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Tuesday 29 November 2011

You Too Can Be Mentally Ill!

Please indulge me in a simulated interview for this post; it's a paraphrase of some conversations we've been having around the clinic. 

Why do we bother diagnosing illnesses?

There are several reasons, some of them a bit cynical. The most important one, from a public health perspective, is to guide treatment. We can take a variety of signs and symptoms, use these as clues to find the common problem producing all of them, and then target that problem. The label guides the treatment.

But why do we treat illnesses?

So that people can be healthier, happier, and (perhaps) more productive.

That’s what I thought.

Yes. But in the field of mental health there are significant controversies about diagnosis.

For one thing, psychiatric diagnosis often fails the treatment specificity test. Knowing a person’s diagnosis is supposed to be useful mainly as a way of informing treatment selection. It does that to an extent, and more for some disorders (e.g., bipolar 1 disorder) than others (e.g., dysthymia), but, on the whole, diagnosis does not help treatment selection nearly as much as it does in many other fields of medicine.

In my own work training clinicians in the treatment of depression, people often become obsessed with determining whether a client fully meets the diagnostic criteria for major depressive disorder, or whether they fall just short of the line. Although of some interest, from a practical perspective for the cognitive behavioural therapist the issue can be almost irrelevant.

Further, knowing that someone has major depressive disorder doesn’t help much with treatment selection. Having packed our client’s individuality into a diagnostic box, we need to unpack it all again and have a look at the person’s life circumstances, triggers, ways of thinking, lifestyle variables, life goals, and activity level. Then we can build a treatment approach.

You can only do this so many times before a still small voice begins to ask “What was the point of spending all that time coming up with the label, when the label doesn’t help you?”

That sounds a bit farcical.

It can be.

You mentioned more than one controversy.

The other big one at the moment is the proliferation of diagnoses, and the watering down of the diagnostic criteria, widening the categories so that more and more people are diagnosable.

In North America, and increasingly around the world, the Bible of diagnosis is the Diagnostic and Statistical Manual of Mental Disorders (or DSM), now in its fourth edition, hence DSM-IV.  (The other is the International Classification of Disease, ICD-10, which includes both mental and physical problems.)

DSM-I, released in 1952, contained 106 disorders.  DSM-II, 1968, contained 185. DSM-III in 1980 had 265, and DSM-IV, released in 1994, has 357. In 42 years the number of mental disorders more than trebled.

Some of this makes sense. Problems that were not recognized in 1952 were added, and some disorders were split into two or more related problems. But the number of people who could find themselves described in the DSM expanded markedly from DSM-I to DSM-IV. As well, the boundary between normal-range experience and disorder was moved in many cases to include more people. In effect, by shifting the definition of abnormality, and hence normality, we created millions of additional cases of “mental illness.”

Currently the American Psychiatric Association is developing DSM-V, scheduled to be released in 2013. Once again, vast swathes of normality are being redefined as mental illness.

Well, vast swathes of normality can still be pretty miserable. If it can be treated, what’s the problem?

Much of the treatment used for mental conditions is pharmacological, and most pharmacological approaches have their downsides as well as potential benefits. The data supporting the treatment of milder conditions is typically much weaker than for their more severe counterparts. So we may be encouraging more and more people to see themselves as mentally ill, and to accept treatments that may or may not be helpful for them.

As well, the boundaries of what it is to be normal are steadily shrinking. Many of us in the field believe we are pathologizing much of the human experience. It is as though we are saying “Pinkie fingers are cancerous growths, and you should seek treatment if you have them.” Sadness, bereavement, shyness, anxiety, anger, and much more are increasingly being viewed as symptoms of mental illness rather than natural elements of being human.

So what’s motivating all this?

Some of it is well-intentioned altruism. If we can help more people to feel better, why not? And in order to treat them, it seems reasonable to try to define what might be going wrong. Critics might say, though, that nothing is going wrong in most people: Life is challenging, and if you find it occasionally difficult this does not mean that there is anything the matter with you.

Some of this widening of mental illness definitions appears to be motivated by profit. If we can convince you that you are ill, we can sell you products. Many of the people on advisory panels for DSM-V also receive funding from pharmaceutical firms. This is no great surprise – pharmaceutical firms and the APA both want good people, and they often settle on the same ones. But the potential for a significant conflict of interest is too great to ignore. The more people we can call mentally ill, the more we can market to them – and the products we market tend not to be curative. So we can have them continue to purchase the product (or have insurers purchase it for them) for many years.

Even the lead developer of past versions of the DSM, Robert Spitzer, has expressed his concerns about the new edition. (This is putting it a bit mildly.) Here is one of his writings on the subject of proposed changes to the description of post-traumatic stress disorder (PTSD):

http://www.beforeyoutakethatpill.com/2009/3/spitzer.pdf

Can I read more?

