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We make decisions based on the data we see. One restaurant serves higher-quality food than another. One presidential candidate aligns more appropriately with our values. One surgical technique yields better outcomes. One applicant submits a stronger job application than a competitor. From these data, we decide what course of action to take. In many cases, these decisions are inconsequential. In others, however, a poor decision may lead to dangerous results. Let’s consider danger.

Imagine you are a surgeon. A patient arrives in your clinic with a particular condition. Let us call this condition, for illustrative purposes, phantasticolithiasis. The patient is in an immense amount of pain. After reviewing the literature on phantasticolithiasis, you discover that this condition can be fatal if left untreated. The review also describes two surgical techniques, which we shall call “A” and “B” here. Procedure A, according to the review, has a 69% success rate. Procedure B, however, seems much more promising, having a success rate of 81%. Based on these data, you prepare for Procedure B. You tell the patient the procedure you will be performing and share some of the information you learned. You tell a few colleagues about your plan. On the eve of the procedure, you call your old friend, a fellow surgeon practicing on another continent. You tell him about this interesting disease, phantasticolithiasis, what you learned about it, and your assessment and plan. There is a pause on the other end of the line. “What is the mass of the lesion?” he asks. You respond that it is much smaller than average. “Did you already perform the procedure?” he continues. You tell him that you didn’t and that the procedure is tomorrow morning.

“Switch to procedure A.”

Confused, you ask your friend why this could be true. He explains the review a bit further. The two procedures were performed on various categories of phantasticolithiasis. However, what the review failed to mention was that procedure A was more commonly performed on the largest lesions, and procedure B on the smallest lesions. Larger lesions, as you might imagine, have a much lower success rate than their smaller counterparts. If you separate the patient population into two categories for the large and small lesions, the results change dramatically. In the large-lesion category, procedure A has a success rate of 63% (250/400) and procedure B has a success rate of 57% (40/70). For the small lesions, procedure A is 99% successful (88/89) and procedure B is 88% successful (210/240). In other words, when controlling for the category of condition, procedure A is always more successful than procedure B. You follow your friend’s advice. The patient’s surgery is a success, and you remain dumbfounded.

What’s happening here is something called Simpson’s paradox. The idea is simple: When two variables are considered (for example, two procedures), one association results (procedure B is more successful). However, upon the conditioning of a third variable (lesion size), the association reverses (procedure A is more successful). This phenomenon has far-reaching implications. For example, since 2000, the median US wage has increased by 1% when adjusted for inflation, a statistic many politicians like to boast about. However, within every educational subgroup, the median wage has decreased. The same can be said for the gender pay gap. Barack Obama in both of his campaigns fought against the gap, reminding us that women only make 77 cents for every dollar a man earns. However, the problem is more than just a paycheck, and the differences change and may even disappear if you control for job sector or level of education. In other words, policy change to reduce the gap need to be more nuanced than a campaign snippet. A particularly famous case of the paradox arose at UC Berkeley. In this case, the school was sued for gender bias. The school admitted 44% of their male applicants and only 35% of their female applicants. However, upon conditioning for each department, it was found that women applied more often to those departments with lower rates of admission. In 2/3 of the departments, women had a higher entrance rate than men.

The paradox seems simple. When analyzing data and making a decision, simply control for other variables and the correct answer will emerge. Right? Not exactly. How do you know which variables should be controlled? In the case of phantasticolithiasis, how would you know to control for lesion size? Why couldn’t you just as easily control for the patient’s age or comorbidities? Could you control for all of them? If you do see the paradox emerge, what decision should you then make? Is the correct answer that of the conditioned data or that of the raw data? The paradox becomes complicated once again.

Judea Pearl wrote an excellent description of the problem and proposed a solution to the above questions. He cites the use of “do-calculus,” a technique rooted in the study of Bayesian networks. Put more simply, his methods find causality between a number of variables. In doing so, one can find the conditioning variables and can then decide whether the conditioned data or the raw data are best for decision-making. The set of variables that dictate causality are the ones that should be used. If you are interested in the technique and have some experience with the notation, I recommend this brief review on arXiv.

