Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-23T10:19:53.209Z Has data issue: false hasContentIssue false

The coevolution of networks and health

Introduction to the Special Issue of Network Science

Published online by Cambridge University Press:  29 August 2017

DAVID R. SCHAEFER
Affiliation:
Department of Sociology, University of California Irvine, Irvine, California, USA (e-mail: [email protected])
JIMI ADAMS
Affiliation:
Department of Health and Behavioral Sciences, University of Colorado Denver, Denver, Colorado, USA (e-mail: [email protected])

Extract

Historically, health has played an important role in network research, and vice versa (Valente, 2010). This intersection has contributed to how we understand human health as well as the development of network concepts, theory, and methods. Throughout, dynamics have featured prominently. Even when limited to static methods, the emphasis in each of these fields on providing causal explanations has led researchers to draw upon theories that are dynamic, often explicitly. Here, we elaborate a variety of ways to conceptualize the relationship between health and network dynamics, show how these possibilities are reflected in the existing literature, highlight how the articles within this special issue expand that understanding, and finally, identify paths for future research to push this intersection forward.

Type
Introduction
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

adams, j., & Schaefer, D. R. (2016). How initial prevalence moderates network-based smoking change: Estimating contextual effects with stochastic actor based models. Journal of Health & Social Behavior, 57 (1), 2238.CrossRefGoogle ScholarPubMed
Aral, S., Muchnik, L., & Sundararajan, A. (2013). Engineering social contagions: Optimal network seeding in the presence of homophily. Network Science, 1 (2), 125153.Google Scholar
Bachrach, C. A., & Daley, D. M. (2017). Shaping a new field: Three key challenges for population health science. American Journal of Public Health, 107 (2), 251252.Google Scholar
Bansal, S., Read, J., Pourbohloul, B., & Meyers, L. A. (2010). The dynamic nature of contact networks in infectious disease epidemiology. Journal of Biological Dynamics, 4 (5), 478489.Google Scholar
Borgatti, S. P., Brass, D. J., & Halgin, D. S. (2014). Social network research: Confusions, criticisms, and controversies. In Brass, D. J., Labianca, G., Mehra, A., Halgin, D. S., & Borgatti, S. P. (Eds.), Research in the sociology of organizations. Volume 40. Bingley, UK: Emerald.Google Scholar
Coleman, J. S., Katz, E., & Menzel, H. (1957). The diffusion of an innovation among physicians. Sociometry, 20 (4), 253270.Google Scholar
Crosnoe, R., Frank, K., & Mueller, A. S. (2008). Gender, body size and social relations in American high schools. Social Forces, 86 (3), 11891216.Google Scholar
DeLay, D., Laursen, B., Kiuru, N., Salmela-Aro, K., & Nurmi, J. (2013). Selecting and retaining friends on the basis of cigarette smoking similarity. Journal of Research on Adolescence, 23 (3), 464473.CrossRefGoogle Scholar
DiMaggio, P., & Garip, F. (2011). How network externalities can exacerbate intergroup inequality. American Journal of Sociology, 116 (6), 18871933.Google Scholar
Haas, S. A., Schaefer, D. R., & Kornienko, O. (2010). Health and the structure of adolescent social networks. Journal of Health and Social Behavior, 51 (4), 424439.Google Scholar
House, J. S., Landis, K. R., & Umberson, D. (1988). Social relationships and health. Science, 241, 540545.Google Scholar
Ip, E. H., Rahmandad, H., Shoham, D. A., Hammond, R., Huang, T. T.-K., Wang, Y., & Mabry, P. L. (2013). Reconciling statistical and systems science approaches to public health. Health Education & Behavior, 40, s123s131.CrossRefGoogle ScholarPubMed
Iwashyna, T. J., Christie, J. D., Moody, J., Kahn, J. M., & Asch, D. A. (2009). The structure of critical care transfer networks. Medical Care, 47 (7), 787793.Google Scholar
Kandel, D. B. (1978). Homophily, selection, and socialization in adolescent friendships. American Journal of Sociology, 84, 427436.Google Scholar