Easily. Just google DSM-V and see what comes up. The Society for Humanistic Psychology has been particularly vociferous on the subject.  Here is their blog:

http://societyforhumanisticpsychology.blogspot.com/

Here is an editorial on, of all things, the Psychology Today blog, by physician Allen Francis:

http://www.psychologytoday.com/blog/dsm5-in-distress/201111/why-psychiatrists-should-sign-the-petition-reform-dsm-5

The problem is not limited to the mental health field, however.  Here is a similar red flag raised for medicine as a whole by health journalist Ray Moynihan, published in the respected British Medical Journal:

http://www.bmj.com/content/342/bmj.d2548?view=long&pmid=21540259

And here’s Moynihan’s website:

http://raymoynihan.com/

And where do you sit on all this?

I share the concerns about overdiagnosis and the narrowing definition of normal experience. I do believe that much of the broadening of disease categories is well-intentioned if naïve, but I also believe that much of it is motivated by the desire for profit.

I believe that if we take normal reactions and reclassify them as illnesses, we remove their usefulness to the person experiencing them. So rather than viewing a sense of ennui and anxious sleeplessness as cues to look at my life, I can begin to see them as a resurgence of a mental illness. I will become even more alarmed, and far from taking constructive measures to take charge of my life, I will see myself as more damaged.

In effect, I believe that classifying experiences as pathology can actually create pathology. Overdiagnosis isn’t just misdiagnosis.  It creates distress and, potentially, the very illnesses it predicts. By broadening disease categories we may not be helping anyone; we may be creating additional misery in the world.

Thanks to Johanna Trimble for sparking this post.

Friday 25 November 2011

Medications: Are Blind Trials Really Blind?

We've been talking about psychopharmacology and the testing of medications.  In the last post on this subject, we considered the idea of the placebo control trial. But what about this "blind" business?

As you'll recall, the point of a double-blind placebo-controlled trial is that neither the treating clinician nor the patient knows which condition the patient is in. 

Why is this important? 

Patients’ belief that they are being treated with a medication can cause them to expect to get better. As a result, they may notice signs of improvement, even if the drug doesn’t really do anything. So if we give one group the “brand new drug” and the other group nothing, then the treated group will almost always do better.

Instead, we give both groups something that looks like a treatment. In fact, it must look identical (because some research suggests that certain pill colours and sizes are seen as more potent than others). If there is an expectancy effect, then it should appear equally in the groups getting the placebo and the active medication. Any differences in the effect between the groups would have to be due to the active ingredient in the pill.

Remind me why the clinician has to be blind.

We all communicate nonverbally. A physician who hands us a prescription confidently will produce more of an expectancy effect (“This’ll clear up your problem!”) than one who exhibits shame, anxiety, or an apologetic manner (“Sorry I don’t have anything more effective to offer you”). If the clinician knows which medication a patient is receiving, he or she might behave differently with clients receiving the real thing than with those receiving the fake. So it’s vital the clinician not know.

Similarly, it’s important that whoever is doing the evaluation of the patient (whether that is the treating clinician or someone else) not know which group the patient is in. If the evaluator really hopes that the test drug works, people who got the drug may be scored as more improved than those who got the placebo – even if the evaluator is trying hard to be even-handed.

So with all these precautions, patients must not know what drug they’re getting, right?

You’d think so. But no. The problem is that there are no perfect medications that change the target symptom (depression, psoriasis, heart rate) and nothing else. Virtually every medication has side effects.  

If you are in a drug trial and you notice that your hair is dry, you have a metallic taste in your mouth, and your libido is gone, you might very easily guess that the pill you are taking isn’t just a jelly bean. In fact, in antidepressant trials patients are sometimes asked at the end of the study “So, any guesses whether you got the test drug or the placebo?” Antidepressants are notoriously “buggy” with side effects, so patients tend to get the right answer. As a result, the supposedly blind trial isn’t blind at all. 

If patients are getting all kinds of side effects they will strongly suspect they are on the active medication, and they may experience a stronger expectancy effect as a result. “I must be getting the real thing so maybe I really will get better.”

There is a problem even if the drug has no side effects. Imagine a stunningly effective drug that eradicates the problem symptom completely. Patients in the medication condition will notice the vast improvement in their condition and will realize that they must be on the real thing, effectively unblinding the study. But this will be a result of the real effectiveness of the drug. A bigger problem is when the side effects give the story away – potentially making an ineffective medication look better than it really is.

So what?

So even in a well-designed placebo control trial, the study may not actually be blind. As a result, patients may have a greater expectancy effect in the genuine-drug condition than in the placebo condition. The study will show that the drug is more effective than placebo, when in reality the drug condition only had a stronger placebo effect than the sugar pill.

How big a problem is this?

No one knows.

Is there any solution?

