DSM-5: A Little Mix Up

Proposals in the upcoming DSM-5 psychiatric manual for diagnosing "mixed" mood states may be muddled, according to a new paper.

The mixed state - the name alluding to a mix between depression and mania - has traditionally been viewed (more or less) as combining the dysphoria of depression with the energy of mania. Anger, agitation, restlessness and so forth.

I've been depressed and I know only too well the difference between that "active" depression and the "inactive" kind; if I had to choose, I'd always go for the latter, because at least you're in less danger of doing or saying something you later regret.

However, in the proposals for DSM-5, "mixed" episodes as such will be abolished. Instead, a depressive episode will have "mixed features" if it is associated with at least 3 of 7 symptoms normally seen in (hypo)mania. But - and here's the key novelty - those 7 are only the "good" symptoms of mania. Not things like anger, irritability, insomnia or 'aimless' hyperactivity. (Edit: There are also separate criteria for "mixed" manic and hypomanic episodes).

What will this mean? In a new paper, psychiatrists Perlis, Cusin, and Fava tried to find out. The large STAR*D antidepressant trial recruited people with depression, but it gave everyone the Psychiatric Diagnosis Screening Questionnaire (PDSQ), amongst many other measures. This helpfully included six items on "mania symptoms", which correspond pretty closely to the DSM-V proposed "mixed" features.

Perlis et al found that depressed patients who reported experiencing these "mixed" items had a better response to antidepressant treatment. The more mixed symptoms, the more likely they were to get better on the common SSRI citalopram, even adjusting for other variables.

That's the exact opposite of what you'd expect from a measure of "mixed states", as these are thought to be less responsive to antidepressants - maybe even caused by them. There was no placebo group, so it's unclear why they got better, but either way, it's unexpected; the authors declare themselves "surprised". Hmm. What a mystery...

Or maybe not. These manic symptoms are all things that you're not when you're depressed. The 6 items actually make a good summary of what depression, even agitated depression (except maybe #6) isn't.

So, one interpretation of these results is that people who endorsed these items just weren't depressed, at some point in the 6 months prior to doing the PDSQ. Assuming they were depressed at other points that means their mood was variable over time.

People whose depression is variable might well be more likely to recover than the ones whose depression was unrelenting.

Now Perlis et al do consider this -

further models were fit incorporating the IDS-C30 pleasure and reactivity items; results were essentially unchanged indicating that they are unlikely to be confounded by mood variability per se...

But this assumes that the IDS-C30 questionnaire is a good measure of mood variability in this sample. Maybe it's not, and these data are telling us so. I'd have said that's more likely than the idea that these people were actually both cheerful and depressed at the same time, which seems like a contradiction in terms.

Maybe I'm wrong, and these people did feel that, but the problem is, we can't tell, because no-one actually sat down and asked these people what was going on, or heard their account of what they meant by ticking both the "depressed" and "manic" boxes.

Did they experience a strange mixed emotional state in which they simultaneously depressed and happy? Did their mood see-saw from one day to the next? Or weekly, monthly? Were they depressed in the day and happier in the evening? Were they depressed, then back to normal, leading them to see the normal as a 'high', by comparison with the lows? Were they depressed when sober and happy when drunk? Vice versa? Are they experiencing normal ups and downs and interpreting them as 'mood swings' because they've become convinced, for whatever reason, that they have a mood disorder? Did they just have a poor command of English and weren't really trying to say what the highly-educated investigators assume they were?

Who knows? No-one, because no-one asked. Rely on questionnaire 'measures' (as if emotions can be measured) as a replacement for understanding, and you'll end up where this paper does - with a 'result' that's impossible to understand.

Don't seek, and ye shan't find.

It's not great news for the DSM-5 proposals, either way, although defenders could hold out hope that the differences between those criteria and the PDSQ measure might mean the DSM-5 will perform better...

 Perlis, R., Cusin, C., and Fava, M. (2012). Proposed DSM-5 mixed features are associated with greater likelihood of remission in out-patients with major depressive disorder Psychological Medicine, 1-7 DOI: 10.1017/S0033291712000281

Broken Hearts and Broken Livers

In a new paper, Beyond the Blues, German psychologists Postert et al discuss how the Hmong people of South East Asia talk about sadness - or rather, how they don't, because they don't really have a word for it.

Based on anthropological fieldwork in a number of Hmong communities in Laos, the focus of this article is on the Hmong term tu siab, literally "broken liver". This is usually translated as "sadness" in the dictionaries, but the authors say that, although it is certainly the closest thing the Hmong have to a word meaning sadness, it is not the same because:

The instance of becoming ‘sad’ in Western contexts is that ‘something bad happened’... This may involve disappointment in personal relationships, but also other afflictions beyond the social realm. At the core of the emotional experience of ‘sadness’ are basic violations of values deeply embedded in Western conceptions of the individual. The afflicted individual feels resigned, passive, out of control...

In Hmong language, the concept of ‘broken liver’ has a strong emphasis on kin relations. It pertains very often to social situations of isolation and neglect from one’s kin including consanguines, patrilineal ancestors, or affines or their unmarried daughters in cases of romantic love. Persons with a ‘broken liver’ may have been voluntarily offended, excluded, or separated from these persons by bad fortune...

