# Transitioning to cannabis dependence

The conditional probability of dependence on a given drug is a question that is of substantial interest to users, parents of users, public policy makers and heath care providers. After all, if people simply stopped using a drug once a problem arises then many of the negative effects could be avoided. There is a fair degree of correlation between meeting diagnostic criteria for dependence and someone failing to stop using a drug despite clear and growing negative consequences. (Indeed this is one of the dependence criteria). Therefore, we must consider dependence to be a target of substantial interest.

It can be difficult to estimate the conditional probability of dependence in humans because we mostly have cross-sectional data to work with. And so we must infer conditional probability from dividing the currently dependent population by some denominator. Depending on what one uses for the denominator, this estimate can vary. Obviously you would like some population that uses the substance but what represents a level of "use" that is relevant? One time ever? Use in the past 12 months? Use in the past 30 days?

A new paper by van der Pol and colleagues uses a prospective design to provide additional data on this question.

The authors recruited 600 frequent cannabis users, aged 18-30, and assessed them for cannabis dependence at start, after 18 months and after 36 months using the:

Composite International Diagnostic Interview (CIDI) version 3.0 (Kessler and Ustun, 2004), and required the presence of three or more of seven symptoms within the 12-month period since the previous interview (without requiring the presence of all symptoms at the same time). It should be noted that the CIDI includes a withdrawal symptom, which is not included in the DSV-IV manual.

The study defined "frequent" use as 3 or more times per week for 12 months or more. This is important to remember when trying to assess the conditional probability. It all depends on what you construe as an at-risk population. Here, I'd say these were already rather confirmed cannabis fans.

The authors were interested in the very first incidence of dependence and so therefore excluded subjects who had ever met criteria, this left 269 subjects at intake (retention in the study left N=216 at 18 mo and N=199 at 36 mo). This is another point of interest to me and affects our estimation. Three or more times per week for 12 months or more and 45% of them had never previously met criteria for dependence. There are two ways to look at this. First, the fact that a lot of similarly screened users had already met criteria for dependence suggest that this remaining population was at high risk, merely waiting for the shoe to drop. Conversely it might be the case that these were the resistant individuals. The ones who were in some way buffered from the development of dependence. Can't really tell from this design....it would be nice to see similar studies with various levels of prior cannabis use.

There were 73 cases of cannabis dependence of the 199 individuals who were followed all the way to 36 months, representing a conditional probability of transitioning to dependence of 36.7% within 3 years.

Now, of course the authors were interested in far more than the mere probability of meeting dependence criteria. They assessed a number of predictor variables to find differences between the individuals that met criteria and those that did not. Significant variables included living alone, mean number of prior cannabis use disorder symptoms, a continual smoking pattern per episode, using [also] during the daytime, using cannabis to "cope", child abuse incidents, motor and attentional impulsivity and recent negative life events. For this latter, followup analysis identified major financial crisis and separation from someone important as driving events.

As the authors point out in the discussion, the predictors differ from those identified from a more general population. This makes sense if you consider that the range on numerous variables has been seriously restricted by their catchment criteria. The amount of cannabis exposure, for example, did not predict transition to dependence in this study--perhaps because it was well over the "necessary if not sufficient" threshold. This underlines my theme that the denominator matters a lot to our more colloquial estimates of the risks of dependence on cannabis.

Another issue identified in the discussion was the choice to start at 18 years of age for the captured population. Cannabis use frequently starts much earlier than this and many studies of epidemiology suggest that initiation of drug use in the early teens, mid teens, late teens and early twenties confers substantially different lifetime risk of dependence. "The earlier someone starts using, the more likely to become dependent" is the general findings. The authors cite a study showing that the mean age of meeting cannabis dependence criteria for the first time is 18. This is at least consistent with the fact that 65% of their collected sample had previously met criteria for dependence. No study is perfect or gives us the exact answer we are looking for, of course.

A final note on estimating the conditional probability of dependence in the population that uses cannabis 3 or more times per week for over a year. Of the original sample, 331 had already met dependence criteria and were excluded because the interest here was on the first time dependent. If we ignore those 70 people lost to followup during the study, and add the 73 to the 331 then we end up with 76% of those individuals smoking that much cannabis who have already, or will soon, meet dependence criteria.

