NCADD ESGPV Blog

“It all comes down to your choices,” said a man in his fifties as he completed treatment following a brief return to drinking lots of alcohol.

In the company of supportive peers and an empathic treatment team, this man had immersed himself for three weeks in mindfulness practices structured by Acceptance and Commitment Therapy (ACT). He also maintained connections with his sponsor and Alcoholics Anonymous.

The man recounted how an offer of alcohol—made amid physical, interpersonal, and financial stressors—precipitated his most recent drinking episode. Similar situations had instigated previous binges.

In the future, he plans to minimize exposure to stressors and drinking opportunities. When stressors or alcohol are unavoidable, he anticipates choosing to notice them without reacting in ways that conflict with his values. “Personal responsibility” for “choices” protects his paramount value, sobriety.

Such clarity is too rare. Many others with addiction—and people around them—would do well to adopt this perspective. Choices represent the way out of active addiction, much as they represent the way in.

Opioid misuse and overdose deaths in the United States have been rising for two decades. Between 2000 and 2013, the opioid overdose rate—among all ages, races, genders, and ethnicities—nearly quadrupled, increasing from 0.7 to 2.7 deaths per 100,000 individuals. Drug overdose is now the single greatest cause of unintentional deaths in America.

Suffolk County, in downstate New York, has been hit particularly hard. With 337 heroin-related deaths between 2009 and 2013, Suffolk County reported more such deaths than any other county in New York State. And in 2014, the age-adjusted opioid-related death rate in Suffolk County was 12.6 per 100,000, compared to the New York State average of 7.2 per 100,000. This article explores why Suffolk County residents are at greater risk for overdose deaths and, more important, how they are now protecting themselves.

The Community

Suffolk County occupies the easternmost two-thirds of Long Island. Its population size of 1.5 million is larger than that of several individual states (Vermont, Rhode Island, Delaware, North & South Dakota, Montana, Wyoming, and Alaska). Compared to the rest of New York State, Suffolk County residents are generally more prosperous (inflation-adjusted median annual household income $85,886 in 2014; third highest of New York’s 62 counties) and less diverse. The income gap between the county’s upper and lower socioeconomic classes is smaller than the state average. In 2015, 68.6 percent of Suffolk County identified as “non-Hispanic white,” compared to 56.0 percent for New York State.

Suffolk and Opioids

The high percentage of Caucasians in Suffolk County may help to explain that county’s high rate of opioid deaths. The following graph of national statistics from a Centers for Disease Control and Prevention (CDC) publication shows that, between 2000 and 2013, the most dramatic jump in heroin-related overdoses was in non-Hispanic white persons aged 18 to 44. New York State statistics are similar—in 2014, the heroin-related mortality rate for all residents of New York State was 6.5 per 100,000, whereas the rate for only non-Hispanic whites was significantly higher (9 per 100,000).

“Drug-Poisoning Deaths Involving Heroin: United States, 2000-2013.” Holly Hedegaard, Li-Hui Chen, & Margaret Warner. NCHS Data Brief #190, March 2015. http://www.cdc.gov/nchs/data/databriefs/db190.htm

Several years ago, a colleague asked me what I thought about his “four months and done” buprenorphine treatment program. He believed that virtually all people with opioid use disorders could “learn” how to stay drug-free in that time.

All his patients were titrated to an effective dose in the first weeks, maintained for the first two months, and tapered off over the next two months. He offered anecdotal evidence of the success of his approach, but it became clear that most of those he tapered simply disappeared. He had no meaningful data, even in the short term. I asked him whether he took a trauma history when his patients initially presented, and he had no idea what I was talking about.

I am an individual in recovery as well as a treatment professional, and I have treated tens of thousands of patients with addiction. Most of those patients, when questioned, had a history of serious early-life trauma, or such significant neglect that it was the equivalent of trauma.

Yet, as little training as I received in medical school and residency about substance use disorders, even less was provided on the role of trauma. This was true in my addiction fellowship as well.

I have reviewed scores of intake forms for treatment programs, and only in the last several years have I seen questions about traumatic experiences routinely asked.   I was involved in an audit of an internal medicine practice that was concerned about the overprescribing of opioids and benzodiazepines by “outlier” physicians. They had an excellent electronic medical record with a section on early-life trauma. Out of hundreds of charts reviewed, however, this section was not completed for even one patient.