One of the highest Hmong values, a person’s vital social integration, is at stake here. However, a state of ‘broken liver’ is usually far from resignation. Contrary to the assumed passivity of a ‘sad’ individual, a ‘broken liver’ is an affective marker highly mobilising social relations and interdependencies ... having a member in one’s group whose liver is ‘broken’ appeals to the collective commitment of all relatives...

[like the English "guilt" and "shame", but unlike "sadness"] ‘broken liver’ demonstrates characteristics of a socio-moral emotion in everyday pragmatics of Laotian Hmong villages. It is typically evoked in a – conscious or unconscious – transgression of an important sociocultural rule. When a man is assumed not to accord to basic principles of social reciprocity by keeping substantial gains from an opium sale for himself, close relatives may develop signs of a ‘broken liver’ signalling their disapproval...

In short, the argument is that the Hmong "broken liver" differs from our "sadness" in being an active response rather than a passive reaction, a social statement rather than an individual feeling, in having a moral dimension, and so on.

But isn't that much like our "broken heart"?

"Breaking someone's heart" is a moral issue. It's not good to be a heartbreaker. If someone broke your friend's heart, you'd be angry. It's a specifically social emotion in the sense that it generally results from betrayal, abandonment, or disrepect. It's true that while the Hmong's "liverbreak" seems to extend to all close relationships, "heartbreak" often has a romantic connotation; but we do talk about "breaking your mother's or father's heart", so even that's not an absolute rule.

Consider this recently broken heart. Doesn't Tulisa's heartbreak fit the tu siab bill?

If so, then the main difference between Hmong and English terminology is that they only have a concept of 'heartbreak', and lack a general concept of 'sadness'. That's quite interesting, but I'm not sure how much to read into it. English doesn't have a word for 'déjà vu'; we had to borrow it from the French, but surely that doesn't mean that no English people ever felt it until the French explained it to them.

I'm no expert but judging by this paper, Hmong emotion terminology is really very similar to ours. The big difference is that the Hmong (in common with other East Asian cultures) link emotions to the liver, which to Westerners sounds silly, but it's no more silly than our talk about emotions being in the heart. They're both just metaphors.

Replace "liver" with "heart", and the following Hmong terms (listed in the paper) look very familar -

• zoo siab  ‘pleased, happy’ (lit. ‘good liver’)
• siab npau  ‘angry’ (lit. ‘liver boiling’)
• chob siab  ‘inwardly offended’ (lit. ‘pierced liver’) etc.

Don't those all make sense? We talk about being "hearty" or "heartened", "taking heart" or having our "hearts lifted" when we're happy or confident; our "blood boils" when we're angry; we talk about feeling "cut", "stung", "pierced" by criticism or insults, and we suffer "heart-rending" traumas.

This is certainly a very interesting paper, but it didn't leave me feeling that the Hmong's emotional life is all that different to ours.

Postert, C., Dannlowski, U., Müller, J., and Konrad, C. (2012). Beyond the Blues: Towards a Cross-Cultural Phenomenology of Depressed Mood Psychopathology, 45 (3), 185-192 DOI: 10.1159/000330944

The Age of ADHD

Diagnosed rates of ADHD in American children have skyrocketed in the past 20 years, and use of medication such as Ritalin and Adderall has increased by an even greater amount.

So says a report just out in Clinical Pediatrics, using data from the major US National Ambulatory Medical Care Survey (NAMCS). The rate of office based visits (i.e. visits when a doctor saw or treated a patient, outside of a hospital) was the main outcome measure. The authors looked at the number of visits reporting a diagnosis of ADHD, and also the number of ADHD visits also involving psychostimulant medication, for kids aged 5 to 18.

See above - that's a big increase, and a lot of visits (remember the Y axis is visits per 1000 children per year.) One thing to remember is that the increase might not mean that there are more patients with ADHD -  it could reflect more visits per patient, but that seems unlikely to account for all of it.

A few thoughts -

The rise of ADHD parallels the recent increase in autism diagnoses. Yet people don't seem to be talking about it to the same extent. We're always hearing about "the autism epidemic", the "Age of Autism". Why aren't we equally concerned about the ADHD 'epidemic'? Why don't we have minor celebs railing about vaccine-damaged ADHD children?

Next - like autism - it seems likely that much or all of the increase is due to changes in awareness and willingness to diagnose the disorder. If so, logically, ADHD must either be being seriously overdiagnosed now, or was being seriously underdiagnosed previously. Or both.

This is especially true of boys. Rates in girls rose pretty much steadily for 15 years but in boys, there have been swings up and down, although the overall trend is still upward. It's always possible that this is a quirk of the NAMCS dataset, but if not, it suggests that ADHD diagnosis in boys is especially prone to changes in diagnostic fashion.

It's tempting, actually, to see the recent fall in boys with ADHD as a consequence of the rise of autism diagnoses over the same period. Autism is predominantly diagnosed in boys and the two disorders are often comorbid.

Maybe, boys are now getting autism diagnoses which are then felt to explain their behaviour, meaning that they don't "need" an ADHD diagnosis, which previously they would have got. But that's just my speculation, and it's probably reading too much into the data, because there was also a peak in 1994 which I can't see any explanation for.