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van der Pol P, Liebregts N, de Graaf R, Korf DJ, van den Brink W, van Laar M. Predicting the transition from frequent cannabis use to cannabis dependence: A three-year prospective study. Drug Alcohol Depend. 2013 Jul 22. pii: S0376-8716(13)00228-7. doi: 10.1016/j.drugalcdep.2013.06.009. [Epub ahead of print]. [Publisher, PubMed]

• Grumble says:

Does that paper tell us anything other than that people using cannabis at more than some arbitrary frequency are likely to show signs of an arbitrarily-defined "dependence" syndrome?

Whatevs.

• dependent says:

76% of users are dependent on cannabis?. More damaging than meth kids, remember that when you get offered weed, ask for meth instead.

• drugmonkey says:

I would hardly describe the population of those who smoke at least three times a week for over a year as "users" in the colloquial sense consistent with "when you get offered weed", dependent. And "damaging" is a nice little goalpost shift when we are only talking about criteria for dependence.

Grumble, yes it does. try reading it. Also, DSM and/or CIDI are not "arbitrarily-defined criteria" which you know full well.

• Isabel says:

Lotta alcohol dependent academics around these parts, by that criterion. Why should cannabis users have to wait around til someone offers it in order to not be considered dependent on the stuff? Also, smoking during the day is better.

• dependent says:

Btw, dependent defined as 3 of 7 and they didnt have to occur at the same time to be considered dependent? What are the 7 again? Also, nice way of using the palatable word 'dependence' instead of the more scrutinized 'addiction'. Addiction marketing FTW

• drugmonkey says:

Lotta alcohol dependent academics around these parts, by that criterion.

by which criterion?

Why should cannabis users have to wait around til someone offers it in order to not be considered dependent on the stuff?

what?

Also, smoking during the day is better.

better than what?

nice way of using the palatable word 'dependence' instead of the more scrutinized 'addiction'.

why "palatable" and why "scrutinized", pray tell? Dependence in this case is defined by the diagnostic criteria. One could similarly operationally define "addiction", this just doesn't happen to be the route taken. You are making a silly argument about semantics when the meaning is already defined for you.

• Fe says:

Money needs to be legally printed by government at no interest paid to anybody and according to a true economy needs. Grab pencil and paper, or a cheap calculator, and estimate how much is needed to pay jobs for all the adults needing one. You'll see is less than is currentely used for funding other programs.

Science could provide many of those jobs that you would come up with.

• Grumble says:

DSM and/or CIDI are not "arbitrarily-defined criteria"

NIMH would beg to differ.

Well, I overstate the case - of course the criteria aren't completely arbitrary. But neither are they based much on biology. There are so many ways to stretch psychological/psychiatric evaluations into whatever you want that the definition of "dependent" (or any other mental health category) approaches arbitrariness. For instance, the paper you reference uses 7 criteria (why exactly those?) of which 3 must be met (why 3 and not 2 or 4 or 5?), not necessarily at the same time (why not? Is someone really "dependent" if he displays 3 different criteria at 3 different times?).

Would the results have been much different if different criteria had been used? And how do these "cannabis-dependent" individuals really function in society compared to "dependent" alcoholics, meth addicts, and opiate addicts? I find that question far more interesting than how many people who smoke lots of pot meet someone's idea of "dependent".

• drugmonkey says:

I find it difficult to believe that you really don't understand the difference between operational definitions and arbitrary criteria.

One of the main points of my post here is the reminder that our estimates of conditional probability depend *entirely* on how we define the population of interest. So when you say

Would the results have been much different if different criteria had been used?

What you really mean here is that you want to know more and that you might select different catchment and operational assessment criteria for your own purposes. That's fine but trying to dismiss other people's choices as "arbitrary" is assy in the extreme. Not to mention denialist.

Is someone really "dependent" if he displays 3 different criteria at 3 different times?

I'm not a clinician and I have nothing to do with the arguments that lead up to DSM or CIDI or any other diagnostic scheme being adopted. If you are an expert, by all means weigh in with your evidence based criticisms of their process. If not, go read up all the published papers and what not and then get back to us with your specific objections.

If your objection is based on "well that doesn't seem right to my uninformed view" then....yeah.

And how do these "cannabis-dependent" individuals really function in society compared to "dependent" alcoholics, meth addicts, and opiate addicts?

That's what we call goal post moving in the school of denialism assessment. Still, it is indeed a fascinating question and one that I've taken up before... I'll have to look for it in the archives. The thumbnail sketch version is that yes, dependence is not equal to a drug "problem". Caffeine being a clear and present example for many of us. Also, if one has endless amounts of money, no dependents and chooses to stay high on heroin all the time this is not necessarily a "drug problem".