Of course, rapid and rather inconsequential decisions need not be based on such formalities. On the other hand, it serves all of us well if we at least consider the possibility of Simpson’s paradox on a day-to-day basis. Be skeptical when reading the paper, speaking with colleagues, and making decisions. Finally, if you’re ever lucky enough to be the first patient with phantasticolithiasis, opt for procedure A.

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Mass Casualty Incidents

April 27, 2013 — 1 Comment

In the wake of the 2013 Boston Marathon bombings, I feel it is helpful to reflect, as many have already done, on the situation. Atul Gawande, for example, has already provided an excellent review of the preparedness of Boston’s hospitals. The city was prepared due to extensive and flexible training, along with the assistance of myriad bystanders. With three deaths and over 260 casualties, this left a mortality rate of about 1%. This is remarkable, and numerous factors may have played a role in addition to any disaster plan.

What could have led this mortality rate to be so low? First, consider the location. This was a major public event, with medical personnel readily available. Additionally, the timing of the bombings was unique. The attack occurred not only on a holiday when operating rooms may not be at capacity, but they took place shortly before the 3:00 p.m. shift change that occurred at nearby hospitals. This created a situation where space was available, and twice the number of medical teams were available at this time. The location itself was beneficial, too. Boston is home to world-renowned hospitals with seven trauma centers. In other words, capacity and quality peak at this location. Even the location of the bomb was beneficial. Indoor attacks tend to produce greater injuries due to concentrated blast waves. The shoddy pressure-cooker bombs in this open venue reduced primary blast injuries compared with a situation indoors. Finally, we can see the effects of medical knowledge from military personnel making its way through trauma centers in the United States.  For example, Boston’s EMS chief hosted a conference to discuss the effects of blast injuries and terrorist attacks across the globe, taking advantage of this military knowledge. Taken together, a combination of superb disaster preparedness with key factors unique to this situation may have played a role in the reduction of the mortality in this attack.

This is not intended to detract from the severity of the Boston Marathon bombings. Like all attacks, this was a national tragedy that struck a chord with many of us. Numerous media outlets reporting on the attack described mass casualties. It is this term that I would like to clarify in this blog post. What does mass casualty mean? Having spoken with numerous colleagues and friends, I find that this term needs some clarification.

First, one must define casualty. This term has both military and civilian usages. A military casualty is any person that is deemed unfit for war, typically due to death, injury, illness, or capture. A civilian casualty, in the broadest sense, refers to both injuries and deaths in some incident. I bring this up because the term casualty is oftentimes incorrectly used synonymously with fatality, with the latter referring to only to deaths, and casualties including both fatal and non-fatal injuries.

But what is a mass casualty? The New York Post may want you to believe that this refers to a large number of fatalities, but we already know that a casualty is not a fatality. Is it then a large number of people injured or killed? The answer is more nuanced than that. A mass casualty incident is a term used by emergency medical services, not referring solely to the number of people injured or killed. It is better to consider this as a protocol that one must follow in a situation where the number of casualties (or potential casualties) outweighs the resources available. A mass casualty incident could thus include both a major explosion with hundreds injured to one building with a carbon monoxide leak where there are not yet any injuries. It comes down to the difference between the number of people that must be triaged versus the supplies available. This term may be related to total casualties, but it is not a measure of them.

In a mass casualty incident, a protocol of triage, treatment, and transport is followed. First, all persons in the vicinity are triaged. This means that medical personnel look at each person to see who requires the most immediate medical attention. Then, triaged patients (color coded) are taken to appropriate treatment areas. In extreme cases, an on-site morgue is set up to handle the worst cases. This happened in Boston, where an EMS tent acted as the morgue. Finally, after initial treatment, patients are transported to hospitals for care. This protocol has specific guidelines for each member of the team, creating a situation for efficient triage, treatment, and transport.