Sclar DA, Robison LM, Bowen KA, Schmidt JM, Castillo LV, and Oganov AM (2012). Attention-Deficit/Hyperactivity Disorder Among Children and Adolescents in the United States: Trend in Diagnosis and Use of Pharmacotherapy by Gender. Clinical pediatrics PMID: 22399571

The Case of the Phantom Phantom Finger

A "phantom limb" is the sensation that an amputated limb (or other body part) is still present.

They can be distressing, especially when they're accompanied by pain in the "limb" which is not uncommon. The leading theory of why they happen is that the brain areas that used to receive sensations from the lost appendage respond to input "spilling over" from nearby brain regions.

Anyway, a phantom limb is bad enough, but a paper just out reports on the case of a phantom finger that was never there in the first place.

A woman, RN, was born with an abnormally short right arm; her right hand was also malformed, with a shortened thumb, no index finger, and immobile ring and middle fingers. Only the little finger was present and correct.

At the age of 18, she then had the misfortune to suffer a car crash; the injuries meant that her right hand had to be amputated. She soon found herself experiencing a phantom hand - with all five fingers. Three of them felt like they were normal length; the "thumb" and "index finger" felt shorter than normal, but remember that the original hand had no index finger at all.

RN also suffered from phantom pains and was distressed by the fact that the "hand" felt like it was bent into an impossible posture. Fortunately, the mirror box technique was able to set things right; while the phantom was still there, it was no longer painful, and all the fingers were the right length.

This is a remarkable case. The authors of the paper, Paul McGeoch and V. S. Ramachandran (perhaps the best known phantom-limb expert) say that it could mean that we're born with an innate, hard-wired "body plan" in the brain, regardless of the way our body actually develops -

While RN’s phocomelic[abnormal] hand was present she did not experience any phantom sensations. Thus, although severely deformed, the mere presence of the hand was sufficient to inhibit the innate representation of her normal hand and prevent any phantom sensations from emerging, presumably from tactile, proprioceptive and visual feedback... the amputation of her hand appears to have disinhibited these suppressed finger representations in her sensory cortex and allowed the emergence of phantom fingers that had never existed in her actual hand.

They do consider alternative explanations though -

Clearly it is beholden on us to consider whether RN’s descriptions do not describe a genuine sensory experience, but rather are confabulatory in origin. We do not believe this to be the case, since if she were confabulating then it would seem unlikely that she should report that her phantom hand had five fingers, but that they were not all of normal length; if this were simply ‘wishful thinking’ then she would likely claim to have five normal length fingers. This appears a persuasive, although not definitive argument, against confabulation.

Seems like a fair assessment.

I don't even know what you'd call the phantom "index finger". A pseudo-phantom? A phantom phantom?

McGeoch, P., and Ramachandran, V. (2012). The appearance of new phantom fingers post-amputation in a phocomelus Neurocase, 18 (2), 95-97 DOI: 10.1080/13554794.2011.556128

Ketamine - Magic Antidepressant, or Expensive Illusion?

Not one but two new papers have appeared from the Carlos Zarate group at NIMH reporting that a single injection of the drug ketamine has rapid, powerful antidepressant effects.

One placebo-controlled study found a benefit in depressed bipolar patients who were already on mood stabilizers. The other found benefits in treatment-resistant major depression, though ketamine wasn't compared to placebo that time. Here's the bipolar trial:

There have now been several studies finding dramatic antidepressant effects of ketamine, a compound that all journalists seem contractually bound to call either a or a "club drug" or a "horse-tranquilizer". Great news?

If you believe it. But hold your, er, horses... there's a problem. As I said almost 3 years ago about one of the earlier ketamine trials:

In theory, the trial was double blind - neither the patients nor the doctors knew whether they were getting ketamine or placebo. But you'll know when you've been injected with 0.5mg/kg ketamine. You get high. That's why people take it [recreationally]. The study can't really be called double blind.

To their credit, Zarate et al did acknowledge this, and suggested that in future ketamine could be compared to another drug which produces noticeable effects. But they really should have done that to begin with.

It's now 2012, and there have still not been any published studies comparing ketamine to an active comparator i.e. a different drug that produces noticable psychoactive effects, to avoid unblinding. This means it's 12 years since the initial pilot report on ketamine in depression, and 6 years since the first large trial appeared.

The authors of the 2006 paper themselves wrote that "limitations in preserving study blind may have biased patient reporting... One potential study design in future studies with ketamine might be to include an active comparator" and suggested amphetamine for the big role.

Good idea. But six years later, we're still waiting. Which is really a bit silly. There have been dozens of papers written about the possible antidepressant effects of ketamine, from human trials to mouse work. That's a lot of research dollars (and dead mice) on something that might just be an active placebo.

Looking at the registered ketamine research on clinicaltrials.gov, I found that four active-comparator ketamine trials are in the pipeline (1,2,3,4), plus one cancelled (5). Only one is for depression though. The others being for OCD, cocaine dependence and suicidal ideation.

In all of these trials a benzodiazepine is the active comparator. Is that a good idea? Well, it's certainly better than nothing, but I wonder.

An active comparator has to "make an impression" on the patient equal to that produced by the real drug.  The null hypothesis, remember, is that ketamine has no specific antidepressant effect. That means it produces improvement through a combination of a) the placebo effect (expectation) and b) non-specific psychoactive changes.