Yes. Use a placebo that has side effects. Instead of a sugar pill, we can use an existing medication that is not thought to have an effect on the condition that is being studied. So if we are looking at, say, depression, we could compare our new antidepressant with a drug that produces similar side effects but that has never been shown to be effective against depression. These are called “active placebos.”

Does anyone do this?

It's not done often. In 2004, the Cochrane Collaboration (an organization that conducts reasonably rigourous analyses of the general trend of medical data) published a review of studies in which antidepressants were compared to active placebos (Moncrieff, Wessely, & Hardy, 2004). They found nine such studies - not a particularly impressive number.  

Only two of the nine demonstrated a consistent statistically significant difference between the antidepressant and the active placebo. When the studies were combined, the overall effect size (the difference between drug and active placebo) was 0.39 standard deviations - a relatively weak treatment effect. When one particularly positive trial was not included, the effect size dwindled to 0.17 standard deviations. These differences are smaller than the differences that are usually found when antidepressants are compared to inactive placebo. 

The United Kingdom's National Institute for Health and Clinical Excellence recently chose an effect size of 0.50 as a lower cutoff to represent an effect large enough to be considered clinically (as opposed to statistically) significant. Not everyone agrees with the cutoff, which is somewhat arbitrary, but these findings for antidepressants fall below it. 

Unlike some reviews that find more powerful drug-placebo differences in severely depressed populations, the studies of inpatient populations produced weaker effects than those of outpatient populations.  

This review of a few studies should not be used to conclude that antidepressants are nothing more than active placebo. But it’s not exactly a ringing endorsement, either. The authors concluded that standard drug trials using inactive placebos ("sugar pills") might overestimate drug effects because subjects often figure out which condition they are in and develop higher expectations when they have side effects than when they do not.  

It would be nice to see more studies comparing antidepressant medication with active placebo, to see if we can demonstrate a genuine drug effect that isn't based on patient expectations. Until we do this, some of our former optimism about the antidepressant drug class must be tempered with a bit of skepticism.

Reference

Moncrieff, J, Wessely, S, & Hardy, R Active placebos versus antidepressants for depression. Cochrane Database of Systematic Reviews 2004, Issue 1. Art. No.: CD003012.

Tuesday 22 November 2011

Smoking and overeating: Ways of reducing healthcare costs?

Do smoking and obesity result in higher healthcare costs? Of course they do. This is trivially easy to document. Just take, for example, some smokers and some nonsmokers and compare healthcare-related billings to government and extended-health plans. Studies that do this routinely find differences in the direction you would expect. Smokers cost more.

For example, the rate ratio found in one study for smokers to nonsmokers is 3-1 for heart disease, 10-1 for lung cancer, 2-1 for stroke, 2-1 for a subgroup of other cancers, and 20-1 for chronic obstructive pulmonary disease (Barendregt, Bonneux, & van der Maas, 1997).

It follows that if we were to reduce the rates of smoking and obesity in our culture, we would have lower healthcare costs overall. Obviously.

Sometimes what seems obvious is untrue, however, and this is one of those instances. In fact, smoking and obesity may save healthcare dollars overall.

The key to this apparent contradiction is that smoking and obesity not only affect health status, they also affect mortality. Smokers die earlier – on average, over 7 years earlier for men and 6 years earlier for women.

When you’re dead, your healthcare costs are zero.

So take a pair of 45 year old men, one a smoker and the other a nonsmoker. Sure enough, the smoker has more colds, more early heart disease, more chest symptoms, and his healthcare costs are higher than his clean-living twin. Over time, healthcare costs rise for both of them, because as people age they make more use of the health system.

At age 67 our smoker is incurring much higher costs than our nonsmoker, but at age 68 he dies of a heart attack. Many of the illnesses that finish off smokers are relatively quick and don’t create too many costs.

Upon his death his healthcare costs vanish, whereas the nonsmoker lives into the years associated with more chronic illness, more health problems, and much greater usage of the healthcare system. The moment our smoker passes away, the nonsmoker’s lifetime costs begin to catch up. Eventually, of course, he dies too. But by the time he does, his lifetime healthcare costs have leapt beyond the smoker’s costs.

Barendregt et al (1997) calculated lifetime healthcare costs among Dutch male smokers at $72,700 and nonsmokers at $83,400, and among women smokers at $94,700 versus nonsmokers at $111,000.

So what would happen if everyone suddenly quit smoking? There would be a short-term reduction in healthcare costs as the smokers reaped the benefits of nonsmoking. But eventually the former smokers would live as long as the nonsmokers and the benefit would be wiped out. In fact, healthcare costs would rise.

What about obesity? A similar phenomenon is observed. Obesity is associated with higher year by year health costs, but also with premature death. In a simulation study based on existing risk factors associated with obesity (van Baal et al, 2008), a cohort of obese individuals would be expected to have higher health care costs each year until age 56 than similar groups of smokers or nonsmoking nonobese individuals. At age 57, smokers began costing more. Lifetime health costs, however, would be highest among the nonsmoking nonobese group, lower for the obese group, and lowest for the smoking group.