It is then disheartening to hear screams of mass casualties used loosely in the media, often implying a large number of civilian mortalities. This creates an air of panic and fear. While we must report cases like this with severity, we must also do it accurately, and the misuse of this term is just one of many mistakes the media made in this scenario. Precision in language is important. More importantly, we must also remain accurate and vigilant in both reporting and understanding of breaking news reports.

Though I only focused on one term, I hope this provides a general lesson to all. Misuse of terms in national media misinforms. We must take it upon ourselves to remain educated, promote vigilance in the reading of such reports, and educate others on what we learned.

A Troubling Divorce

March 23, 2013 — Leave a comment

The unhappy marriage between the United States government and science (research, education, outreach) ended this month. We’ve known for years now that the relationship was doomed to fail, with shouting matches in Washington and fingers pointed in all directions. I would more likely describe an end to the relationship between elected officials and human reason, but that would be harsh, and I still have hope for that one. Sadly, this generation of congresspeople signed the paperwork for a divorce with science.

America’s love affair with science dates back to its origins. Later, Samuel Slater’s factory system fueled the Industrial Revolution. Thomas Edison combatted with Nikola Tesla in the War of the Currents. It was a happy marriage, yielding many offspring. The Hygienic Laboratory of 1887 grew into the National Institutes of Health approximately 50 years later. We, the people, invented, explored, and looked to the stars. Combined with a heavy dose of Sputnik-envy, Eisenhower formed the National Aeronautics and Space Administration (NASA) in July 1958. We, the people, then used our inventions to explore the stars.

Since then, generations of both adults and children have benefited from the biomedical studies at the NIH, the basic science and education at the NSF, and the inspiration and outreach from NASA. Since Goddard’s first flight through Curiosity’s landing on Mars, citizens of the United States have not only directly benefited from spin-offsbut also through NASA’s dedication to increasing STEM (science, technology, engineering, mathematics) field participation. Informed readers will know that although the STEM crisis may be exaggerated, these fields create jobs, assuming benefits from manufacturing and related careers. Such job multipliers should be seen as beacons of hope in troubling times.

Focusing on the NIH, it should be obvious to readers that biomedical science begets health benefits. From Crawford Long’s (unpublished and thus uncredited) first use of ether in the 18th century through great projects like the Human Genome Project, Americans have succeeded in this realm. However, as many know, holding a career in academia is challenging. Two issues compound the problem. First, principal investigators must “publish or perish.” Similar to a consulting firm where you must be promoted or be fired (“up or out”), researchers must continue to publish their results on a regular basis, preferably in high-impact journals, or risk lack of tenure. The second problem lies in funding. Scientists must apply for grants and, in the case of biomedical researchers, these typically come from the NIH. With funding cuts occurring throughout the previous years, research grants (R01) have been reduced both in compensation per award and number awarded. Additionally, training grants (F’s) and early career awards (K’s) have been reduced. Money begets money, and reduction in these training and early career grants make it even more difficult to compete with veterans when applying for research grants. Thus, entry into the career pathway becomes ever the more difficult, approaching an era where academia may be an “alternative career” for PhD graduates.

The United States loved science. The government bragged about it. We shared our results with the world. Earthriseone of my favorite images from NASA, showed a world without borders. The astronauts of Apollo 8 returned to a new world after their mission in 1968. This image, the one of the Earth without borders, influenced how we think about this planet. The environmental movement began. As Robert Poole put it, “it is possible to see that Earthrise marked the tipping point, the moment when the sense of the space age flipped from what it meant for space to what it means for Earth.” It is no coincidence that the Environmental Protection Agency was established two years later. A movement that began with human curiosity raged onward.