More on that second one: any psychoactive drug might relieve depression by "taking your mind off it" and a change in mental state, as provided by a drug, also provides a demonstration that "I won't always feel this way". By showing that states of consciousness are products of brain chemistry, almost any drug could therefore offer a "glimmer of hope" to the depressed. If all this sounds very subjective, it is, but that's the point. Psychiatry is.

Would a benzo make as big an impression as 0.5 mg/kg ketamine IV? It's impossible to predict, really; so we'd need to ask people about the subjective strength of the drug effect. Personally, I worry that a lot of people just get sleepy on benzos and don't really feel much, so I'd prefer they used something a bit more hard-hitting like amphetamine, but maybe that's just me.

There's a deeper problem though. Suppose our ketamine-benzo trial finds no difference between ketamine and benzo. A critic could say, ah, but maybe it was just a "failed trial", so it doesn't overturn the positive studies. The patients weren't properly diagnosed, or weren't depressed enough, or were too depressed, etc.

Nitpicking such differences between studies is a well-practiced art.

Critics could complain in other ways if the study did find a benefit of ketamine. As I see it, the only way to settle this once and for all is to do a three-way randomized controlled trial - inactive placebo vs. active comparator vs. ketamine.

That way, if it's a failed trial, we'd know: there'd be no difference between ketamine and the inactive placebo. If there was a difference, but the active comparator was just as good as ketamine, that means it was all about nonspecific effets. Finally, if ketamine was better than the other two conditions, we could be pretty confident it was really working.

Also important is the question of volunteer expertise; subjects shouldn't be able to tell what drug they're on, but people who'd taken ketamine and/or the comparator drug before might be able to do that, so you'd want naive volunteers.

In conclusion: It's possible that ketamine has no specific antidepressant effects. To find out we ideally need a three-way trial, with both active and inactive comparators, careful monitoring of subjective drug effects and patient knowledge and expectations. Until that happens, I will be skeptical of ketamine in depression.

This is not because I just think it's impossible. Ketamine profoundly affects the brain in ways that we don't understand. I've suffered depression and I know it can come and go in a matter of minutes. So I think it's entirely possible that it works - but it's also possible that it's a nonspecific effect.

Look. I really want to know the answer to this. Both as a neuroscientist, and as a depression sufferer, this is very important to me. That's why we urgently need a good trial.

Link: See also the discussion and the comments over at The Neurocritic and this Scientific American piece which is pretty good except that it doesn't cover the active placebo issue.


Zarate CA Jr, Brutsche NE, Ibrahim L, Franco-Chaves J, Diazgranados N, Cravchik A, Selter J, Marquardt CA, Liberty V, and Luckenbaugh DA (2012). Replication of Ketamine's Antidepressant Efficacy in Bipolar Depression: A Randomized Controlled Add-On Trial. Biological psychiatry PMID: 22297150

Ibrahim, L., et al. (2012). Course of Improvement in Depressive Symptoms to a Single Intravenous Infusion of Ketamine vs Add-on Riluzole: Results from a 4-Week, Double-Blind, Placebo-Controlled Study Neuropsychopharmacology DOI: 10.1038/npp.2011.338

The World Mental Health Missionaries?

Is research on the global distribution of mental health problems a kind of modern-day missionary work?

Maybe, says Australia's Dr Stephen Rosenman in a provocative paper: Cause for caution: culture,sensitivity and the World Mental Health Survey Initiative.

The World Mental Health Survey (WMHS) is a huge World Health Organization project that aims to measure the rates of various psychiatric disorders in countries around the world. The WMHS has produced a great deal of data, but Rosenman points out that this assumes that people all over the world suffer from the same psychiatric disorders (and display them in the same ways) as the Americans and Europeans about whom the diagnostic manual was originally written.

The surveys translated the diagnostic criteria into the local languages, of course, but that doesn't mean they were appropriate to the local cultures.

He suggests that all this is a bit like missionaries who went around translating the Bible and trying to convince people to read it -

Looked at with a less admiring eye, the [WMHS] resembles in some ways the missionary movements of the last two centuries. Like the missionaries, the organisers are committed, selfless people of extraordinary goodwill who have come to poor countries from cultures at the apogee of their wealth, prestige and intellectual power.

They bring an evolved and highly developed system of thought. They set about delivering the fruits of that to the people. The survey initiative has engaged the leaders of the profession in the countries and, in a sense, has converted them to this view of psychopathology.

It is difficult to know if their success is due to the power of the ideas they brought, or the power and prestige of the cultures they came from, or from their technique of taking over both the centre and the contours of the beliefs of a culture. Missionaries brought a ‘colonisation of consciousness’... etc.

He does goes on to say though, "I do not want to push the missionary analogy too far" which is wise I think; there are important differences and other analogies are equally apt.

The paper's a good read though. It refers to Crazy Like Us, a book I'm fond of.

Although Rosenman doesn't cite another important source (cough cough): he points out that the WMHS national estimates of rates of depression don't correlate at all with national suicide rates, which is seriously odd -

According to the CIDI [the psychiatric interview used in the WMHS], Japan, for example, has one-third the rate of mood disorders (3.1%) seen in the USA (9.6%). At the same time, Japan’s suicide rate (20.3/100,000) is twice that of the USA (10.8/100,000). Suicide rates seem to have almost no relationship with CIDI diagnoses of affective disorder... Suicide, of course, is complexly shaped by the culture but are we to believe that answers to the CIDI are any less culturally determined and which is to be considered the better index of disorder?