This intriguing study is only a simulation, and it would be nice to see it borne out in a large-scale epidemiological study. Nevertheless, it offers support for the idea that smokers have lower healthcare costs overall, and it provides a hint that the same may be true for people who are overweight.

People often hate research like this and wonder if those who report on it support obesity and smoking, or are in thrall to the tobacco companies. So does this mean that I am opposed to smoking reduction efforts or the idea of healthy eating? Of course not. I think that the benefits of longevity strongly outweigh the costs. I am no more in favour of people smoking than I am of handing out cyanide-laced lemonade at retirement parties (which would reduce healthcare costs in about the same way), and I work with many clients on developing healthier lifestyles.

In recent years, many governments have attempted to sue cigarette manufacturers for the “additional healthcare costs” associated with smoking. I’ve heard rumblings that we should be doing the same with fast food suppliers.

But if this research on costs is accurate, such additional costs may not exist. I’ve paid attention to these debates, and it appears that the tobacco companies never seem to defend themselves using this data.  Perhaps we shouldn’t be surprised. “Actually, we kill our customers so they wind up costing the healthcare system less” probably wouldn’t make a good sound bite.

References

Barendregt, JJ, Bonneux, L, & van der Maas, PJ (1997). The health care costs of smoking.  New England Journal of Medicine, 337, 1052-1057.


Van Baal, et al.  (2008).  Lifetime medical costs of obesity: Prevention no cure for increasing health expenditure.  PLoS Medicine, 5(2): e29.

Friday 18 November 2011

Medications: The Double-Blind Trial

(This post is part of a series on psychopharmacology and medication.)

We've been talking about neuronal signal transmission, the monoamine hypothesis, and the theory of how SSRIs work. Much of the recent controversy about medication rests on the examination of medication outcome trials. So let's take a time out and consider the nature of these studies.

The double-blind placebo control trial has, for better or worse, become the gold standard for the evaluation of healthcare interventions – in the areas of both mental and physical health. These studies sound straightforward enough, but like most subjects in science, things get more complicated the closer we look.

The nature of placebos

A placebo is an inactive treatment - one that no theory would suggest should work from its physical effects alone. Placebos are often referred to as sugar pills, but in fact they might be made of almost anything, so long as the substance is not believed to have any effect on the disorder being examined.

Placebos may not even be pills. Placebo surgery (in which an incision is made but nothing else is done), placebo psychotherapy (in which a clinician meets with a person but doesn't do anything believed to be effective), and placebo light therapy (in which people sit before a light box that doesn't really give off enough light to be helpful) have all been used.

Usually the placebo treatment is made to seem as similar as possible to the other (hopefully active) treatment being tested. So when you're testing the effectiveness of a medication in pill form, your placebo comparison would be a pill of the same colour, size, and shape.

The Confirmatory Bias

Why not just compare a new medication with doing nothing? That, after all, is the usual alternative in healthcare: Treat the person with something thought to be effective, or watch and wait to see whether the problem resolves itself. Why bother with a placebo control?

Human beings are prone to a powerful confirmatory bias. This means that when we develop a theory about something, we automatically assign greater significance to information that conforms to our theory than to information that contradicts it.

If I develop a conviction that rain tends always to fall on my days off, I will notice the sunny days when I am working and the rainy days on the weekend. I will tend to forget the rainy days when I am working, and the few sunny days when I am not. Over time, my theory will seem more and more true.

Similarly, if I think that life goes better when I wear blue socks, I will begin to notice that this seems more and more true. If I think that Vitamin Z cures colds, I will notice my recovery when I take it, and the persisting symptoms when I don't. When we look for evidence of almost anything (unusual behaviour at the full moon, personality types associated with star signs, mood changes associated with certain crystals), we tend to find it. Disconfirming evidence tends to be ignored.

There is a lot of uncertainty in healthcare, but we know this: the expectation of improvement will lead to a perception of improvement - in at least some symptoms, in some disorders, for some period of time. In general, the symptoms most affected will be subjective ones - things like mood, pain, and discomfort.

Placebos do not work with everything. If we give placebos to patients with high cholesterol, this does not seem to reduce their cholesterol over time. Objective measures like blood tests, tissue regrowth, and tooth decay do not seem to be nearly as affected by placebos as subjective indicators. There are exceptions to this principle, but let's leave those alone for the time being.

The Rationale for Placebo Trials

When we administer a treatment for a disorder, we can say (with a bit of oversimplification) that there are two effects:

  1. The genuine, measurable effect produced by the expectation of receiving a treatment for the problem.
  2. The physical impact of the treatment on the problem, regardless of what the client expected.

So if we violate all ethics and sneak pain medication into the food of a person with back pain (producing effect 2 but not effect 1), they should notice a reduction in pain even though they don't know why it is happening. And if we manufacture sugar pills that look like powerful pain medication (resulting in effect 1 but not effect 2), they should also reduce the pain to at least some extent.

