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> Here, you are confusing P(A|B) and P(B|A). This is a common mistake. What you are not observing are all of the people who use these substances without problem

by waps 13y ago

> Here, you are confusing P(A|B) and P(B|A). This is a common mistake. What you are not observing are all of the people who use these substances without problems. > Of course if you visit a prison, you're going to find criminals. If you visit an ICU, you will find people who are critically ill. And I argue that diseases should be eradicated if possible just the same. I've been to a leprosy clinic, and how many people does that disease infect, really ? 10 worldwide, on a yearly basis ? It should still be eradicated from the planet. There is no inconsistency here. Furthermore if P(criminally_destructive_behavior|drug_available) > 1/1000000 (or so), I think there is a very strong case to be made for outlawing these substances. You can't allow things that destroy a significant number of people they touch roam free through society, and the discussion should end there. A certain level of harmfulness cannot be avoided in society. Building, cars, ... all cause harm. But when it is not a necessity that harm should be avoided, even at the expense of personal freedom. Otherwise, society is not livable. > No numbers are ever going to convince people who make their judgments based on emotional reactions, as you seem to have. However, there is a reason that modern addiction treatments, which are far more successful, involve harm-reduction and maintenance-based approaches. Having met quite a few hard-drug recovered individuals, I'm pretty convinced that there is no treatment, not really. Just like there is no such thing as a recovered alcoholic, there is no such thing as a recovered addict. There are simply people who've trained in behavioral patterns that avoid triggering certain impulses, often by introducing a constant background level of discomfort (look at the number of suicides for recovered alcoholics versus general population, the number of suicides is WAY higher for recovering drug addicts even compared to recovering alcoholics).

nitrogen 13y ago
(look at the number of suicides for recovered alcoholics versus general population, the number of suicides is WAY higher for recovering drug addicts even compared to recovering alcoholics). I realize this thread is getting old, but that's another possible reversal of causality (P(A given B) vs. P(B given A). It's also possible that drug addicts are from a segment of the population that is more likely to commit suicide, but the drugs medicate away the suicidal urge. You also have a strong selection bias; as mentioned upthread, you haven't studied the habitual drug users who didn't end up in prison. There's no way the drug market could be as big as the TV news likes to say it is, unless the majority of users were living ordinary lives despite their drug use. Nobody's saying that drug addiction should be ignored; they're saying that you can treat the problem more effectively by treating society itself rather than trying to prevent access to drugs.
- waps 13y ago
  Hmmm true. So let's see what Bayes' formula says : A = recovering drug addict B = suicide victim Bayes theorem P(B|A) = P(A|B) P(A) / P(B) First link google found with some numbers : http://www.ncbi.nlm.nih.gov/pubmed/1932152 http://www.ncbi.nlm.nih.gov/pubmed/1932152 P(B) is much smaller than P(A), assuming most recovering drug addicts do not actually commit suicide. Let's say 3/4 don't (this is meant to be a lower bound, since increasing this number will mean drugs are responsible for more suicides, given the rest of the calculation). Therefore P(A) / P(B) ~= 4. So this depends on what fraction of suicides drug addicts represent. If that fraction is above 25%, that means drugs lead to suicide. If that fraction is less, then they don't. According to the article that fraction is between 25% and 70% (in 25% of cases suicide victims were clearly addicts, in 75% of cases drug abuse was seen before the suicide). While this is not too rigorous (esp. the sources part), this seems to indicate that "scientifically" you'd clearly find drugs cause suicide. If the fraction of suicides were to be ~ 45%, that would mean drugs increase suicide risk about 4-fold (and thus the number of suicides in a given group). That does not sound like an unreasonable number to me. It also means that free availability of drugs, increasing the number of people exposed will increase suicides by a factor between 1 and 4, depending on how big the problem currently is. An effective banishment of drugs from our society would cut suicides by that number, between 25% and 70%, assumed to be about 45%. The obvious criticism of this would be that P(A) and P(B) are nothing but a rational estimate, given that you ONLY know the things on the right side of the equation. In practice we know more. It's still very likely to be a good approximation though. So good point about reversal of causality, but following through on that point yields more evidence for it to be true, not less.

by waps 13y ago

nitrogen 13y ago

(look at the number of suicides for recovered alcoholics versus general population, the number of suicides is WAY higher for recovering drug addicts even compared to recovering alcoholics). I realize this thread is getting old, but that's another possible reversal of causality (P(A given B) vs. P(B given A). It's also possible that drug addicts are from a segment of the population that is more likely to commit suicide, but the drugs medicate away the suicidal urge. You also have a strong selection bias; as mentioned upthread, you haven't studied the habitual drug users who didn't end up in prison. There's no way the drug market could be as big as the TV news likes to say it is, unless the majority of users were living ordinary lives despite their drug use. Nobody's saying that drug addiction should be ignored; they're saying that you can treat the problem more effectively by treating society itself rather than trying to prevent access to drugs.

waps 13y ago
Hmmm true. So let's see what Bayes' formula says : A = recovering drug addict B = suicide victim Bayes theorem P(B|A) = P(A|B) P(A) / P(B) First link google found with some numbers : http://www.ncbi.nlm.nih.gov/pubmed/1932152 http://www.ncbi.nlm.nih.gov/pubmed/1932152 P(B) is much smaller than P(A), assuming most recovering drug addicts do not actually commit suicide. Let's say 3/4 don't (this is meant to be a lower bound, since increasing this number will mean drugs are responsible for more suicides, given the rest of the calculation). Therefore P(A) / P(B) ~= 4. So this depends on what fraction of suicides drug addicts represent. If that fraction is above 25%, that means drugs lead to suicide. If that fraction is less, then they don't. According to the article that fraction is between 25% and 70% (in 25% of cases suicide victims were clearly addicts, in 75% of cases drug abuse was seen before the suicide). While this is not too rigorous (esp. the sources part), this seems to indicate that "scientifically" you'd clearly find drugs cause suicide. If the fraction of suicides were to be ~ 45%, that would mean drugs increase suicide risk about 4-fold (and thus the number of suicides in a given group). That does not sound like an unreasonable number to me. It also means that free availability of drugs, increasing the number of people exposed will increase suicides by a factor between 1 and 4, depending on how big the problem currently is. An effective banishment of drugs from our society would cut suicides by that number, between 25% and 70%, assumed to be about 45%. The obvious criticism of this would be that P(A) and P(B) are nothing but a rational estimate, given that you ONLY know the things on the right side of the equation. In practice we know more. It's still very likely to be a good approximation though. So good point about reversal of causality, but following through on that point yields more evidence for it to be true, not less.