Most healthcare professionals promote the well-being of one individual at a time. Those who work in public health, however, promote the well-being of groups of individuals. The U.S. Public Health Service and the rest of the U.S. Department of Health and Human Services (HHS) promote the well-being of overlapping groups that taken altogether represent the entire population of the United States.

Individuals do not always collaborate with healthcare providers. For example, only about 50 percent of patients with chronic diseases take their medications as prescribed. It remains to be seen whether the population of the United States will collaborate with HHS’s current initiative to protect the well-being of the Nation.

In November 2016, HHS released FACING ADDICTION IN AMERICA: The Surgeon General’s Report on Alcohol, Drugs, and Health. Reports from the Surgeon General are not routine government publications. They address serious threats to the health of the population (e.g., HIV/AIDS) to raise awareness, provide scientific background, and generate interventions to reduce the danger. The reduction in American adults who smoke from 42 percent in 1960 to 18 percent in 2012 is due in part to a series of Surgeon General’s reports on smoking and health that began in 1964.

FACING ADDICTION IN AMERICA conveys authoritative information in accessible language and lists abundant references for readers who desire more detail. The report presents persuasive statistics for anyone who may doubt that alcohol and drugs put our health at risk. For example, “In 2015, 66.7 million people in the United States reported binge drinking in the past month and 27.1 million people were current users of illicit drugs or misused prescription drugs.” (p 1-1) And, “Substance misuse and substance use disorders… [cost] more than $400 billion annually in crime, health, and lost productivity.” (p 1-2)

 Scientific background in this report encompasses not only a neurobiological explanation of why substance-using behaviors are so difficult to change, but also research that shows which prevention and treatment methods are most likely to succeed. Health services research supports the integration of substance use prevention and treatment with general healthcare services, which is in keeping with Surgeon General Vivek Murthy’s call for “a cultural shift in how we think about addiction…addiction is not a character flaw—it is a chronic illness that we must approach with the same skill and compassion with which we approach heart disease, diabetes, and cancer.” (Preface)

Attention Deficit Hyperactivity Disorder (ADHD) is a condition characterized by inattention, disorganization, and/or hyperactivity-impulsivity that consistently disrupt a person’s activities and relationships. According to DSM-5 (p 32), “Inattention and disorganization entail inabil­ity to stay on task, seeming not to listen, and losing materials, at levels that are inconsistent with age or developmental level. Hyperactivity-impulsivity entails overactivity, fidgeting, in­ability to stay seated, intruding into other people's activities, and inability to wait—symptoms that are excessive for age or developmental level.”

This conception of ADHD is relatively new, although literature of the past 200 years depicts individuals who might meet current criteria for ADHD. In 1844, for example, German psychiatrist Heinrich Hoffman created a children’s story about Fidgety Phil (“Zappelphilipp”). In 1902, English pediatrician George Still described children with an “exaggeration of excitability” whose behavior was so disruptive that he considered them to have a defect of moral control. In 1937, Rhode Island physician Charles Bradley, while attempting to treat headaches that followed pneumoencephalograms, discovered that the stimulant benzedrine improved learning and behavior in hyperactive children. The modern understanding of ADHD began to emerge with descriptions of “minimal brain dysfunction” in the 1960s and 1970s. (Lange et al. 2010)

Estimates vary, but about 10 percent of children and 4 percent of adults may meet criteria for ADHD. ADHD in childhood is a risk factor for early substance use and adult substance use disorder. Up to 30 percent of adults with ADHD are estimated to have a substance use disorder. The common comorbidity of ADHD and addiction makes it important for clinicians who treat ADHD in adults to assess patients comprehensively—even though their patients don’t like to wait.

When assessing adults for ADHD, symptoms may be misleading and accurate diagnoses elusive. Family histories of ADHD, other mental illnesses, and addiction are relevant. So is evidence of when patients’ ADHD symptoms began, since rigorous diagnosis of adult ADHD requires that several symptoms were present before age 12. Old report cards help, or talking with individuals who were adults when they knew the patient as a child.

ADHD, bipolar disorder, and addiction mimic one another, yet any two—or all three—conditions may co-occur in one individual. Hyperactivity and impulsivity, for example, suggest both ADHD and bipolar disorder. (Bipolar disorder is favored when the behaviors are episodic and accompanied by elevated mood.) Inability to wait (“I want what I want when I want it”) can be a manifestation of any of the three conditions.

