In today's world the Social determinants of health include socioeconomic, familial structure, health insurance coverage and other sociological factors, religion, community, social networks and more.
Remarkable advances in medical science, clinical care, and therapeutics over the last 60 years have established the current understanding of the “nature” side of disease. The “nurture” components of disease also have been explored, revealing strong associations between social support and health outcomes. However, prior investigations into social determinants have often been limited by self-reported information based on reductionist instruments with standardized responses. Moreover, social determinants are complex, and entail networks and behaviors that are best revealed by what actually occurs in life, rather than the perception of these complex relationships. Individual and network data available within social platforms therefore have the potential to elucidate the understanding of social determinants of health and could offer measurable, actionable insights into how disease can be prevented. To date, only limited direct links between medical and complex social network data have been made.
Corresponding Author: Freddy Abnousi, MD, MBA, MSc, Facebook Inc, 1 Hacker Way, Menlo Park, CA 94025 (abnousi@fb.com).
In this Viewpoint, Harlan Krumholz and colleagues discuss the promise that social media data hold for helping researchers better understand social determinants of health, and the challenges that must be overcome to reliably link social network data to clinical and health outcomes.
Leveraging the Social Determinants of Health: What Works?
The roots of interest in social determinants of health can be traced back in part to the World Health Organization (WHO), which, in 1946, notably defined health as “complete physical, mental, and social well-being.”3 Since then, a number of national and international efforts have increased awareness of the field, such as the WHO’s Commission on Social Determinants of Health and initiatives by the MacArthur and Robert Wood Johnson Foundations.4-6 From a research perspective, numerous studies have shown associations between social determinants of health and life expectancy. While these studies reflect the overall importance of social determinants of health in relation to health outcomes, an important limitation of current research on social determinants of health is that many of the identified factors, such as income and education, cannot easily be changed.8 This is in part because of a lack of granularity in understanding the person and his/her community, compounded by the potential flaws introduced by survey self-reported social/behavioral variables as opposed to observed factors. Access to information that captures the habits, behaviors, and networks of individuals has been limited in the existing body of work as these parameters relate to health outcomes. As such, it is not surprising that actionable variables continue to be elusive.
Better approaches are needed for accessing information about observed habits, behaviors, and networks to foundationally understand their relationship with health and health outcomes. Despite the exponential increase in the role of social media in the daily life of individuals around the world over the last decade, most studies have not directly evaluated social variables from social network sources in relation to clinical outcomes.
Evaluating social network data in combination with increasingly available digital health care data (such as from large, national clinical registry programs or electronic health records) could lead to novel, more nuanced understanding of social and behavioral variables that account for the interplay of the individual and the network in relation to health outcomes. These may transform the traditionally held social determinants of health, including education, income, housing, and community, to encompass a more granular tech-influenced definition, ranging from simple factors, such as numbers of online friends, to complex social biomarkers, such as timing, frequency, content, and patterns of posts and degree of integration with online communities. With data related to millions of users, network effects may amplify the total range of patterns and associations.
These aspects lean toward 'population health' measures. this kind of research also harbors potential risk and clear challenges. As was done for the Human Genome Project, the first step will be to establish the legal and ethical framework for this endeavor. Social network data raise unique challenges to deidentification beyond the typical demographic identifiers. For example, when an individual posts a simple phrase, the exact composition of words used can become a form of identification in its own right; developing the techniques to de identify this kind of data will require thoughtful approaches. In addition, a combination of physical and software-driven isolation needs to tightly control access to the data. Concurrently, investment in research towards the creation of “synthetic data sets” (ie, data sets that maintain associations but have the original data removed) may serve to advance security and privacy for the next iteration of this research.Some authors have even suggested the use of social media as a measure for social determinants. For those not familiar with the standards of health care professionals this would be a dangerous measurement.
Facebook has had serious privacy violations in the breast cancer group Thousands of women who carry mutations in the genes BRCA1 and BRCA2 and joined ‘private’ Facebook groups recently learned that their groups were vulnerable to a Chrome plug-in that allowed marketers to discover group members’ names and other private health information. That Chrome plug-in has since been removed from this, and apparently all other private groups, but has left a deep scar in the BRCA community’s trust in Facebook.
Safeguards have been put in place for Facebook which include removing the chrome extension grouply.io. This extension allowed for mass harvesting of group members data.
The bottom line is that these methods are not yet ready for prime-time and should carefully be investigated until ethical and legal matters are addressed and codified.
Social Determinants of Health in the Digital Age: Determining the Source Code for Nurture | Health Disparities | JAMA | JAMA Network:
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