And if we show the person the pill bottle, describe the predicted effects of the medication, and provide a pill containing the active ingredient, we will get both effects: expectation plus physical impact.

The question, obviously, is to what extent the improvements we see are attributable to Effect 1 versus Effect 2.

Perhaps our supposed miracle cure is actually no better than placebo, and all of the improvement we see is the product of expectancy. Or maybe we have made a real discovery, and the improvement is partly expectancy but partly physical impact.

Why do we care whether an effect is due to expectancy?

A placebo effect, after all, is still an effect. It's not imaginary, it's real. Do we care whether it is produced by expectancy or by the chemical ingredient?

Well, yes, for a number of reasons.

  1. Placebo effects tend to be somewhat time-limited in their action, and may make a disease process seem to improve while the underlying pathology continues. 
  2. Most medical treatments have disadvantages as well as advantages. A medication that alleviates cholesterol might strain the liver, for example. If the chemical ingredient of our medication does no good but causes harm, we need to know this.
  3. There's an ethical issue involved in charging large sums of money for inactive ingredients.

Plus, the healthcare professions pride themselves in having treatments that are more advanced than the superstitions of centuries past. If our new patented medication is no better than repeating an incantation three times, then why do we fund medical healers but not faith healers?

The double-blind trial

In a double-blind trial, neither the person taking the placebo (the patient) nor the person giving it (the clinician) knows which medication the person is receiving.

It's obvious by now why the patient shouldn't know which treatment they are getting: This controls for expectancy, or at least it should. (There are some problems with this reasoning, but I'll leave that for another post.) So people who receive Treatment A should have about the same expectation of improvement as those receiving Treatment B. If we have succeeded in keeping expectancy the same in both groups, then any differences we see should be attributable to the chemical ingredient in the pill.

But why do we need the caregiver to be blind as well?

We know that people communicate a great deal by their nonverbal behaviour. Presumably no one in a blind trial would announce to the patient, "You're in luck - you get the real drug!" But they might do so involuntarily. If they believe that the drug is effective, they might show more anxiety and less optimism when seeing people who are taking the placebo. The result could be that patients in the placebo group would develop less powerful expectancy effects than those in the active treatment group.

As well, some of the outcome measures are collected by the treating clinician. For example, one of the outcome measures for many depression trials is a physician-rated scale. If the clinician believes in the effectiveness of the medication, he or she might see greater improvement in people receiving the active treatment than in those receiving placebo - even if they are trying their hardest to be honest and even-handed. Similarly, if they believe the medication doesn't work, they may fail to see genuine effects in the drug condition.

Consequently, it's important that the clinician - and anyone else doing evaluations of patients - not know which treatment a given patient received (particularly if there is any subjective element whatsoever to the outcome measure).

Sounds great.  But...

The problem is that placebo control trials are not quite as simple as advertised. A lot of assumptions are made about how they work, and it is easy to make interpretations that aren’t warranted. In upcoming posts we’ll explore several of these:

  • In a double-blind trial, neither patient nor clinician knows which condition the patient is in.
  • Differences between placebo and medication can be attributed to the chemical effects of the medication.
  • The placebo effect is the degree of improvement seen in the group of patients given the inactive medication.
  • Expectancy is the only determinant of improvement in the placebo group.

In fact, none of these statements is necessarily true. Stay tuned.

Tuesday 15 November 2011

PsychologySalon November 22 at UBC Robson Square: When Our Minds Play Tricks On Us


The Tuesday November 22 PsychologySalon presentation at UBC Robson Square (7-9 pm) will feature Dr Lindsey Thomas. For tickets, call Changeways Clinic at 604 871 0490 or buy online here.

Dr Thomas is a registered psychologist at Changeways Clinic who works with people experiencing a wide variety of difficulties – mainly using the perspectives of Cognitive Behaviour Therapy and Acceptance and Commitment Therapy. I spoke with her about her upcoming talk.

What is your talk about?

I’m going to be talking about some of the different distortions that can happen in our thinking – distortions that tend to become more pronounced in people when they are experiencing anxiety, depression, and anger.

Is this a talk that’s applicable for everyone?

Definitely. Cognitive distortions are things that we are all vulnerable to. I think that everyone will see themselves in at least some of what I talk about.

Can you give me an example of a distortion?

Sure. One of these is all or nothing thinking, which is a tendency to think in extremes. Things are either right or wrong, good or bad. The in-between or grey area gets missed. We see this particularly in people who have difficulties with depression and managing anger.

When might a person use all or nothing thinking?

One way would be to assume that we have all the answers. For example, I might assume that I have the right answer and that everyone else is wrong. As you can imagine, this can set people up for having difficulty relating to others.

I bet.  But why bother knowing our mistakes? Why is it useful to know how we distort things?