Once again, the holiday season is upon us.  The Addiction Medicine Update, Hope & Caution—for Happy Holidays,  originally published in November 2012, receives thousands of views, telling us that it strikes a chord in readers.  With that in mind, we are reprinting it this year.

 As we approach the holiday season—the time of year from Thanksgiving through New Years when "joy" is the word but not necessarily the reality—it's worth reflecting on ways we can protect ourselves and those we care about from inconvenience and tragedy due to use of alcohol or other mood-changing substances. Start by believing that some measure of holiday joy and fulfillment, provided we are open to it, is available to us all.

 Caution is needed. But the holidays evoke strong feelings, and strong feelings often override caution. Strong feelings could include the stress of keeping up with the seasonal parade of expectations and events such as shopping, travel, cooking, social gatherings, and so forth—or the stress of not having any of those to keep up with. Strong feelings also arise from our past. And our past is more present at the holidays, especially past family life. Cherished holiday memories hurt when special people are no longer with us. Painful holiday memories hurt even more when the holidays arrive, whether the people involved are still with us or not.

As a general precaution, reduce holiday stress by talking about your feelings with an empathic person and by letting go of unrealistic expectations. Specific precautions against hazardous holiday substance use depend partly on whether a person is in recovery or not. Individuals in recovery want to abstain from all mood-changing substances. But an occasional drinker may simply wish to limit her or his alcohol consumption enough to avoid disinhibited behavior (at an office party, for instance) or driving under the influence.

Motor vehicle crashes caused by drunk or drugged-driving end too many lives and damage countless others. For that matter, even DUI offenses can have life-changing consequences. The statistics are hard to ignore.

Efforts to create electronic cigarettes date from the 1930s. The first commercially successful devices were produced in China in 2003. Electronic cigarettes were introduced to Europe in 2006 and America in 2007. In the United States, regulation of these and similar products became much more stringent in 2016.

The Family Smoking Prevention and Tobacco Control Act became law June 22, 2009, and gave the U. S. Food and Drug Administration (FDA) regulatory authority over the manufacture, distribution, and marketing of tobacco products. The FDA has deemed electronic nicotine delivery systems (ENDS) to be tobacco products and issued regulations that affect not only electronic cigarettes (e-cigarettes) but also other devices that produce an inhalable cloud containing atomized nicotine. Initial stipulations took effect August 8, 2016. Additional requirements are scheduled for 2018.

Some ENDS resemble conventional means for smoking tobacco, such as e-cigarettes, e-cigars, electronic pipes, and electronic waterpipes. There are also hand-held personal vaporizers that look like oversized pens or electronic boxes with high-tech tubes on one end. Usual components of these devices include a cartridge or reservoir (“tank”) to hold a solution containing nicotine, the solution itself (e-liquid or “juice”), a heating coil to vaporize the solution, a wicking mechanism to bring solution to the coil, a battery to power the coil, and a mechanism to turn the power on and off. The user briefly activates the unit and inhales nicotine-containing vapor as it is generated.

Most e-liquids contain nicotine extracted from tobacco. Synthetic nicotine is sometimes used, but it’s more expensive and unlikely to avoid FDA regulation despite not being a tobacco product. E-liquids listing no nicotine content are still subject to regulation.

E-liquids are manufactured with a range of nicotine concentrations to accommodate different consumer preferences and methods of use. A light-to-moderate strength e-liquid, for example, contains 6 milligrams of nicotine per milliliter of solution. The bulk of e-liquids (80 to 90 percent or more) are either propylene glycol (PG), vegetable glycerine (VG), or a blend of the two. The rest is nicotine, flavoring, and perhaps added distilled water. PG and VG are common food additives considered safe for humans to eat. Their safety when inhaled has not been established.

Imagine two stalwart fans of professional wrestling locked in debate. One holds that the wrestlers are athletes. The other argues that they are not athletes but entertainers, performing in a variety of theater. Both fans are thoughtful and persuasive. Notice that their disagreement is not about the physical attributes of professional wrestlers, or about what they do inside and outside the ring. Their disagreement is about how to name, or classify, the group of people who engage in professional wrestling.