I made the very same point using the very same datasets in 2009 (although I looked at 'all mental illness' rather than 'mood disorders').

Rosenman, S. (2012). Cause for caution: culture, sensitivity and the World Mental Health Survey Initiative Australasian Psychiatry, 20 (1), 14-19 DOI: 10.1177/1039856211430149

Beware Reverse Publication Bias

In all the fuss over the pressure for scientists to publish positive results, we may have been missing an equally dangerous kind of publication bias operating in the opposite direction.

So say Luijendijk and Koolman in the Journal of Clinical Epidemiology: The incentive to publish negative studies: how beta-blockers and depression got stuck in the publication cycle.

The background here is the possible link between beta blockers and depression. Beta blockers are drugs widely used to treat high blood pressure. Some studies have reported that they raise the risk of depression, though many others found no link. Propranolol is said by some to be the worst offender because it's best at entering the brain.

Luijendijk and Koolman say that beta blocker-depression studies have appeared in the form of "publication cycles" - first a positive study appears, and then negative ones follow. Then another study finds a positive link using a different method - and rebuttals, using those methods, soon appear. They sketch out several such positive-negative cycles based on different methods and particular hypotheses.

Now, there's two ways to look at this. You could explain this in terms of standard positive publication bias. Maybe lots of people looked into a possible link, the ones who found nothing didn't publish. Then someone, by chance, did find an association with depression, and they published it. Once that happens, the question became a hot topic so the unpublished negative studies were dusted off and submitted.

But there's a more worrying possibility. What if the original positive studies were correct, and the subsequent negative studies were the product of an inverse publication bias in favor of contrarian negative results?

The publication cycles in the literature about beta-blockers and depression seem to suggest that
the very publication of positive studies, whether true or false, increases the incentive to publish negative results, whether true or false... [in the case in question] the first as well as a significant number of subsequent negative studies were published in high-impact journals (8 of 19 journals with 2009 impact factor greater than 4.0). Third, power analysis showed thatd in two cycles, the first negative studies were underpowered...

If a true-positive study stimulated the publication of one or more false-negative studies, again an invalid picture of the true association would emerge. Publication of false-negative studies may thus give rise to publication bias, just like publication of false-positive studies. Research groups usually compete to get the first positive study published in a high-impact journal. It has been suggested that it could also be worthwhile to aim at getting the first study that challenges the former published.

This is not an entirely new idea. It was described in the classic Why Most Published Research Findings Are False, but only in passing.

To be honest it's impossible to know, in any particular case, whether inverse publication bias is at work. Depending upon whether you think beta blockers cause depression (and that's still controversial), your interpretation of the biases in the literature will probably differ.

However, I think the basic idea is important. Publication bias isn't a bias in favor of positive results per se. It's a bias towards "interesting" results - which in most cases means positive ones, but could equally well include negative ones, in certain contexts. In some ways, this could be a good thing, if the negative and positive biases eventually cancelled out, leaving a neutral playing field; but there's no guarantee that would ever happen.

As for how to fix publication bias - my opinions on that question are well known...

Luijendijk, H., and Koolman, X. (2012). The incentive to publish negative studies: how beta-blockers and depression got stuck in the publication cycle Journal of Clinical Epidemiology DOI: 10.1016/j.jclinepi.2011.06.022

The Stigma(s) of Mental Illness

Fighting "the stigma of mental illness" is big business at the moment. But does "the stigma" really exist?

As I said back in 2010 :

There is a stigma of schizophrenia, and there's a stigma of depression, etc. but they're not the same stigma. We're told it's a myth that "the mentally ill are violent" - [but] no-one thinks depressed or anorexic people are violent. They think (roughly) that people with psychosis are. They have other equally silly opinions about each diagnosis, but there's no monolithic "stigma of mental illness".

Now a paper has come out which explores this idea in some detail: Stereotypes of mental disorders differ in competence and warmth. The title says it all : people have stereotypical views of people suffering from different mental disorders, but these stereotypes vary substantially.

The authors use the "Stereotype Content Model" framework, which despite the fancy name is very simple. On this view stereotypes are characterised by two dimensions, "competence" and "warmth". These are pretty self-explanatory. Warmth is whether you're seen as nice and friendly, or hostile and dangerous. Competence is whether you're thought to be good at it.

We all know that warmth and competence are distinct and indeed orthogonal concepts, and they crop up in other languages and in popular culture.

Anyway, in two Mechanical Turk online surveys of American adults, they first showed that respondants felt that "people with mental illness" were low on competence and (slightly) low on warmth, compared to other social and ethnic groups. That's similar to the ratings of the homeless, poor, and welfare recipients.

However in the second study, they asked about specific diagnoses, and this revealed a more complex pattern. I've shown the results above (colors are mine). There seemed to be four clusters. Mental retardation and Alzheimer's were perceived as warm, but incompetent; sociopaths and violent criminals were the opposite.

Schizophrenia clustered with homelessness and addiction in a worst-of-both-worlds category of low warmth and competence, while what could broadly be called "emotional" disorders, like bipolar, depression and anxiety, were rated more favorably. For what its worth, OCD was the least bad diagnosis.