Recently, however, the marriage between our government and its science and education programs began to sour. Funding was cut across the board through multiple bills. Under our current administration, NASA’s budget was reduced to less than 0.5% of the federal budget, before the cuts I am about to describe. The NIH has been challenged too, providing fewer and fewer grants to researchers, forcing many away from the bench and into new careers. Funding for science education and outreach subsequently fell, too. Luckily, other foundations, such as the Howard Hughes Medical Institute, picked up part of the bill.

I ran into this problem when applying for a grant through the National Institutes of Health and discussing the process with my colleagues. I should note as a disclaimer that I was lucky enough to have received an award, but that luck is independent of the reality we as scientists must face. The process is simple. Each NIH grant application is scored, and a committee determines which grants are funded based upon that score and funds available. With less money coming in, fewer grants are awarded. Thus, with cuts over the past decade, grant success rates plummeted from ~30% to 18% in 2011. When Congress decided to cut its ties with reality in March and allow for the sequester, it was estimated that this number will drop even further. (It should be noted that a drop in success rate could also be due to an increase in the number of applications, and a large part of that decrease in success rate over 10 years was due to the 8% rise in applications received.) This lack of funding creates barriers. Our government preaches that STEM fields are the future of this country, yet everything they have done in recent history has countered this notion. As an applicant for a training grant, I found myself in a position where very few grants may be awarded, and some colleagues went unfunded due to recent funding cuts. This was troubling for all of us, and I am appalled at the contradiction between rhetoric in Washington and their annual budget.

Back to NASA. As we know, President Obama was never a fan of the organization when writing his budget, yet he spoke highly of the agency when NASA succeeded. Cuts proposed by both the White House and Congress to NASA in 2011 for a reduction of $1.2 trillion over 10 years have already been in place. This was enough to shut down many programs, reduced the number employed, and led to the ruin of many of its buildings. However, the sequester, an across-the-board cut, also hit NASA very hard. As of yesterday, all science education and outreach programs were suspended. This was the moment that Congress divorced Science.

All agencies are hit hard by these issues, and it isn’t just fields in science, education, and outreach. Yet, speaking firsthand, I can say that these cuts are directly affecting those of us on the front line, trying to enter the field and attempting to pursue STEM-related careers. Barriers are rising as the result of a dilapidated system. Having had numerous encounters with failed F, K, and R awards amongst friends and colleagues simply due to budget constraints (meaning that their score would have been awarded in a previous year, but the payline was lowered to fund fewer applications) and seeing children around New York who are captivated by science education but are within a system without the funds to fuel them, I can comfortably claim that we are all the forgotten children of a failed marriage.

Whether it be due to issues raised in this post or your own related to the sequester, remember that this is a bipartisan issue. There are no winners in this game, except for those congresspeople whose paychecks went unaffected after the sequester. I urge you to contact your elected official. Perhaps, we can rekindle this relationship.

The text below is modified from a document another Director and I wrote regarding our free clinic based in New York City. I feel it is necessary to disseminate this information in order to dispel beliefs that nearly all those living in the United States will have access to healthcare in the next 5-7 years.

Our clinic has a mission “to provide high-quality, accessible healthcare to uninsured adults through consultation, treatment, preventative care, and referral services, at little or no cost.”  The signing of the Affordable Care Act (ACA) in 2010, colloquially known as “Obamacare,” redefines the population of uninsured adults in the United States. However, a significant portion of this group will remain uninsured, and free clinics will continue to provide a safety net for this population.

We currently admit uninsured adults who earn less than 400% of the Federal Poverty Level.  Thus, our clinic provides services to those who do not have access to healthcare and cannot afford the options available.  The ACA is often portrayed as near “universal coverage,” especially in the popular media.  Unfortunately, this portrayal does not reflect reality. The Congressional Budget Office estimates that from 2014 through 2019, the number of uninsured adults in the United States will be reduced by about 32 million through mandates and subsidies.  However, this leaves over 23 million uninsured by 2019. While a significant reduction, this leaves a wide gap that must be filled by safety net programs.  About 4-6 million will pay some penalty in 2016, with over 80% earning less than 500% of the Federal Poverty Level. (Note that increases in the estimates of the number of insured from 23 to 26 million by the CBO reflects changes in Medicaid legislation.) The uninsured population will include, but will not be limited to, undocumented immigrants, those who opt to pay penalties, and those who cannot afford premiums (often those earning less than 500% of the Federal Poverty Level). Thus, many may still be unable to afford options available, and free clinics will continue to welcome them.

