Taking the Medical Sciences Seriously: Why and How Medical Sociology Should Incorporate Diverse Disciplinary Perspectives

  • Brea L. Perry
Part of the Handbooks of Sociology and Social Research book series (HSSR)


Over the past two decades, sociologists have increasingly begun to advocate the synthesis of sociological and biological approaches to health and illness (Mechanic and Aiken 1986; Cohen and Williamson 1991; Fremont and Bird 2000; Guo 2006; Schwartz 1999), and several recent reports from the National Research Council suggest that biomedical scientists also promote an integrative model (e.g., From Neurons to Neighborhoods; Shonkoff and Phillips 2000; New Horizons in Health; Singer and Ryff 2001; Genes, Behavior, and the Social Environment; Hernandez and Blazer 2006). Scholars from diverse disciplines now recognize the futility of the nature/nurture debate (Hernandez and Blazer 2006; Shonkoff and Phillips 2000), and instead assert that health outcomes are the result of complex interactions between social, psychological, and biological factors being mediated in the brain and body (Hamer 2002; Singer and Ryff 2001). Arguably, the twenty-first century holds the promise of a new kind of health science in which disciplinary boundaries are becoming increasingly blurred. Medical sociology is at a crossroads: On the one hand, we can continue to focus narrowly “on the connections of social conditions to single diseases via single mechanisms at single points in time (Link and Phelan 1995, p. 81),” a strategy which limits our ability to achieve a complete understanding of even those causal factors that are central to sociology. Alternatively, sociologists have the opportunity to contribute to a process of integration and collaboration in which the best theoretical and methodological approaches, irrespective of discipline, are brought to bear on the most pressing empirical questions and public health problems of our generation.


Social Network Mental Illness Hypothalamic Pituitary Adrenal Mental Health Outcome Illness Experience 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Authors and Affiliations

  1. 1.Department of SociologyUniversity of KentuckyLexingtonUSA

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