These thoughts are automatic; they often happen without our awareness. The goal is to slow the process down, learn to see the distortions as they occur, and work toward changing them if necessary.

Is this all about positive thinking?

Not at all. Although there is some value to seeing the positive side of things, this is more about looking for the evidence, and challenging the problematic thoughts that get us into trouble.

Is there anything wrong with positive thinking?

It’ll only take us so far. Cognitive distortions can shift us toward being either too positive or too negative; both of these can be a problem. This is more about coming into line with what’s really happening.

How do we make our thinking more realistic?

One of the main ways is to stop ourselves, look at what we are actually thinking, and then look at the evidence behind those thoughts. I’ll show some particular strategies in action at the talk.

What if I’m not depressed or anxious?

Again, this is something we all do, whether we are extreme enough to say we’re depressed or not. I’ll be giving a lot of examples, and demonstrating some strategies. I want the talk to be as practical as possible, so that people will take away useful ideas that they can use in their own lives.

*     *     *


This will be our final talk for 2012. We will start up again on March 27 with Out of the Blue: The Nature and Treatment of Clinical Depression with Dr Randy Paterson.

Information and online registration for all talks can be found here. Tickets can also be purchased at the door.

Friday 11 November 2011

Medications: How are SSRI Antidepressants Supposed to Work?

(This is part of a series of posts on the basics of psychopharmacology that I’m posting so that I can refer people back to it. Here is the first in the series.)

The SSRI antidepressants include medications such as citalopram (Celexa), escitalopram (Lexapro), fluoxetine (Prozac), fluvoxamine (Luvox), paroxetine (Paxil), and sertraline (Zoloft).

SSRI stands for Selective Serotonin Reuptake Inhibitor, which summarizes how the drugs are supposed to work. Let’s consider these terms:

Selective. Unlike some of the older antidepressants (such as the tricyclics like amitriptyline and clomipramine), SSRIs are intended to act on a single neurotransmitter system. They are, thus, selective in the system they act upon.

Serotonin. The specific neurotransmitter affected by SSRIs is serotonin.

Reuptake. Reuptake (discussed at greater length here) is essentially a recycling process. The sending neuron dumps neurotransmitter into the gap between it and the receiving neuron, then opens its own ports and takes some of the transmitter back for use next time. If there is a problem with the pathway, however (not enough neurotransmitter, for example, or too few receptors), reuptake runs the risk of preventing signal transmission.

Inhibitor. The action of an SSRI is to inhibit the reuptake process. It closes the gates to the reabsorption, or reuptake, of serotonin by the sending neuron. As a result, more serotonin is left in the gap, increasing the likelihood that enough will get across to the receiving neuron’s receptors that it will fire.

So an SSRI should make serotonin systems work better by keeping released transmitter in the gap, rather than prematurely depleting it through reuptake.

Note what an SSRI does NOT do, contrary to what some people might believe:

  • It doesn’t create more serotonin in the brain.
  • It doesn’t correct any flaw in the system.
  • It doesn’t produce more serotonin receptors.
  • It doesn't "rebalance" the neurotransmitters.
  • It does not treat the cause of the depression, whatever that might be.

The last point is important. No one believes that the root cause of depression is excessive reuptake in serotonin systems. A reuptake inhibitor might help, just as a brace might help a person with a bad knee to get around, but it does not correct any known cause of depression.

What is an SNRI?

An SNRI is a Serotonin and Norepinephrine Reuptake Inhibitor. In other words, it is thought to work much the same as the SSRIs. But rather than being selective, it does the same thing on both serotonin and norepinephrine systems.

The SNRIs include venlafaxine (Effexor), desvenlafaxine (Pristiq), duloxetine (Cymbalta), and others. Pristiq is a remarkably similar drug to Effexor, and was introduced to the market in 2008, shortly before the patent (hence profitability) of Effexor ran out. This may have been coincidental. Or not.

A variant of the monoamine hypothesis suggests that some depressed people may have a problem in serotonin-based systems, some might have more of an issue with norepinephrine-based systems, and some might have problems in both.

This notion has some appeal, because depression looks very different in different people. Some people are agitated, others look very slow-moving. Some sleep all the time, others have insomnia. Some can’t stop eating, others have no appetite. Maybe the differences have to do with different chemical problems in the brain.

The test of this idea is probably obvious. If an SSRI treats only one subgroup of depressed people, and an SNRI treats two subgroups, then SNRIs should be more effective overall.

Yes, but the data in depression treatment tends not to match the theories. There is relatively little evidence for the superiority of SNRIs over SSRIs. Response rates are about the same.

Coming up:  Let's consider some of the ideas indicated by the monoamine hypothesis.

Tuesday 8 November 2011

The Construction of Depression

Many years ago a client told me that she knew how to eliminate her depression. Not reduce it, not make it tolerable. Eradicate it.