These are interesting results. The only oddity about the method was that people weren't actually asked what they thought about these people; they were asked “In general, how much do Americans believe that..." This is, apparantly, standard procedure in this kind of stereotype research, but it seems a little strange to me.

Sadler, M., Meagor, E., and Kaye, K. (2012). Stereotypes of mental disorders differ in competence and warmth Social Science and Medicine DOI: 10.1016/j.socscimed.2011.12.019

Tired Brains Are More Excitable

An important new study shows how being awake causes progressive changes to the brain. This could shed light on the function of sleep - but it also raises warnings for neuroscientists.

Italian researchers Huber et al report that Human Cortical Excitability Increases with Time Awake. The experiment was conceptually simple - they measured cortical excitability when people were well rested and then looked to see how it changed as they were kept awake for over 24 hours.

The participants woke up at 7 am on Day 1 and were kept awake all of that day, all of the subsequent night, and all of Day 2. The excitability measurements spanned a period of 30 hours, from 9 am to 3 pm the next day. They were finally allowed to go to sleep on the next night and one final session took place on Day 3. I hope they got well paid for taking part.

The results showed a nice linear increase in excitability with increasing time spent awake. Sleep put this back to normal - mostly:

"Excitability" was measured using electroencephalography (EEG) combined with transcranial magnetic stimulation (TMS). Essentially, they zapped the brain (left frontal cortex) with a strong magnetic pulse, and measured the electrical activity that this provoked in the brain.

It was a small study but the findings look solid, with all six participants showing clearly higher stimulation-evoked potentials after sleep deprivation. EEG cortical theta band activity was also correlated with time spent awake, replicating previous findings.

The authors say that these data fit with the idea that the function of sleep is to prevent the brain from becoming too excitable. I previously described this as the "defragmentation" hypothesis of sleep.

The theory goes that while we're awake, our brains are constantly forming new and stronger synaptic connections, as we learn and remember. Most of the new connections are excitatory. However this creates a problem because the brain must maintain a delicate balance between excitation and inhibition. Too much neural excitation and you'll have a seizure, amongst other things. So some researchers believe that during sleep, the brain "prunes" the new excitatory connections in such a way that the information they store is preserved, but the overall excitability is reset.

These data are the first clear-cut human evidence in favor of the theory. Most of the previous work was in animals.

So sleep researchers will be very interested by this paper, but all neuroscientists should take note. If being awake changes cortical excitability, it means that the time of day that you conduct your experiments could have an impact on your results. EEG researchers should pay particular notice, but it could well be that these changes also affect the fMRI signal.

This could be a serious confounding factor in your data. Suppose, for example, that your healthy controls are more likely to have jobs than your patients with, say, autism or depression - which is sadly all too common. Now people with jobs would naturally prefer to attend your study later in the day, after work, leaving those with more flexible schedules to come in bright and early... you see the problem.

Huber, R., Maki, H., Rosanova, M., Casarotto, S., Canali, P., Casali, A., Tononi, G., and Massimini, M. (2012). Human Cortical Excitability Increases with Time Awake Cerebral Cortex DOI: 10.1093/cercor/bhs014

Good Science, Bad History, in the British Journal of Psychiatry

The latest February 2012 issue of the British Journal of Psychiatry features a paper about the association between child abuse and later mental health problems. I haven't read it yet, but it looks pretty good.

However, it also includes an editorial from John Read and Richard Bentall which argues that:

Just 20 years ago, however, it would have been difficult to get the paper published. Mental health professions have been slow, even resistant, to recognise the role of childhood adversities in psychiatric disorder... Until very recently the hypothesis that abuse in childhood has a causal role in psychosis was regarded by many biologically oriented psychiatrists as heresy...

Really? I checked the BJP from exactly 20 years ago. The February 1992 issue contained:

• A paper about child sexual abuse in female psychiatric patients.
• A letter praising a different article, on the same topic.
• A review of 11 studies on psychosocial family interventions as treatments for schizophrenia.
• A paper looking at the effect of the social environment on symptoms of schizophrenia.

Four strikes and they're out. It's not true that this kind of thing wasn't being discussed 20 years ago.

Such grandstanding is bad for science. Few would deny that psychiatry in recent years has undervalued psychosocial factors and overvalued genetics and neuroscience, but it's actually quite a complicated story, not a Punch and Judy show with bad guys on one side and good guys on the other.

Rhetorical flourishes like this editorial certainly get attention but in the long run, down that road lies madness.

Read, J., and Bentall, R. (2012). Negative childhood experiences and mental health: theoretical, clinical and primary prevention implications The British Journal of Psychiatry, 200 (2), 89-91 DOI: 10.1192/bjp.bp.111.096727

Mystery Joker Parodies Neuroscience

Someone has created a hilarious spoof paper poking fun at neuropsychoanalysis (but all of fMRI takes some hits too): A Triple Dissociation of Neural Systems Supporting ID, EGO, and SUPEREGO.