This has zero, however, to do with estimating the conditional probability of dependence as far as I can see.

I find that question far more interesting than how many people who smoke lots of pot meet someone's idea of "dependent".

I look forward to your efforts to operationalize and validate your personal version of what represents a drug problem so that everyone can study what is really important.

• drugmonkey says:

NIMH would beg to differ.

funny I am unable to find any such criticism in that document. the only two uses of arbitrarily/arbitrary have nothing to do with your point.

What the RSoC is trying to do is to move on to a next level of diagnosis which leverages scientific information on a host of dimensions instead of just behavioral symptom assessment.

Currently, diagnosis in mental disorders is based on clinical observation and patients’ phenomenological symptom reports. This system, implemented with the innovative Diagnostic and Statistical Manual-III (DSM-III) in 1980 and refined in the current DSM-IV-TR (Text Revision), has served well to improve diagnostic reliability in both clinical practice and research. The diagnostic categories represented in the DSM-IV and the International Classification of Diseases-10 (ICD-10, containing virtually identical disorder codes) remain the contemporary consensus standard for how mental disorders are diagnosed and treated, and are formally implemented in insurance billing, FDA requirements for drug trials, and many other institutional usages. By default, current diagnoses have also become the predominant standard for reviewing and awarding research grants.

However, in antedating contemporary neuroscience research, the current diagnostic system is not informed by recent breakthroughs in genetics; and molecular, cellular and systems neuroscience. Indeed, it would have been surprising if the clusters of complex behaviors identified clinically were to map on a one-to-one basis onto specific genes or neurobiological systems. As it turns out, most genetic findings and neural circuit maps appear either to link to many different currently recognized syndromes or to distinct subgroups within syndromes. If we assume that the clinical syndromes based on subjective symptoms are unique and unitary disorders, we undercut the power of biology to identify illnesses linked to pathophysiology and we limit the development of more specific treatments.

Where does it say DSM/symptom based diagnosis is "arbitrary"? or even anything close to this?

• drugmonkey says:

Continuing on with the NIMH RDoC

The RDoC research framework can be considered as a matrix whose rows correspond to specified dimensions of function; these are explicitly termed “Constructs,” i.e., a concept summarizing data about a specified functional dimension of behavior (and implementing genes and circuits) that is subject to continual refinement with advances in science. Constructs represent the fundamental unit of analysis in this system, and it is anticipated that most studies would focus on one construct (or perhaps compare two constructs on relevant measures). Related constructs are grouped into major Domains of functioning, reflecting contemporary thinking about major aspects of motivation, cognition, and social behavior; the five domains are Negative Valence Systems (i.e., systems for aversive motivation), Positive Valence Systems, Cognitive Systems, Systems for Social Processes, and Arousal/Regulatory Systems.

Huh, sounds pretty "arbitrary" to me.

The point being that *any* schema for diagnosing behavioral disorder is going to involve some choices being made as to what represents significant categories or severity of symptoms, behavior and, yes, biology. Choices which can lead to trite dismissals as "arbitrary" from any yahoo who simply doesn't like the conclusions being reached.

• Grumble says:

trying to dismiss other people's choices as "arbitrary" is assy in the extreme. Not to mention denialist.

Assy, yes. Not denialist - I'm not at all denying that the study found the results that it found. I'm obnoxiously (assily?) stating that the findings are meaningless. There is no more to their story than "smoke a lot of pot and eventually you get characterized as dependent." Big. Whup.

That's what we call goal post moving in the school of denialism assessment. Still, it is indeed a fascinating question and one that I've taken up before

Uh, no. I am neither moving the goalposts nor engaging in any sort of denialism (I'm not even sure what I'm being accused of denying). I am simply pointing out that I would be more interested in comparing the real effects of cannabis addiction/dependence to those of addiction/dependence of other drugs - a question you yourself admit is interesting. To my mind that question has far more value than asking how many drug users sometimes pass some threshold value of question-answering that classifies them as "dependent".

funny I am unable to find any such criticism in that document [RDoC]

The criticism is inherent in the assertion that biological definitions of psychiatric disease should replace psychological criteria. What is wrong with psychological criteria? They are imprecise and arbitrary. Why might biological definitions be better? Because they have the potential to be more precise and less arbitrary.

Huh, [the RDoC framework] sounds pretty "arbitrary" to me

I'd have to agree. It's a start, though, and the intention is *not* to use the proposed framework as a new basis for classifying mental illness. It is to get researchers to think about both normal and supposedly aberrant behavior as the result of biological processes that are continuous in nature, and therefore produce continuous (rather than discrete categorical) behavioral outcomes.

