Health

Peter J. Teravskis, MD/JD Candidate, MJLST Staffer

Medicalization is “a process by which human problems come to be defined and treated as medical problems.” Medicalization is not a formalized process, but is instead “a social meaning embedded within other social meanings.” As the medical domain has expanded in recent years scholars have begun to point to problems with “over-medicalization” or “corrupted medicalization.” Specifically, medicalization is used to describe “the expansion of medicine in people’s lives.” For example, scholars have problematized the medicalization of obesity, shyness,  housing, poverty, normal aging, and even dying, amongst many others. The process of medicalization has become so pervasive in recent years that various sociologists have begun to discuss it as the medicalization “of everyday life,” “of society,”  “of culture,” of the human condition, and “the medicalization of everything”—i.e. turning all human difference into pathology. Similarly, developments in “technoscientific biomedicine” have led scholars to blur the line of what is exclusively “medical” into a broader process of “biomedicalization.”

Medicalization does not carry a valence of “good” or “bad” per se: medicalization and demedicalization can both restrict and expand personal liberties. However, when everyday living is medicalized there are many attendant problems. First, medicalization places problems outside a person’s control: rather than the result of choice, personality, or character, a medicalized problem is considered biologically preordained or “curable.” Medicalized human differences are no longer considered normal; therefore, “treatment” becomes a “foregone conclusion.” Because of this, companies are incentivized to create pharmacological and biotechnological solutions to “cure” the medicalized problem. From a legal perspective, Professor Adele E. Clarke and colleagues note that through medicalization, “social problems deemed morally problematic . . . [are] moved from the professional jurisdiction of the law to that of medicine.” This process is referred to, generally, as the “medicalization of deviance.” Further, medicalization can de-normalize aspects of the human condition and classify people as “diseased.”

Medicalization is important to the sociological study of social control. Social control is defined as the “mechanisms, in the form of patterns of pressure, through which society maintains social order and cohesion.” Thus, once medicalized, an illness is subject to control by medicinal interventions (drugs, surgery, therapy, etc.) and a sick people are expected to take on the “sick role” whereby they become the subjects of physicians’ professional control. A recent example of medical social control is the social pressure to engage in hygienic habits, precautionary measures, and “social distancing” in response to the novel coronavirus, COVID-19. The COVID-19 pandemic is an expressly medical problem; however, when normal life, rather than a viral outbreak, is medicalized, medical social control becomes problematic. For example, the sociologist Peter Conrad argues that medical social control can take the form of “medical surveillance.” He states that “this form of medical social control suggests that certain conditions or behaviors become perceived through a ‘medical gaze’ and that physicians may legitimately lay claim to all activities concerning the condition” (quoting Michel Foucault’s seminal book The Birth of the Clinic).

The effects of medical social control are amplified due to the communal nature of medicine and healthcare, leading to “medical­legal hybrid[]” social control and, I argue, medical-corporate social control. For example, employers and insurers have interests in encouraging healthful behavior when it reduces members’ health care costs. Similarly, employers are interested in maximizing healthy working days, decreasing worker turnover, and maximizing healthy years, thus expanding the workforce. The State has similar interests, as well as interests in reducing end-of-life and old age medical costs. At first glance, this would seem to militate against overmedicalization. However, modern epidemiological methods have revealed the long term consequences of untreated medical problems. Thus, medicalization may result in the diversion of health care dollars towards less expensive preventative interventions and away from more expensive therapy that would help later in life.

An illustrative example is the medicalization of obesity. Historically, obesity was not considered a disease but was a socially desirable condition: demonstrating wealth; the ability to afford expensive, energy-dense foods; and a life of leisure rather than manual labor. Changing social norms, increased life expectancy, highly sensitive biomedical technologies for identifying subtle metabolic changes in blood chemistry, and population-level associations between obesity and later-life health complications have contributed to the medicalization of this conditions. Obesity, unlike many other conditions, it not attributable to a single biological process, rather, it is hypothesized to result from the contribution of multiple genetic and environmental factors. As such, there is no “silver bullet” treatment for obesity. Instead, “treatment” for obesity requires profound changes reaching deep into how a patient lives her life. Many of these interventions have profound psychosocial implications. Medicalized obesity has led, in part, to the stigmatization of people with obesity. Further, medical recommendations for the treatment of obesity, including gym membership, and expensive “health” foods, are costly for the individual.

Because medicalized problems are considered social problems affecting whole communities, governments and employers have stepped in to treat the problem. Politically, the so-called “obesity epidemic” has led to myriad policy changes and proposals. Restrictions designed to combat the obesity epidemic have included taxes, bans, and advertising restrictions on energy-dense food products. On the other hand, states and the federal government have implemented proactive measures to address obesity, for example public funds have been allocated to encourage access to and awareness of “healthy foods,” and healthy habits. Further, Social Security Disability, Medicare and Medicaid, and the Supplemental Nutrition Assistance Program have been modified to cope with economic and health effects of obesity.