The gap in healthcare access will be reduced over the coming years.  Even with this reduction, the number of uninsured adults will remain many. Community healthcare programs across the country shall continue to provide coverage for those who need it most.

References:

  1. Congressional Budget Office, “Selected CBO Publications Related to Healthcare Legislation, 2009-2010.” http://cbo.gov/sites/default/files/cbofiles/ftpdocs/120xx/doc12033/12-23-selectedhealthcarepublications.pdf
  2. Congressional Budget Office, “Another Comment on CBO’s Estimates for the Insurance Coverage Provisions of the Affordable Care Act.” http://www.cbo.gov/publication/43104
  3. Congressional Budget Office, “Estimates for the Insurance Coverage Provisions of the Affordable Care Act Updated for the Recent Supreme Court Decision.“ http://www.cbo.gov/publication/43472
  4. Chaikand et al, “PPACA: A Brief Overview of the Law, Implementation, and Legal Challenges.” http://www.nationalaglawcenter.org/assets/crs/R41664.pdf

Recently, the Lancet posted yet another article on Obama’s Global Health Initiative. In it, the writer points out the numerous failures of the GHI. The $63 billion budget was not new money and was instead a new label for funds already budgeted elsewhere. Where GHI differed was in its goal to place all of the leadership under one organization. A central office was created, but this was shut down in July. The article then focuses its text on the tensions that arose when USAID took over as the leaders of the program. I could go on about the successes and failures of the global health initiatives, but I would prefer to focus on a more important issue. What are the GHIs? It is my belief that productive debate will arise if and only if we are adequately informed.

The Global Health Initiatives focus mainly on infectious disease and strengthening healthcare systems around the world. Prior to the Obama administration, they were many organizations (and if we are to be honest, still act as such). PEPFAR and the Global Fund to Fight AIDS focused on HIV/AIDS. The Global Fund also targeted tuberculosis and malaria. The GAVI Alliance put its efforts into immunization. The World Bank’s MAP dealt with AIDS and nutrition. These are not foci of the United States, and Obama’s plan called for a comprehensive effort similar to (and including) these programs that would combine their efforts to improve their effectiveness.

I will instead focus on the current administration’s global health initiative, without a critique. In November 2009, the goal of the GHI was to double US aid for global health to approximately $16 billion per year in 2011, establish goals for the US to assist in addressing the Millennium Development Goals, and attempt to scale up domestic health efforts. The six areas of focus included HIV, tuberculosis, malaria, reproductive health, health systems, and neglected tropical diseases. The November report made three recommendations. First, the group wished to define measurable GHI targets. These would be US-specific and would focus on the delivery of care. Second, they recommended funding be increased to $95 billion over six years, an increase from the original budget. Finally, the recommended that the GHI focus on outcomes and be people-based. Overall, the recommendations were subtle and not clearly defined, but they hinted at the theme of the GHI. The goal was to provide a comprehensive program in which the United States could better address global health initiatives. This was sold as change from the disease-specific nature of Bush’s programs to one that focused on health systems and delivery.

In July 2012, the GHI office was officially closed by the Obama administration. It was touted as a productive shift, but the reality was that this closure was due to myriad problems encountered by the program. The program lacked core leadership, and those in the developing world had troubles with knowing what defined a GHI project. While it had a huge budget, there were only four full-time employees in the office. The idea remained, but the office did not.

There is far more to this story, but that is what you should know about Obama’s GHI. It was and still is an interesting idea, but it remained an idea. What we need are solutions with better focus.