Which brings us back to the cannabis conditional dependence paper. Think of cannabis users as falling on a wide bell curve ranging from light to heavy users. You could probably find any number of variables that correlate with use. For instance, answering "yes" to the interview question "I often find myself using more pot than I intended" is probably far more common among the heavier users than the light users. The point is that these behaviors (and their consequences) fall along a continuum. They don't fall into discrete categories -- dependent people do/think/feel/act this way and non-dependent people do/think/etc this other way. To study the questions relevant to addiction (why do some people use more than others? does heavy use result in harmful outcomes, and if so, how? etc) I think (and apparently NIMH agrees) that it makes far more sense to treat the variables as continuous than as discrete.

Which is why I don't think that a paper saying "here's how many people transition into the category of dependent given these starting variables" has much value.

• drugmonkey says:

There is no more to their story than "smoke a lot of pot and eventually you get characterized as dependent." Big. Whup.

I realize that Isabel types are amusing but do you really not understand that this is a point of serious contention for many, many people? It IS a "Big Whup" to continue to demonstrate the risks attributable to cannabis smoking, and to show that dependence is associated with things that make pharmacological sense (i.e., exposure levels) and not hand waving about "addictive personality" and suchlike.

What is wrong with psychological criteria? They are imprecise and arbitrary.

first they are not "psychological" criteria they are *behavioral* criteria. and again with the arbitrary. They are NOT arbitrary. They may, however, be imprecise. In this we agree.

They don't fall into discrete categories

You act like this is news to me or that this somehow invalidates the study I am discussing. Wrong on both counts. Indeed the paper, and my description, make it very clear that thresholds are being drawn within a messy distribution.

it makes far more sense to treat the variables as continuous than as discrete.

really? how does the RDoC do this exactly?

Which is why I don't think that a paper saying "here's how many people transition into the category of dependent given these starting variables" has much value.

Your forgoing commentary has entirely failed to demonstrate any sort of "why". You are criticizing the paper for things ("arbitrary", "categorical variable") that the RDoC that you apparently lurv *also* suffers from . You admit fully that biological variables only have the *potential* to be more precise. Clearly we are no where close to any such things.

So really, in the end, this comes down to 1) your distaste for behavioral criteria and 2) some foggy notion that you know what is "real" about substance abuse that all the people participating in clinical evaluation and the research going into the DSM, etc diagnostic criteria have missed.

• Grumble says:

It IS a "Big Whup" to continue to demonstrate the risks attributable to cannabis smoking, and to show that dependence is associated with things that make pharmacological sense (i.e., exposure levels) and not hand waving about "addictive personality" and suchlike.

If that's the goal, then we need studies that show that smoking a lot of pot is harmful, and how. Telling us that people who smoke a lot will eventually fall into the dependence category doesn't tell us much we didn't already know given that half the original sample of heavy users was already dependent.

how does the RDoC do this exactly?

By encouraging researchers not to design studies (like the one you cited) that have the goal of using DSM and similar criteria to define human sample groups or behavioral outcomes.

Your forgoing commentary has entirely failed to demonstrate any sort of "why". You are criticizing the paper for things ("arbitrary", "categorical variable") that the RDoC that you apparently lurv *also* suffers from . You admit fully that biological variables only have the *potential* to be more precise. Clearly we are no where close to any such things.

The RDoC is arbitrary only in the specific dimensions of behavior they propose (affective, aversive, all that). What they are asking researchers to do is consider the whole range of human behavior (from apparently normal to apparently aberrant) and try to relate the range to biological variables. It doesn't specify those biological and behavioral variables -- that would indeed be arbitrary. It suggests a few starting points.

So really, in the end, this comes down to 1) your distaste for behavioral criteria and 2) some foggy notion that you know what is "real" about substance abuse that all the people participating in clinical evaluation and the research going into the DSM, etc diagnostic criteria have missed.

My distaste for behavioral categorization and criteria is part of what I think is a valid way of thinking about human behavior. I don't "lurv" the RDoC, which promotes a similar way of thinking, but as I said, I think it's a start.