Professional wrestlers are what they are and do what they do.  Naming and classifying, however, are conceptual, and therefore somewhat arbitrary.  This arbitrariness is no revelation.  As Shakespeare’s Juliet said: 

What's in a name? that which we call a rose
By any other name would smell as sweet

But when debates about classification heat up, people often think and act as if the issues are absolute rather than arbitrary, especially if debaters have a personal or professional stake in one point of view.  Or just like to debate.

Diseases are classifications. They designate groups of people with health problems whose problems are not identical but are so similar in their biological mechanisms and responses to treatments that, when individuals are accurately diagnosed with a disease, they can benefit from knowledge of causes and treatments drawn from research on others like them.

Healthcare providers are charged with helping individuals who come to them with physical, emotional, and behavioral problems.  As they prepare to help, providers usually follow a routine—they get to know the person and their problem(s), examine the person, and, frequently, obtain additional information such as blood tests or x-rays.  Prior to recommending specific treatment, providers “make a diagnosis,” which then guides providers and patients to treatment options relevant to the problem at hand.

    Diagnoses are commonly expressed in terms of the manifestations of a problem (hives, for example) or the cause of a problem (for example, penicillin allergy).  Clinicians sometimes make diagnoses quickly and confidently or, at other times, slowly and tentatively.  They may entertain several candidate diagnoses, “the differential diagnosis,” before settling on a provisional, or working, diagnosis.

    A biology professor periodically reminded his students, “Variation is the law of life!”  Clinicians can testify to this.  No two patients—or the problems they present—are identical, which means that when clinicians make the same diagnosis in two individuals, they are not saying the two people have exactly the same problem.  They are saying that the problems of the two patients have important characteristics in common, often at a cellular level, and that both patients are likely to respond to similar treatments.

    For example, the thick, scratched blotches on the neck of the woman under stress do not look precisely like the raised, itchy patches that appeared on the arm of the young man after a dose of penicillin.  But if clinicians diagnose hives in both cases, both patients will likely obtain relief if they accept treatment with an antihistamine.

The two people and two skin eruptions are not identical, but the underlying cellular processes and responses to medication are so much alike that both individuals, with different but similar problems, benefit from receiving the same diagnosis—and ensuing treatment guided by that diagnosis.

Crimes related to illegal drugs often make headlines—seizures of substances, arrests of drug lords and dealers, and laws broken to support habits. Crimes related to alcohol are also in the news, but we may have to turn to police logs to find them. Yet alcohol is implicated in 56.6 percent of incarcerations in America, which includes 57.7 percent of inmates who committed a violent crime such as murder, forcible rape, robbery, or aggravated assault. Alcohol has more links to crime than any other single drug. (Behind Bars II: Substance Abuse and America’s Prison Population).

Consumption of alcohol does not in itself cause crime. But alcohol impairs coordination and judgment, which makes driving dangerous, especially for young, inexperienced drinkers. Estimates vary, but some authorities report alcohol-impaired driving contributes to more than 50 percent of motor vehicle crashes and more than 50 percent of highway fatalities. Driving under the influence (DUI) of alcohol is against the law for good reason.

About one-third of individuals arrested or convicted of drunk driving are repeat offenders. Of course a calamity may occur the very first time someone drinks and drives, but over 80 percent of DUI offenders are estimated to be more than casual users of alcohol and/or other drugs. Screening, intervention, and treatment of offenders reduce future risks to them and to others on the road.

Again, alcohol consumption does not in itself cause crime. But alcohol is disinhibiting, which means individuals under the influence of alcohol are more likely to do things they would not otherwise do. Alcohol is also addictive, which means some individuals will do things they would not otherwise do—repeatedly.

Following incarceration for addiction-related crimes, recidivism to substance use and to crime is probable unless those released engage in addiction recovery. A study that found only eleven percent of inmates with substance use disorders received relevant treatment during incarceration also reported that each former inmate who remains sober, crime-free, and employed will save the nation $91,000 per year.

In the December, 2015, edition of this Science Update we responded to a recent article appearing in The Atlantic.1 Its author, Gabrielle Glaser, claimed that AA and its 12-step programs lack scientific foundation, asserting that “nothing about the 12-step approach draws on modern science …..” We presented the data supporting the opposite case, citing several published scientific reports that she did not mention. In the present installment, we review the basis on which she asserts her claim that the success rate of AA is only 5-8 percent. Relying on a single secondary source2 for this claim, Ms. Glaser writes, “That is just a rough estimate [of AA’s effectiveness], but it’s the most precise one I’ve been able to find.” Because flawed science can cause harm, we offer a critique of the scientific basis she cites for her claim.