Orwellian Semantics

September 30, 2012 — Leave a comment

I have numerous issues with the bad habits of modern writing, including an overuse of the passive voice, laziness through use of metaphor, and an abundance of technical jargon or pretentious vocabulary. My writing often falls victim to this, especially with my personal poor habit of the use of the passive voice. It becomes problematic in medical or technical communication when jargon and abbreviations render listeners incapable of understanding. In political speech, we hear perversions of metaphorical language, with a bit of Latin thrown in where a Saxon word would suffice. This lack of precision becomes problematic, and such issues were discussed by George Orwell in his fierce essay, ‘Politics and the English Language.’

I’ve often heard, in casual conversation or, worse, in public arenas, the phrase ‘it’s only semantics’ or a phrase of that nature. This implies that the person is either lazy in speech or uninformed. I like to think that our downfall is sloth rather than lack of knowledge, so I will assume that these people know the premises behind semantics, what they imply, and why they are so very important. If that is true, then the speaker is simply tired of the disconnect in language that is being proposed.

Let’s assume one hasn’t read the precision of Ernest Hemingway, the frugality of EB White, or the aforementioned essay by Orwell. I’ll relate semantics to the study of information, information theory. Let’s trace a message from you to me,if we were speaking or writing to one another. A message begins at its source, such as a thought or argument in your brain. You must codify this message into language, either written, spoken, signed by hand, or some variation. That message is transmitted, by air, telecommunications, visually, or the like, to me. I must then, as the receiver, decode the message. Thus, information passes from you to me. A problem at any level leads to a breakdown in our conversation and, according to the optimist Orwell, decline of civilization.

Semantics is the study or philosophy of how we communicate with and understand one another. In terms of the information theory example above, this refers to the coding and decoding of speech. The words we use attempt to convey information. If the words are not precise, the information will be lost or misunderstood. If you heard me state that ‘John is a wild card, but Jane is solid,’ would you say this is precise? Sure, in context, you might understand the message, but that is no excuse and is thus laziness of speech. If you heard ‘John’s exam performance varies based upon his mood, but Jane always performs well,’ you can already see an improvement in the message’s precision. Again, we should remain as precise as possible, no matter the context.

In communicating between those in medicine, those in science, those in economics, and those in countless other fields, I can see this lack of focus on semantics. We become lazy and begin to use metaphors, jargon, or lack of descriptive terms. We then become annoyed when a person begins to focus on the meaning behind individual words or phrases, stating that it is only semantics. Thus, I believe this phrase stems from a laziness founded in sloth.

I am a horrid writer. Specifically, I mean that I tend to use the passive voice too often, use unnecessary words to balance the flow of a sentence, and often lack precision. However, I believe very strongly in proper communication. Many say this has to do with listening, but the act of listening is limited by the quality of the message transmitted.

This post stems both from issues in my research proposal revisions and with my status lying at the meeting point between medical and graduate students. They don’t understand each other quite often, and my split personality feels a sense of cognitive dissonance. I urge those in any field to practice in precision and recoding of speech for those outside your field. I’m working on it, too, and it is difficult to break bad habits.

Two years ago, I wrote a piece for a public health group based upon a project based in medical school. An excerpt follows:

“In June 2009, President Barack Obama signed into law the Family Smoking Prevention and Tobacco Control Act (HR 1256). This legislation would require all tobacco products and advertising to have a graphic warning covering 50 percent of the front and back iof the package. The FDA has proposed a number of graphic designs […] The proposed designs include grotesque imagery in an attempt to dissuade smoking in the United States. According to the Center for Disease Control, smoking accounts for approximately 443,000 deaths per year in the US, including deaths from lung cancer, cardiovascular disease, COPD, and numerous other morbidities. It is thus apparent that smoking is a public health concern, and these new warning labels hope to address the concern by deterring such behavior. However, though the proposed graphic labels may be more effective than the previous Surgeon General’s Warning (a text-only message on the side of the package), these labels can be greatly improved through what will be defined as a gains-based message as opposed to the proposed loss-based message. In doing so, the labels would not only educate the public on the dangers of smoking, but it will be argued that they will encourage smoking prevention and cessation behavior. In fact, it is argued that the currently proposed labels may do more harm than good. To make this argument, three assumptions must be made. First, as hinted above, smoking is a public health concern. Second, tobacco warning labels are designed to result in human behaviors of smoking cessation and prevention. Finally, human behavior is, in some circumstances, predictable.