I'm not sure where you get that I have "a foggy notion" that I know better than anyone else what's real about substance abuse. Sure, the DSM et al crowd know a lot more about it than I. They can point to any individual and say "he's addicted" or "he's not," whereas I can't - I'm not a trained psychiatrist. But these are just labels, and there is plenty of evidence that psychiatric/psychological/human BEHAVIORAL variables can be stretched to fit any criteria a psychiatrist wants. For instance, as soon as a blockbuster psychiatric drug becomes heavily marketed, we end up with the strange phenomenon of *more* people coming down with that disease than before the drug. That doesn't happen in other fields of medicine - as soon as the blockbuster treatment becomes available, people get cured and rates of illness go down. If the DSM criteria were valid, psychiatry wouldn't have this problem.

• Grumble says:

Here's some support for that last statement - a very detailed and persuasive description of how DSM-like classification and the involvement of pharma companies has resulted in over-diagnosis of mental illness and over-prescribing of neuroactive drugs: part 1 and part 2.

• drugmonkey says:

we end up with the strange phenomenon of *more* people coming down with that disease than before the drug.

well yes COI of pill pushing psychiatrists is one issue, as is the reverse logic of diagnosis by therapeutic response.

but you are not entirely right about exclusivity to the behavioral disorders. I mean, the rates of people who "need" hip and knee replacement certainly went up as those procedures became available (and cheaper, less risky), no? the rate of people who "need" statins went up as they became available and had demonstrated efficacy.

the logic of "if we can't do anything about it, there is no point in diagnosing it as a disorder/disease/syndrome" is not unique to behavior either. see Louis CK's routine about being told at 40 his ankle was just going to be shitty now.

then there is the question of stigma. where, again, the appearance of successful treatment tends to make people step forward with their condition. if it can be treated with something that seems medicine-y to people (i.e. a drug) then it must be "real".

So I am not anywhere near as sure as you are that an increase in diagnosis upon the appearance of a new treatment modality means there is something fake about the disorder.

• Grumble says:

You're right that there's a tendency for doctors to increase the rate of diagnosis as soon as a treatment becomes available. The problem is just worse - I'd say far worse - in psychiatry because of the absence of any physical criteria for diagnosis. On top of that, drug companies have a huge stake in defining what a mental illness is and what the interview/observational criteria are. (Increasingly, it's not even just drug companies - for instance, the diagnosis of mental disorder can get you social security disability benefits, resulting in whole constituencies of people seeking a diagnosis and to influence the diagnostic criteria.) By itself, the absence of physical criteria + presence of outside influences on the criteria themselves makes me more suspicious of psychiatry than of other branches of medicine (although I'm suspicious of them as well). For one thing, as the article I linked to points out, something like 40 or 50% of people could be easily diagnosed with a mental illness. To my mind, that means there are too many mental illnesses in the DSM and the standards for inclusion are far too loose.

Does that mean there is "something fake" about all the 300+ disorders in the DSM? Well, it does suggest that there is something arbitrary about them. Your defense against the accusation of arbitrariness is essentially that the criteria aren't arbitrary because they come from experienced professionals who've seen a lot of patients and have thought a lot about how to classify them. That might be partially true, but when they result in half the population with mental illness, I find that as ludicrous as making a big deal about a "statistically significant difference" when the effect size is miniscule: if you tell me there are 300+ mental disorders and 5 billion people on the planet who have them, that flies in the face of common sense. I reject it.

Which brings us back to the conditional probability of cannabis dependence - dependence being one of those arbitrary criteria. I think it would be far more useful to ask what the probability of specific behaviors and other measurable outcomes is, as a function of history of cannabis use. If you smoke X times per week for X many years, what is the likelihood that you resort to welfare because you can't hold a job? What is the likelihood of a failed family relationship? etc. And how do all these things change with greater or smaller consumption? The results of a study like that would be far more meaningful to me than "smoking X amount results in X probability of showing 3 signs of a total of 7 criteria for dependence, not necessarily at the same time." Why? Because then you understand much more about how consumption might influence peoples' lives. If people who use heavily over a long time are having a very rough time (like, as rough as meth addicts or alcoholics), I'd be convinced that cannabis addiction is a problem on the order of magnitude of alcohol, meth etc addiction. If heavy prolonged users can function perfectly well in society, then not so much.

My point is that you can answer questions about addiction (and other mental disorders) at least as satisfactorily, and probably more so, without diagnostic criteria as you can with them.

• Tal says:

I think this may be an interesting study in terms of identifying factors that precipitate change in cannabis use, but I fail to see how it's informative about the conditional probability of dependence. As you noted, DrugMonkey, the sample in question is very far from representative. You suggest that "the fact that a lot of similarly screened users had already met criteria for dependence suggest that this remaining population was at high risk, merely waiting for the shoe to drop". That's entirely possible, but it doesn't have to be. Given this kind of setup, you will tend to get a high proportion of cases crossing the threshold into "dependence" for purely statistical reasons.

