I once delivered a guest lecture concerning policies to prevent adolescent tobacco use. Halfway through, a public health student raised his hand to suggest that we must understand why young people choose to smoke before we can design effective interventions. That’s not a stupid perspective. Indeed we often take this perspective for granted: When we want to solve a problem, we often start by investigating its causes. Yet it’s worth asking ourselves when this perspective is always useful or wise.
I noted one problem in a recent post on the Blog of the Century: Our causal understanding is very poor in many areas of social policy. The available data and conceptual models are often poor. If you ask why some people commit crimes, or why some young people misuse intoxicating substances, the social science literature surely provides useful information. Yet identifying risk-factors and root causes may or may not provide specific or useful guidance for feasible interventions.
Suppose a reputable study establishes that low IQ scores are a risk-factor for engaging in crime. That could certainly be helpful… since it suggests a population that merits special focus in criminal justice policy. But what should we actually do when there are many plausible reasons for this correlation. Some people with low IQs behave impulsively. Others have specific psychiatric concerns. Others commit property crimes because their opportunities in the legitimate economy are limited. Still others are scarred in childhood by difficult family and community experiences that promote criminal behavior.
These diverse pathways suggest different possibilities for intervention. If impulsivity is a concern, we can design interventions for impulsive kids to address that. If meager opportunities in the legitimate labor market are key concerns, we would presumably look to labor market supports for low-wage workers. If we are most concerned about adverse early childhood experiences, maybe we should implement home visiting interventions for families that appear to benefit. Each of these interventions is plausible. Indeed I might want to do them all. Then again, I might want to do them all even if I had never heard of the IQ study.
Forty years ago, oncologist Sidney Farber made this point well in congressional testimony regarding what would be known as “the war on cancer.” As Farber put things:
We cannot wait for full understanding; the 325,000 patients with cancer who are going to die this year cannot wait; nor it is necessary, to make great progress in the cure of cancer, for us to have the full solution of all the problems of basic research… The history of medicine is replete with examples of cures obtained years, decades, and even centuries before the mechanism of action was understood for these cures – from vaccination, to digitalis, to aspirin.
I found that quote in Siddhartha Mukherjee’s The Emperor of All Maladies a gripping nonfiction thriller about the history of cancer. Farber’s comment is all-too-accurate regarding both the challenges and the triumphs of cancer treatment over much of the 20th century. The most common chemotherapies are powerful poisons that attack rapidly dividing cells in the human body. Through accident, inspired guesswork, and simple trial-and-error, clinicians discovered that compounds such as mustard gas had valuable properties in treating particular cancers. Biologists, physicians, and chemists have won dozens of Nobel Prizes for beautiful research that illuminated cancer biology. Meanwhile, for many decades as these researchers described the intricate molecular-genetic pathways that lead to cancer, their counterparts at the bedside were infusing human patients with toxic chemotherapies and punishing radiation in sometimes-successful, often-desperate efforts to treat metastatic cancer.
The embarrassing gap between increasingly sophisticated biological understanding and painfully slow progress in therapeutic interventions was apparent to everyone—not least to cancer patients. Mukherjee describes speaking to a patient in some depth about the intricate biological processes that underlay her own deadly cancer. Her response, roughly speaking, was: If you know so much about this damn thing, why can’t you help me?
In this clinical enterprise, rigorous research relied on rough-and-ready understanding of biological mechanisms. Much of clinical oncology’s discipline and rigor did not reside in the cell biology. Instead the rigor and discipline resided in the ability to conduct useful randomized trials to understand whether and how various fairly blunderbuss therapies could actually help people.
Something similar might be said for the first fifteen years of the HIV/AIDS epidemic. AZT, the first notably effective medication, did not emerge from any deep molecular understanding of HIV. Roughly speaking, it was an off-the-shelf drug discovered through trial-and-error to be useful in HIV treatment.
Similar stories can be told for prominent vaccinations and in many other areas. Untold millions of lives have been saved through medical therapies whose biological mechanisms were only understood decades or centuries after these therapies had been in widespread use. It’s easy to draw logic models and “pipeline” Powerpoint slides that show basic science being processed downstream into effective therapies. The real-world process is sloppier than that. In many cases, researchers had enough of a basic causal understanding to infer that a particular medication might be helpful. They often didn’t know much more.
Blunderbuss interventions are also applied in social policy. Interventions to prevent crime, provide job training, or expand health insurance coverage don’t resemble cancer treatment. The available data and the available causal theories are more limited. The study of causation is inherently less rigorous. By necessity, there’s a good deal of trial and error. Fortunately these interventions can still be carefully evaluated through well-designed effectiveness trials. And once we know which interventions can be helpful, that often narrows the scientific search in seeking causal mechanisms that help us understand why.
Farber wasn’t entirely right, either. Ignorance about causal mechanisms brings real costs.
Traditional chemotherapies lacerate the human body because these treatments are so undiscriminating. Within the past fifteen years, researchers have developed targeted drugs such as Gleevec that use advanced biology to treat previously-untreatable cancers. Targeted therapies tend to have fewer side-effects because they attack a smaller range of human cells. In similar fashion, protease inhibitors have revolutionized HIV/AIDS care. These treatment advances would not have been possible without fundamental scientific advances.
So it is in social policy. As discussed in this terrific paper, if we thought more carefully about these issues, we could design better interventions. We could waste less time pursuing superficially promising interventions based on causal premises that turn out not to work. We could also design more effective evaluations of public policies.
To note one pressing example, America incarcerates hundreds of thousands more prisoners than we used to do. This treatment has genuinely helped to reduce crime. It has also lacerated our body politic. I am convinced that we could achieve the same crime reductions at lower human and financial cost if we had a more granular understanding of the mechanisms underlying criminal offending and deterrence for different populations. That’s why I’m excited by efforts such as the Hawaii HOPE intervention that seem to accomplish this goal, at least in one time and place. That’s also why I’m convinced that rigorous violence prevention research can yield real dividends.
I wish the United States Senate agreed. The Senate Appropriations 2012 Budget zeroed out CDC’s major youth violence prevention research and intervention effort. That saved the federal government something like $19.7 million. This is a foolish economy.
I wouldn’t want to oversell things, but we sometimes do better when we know what we are talking about.