This is not to say that the proposed labels by the FDA or those currently being used around the world are completely ineffective. In fact, the graphic labels may be more effective than the small text-only Surgeon General’s Warning. However, there is a wide margin for improvement. The proposed labels appear to be far too grotesque. Though admittedly fear-inducing, this negative emotion will most likely lead to reactance behavior. Expect sales of slip covers to increase, along with the possibility of some smokers increasing their smoking behavior. Smoking rates may continue to decline, but the rate of this decline may not yet be optimal. Data from other countries, along with numerous experimental studies, have demonstrated that confounding factors can contribute to the decline in these countries, and grotesque imagery can result in maladaptive behavior. A truly effective label would be designed with a positive, gain-framed message. It would be designed to motivate behavioral change and encourage self-efficacy. Data from others who were able to quit can enhance subjective norms. Imagery depicting the benefits of quitting or those who were able to quit can further eliminate reactance. All of this would then be coupled with resources on quitting, such as phone numbers, web sites, and support groups. This is a war that cannot be fought with fire. As demonstrated every time a cigarette is lit, fire is only good for lighting up.”

First, I believe that this claim still holds, and my predictions, while still probably true, mean little when compared to the growing need to reform healthcare. Howevera greater concern lies in how we approach public health research. Within basic science, and especially physics, we like to break down larger systems into their components, analyze them, and search for unifying hypotheses. That is one method, but the concept is simple: Focus on the rules of a system in order to predict behavior.

Often, this concept is lost in public health research. Perusal of the literature will reveal that such concepts are hypotheses in the discussions of papers, but one sees very few examples where they are applied. In the case of tobacco warning labels, concepts in behavioral psychology may be applied to predict behavior resulting from labeling campaigns. The validity of these models remains to be seen, due to a low sample size. Nonetheless, studies were performed. Phone surveys revealed results similar to what was predicted by the theory of reactance.

Briefly, the theory of reactance predicts a cycle in human behavior. One begins with some level of (1) freedom, which is then (2) threatened. The human will (3) react, and undergo a (4) restoration of this freedom. Types of reactance include those exhibited by certain groups (trait reactance) and various threats to freedom (state reactance). These can be measured through fear, anxiety, disgust, and the like, all of which are predicted to increase with the level of reactance. The restoration of freedom is key. This is done through avoidance, acting out, or the like. In the case of smoking, this would be manifested in increased rates of smoking, a reduced desire to quit, downplay of harmful effects, and avoidance through the purchase of slip covers. A study by Dillard et al. in 2005 pointed out such concepts, and phone surveys on tobacco noted such reactions.

Another concept is message framing. There are two types of messages in this theory, gain-framed and loss-framed. A gain-framed message focuses on the benefit of performing a task, while a loss-framed message focuses on the risks associated with not performing the task. Loss-framed messages include pointing out the risks associated with not performing regular mammographies or other early detection methods of disease. Gain-framed messages include those associated with the benefits of exercise and sunscreen use. The current tobacco warning labels would be improved by avoiding reactance through the use of gain-framed messages, as was pointed out by Tamera Schneider in the Journal of Applied Psychology in 2001.

This highlights an important issue in public health and other epidemiological studies. The studies often do not cite and properly utilize the foundational psychological or basic science research. This shapes policy in a less-informed manner, sometimes leading to unforeseen negative outcomes. By increasing effective communication between the sciences and epidemiology, policy changes may become more effective