Lying to Children about Drugs

June 22, 2007

Uncertain Principles takes an interesting new tack on the scientists versus journalists debate. The post points out, quite rightly, that in some cases education requires that the “simple version” of the truth be conveyed because the nuanced, highly accurate version can’t possibly work. Better to communicate the gist than nothing whatsoever, right? The “simple version” of the truth can become lies-to-children which Chad attributes to Terry Pratchett.

I’ve previously touched on the frightening possibility that perception is everything in changing drug use epidemiology. I say “frightening” because it suggests that the real risks, the subject of my professional life, are somewhat tangential. I touch on our most fundamental lies-to-children in that post as well. Namely that “Drugs are bad”, meaning that if you try recreational drugs, even just a little you are going to be hooked into a spiral of drug dependency and despair. The Nancy Reagan “Just Say No” version of the “truth” about drug use.

There are at least two problems with our version of lies-to-children, although I’m not debating the merits of using the simple version with actual children. The first problem is that as scientists we tend to actually believe a version of this because it helps to keep us funded and keeps us working with scientific models that “pay off” rather consistently. I covered this a bit in the prior post but failed to tie this back to the essential question. Namely, what is the conditional probability that one will become addicted (or suffer toxicity or some other lasting damage) to a drug given that one samples that drug? [As a sidebar the Monitoring the Future publications contain data on opinions of drug risk such as "Is it dangerous to try MDMA once or twice?" "smoke crack daily?", etc. Attitudes do not line up with scientific evidence in my view...] The relative risk of dependence given one takes a drug is one of the most difficult things to pull out of the epidemiological publications, believe it or not. The most commonly cited one is Anthony et al, 1994 Exp Clin Psychopharm 2(3):244-268 from which we find an approximation that the conditional probability of dependence for illicit drugs runs from about 4% (psychedelics) through 8% (cannabis, anxiolytics) to about 23% (heroin). Nicotine, btw, is higher up around 32% or so. HUH? Even if you shoot up heroin your chances of getting hooked are only 1 in 4 or 5? Well, that seems to be what the available data suggest. As a caveat, the concept of conditional probability can be viewed in a number of ways and depending on what you use as the denominator (lifetime use? annual use? 30 day use) these numbers can shift around. This consideration just highlights how absurd it is that it is difficult to extract these types of estimates. Given the fundamental importance of this issue it is amazing how hard it is to resolve from current published work. The main point, however, is that it is likely only a small (but significant) minority of individuals exposed to drugs (even repeatedly exposed) that become dependent. Our preclinical drug-abuse models, however, are frequently predicated on the notion that essentially all individuals will express “dependence” or related phenomena. I think this approach may be missing the boat on what is really important, namely identifying the rarer conditions that lead to real-world problems with drugs.

The second problem is the practical and applied problem of minimizing drug use in adolescents. My difficulty is that when teenagers catch you in the lies-to-children you tend to lose credibility. Thus, if they figure out you are lying before you update the lies-to-children to lies-to-adolescents or lies-to-non-scientific-audiences, you may have lost your opportunity to do so. Take the situation with MDMA and neurotoxicity. The 2002/03 Ricaurte affair was a scientific screw up but it shows what happens when credibility is lost. The retraction of one paper resulted in a lot of (unjustified) rejection of scientific findings from the past decades of research. So even though the original (erroneous) Ricaurte Science paper in 2002 likely had a suppressing effect on MDMA use, it remains to be seen if we get a rebound as is being suggested in the latest surveys from Monitoring the Future. More importantly, for those habitual users of MDMA, those most likely at risk for lasting effects of repeated exposure, the scientific side has lost important credibility to communicate what we can discover about the risks of MDMA.

Obviously the “drugs are bad” lies-to-children affects public policy but I’m Not. Going. There.

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3 Responses to “Lying to Children about Drugs”

  1. Thomas Robey Says:

    How would the so-called “addictive phenotype” impact the propensity to become addicted to illicit (or other) drugs? And can that personality be controlled for or stratified?

    On a personal note, I have kept a square perspective about drug use because I learned early on that once I develop a habit, it is very difficult to stop. As an elementary schoolkid during the Regan years, I feared that about drugs. My parents never lied to me about drugs, but I am sure my teachers did. That says something on its own.

    By the way, I appreciate the pun in your filing scheme. Is it the drug that’s abused or the science?

    Like

  2. drugmonkey Says:

    Sounds as though you’ve been reading over some MDMA-denialist positions over at wikipedia…:-).

    Seriously though, I tend to take the view that “addictive personality” is likely in the sense that some individuals are at increased liability for addiction and others are at decreased liability. Duh. We have some targets for a final common pathway for some aspects of drug addiction like “reward” and “negative affect”. We have correlations from human studies looking at all kinds of factors from specific genes (like the serotonin transporter promotor) to loci to environmental and developmental influences. and yes “personality” factors.

    Nevertheless we don’t really know the definitive answer yet to what makes the difference in the substance addict. It may be many things or we may yet find a couple of smoking guns. Therefore, no definitive answer on what might be the underlying genes/circuits/neuropharmacology of “addictive phenotype”.

    Not being in that aspect of behavioral science, I’m loathe to entertain “personality” as a contributing factor. As you might suspect my worldview suggests that “personality” is an interaction of genetic endowment and the environment. again, duh. but since it isn’t a satisfying level of analysis of behavior to me i don’t tend to go there. it isn’t something that seems readily treatable or even mutable so again, I tend to focus elsewhere. not to say it might not hold value for others as a level of explanation and even treatment/prevention.

    getting back to the point of my post, you land square on the difficult interaction of science with public policy goals. the science side wants to explain as much as possible about possible contributions to drug abuse, one of which might be “personality”. But it is known that we are dealing in the realm of probabilities, not binary outcomes. Politics believes (with some justification) that people are only able to understand binary. To, say, identify your third grader as “nonaddictive” and therefore think “well she’ll never become addicted”. To understand “one drink a day good, five drinks a day and you are an addict”. Science understands there is no such thing as perfect prediction, policy does not. And the perception is that there is no cost to an abolitionist perspective so why not go beyond the “truth” as we know it and say “no drugs for anyone- else you’ll be having opiate withdrawal before you know it”?

    My trouble with this formulation is that I *do* think that there is a cost and it has to do with the real risks being overlooked because the individual has figured if the cartoonish lies-to-children is wrong, there must be NO risk. This is a particularly prominent feature of the MDMA-advocate and the cannabis-legalize-eet-mon perspective.

    Like

  3. Thomas Robey Says:

    Thanks for that response and its additional pearls.

    Like


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