Featuring gems such as

• Authors "Steven Z. Fisher and Stephen T. Student" with contact details "mother@amaliastate.edu".
• "Twenty-four healthy participants (all 19-year-old white, male undergraduates who sat near each other in an Introductory Psychology course and were raised in upper middle class suburban New
  England neighborhoods) were scanned but 17 were excluded for not following instructions or falling asleep in the scanner."
• "If you’re like us, you’ve probably been thinking that Social Neuroscience, Neuroeconomics, and Developmental Social Cognitive Affective Clinical Neuroscience are just not cutting edge enough
  anymore. Do not despair. This study represents the first of what is likely to be a productive and active new field of Psychoanalytic Neuroscience."

It really is very funny, but it's also deadly accurate in its highlighting serious problems that plague a certain genre of neuroimaging papers. Who made it? The PDF appeared on Dropbox a couple of weeks ago and, while a few people have Tweeted about it, no-one has claimed ownership, yet.

For the record, it wasn't me.

Psychiatry's True Blood? Pt 1.

Imagine that there was a blood test that could detect depression. Wouldn't that be useful?

It depends.

Ridge Diagnostics are a US company who offer such a test. They've just published some results of the technology in Molecular Psychiatry. In two samples of patients with major depressive disorder (MDD), they report differences in the"MDDScore", between the patients and healthy controls.

The MDDScore is an aggregate value, calculated from the levels of 9 metabolites in blood serum. They're all well-known molecules, including hormones, such as cortisol and prolactin. The novelty is in how they're put together to make the MDDScore. We're given equations - but the key variables are not provided, because they're proprietary:

Long-term Neuroskeptic readers will recall that this "secret ingredients" approach to publishing science was also adopted by another company offering a different depression test.

Anyway, the performance of the test was impressive. In both the pilot and the replication samples, the MDDScore was significantly higher in the depressed people than in the controls. In both cases, the test had a sensitivity of over 91% and a specificity of over 81%, which is pretty good. Ridge Diagnostics are already offering the MDDScore clinically. For $745 a pop.

However...

Although there were two depressed patient groups (n=36 and 34), there was only one set of controls (n=43); both patient samples were compared to it. This means the second, "replication", test was not fully independent of the first one. If the first finding was a fluke caused by the control group having weird results by chance, for instance, then the second study would just repeat the fluke.

The patients were significantly older, and with a higher BMI, than the controls. They did control for these variables, which is good, but this raises the question of whether these folks differed in other ways, that they didn't measure, and hence couldn't control for.

In both samples, the patients had a very significantly higher MDDScore than the controls (p less than 0.0001, both times). But in both cases, the difference in levels of EGF (epidermal growth factor) was almost as strong: p=0.0003 and p less than 0.0001, respectively. Other metabolites weren't far behind. Testing for EGF would almost certainly be cheaper than getting an MDDScore.

Finally, all these data demonstrate is that the test can distinguish between people with MDD and entirely healthy people. But how often are doctors going to need to do that? More likely, they'll want to distinguish depression from other things that are often confused with it, such as: bipolar disorder, anxiety disorders, chronic fatigue syndrome, bereavement, "stress", and all manner of physical illnesses e.g. thyroid problems. Daniel Carlat said last year that

If the test cannot distinguish different psychiatric problems, then the MDDScore is simply a non-specific "biomarker" for emotional difficulties of all stripes, and would be essentially useless.

How disorder-specific is the MDDScore? This paper doesn't tell us. And to date, this is the only published paper mentioning the MDDScore. The website mentions some conference presentations, but none have yet appeared in a peer reviewed journal.

Ridge Diagnostics have an interesting history. But that's another story - stay tuned for Part 2.

Papakostas, G., Shelton, R., Kinrys, G., Henry, M., Bakow, B., Lipkin, S., Pi, B., Thurmond, L., and Bilello, J. (2011). Assessment of a multi-assay, serum-based biological diagnostic test for major depressive disorder: a Pilot and Replication Study Molecular Psychiatry DOI: 10.1038/mp.2011.166

The Trojan Horses of Medicine

Dodgy science is being smuggled into medical journals thanks to a loophole in the regulations, say Italian psychiatrists Barbui and Cipriani in an important article.

They focus on agomelatine, a recently-approved antidepressant. But their point applies to all of medicine, not just psychiatry.

Here's the problem. Nowadays, major medical journals have rules governing systematic reviews and meta-analyses of clinical trial data. If you want to review the evidence about how well a certain drug works, or its safety, you've got to do it properly. You have to consider all of the data, not just focus on the results that suit you. And so on.

However, these rules don't apply to "narrative" review papers, which is a broad term meaning any kind of article meant to give a discussion of the pharmacology, history, chemistry etc. behind a particular drug. For a narrative review, there are no rules.

In particular, you can write about the clinical trial data in such articles with no restrictions. Unlike in a proper systematic review, you can cherry-pick trials and so on to your heart's content. Some narrative reviews have so much clinical data in them that they end up being, in effect, a bad systematic review. One that would never have been deemed acceptable as a systematic review.

Barbui and Cipriani argue that narrative reviews are often used in this way, namely to paint drugs in a positive light. In the case of agomelatine, they mention a number of recent narrative reviews which were supposedly about the drug's mechanism of action, but which actually contained extensive (but biased) reviews of the clinical trial data.

It's not hard to see how pharmaceutical companies might take advantage of this process.

However, the problem is surely not limited to agomelatine. It's a loophole that affects every branch of medicine:

Most medical journals require adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). It is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses. Adherence to PRISMA is not required in review articles dealing with basic science issues as these articles are not focused on clinical trials.