Other tools of control are available to employers and insurance providers. Most punitively, corporate insurance plans can increase rates for obese employees.  As Abby Ellin, writing for Observer, explained “[p]enalizing employees for pounds is perfectly legal [under the Affordable Care Act]” (citing a policy brief published in the HealthAffairs journal). Alternatively, employers and insurers have paid for or provided incentives for gym memberships and use, some going so far as to provide exercise facilities in the workplace. Similarly, some employers have sought to modify employee food choices by providing or restricting food options available in the office. The development of wearable computer technologies has presented another option for enforcing obesity-focused behavioral control. Employer-provided FitBits are “an increasingly valuable source of workforce health intelligence for employers and insurance companies.” In fact, Apple advertises Apple Watch to corporate wellness divisions and various media outlets have noted how Apple Watch and iPhone applications can be used by employers for health surveillance.

Indeed, medicalization as a pretense for technological surveillance and social control is not exclusively used in the context of obesity prevention. For instance, the medicalization of old age has coincided with the technological surveillance of older people. Most troubling, medicalization in concert with other social forces have spawned an emerging field of technological surveillance of mental illness. Multiple studies, and current NIH-funded research, are aimed at developing algorithms for the diagnosis of mental illness based on data mined from publicly accessible social media and internet forum posts. This process is called “social media analysis.” These technologies are actively medicalizing the content of digital communications. They subject peoples’ social media postings to an algorithmic imitation of the medical gaze, whereby, “physicians may legitimately lay claim to” those social media interactions.  If social media analysis performs as hypothesized, certain combinations of words and phrases will constitute evidence of disease. Similar technology has already been coopted as a mechanism of social control to detect potential perpetrators of mass shootings. Policy makers have already seized upon the promise of medical social media analysis as a means to enforce “red flag” laws. Red flag laws “authorize courts to issue a special type of protection order, allowing the police to temporarily confiscate firearms from people who are deemed by a judge to be a danger to themselves or to others.” Similarly, it is conceivable that this type of evidence will be used in civil commitment proceedings. If implemented, such programs would constitute a link by which medical surveillance, under the banner of medicalization, could be used as grounds to deprive individuals of civil liberty, demonstrating an explicit medical-legal hybrid social control mechanism.

What protections does the law offer? The Fourth Amendment protects people from unreasonable searches. To determine whether a “search” has occurred courts ask whether the individual has a “reasonable expectation of privacy” in the contents of the search. Therefore, whether a person had a reasonable expectation of privacy in publicly available social media data is critical to determining whether that data can be used in civil commitment proceedings or for red flag law protective orders.

Public social media data is, obviously, public, so courts have generally held that individuals have no reasonable expectation of privacy in its contents. By contrast, the Supreme Court has ruled that individuals have a reasonable expectation of privacy in the data contained on their cell phones and personal computers, as well as their personal location data (cell-site location information) legally collected by third party cell service providers. Therefore, it is an open question how far a person’s reasonable expectation of privacy extends in the case of digital information. Specifically, when public social media data is used for medical surveillance and making psychological diagnoses the legal calculation may change. One interpretation of the “reasonable expectation of privacy” test argues that it is an objective test—asking whether a reasonable person would actually have a privacy interest. Indeed, some scholars have suggested using polling data to define the perimeter of Fourth Amendment protections. In that vein, an analysis of the American Psychiatric Association’s “Goldwater Rule” is illustrative.

The Goldwater Rule emerged after the media outlet “Fact” published psychiatrists’ medical impressions of 1964 presidential candidate Barry Goldwater. Goldwater filed a libel suit against Fact, and the jury awarded him $1.00 in compensatory damages and $75,000 in punitive damages resulting from the publication of the psychiatric evaluations. None of the quoted psychiatrists had met or examined Goldwater in person. Subsequently, concerned primarily about the inaccuracies of “diagnoses at a distance,” the APA adopted the Goldwater Rule, prohibiting psychiatrists from engaging in such practices. It is still in effect today.

The Goldwater Rule does not speak to privacy per se, but it does speak to the importance of personal, medical relationships between psychiatrists and patients when arriving at a diagnosis. Courts generally treat those types of relationships as private and protect them from needless public exposure. Further, using social media surveillance to diagnose mental illness is precisely the type of diagnosis-at-a-distance that concerns the APA. However, big-data techniques promise to obviate the diagnostic inaccuracies the 1960s APA was concerned with.

The jury verdict in favor of Goldwater is more instructive. While the jury found only nominal compensatory damages, it nevertheless chose to punish Fact magazine. This suggests that the jury took great umbrage with the publication of psychiatric diagnoses, even though they were obtained from publicly available data. Could this be because psychiatric diagnoses are private? The Second Circuit, upholding the jury verdict, noted that running roughshod over privacy interests is indicative of malice in cases of libel. Under an objective test, this seems to suggest that subjecting public information to the medical gaze, especially the psychiatrist’s gaze, unveils information that is private. In essence, applying big-data computer science techniques to public posts unveils or reveals private information contained in the publicly available words themselves. Even though the public social media posts are not subject to a reasonable expectation of privacy, a psychiatric diagnosis based on those words may be objectively private. In sum, the medicalization and medical surveillance of normal interactions on social media may create a Fourth Amendment privacy interest where none previously existed.