At the outset, Ms. Glaser’s source presents neither new data nor any of the studies we have cited that report first-hand observations targeting AA’s effectiveness. Rather, her source itself refers only to data gathered by others, mostly for purposes other than judging AA’s effectiveness. This forms the basis for three separate, questionable, calculations that arrive at the 5-8% figure. In each calculation, all dropouts—counted after as few as one AA meeting—are treated as AA failures. By analogy, this seems to us like counting insulin for diabetes as a failed treatment after only one insulin injection. In our view, looking at outcome rates for active AA members offers a more accurate estimate of AA’s effectiveness. But let us examine the 5-8% figure.

In the first calculation, The Atlantic article’s source multiplies a 25% AA attendance figure by a 22% abstinence figure to arrive at a 5.5% estimate of AA’s effectiveness. Where do these figures come from? Another second-hand source3 that also cites the work of others: two publications from the Rand Corporation that examined, among other things, attempts at controlled drinking and offered little focus on AA’s effectiveness.  At 4-year follow-up the Rand group identified patients with at least one year abstinence who had been regular members of AA 18 months after the start of treatment: 42% of the regular AA members were abstinent, not the “calculated” 5.5% figure. The Rand Reports are public and both Ms. Glaser and The Atlantic editors could have read them rather than rely on a third-hand source.

The second calculation repeats the 25% AA attendance rate multiplying it by another “abstinence rate” of 21%. This rate is taken from an article by Harris and colleagues4 who surveyed 150 alcoholics entering a residential treatment program because they were not abstinent. Based on the reports of those entering, the study concluded that the sample did “not represent ‘typical’ AA recruits.” Despite this, the third-hand calculation method uses two percentages lifted out of context from the Harris study—16% who had reported ever taking at least one step of the 12-step program divided by 75% who had ever attended an AA meeting—and gives a figure of 21%. This calculation has no bearing on abstinence from alcohol, nor does it apply to AA participation over time. Ms. Glaser and her editors at The Atlantic might have looked into these available data in greater detail in the interest of accuracy.

The third calculation applies the 21% “abstinence” rate claimed above to an alleged 40% sustained abstinence rate noted in yet another report, a paper by Fiorentine (1999).5 Ms. Glaser’s source quotes Fiorentine as writing “’approximately 40 percent of individuals categorized as having continued active participation in AA maintained high rates of abstinence.’” Our reading of Fiorentine’s paper fails to find any such statement. Curiously, Fiorentine reports on a study of drug addicted individuals, only a portion of whom were identified as having an alcohol problem, to offer an estimate of the success of AA. That being said, the data Fiorentine presents is as follows: 77.7% of individuals who attended AA 12-step meetings at least weekly reported being free of drug use for 6 months prior to a 24-month follow-up, a finding corroborated by urinalysis at the time of the interview, and 74.8 % reported being free of alcohol use during the same time period. These figures suggest that a high observed abstinence rate is associated with regular participation in AA. Neither The Atlantic editors nor Ms. Glaser indicate an awareness of these factual discrepancies.

Alcoholics Anonymous is the most widely used treatment for alcoholism in the world, yet it continues to come under attack by popular media ignorant of the science behind its success. A recent high profile attack appeared in the April 2015 issue of The Atlantic, in the form of an article by Gabrielle Glaser titled, “The Irrationality of Alcoholics Anonymous.”   In this article, Ms. Glaser boldly states that 12-step programs lack a scientific foundation and that most professional treatment programs fail to provide scientifically supported treatment, largely because they are 12-step oriented. Ms. Glaser writes, “The problem is that nothing about the 12-step approach draws on modern science: not the character building, not the tough love, not even the standard 28-day rehab stay.”