What's happening here is that the sample is already bumping up against the threshold; indeed, most of them were already up against it and had to be excluded. Now, both because of measurement error (which the authors address, poorly) and because of reliable but uninteresting factors, many of the people who at T0 were below threshold will at T1 be above it. For example, some of the T0's will be people who already *should* have been above threshold at intake, but, either because of measurement error, or because they were having a particularly good stretch in their life, were misclassified. And vice versa. Given even very modest assumptions about what the initial rate of misclassification is, and how reliable the measures are, you are going to get a very high conditional probability of transition in this kind of case. It's not interesting, and it tells you nothing at all about what's true in the general population.

By way of analogy, imagine the study had been done on cigarette smokers. Suppose the selection criteria were smoking 5 cigarettes a day, and 10 cigarettes a day was considered dependence. And further, suppose we had to exclude half of our participants because they were already dependent. Now what have we shown if 18 months later, 36% of the remaining participants report a stretch in which they smoke 10 cigarettes? Not much. It's not in the least bit surprising, because we essentially designed the study that way. Other aspects of the study could still be interesting (e.g., the observation that negative life events were associated with an increase in dependence), but we have almost no sense of what the "true" rate of change is.

Note that the problem here is not that the criteria are arbitrary, but that they're discrete. Had the authors simply reported the change in actual symptoms, we would be in a much better position to determine if the observed changes are actually meaningful. By way of the cigarette analogy, if the mean increase in cigarette use had only been, say, 1.8, even though that was sufficient to take a large proportion of users from below the threshold to above it, an appropriate way to interpret the results would be to say "habitual users don't seem, on average, to increase use much over short periods of time". The discretization makes the number seem very high, but you can have that number be essentially whatever you like simply by varying the properties of the sample and the cut-off you use.

To be clear, I'm not making any kind of argument about whether cannabis is or isn't harmful. I'm not saying it doesn't cause harmful dependence. It clearly can. What I'm saying is that the finding you point to is almost completely uninformative as an indicator of the conditional probability of dependence since it could not really have been any other way given the way the study was set up. What we want to know is not "what proportion of users cross some threshold, even if the actual movement is clinically insignificant and driven by statistical artifact", it's "how much worse does use tend to get over time given different levels of baseline use". The authors *could* have addressed the latter question much more rigorously given their data (and hey, maybe someone else will), but they didn't.

• Grumble says:

Excellent points, Tal, except:

"I'm not saying it doesn't cause harmful dependence. It clearly can."

Clearly? Not from this data. I don't know this field very well, but if this paper is representative of the kind of analysis that drives the conclusion that "cannabis can cause harmful dependence," I begin to wonder.

• dependent says:

Denialist here. Fewer and fewer people believe your implied supposition that pot is harmful. You are part of a decreasing number of people that equate pot with other much more neurotixic and addictive drugs. Only the sith deal in absolutes, little future in your alarmism.

• drugmonkey says:

dependent-

Dependence is clearly a harm and clearly occurs. So it is neither implied nor a supposition that pot is "harmful". I did not in fact "equate" pot with any other psychoactive drug as it happens.

• dependent says:

If you are alarmist about pot, kids will think you are alarmist about heroine. Do it for the children!

Dude, it's kind of embarrassing the way you argue with your commenters on your own blogge. Have a little dignity.

• Grumble says:

Good point, CPP. Clearly it's far less "embarrassing" to post the same vituperative political commentary over and over again.

If you have a good blog that people like to read, then you attract more than a few interesting comments, and I imagine that engaging those commenters must be one of the reasons for having a good blog in the first place.

If, on the other hand, you have a blog filled with insane ranting and what you ate for dinner... well, mostly you attract people who like to laugh at you. So of course the "dignified" response is not to engage them.

• what says:

vituperative all over the place. yea, I know words...what?

• non-dependent says:

I've been doing cannabis for more than 10 years and decided to quit a month ago. Today I am having a hard day and decided to calm myself by having a cigarette. Went to the nearby rite-aid and asked for marlboro pocket. The guy asked: May I have your ID, please?. I said: Why?. And he responded: It is the law, pointing to a sign on the counter. He took my ID and looked at the computer. What the hell is going on?. I'd never shown my ID when purchasing cannabis and now I have to disclose that I am having a cigarette?. WTF!.

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