All she had to do, she said, was fly a glider.

Gliding was something of a hobby. She noticed that the moment the glider left the ground, hauled upward by the tow plane, she was not at all depressed. The depression was utterly absent the entire time she was in the air. The problem, of course, was that she couldn’t fly 24 hours a day.

At one level, this is a simple and familiar story about working with depression: Do the things you like, whether you want to or not. Get out of the house. Follow your bliss.

But that wasn’t what she got from her experience. Sure, she enjoyed gliding – why spend all that money if you don’t? But not all enjoyable activities seemed to have the same effect.

She said that gliding is a fully involving activity. The moment the plane leaves the ground, you are fully and completely there, occupied with the winds, the plane, the surrounding terrain.

What she realized was that depression wasn’t something that happened to her.

Depression was something she did.

In each depressed moment, she had to be creating the depressive world. The depression was an artfully constructed reality, carefully held together with a depressive story. This took effort.

While gliding, she simply did not have the leftover attention – the processing power – to create that world. Instead, she was fully in the world of the experience itself. She was in the glider, not in the depression. Gliding, in effect, crowded out the depression.

Realizing that her mood was something of a creation, she became more able to stand back and examine it. It was an experience. She was not a depression, and the depression was not her. The task was not to go gliding all the time. It was to recognize the process of constructing the story, and gradually, millimeter by millimeter, to withdraw her energy and dedication from the project.

Certainly, she had problems. There were big challenges in her life. Some of them required action and problem solving. Others required acceptance or grieving. The depression was not incomprehensible. But the feeling itself, the inner hell, was for her largely the result of the automatic and unintentional rehearsal of a story.

We hear a lot about the idea of flow, a sense of immersion in a challenging activity, and how useful it can be in creating a positive emotional state. Flow experiences may be valuable in and of themselves. But much of their value may come from interrupting our personal story-making process – a process that pulls us out of our actual experience and into a constructed world.

We also hear about the value of mindfulness, and its dual mission of becoming present to the real world while maintaining awareness of the mental construction team. An awareness of the act of construction can assist us in taking our creations somewhat less seriously.

So should we all take up gliding? No. But it’s useful to identify positive activities that challenge and immerse us – and the addictive activities (video games, alcohol, gambling) that we may have adopted to pull us in and shut off the story-making process. Perhaps there are ways of simply sitting with our construction crew, knowing their names, and inviting them to take a coffee break now and then.

Or an extended vacation.

Friday 4 November 2011

Medications: What is the Monamine Hypothesis?

(This is part of a series of posts on the basics of psychopharmacology that I’m posting so that I can refer people back to it.  Here's the first of the series on neurons, and here's one on signal transmission from neuron to neuron.  )

Monoamines are neurotransmitters that, naturally, have a single (mono) amino group as part of their chemical structure. When it comes to brain-based neurotransmitters, there are several monoamines:

Serotonin, or 5-HT
Dopamine
Epinephrine (or adrenaline)
Norepinephrine (or noradrenaline)

When neurons release a monoamine into the gap between neurons, the chemical crosses and binds to the receptor sites on the next neuron, potentially resulting in the next neuron firing. A naturally-occurring substance called monoamine oxidase (MAO) sits in this gap, however, and begins breaking down some of the neurotransmitter before it can cross.

In the 1950s it was discovered that MAO inhibitors, which prevent the action of MAO, were effective in reducing clinical depression. By reducing the action of MAO, more neurotransmitter might be able to cross the gap and bind to the next neurons.

This was exciting. The results suggested that the problem in depression might be a deficiency in one or more of the monoamines. Here’s the reasoning: If there isn’t enough, say, serotonin available, then less will be released into the gap. MAO will then break it down and not enough will get to the next neuron in line. Stopping MAO means that the small amount of serotonin is able to stay in the gap long enough to trigger the next neuron.

Subsequent studies suggested that certain drugs which affected mainly serotonin (5-HT) and norepinephrine systems also worked against depression. These drugs came to be known as the tricyclic antidepressants, and included imipramine and amitriptyline. They operate by reducing reuptake – the process whereby the sending neuron gathers back some of the transmitter before it crosses to the next cell.

The result of these two lines of evidence was the monoamine hypothesis, which (in a nutshell) states that depression is caused by a deficiency of serotonin and/or norepinephrine, and can be corrected by medications which enable these deficient amounts of serotonin to last long enough in the gap between neurons to pass the signal along.

What is a good hypothesis?

Hypotheses are particularly useful if they meet two primary criteria:

1. They point the way toward useful action.
2. They generate testable questions.

Note that a hypothesis doesn’t have to be true to be good.  “The moon is made of green cheese” is a reasonably good hypothesis, because we can build a spacecraft, visit the moon, collect a sample, and see if it really is green cheese.