Keyes, K. M., & Galea, S. (2016). Setting the agenda for a new discipline: Population health science. American Journal of Public Health, 106 (4), 633634.CrossRefGoogle ScholarPubMed
Lomi, A., & Pallotti, F. (2012). Relational collaboration among spatial multipoint competitors. Social Networks, 34 (1), 101111.Google Scholar
Martin, C. L., Kornienko, O., Schaefer, D. R., Hanish, L. D., Fabes, R. A., & Goble, P. (2013). The role of sex of peers and gender-typed activities in young children’s peer affiliative networks: A longitudinal analysis of selection and influence. Child Development, 84 (3), 921937.CrossRefGoogle ScholarPubMed
McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27, 415444.Google Scholar
Mollborn, S., James-Hawkins, L., Lawrence, E., & Fomby, P. (2014). Health lifestyles in early childhood. Journal of Health and Social Behavior, 55 (4), 386402.Google Scholar
Moody, J. (2001). Race, school integration, and friendship segregation in America. American Journal of Sociology, 107 (3), 679716.Google Scholar
Moody, J., Adams, J., & Morris, M. (2017). Epidemic potential by sexual activity distributions. Network Science, forthcoming. doi: 10.1017/nws.2017.3.CrossRefGoogle ScholarPubMed
Morris, M., Kurth, A. E., Hamilton, D. T., Moody, J., & Wakefield, S. (2009). Concurrent partnerships and HIV prevalence disparities by race: Linking science and public health practice. American Journal of Public Health, 99, 10231031.Google Scholar
Rambaran, A. J., Dijkstra, J. K., & Stark, T. H. (2013). Status-based influence processes: The role of norm salience in contagion of adolescent risk attitudes. Journal of Research on Adolescence, 23 (3), 574585.Google Scholar
Rambaran, J. A., Hopmeyer, A., Schwartz, D., Steglich, C., Badaly, D., & Veenstra, R. (2017). Academic functioning and peer influences: A short-term longitudinal study of network–behavior dynamics in middle adolescence. Child Development, 88 (2), 523543.Google Scholar
Salathe, M., & James, H. J. (2010). Dynamics and control of diseases in networks with community structure. PLoS Computational Biology, 6 (4), e1000736.Google Scholar
Schaefer, D. R. (2017). A network analysis of factors leading adolescents to befriend substance-using peers. Journal of Quantitative Criminology, forthcoming. doi: 10.1007/s10940-016-9335-4.Google Scholar
Schaefer, D. R., Haas, S. A., & Bishop, N. J. (2012). A dynamic model of US adolescents’ smoking and friendship networks. American Journal of Public Health, 102 (6), e12e18.Google Scholar
Schaefer, D. R., Kornienko, O., & Fox, A. M. (2011). Misery does not love company: Network selection mechanisms and depression homophily. American Sociological Review, 75 (5), 764785.Google Scholar
Shalizi, C. R., & Thomas, A. C. (2011). Homophily and contagion are generically confounded in observational social network studies. Sociological Methods & Research, 40 (2), 211239.Google Scholar
Snijders, T. A. B., van de Bunt, G. G., & Steglich, C. E. G. (2010). Introduction to stochastic actor-based models for network dynamics. Social Networks, 32 (1), 4460.Google Scholar
Steglich, C., Snijders, T. A. B., & Pearson, M. (2010). Dynamic networks and behavior: Separating selection from influence. Sociological Methodology, 40 (1), 329393.CrossRefGoogle Scholar
Valente, T. W. (2010). Social networks and health: models, methods, and applications. Oxford: Oxford University Press.Google Scholar
Valente, T. W. (2012). Network interventions. Science, 337 (6090), 4953.Google Scholar
Veenstra, R., Dijkstra, J. K., Steglich, C. E. G., & van Zalk, M. H W. (2013). Network-behavior dynamics. Journal of Research on Adolescence, 23 (3), 399412.Google Scholar
Winship, C., & Morgan, S. L. (1999). The estimation of causal effects from observational data. Annual Review of Sociology, 25, 659707.Google Scholar
Zhang, J., Shoham, D. A., Tesdahl, E., & Gesell, S. B. (2015). Network interventions on physical activity in an afterschool program: An agent-based social network study. American Journal of Public Health, 105 (S2), S236–S43.CrossRefGoogle Scholar