Contrary to Ms. Glaser’s sweeping statements about the lack of science concerning AA, a significant body of research has been conducted on this organization and its impact on drinking and other variables. For example, three colleagues and one of the authors (CDE) published a meta-analysis of the scientific literature on Alcoholics Anonymous in 1993, incorporating a grand total of 107 data sets in the overall analysis. The findings of this meta-analysis were correlational due to the fact that most of the available data at that time were correlational in nature. These results showed positive correlations between AA membership and drinking outcome, as well as other outcome measures such as psychological health. Of course, correlation does not mean causation. Thus, the data at that time offered promising evidence for the effectiveness of AA but could not support the conclusion that involvement in AA causes better outcomes with respect to drinking and other variables.

But science moves on. A more recent publication (Vaillant 2012) offers yet another example of high-quality research on AA. Dr. George Vaillant of Harvard University reported his analysis of two male cohorts (Harvard undergraduates and inner-city Boston youth) who were studied in depth for 60 years (from the time they were 20 until they were 80)! Over the course of the study, 39 men in the college cohort and 101 men in the inner city cohort were identified as alcoholics. When the lives of these men were studied at age 80 (some of the men were deceased but information was obtained on the status of these individuals at the time of their death), 9 of the college cohort who became alcoholic had been abstinent an average of 15 years and 57 of the inner city cohort alcoholics had been abstinent for an average of 16 years. The remaining men in both cohorts had been abstinent an average of only 1 year over the course of their lives. It is important to note that the duration of active alcoholism did not differ between those who developed long-term abstinence and those who did not. Of relevance to the present article is that those who achieved long-term abstinence in the college cohort attended an average of 137 AA meetings compared to just 2 meetings among those with only short-term abstinence, while those in the inner-city cohort who maintained long-term abstinence attended 143 AA meetings, on average, compared to just 8 meetings among those who did not acquire long-term abstinence. In answer to the question, “is recovery through AA the exception or the rule?” Dr. Vaillant concludes, “In both cohorts, the men who were stably abstinent attended about twenty times as many AA meetings as the chronically alcoholic.” These data, while remarkable, are, as with the Emrick et al. findings, plagued with the issue of self-selection bias. It could be that individuals who go to AA are more motivated to stop drinking than those who don’t become AA involved, with the result that AA members have better drinking outcome, not because they are participating in AA, but rather because they were a more motivated group of alcoholics to begin with. The possibility of self-selection bias thus prevents Vaillant’s (as well as Emrick et al.’s) data from offering evidence that AA involvement causes better drinking outcome.

Fortunately, scientific investigations of AA have continued to advance. From 1993 to 2010, five randomized clinical trials were conducted in which AA Facilitation Interventions (AAFI) was one of the treatments studied. A general finding of these studies is that patients who received some form of AAFI had better drinking outcome than patients receiving alternative treatment(s), with the better outcome appearing to be mediated by AA involvement. Unfortunately, even with these and other clinical trials on AA, selection bias continues to be a thorny problem. That is, some patients assigned to AAFIs do not become involved in AA and patients assigned to alternative interventions become involved despite their being in treatment that does not encourage participation in AA. Given this situation (known as crossover) if AA participation in these studies is found to lead to better outcome than non-participation, we cannot be sure that involvement in AA per se is causing the better outcome. This is because the better outcome seen in AA members may be due, at least in part, to their having stronger motivation to recover from alcohol problems than do non-AA participants. Thus, selection bias is not fully eliminated even when using a randomized clinical trial research design.

In order to address this nagging issue pertaining to the aforementioned randomized clinical trials, Dr. Keith Humphreys, a professor at Stanford University, and colleagues employed an innovative statistical analytic method that controls for selection bias--a procedure called instrumental variables modelling. This analysis enabled the researchers to determine if increased AA involvement due to AAFIs made a difference in drinking outcomes when the role of the participants’ motivation to recover from alcoholism was taken out of the comparison between patients receiving AAFIs and those getting alternative treatments. The results of this study were published in the prestigious peer-reviewed journal, Alcoholism: Clinical and Experimental Research in November of 2014. Humphreys et al. used the number of days abstinent as the outcome measure. The main finding was that at both three and 15-month follow-ups, those who increased AA attendance due to the effects of AAFIs (not personal motivation) had significantly more days of abstinence than those getting alternative treatments who did not go to AA.   To clarify, involvement in AA was the variable that led to better drinking outcome, not receipt of AAFIs per se. The scientists conclude, “For most individuals seeking help for alcohol problems, increasing AA attendance leads to short- and long-term decreases in alcohol consumptions that cannot be attributed to self-selection.”