The statement “Depression is caused by an imbalance in undiscovered and unmeasurable energy fields”, for example, fails both tests. It’s unclear what to do about these imbalances, and the lack of measurability makes it hard to test the idea. The very fact that we can’t detect the fields or anomalies in question makes the hypothesis useless – the product of imagination rather than observation.

So is the monoamine hypothesis a good one?

The monoamine hypothesis, by contrast to the ideas above, is admirable. It generates a number of ideas that can be tested.  For example:

  • Depressed individuals should, on average, show differences in serotonin levels or function relative to nondepressed individuals.
  • People should generally have lower levels of serotonin or serotonin function when they are depressed than when they are not depressed.
  • Medications that correct these differences should correct the depression to at least some extent, compared to measures (like placebo treatments) that work primarily by belief and expectancy.
  • If we take nondepressed volunteers and take measures to produce these differences associated with depression (like feeding them a diet that will produce a serotonin deficiency), we should see an upswing in depressive symptoms.
  • Measures, such as drugs, that produce opposite effects on serotonin function should have opposite (or at least different) effects on mood.

We can quibble with any of these hypotheses and find possible exceptions to them, but on the whole they are reasonably sound. If we go out and test them and find support for none of these ideas, then we can reasonably say that the monoamine hypothesis has not been supported and is probably best tossed on the junkheap of scientific history.

You can guess, I think, where this is going eventually.

Tuesday 1 November 2011

The Authentic Quest: Plato Revisited

A pre-ordained path?
Is there such a thing as the “genuine you”?

How do you recognize an object to be a chair? Chairs come in all different shapes and sizes, and none of their features (four legs, a back, a certain height) is absolutely essential.

Plato suggested that there is a world of ideal objects to which we have a kind of unconscious access. In this world there is an “ideal chair”, and all earthly chairs bear some vague resemblance to it, sharing their “chairness”. We recognize the link, then identify the object before us as a chair.

Fun idea, but nobody believes it. We can recognize computers too, but no one thinks there is another dimension where an ideal computer has been lurking for thousands of years awaiting their invention in our world.

That is, we don’t believe it for furniture and electronics. We still find it tempting, however, to believe in the world of ideals for one thing:  ourselves.

We imagine that there is a “real” version of ourselves, a noble and true self, and that our day-to-day existence is a mere pale reflection of that self. Our “authentic self” is unfailingly kind, generous, fearless, skillful, and insightful. These aspects seem universal: we sometimes hear that all of us share in these timeless qualities. Furthermore, our true self has a firm mission in life, a purpose or quest that may be unique to us.

Our actual existence gets in the way. We get tired, cranky, anxious, confused. We say that we feel foggy, or lost. By this we mean that, as in a fog, we have lost sight of (or a sense of connection with) the true self.

When we misbehave we say “I wasn’t myself.” We loaf around, we watch television, we get bored, we are petty, we eat things we know we shouldn’t, we snap at our loved ones, and we imagine that somewhere there is another version of ourselves that doesn’t do any of these things.

With respect to our uniqueness, we long for an awareness of our life task, as though it sits undiscovered out there somewhere, perhaps buried in the back yard. We hear of the soul’s journey, and suspect that there is a trip we are supposed to take that we have forgotten about, or only dimly understand.

Wander through the self-help section of any good-sized bookshop and you will find dozens of titles aiming to reconnect you with your true self, advertising themselves in a variety of ways: “Becoming More Authentic”, “Finding Yourself”, “Your Hidden Purpose”, “The Guru Within” and so on. We take magazine quizzes to find out if we truly are a seeker, a people person, a creator, a joiner, a connector.

This is not all nonsense. There are ways of life that are more and less satisfying for all of us. Some of us see little point in the chatter of social intercourse and would make fine keepers of lighthouses. Some gain a great sense of reward from physical activity, and make poor office workers. Some want to use their minds for creative work and are dissatisfied performing manual labour.

But the belief in an invisible doppelganger who is vastly more admirable that ourselves can be an attempt to reject who we truly are. We really do get tired and impatient with our families. We really do break wind. We really do get dissatisfied when we overemphasize one aspect of our lives to the detriment of others. We really do fear things unreasonably, get preoccupied with trivia, avoid exercise, neglect our friends, and repeat foolish patterns.

In other words, perhaps that person who spent most of last evening sitting on the couch watching “American Idol” really is the authentic you. Perhaps there isn’t another one, either in this dimension or anywhere else.

The life we lead may not be satisfying. But if we are to find a better way to live, we had best know what we are looking for. If we imagine it is some magical alter-ego lurking in the ether we run the risk of wasting our lives on a wild goose chase, watching inspirational videos and feeling like failures because we can’t seem to channel this mythical entity.

Perhaps we need to throw out the Ouija Board, look ourselves squarely in the mirror, admit that we are who we are, and accept the responsibility to take the next step, rather than waiting for the universe to speak to us – or lamenting that it seems to be silent.