are very much inspired by Text books n°9  and 10. Students choose two papers among the number 2, 4 ,11 and 12 for the exam.

1.     Carrington, P. J. and J. Scott (2011). The SAGE handbook of social network analysis. London, SAGE.

2.     Centola, D. (2011). "An experimental study of homophily in the adoption of health behavior." Science 334(6060): 1269-1272.

3.     Christakis, N. A. and J. H. Fowler (2010). Connected : the amazing power of social networks and how they shape our lives. London, HarperPress.

4.     Dimaggio, P. and F. Garip (2012). "Network effects and social inequality." Annual Review of Sociology 38: 93-118.

5.     Knoke, D., et al. (2008). Social network analysis. Los Angeles, Sage Publications.

6.     Oakes, J. M. and J. S. Kaufman (2006). Methods in social epidemiology. San Francisco, CA, Jossey-Bass.

7.     Provan, K. G., et al. (2005). "The Use of Network Analysis to Strengthen Community Partnerships." Public Administration Review 65(5): 603-613.

8.     Robins, G., et al. (2007). "An introduction to exponential random graph (p *) models for social networks." Social Networks 29(2): 173-191.

9.     Robins, G. (2015). Doing social network research : network-based research design for social scientists. London, SAGE

10.   Valente, T. W. (2010). Social networks and health models, methods, and applications. Oxford, Oxford University Press.

11.   Valente, T. W. (2012). "Network Interventions." Science 337(6090): 49-53.

12.   Sweet D, Byng R, Webber M, Enki DG, Porter I, Larsen J, et al. Personal well-being networks, social capital and severe mental illness: exploratory study. The British journal of psychiatry  2017.