In practice, however, the agomelatine case indicates that clinical data are regularly included and reviewed with no reference to the rigorous requirements of the PRISMA approach. These articles have this way became a modern Trojan horse for reintroducing the brave old world of narrative-based medicine into medical journals.

How do we stop this? It's simple, the authors say: just make all references to clinical data subject to PRISMA, or other accepted regulations, whatever the supposed 'primary focus' of the paper:

We argue that medical journals should urgently apply this higher standard of reporting, which is already available, easy to implement and inexpensive, to any form of clinical data presentation.

Of course, there are plenty of good narrative reviews that really do cover the pharmacology or other science in a useful way. The problem is not narrative reviews as such, but the way they're used.

Barbui, C., and Cipriani, A. (2012). Agomelatine and the brave old world of narrative-based medicine Evidence-Based Mental Health, 15 (1), 2-3 DOI: 10.1136/ebmh.2011.100485

The Age (Cohort) of Autism

New data shed light on the recent mysterious rise in the number of kids being diagnosed with autism.

The new research doesn't explain the increase, but it tells us more about it. It shows that the rise in Californian autism diagnoses (reported to the state DDS) over the period 1996 to 2005 was a cohort effect, meaning that the rates of diagnosis have got higher, the later a child was born.

A child who's 10 today (born 2002) has double of the chance of having a recorded diagnosis compared to a 14-year-old born just four years earlier, in 1998.

"That doesn't tell us anything new!" you might object (I did at first). "All that means is that rates have risen, and we knew that already". But actually it does tell us something important. Because the data could have turned out differently; rates could have risen without a cohort effect, if, in recent years, lots of diagnoses were being handed to children regardless of their age.

That didn't happen. Almost all children in California who get a diagnosis, get it at age 3 or 4. In more recent years, the average age at diagnosis actually fell slightly. The peak used to be age 4, it's now 3.

So it's not that children in general have been getting diagnosed with autism more. It's that young children are getting diagnosed more; children aren't being diagnosed "retrospectively", as it were.

Another interesting finding is that the rise in rates of 'high-functioning' autism has been much bigger than the rise in low-functioning autism (i.e. autism alongside intellectual disability), although that has risen as well. Edit: but note that their defintion of 'functioning' is rather unique; see the comments.

So what does this mean?

These data are consistent with various interpretations. It could be that rates of autism have really risen in California over this time period. But it could also be that people are getting more likely to detect and diagnose it - in young children.

Keyes, K., Susser, E., Cheslack-Postava, K., Fountain, C., Liu, K., and Bearman, P. (2011). Cohort effects explain the increase in autism diagnosis among children born from 1992 to 2003 in California International Journal of Epidemiology DOI: 10.1093/ije/dyr193

Challenging the Antidepressant Severity Dogma?

Regular readers will be familiar with the idea that "antidepressants only work in severe depression".

A number of recent studies have shown this. I've noted some important questions over how we ought to define "severe" in this context, and see the comments here for some other caveats, but I'm not aware of any studies that directly contradict this idea.

Until now. A new paper has just come out which seeks to challenge this dogma - not the author's term, but I think it's fair to say that the severity theory is becoming a dogma, even if it's an evidence-based one (but then, all dogmas start out seeming reasonable).

However, while the new paper is interesting, I think the dogma survives intact.

The authors went through the archives of all of the trials of antidepressants for depressive disorders conducted at the famous New York State Psychiatric Institute for the past 30 years. They excluded any patients who were severely depressed, and just looked at the milder cases. The drugs were mostly the older tricyclic antidepressants.

With a mean HAMD17 score of about 14, the patients they looked at were certainly mild. By comparison, most trials today have a mean of well over 20, and according to the main studies supporting the severity dogma, you need a score of about 25ish to benefit substantially:

So what happened? They reanalyzed 6 trials with over 800 patients. Overall there was a highly significant effect of antidepressants over placebo in mild depression, with an effect size d=0.52, or about 3.5 HAMD points. This is actually better than most other studies have found in "severe" depression. If valid, these results would torpedo the severity theory.

This seems very interesting... but. There's a big but (I cannot lie). Although the authors say they wanted to include all the relevant trials from the NYSPI, they only had access to the data from 6. There were another 6 projects, but they were "pharmaceutical company studies from which data were not released to the investigators."

This pretty much wrecks the whole deal. If those 6 studies all found no benefit of the drug, the overall average results would be much less impressive. We have no way of knowing what those studies found, but I'd wager that most of them were negative, because of publication bias - we know that drug companies tend to publish positive studies and bury negative ones. Or at least they did, at the time these studies took place (there are better regulations now).

By contrast, severity dogma classic Kirsch et al (2008) avoided publication bias by looking at unpublished data. Fournier et al (2010), the other major severity study, didn't but the data were very similar to Kirsch et al so it's not hard to believe them.

So in my view, until we know what happened in the other 6 trials, we can't really interpret these results, and the severity theory stands.

Stewart, J., Deliyannides, D., Hellerstein, D., McGrath, P., and Stewart, J. (2011). Can People With Nonsevere Major Depression Benefit From Antidepressant Medication? The Journal of Clinical Psychiatry DOI: 10.4088/JCP.10m06760