Mental Illness and Crime, Yet Again

As if on cue, a major study about the relationship (if any) between mental disorder and crime has appeared just when everyone's talking about that.

Although having said that, people seem to be interested in that issue most of the time nowadays, in the UK at any rate, with schizophrenia topping the list of supposedly scary syndromes.

So - should we be worried?

The new research, from Australian team Morgan et al, surveyed everyone born in the state of Western Australia between 1955 and 1969. About 1.6 million people lived there over the course of the study so this was a big project.

By linking local records of arrests over the period 1985 to 1996 to the database of psychiatric diagnosis, the researchers were able to examine disorder-crime correlations in the entire population - meaning that there was no possibility of bias.

So what happened? Here's some highlights:

• 32% of psychiatric patients had been arrested at least once. Unfortunately, it's not clear what the rate was in the general population, but that falls into the range of overall arrest rates in most countries.
• 11% of those arrested had a psychiatric diagnosis. This rose to 20% of arrests for violent offences.
• 0.8% of suspects had schizophrenia, rising to 1.7% for violent offences.
• The number of arrests in people without a disorder fell over the period 1985-1996, reflecting the well-known fact that people commit fewer crimes as they get older. However, in psychiatric patients, there was no change over time.
• For murder, 30% of suspects had a psychiatric history while 3% had a diagnosis of schizophrenia.
• Both substance abuse and personality disorders were associated with higher arrest rates than schizophrenia, but schizophrenia in turn was higher than depression, anxiety, and other miscellaneous disorders.
• Although only 1.7% of violent offenders had schizophrenia, those with the disorder were somewhat more likely to involve strangers, and to take place in public places, and less likely to target family and partners.

Overall this confirms that the great majority of crimes, including violent ones, are not committed by people with mental illness, and that your chance of getting 'murdered by a lunatic' is incredibly low. This strikes me as the only statistic that matters to most people.

There's a long-standing debate over whether people with various disorders are more likely to commit crimes than they would be if they didn't have one, the relative risk. While interesting, this is a purely academic question. What the rest of us need to know is the absolute risk, and this is low.

Morgan VA, Morgan F, Valuri G, Ferrante A, Castle D, and Jablensky A (2012). A whole-of-population study of the prevalence and patterns of criminal offending in people with schizophrenia and other mental illness. Psychological medicine, 1-12 PMID: 23234722

Religion Rises After Disaster Strikes

People turn to religion after natural disasters - but it doesn't actually provide much solace.

So say researchers Sibley and Bulbulia, who examined the population of Christchurch, New Zealand, before and after the 2011 earthquake. 185 died and many city landmarks were damaged in the disaster.

The paper, Faith after an Earthquake, opens with a Biblical quote.

Sibley and Bulbulia took advantage of the fact that a longitudinal study of the 'health and values' of the New Zealanders was already underway when the quake struck, and the survey included questionnaires about religious beliefs.

They found that, compared to before the event, residents of the affected Canterbury region were more likely to report becoming religious (8.6%) than of losing their faith (5.3%); in the rest of the country religion declined from 2009 to 2011, so the earthquake-hit area was exceptional.

The authors say:

Philosophers have plausibly argued that natural disasters such as the Christchurch earthquake are rationally incompatible with the existence of an all-powerful, all-loving God, because natural disasters cause pointless suffering to innocents... though faith eroded elsewhere in New Zealand, there was a significant upturn in religious faith among those who experienced the misery of New Zealand's most lethal natural disaster in eighty years.

But did faith help people cope with the disaster?

No - believers reported no better subjective well-being compared to the non-religious, either before or after the earthquake, although those who both lost their faith (apostates) during the period and were personally affected suffered a decline.

What's rather odd about this, however, is that other results showed that apart from the apostates, well-being wasn't affected by the earthquake at all. So it's no surprise that the religious coped no better: the irreligious already coped very well, so there was no room for improvement.

Sibley, C., and Bulbulia, J. (2012).Faith after an Earthquake: A Longitudinal Study of Religion and Perceived Health before and after the 2011 Christchurch New Zealand Earthquake PLoS ONE, 7 (12) DOI: 10.1371/journal.pone.0049648

The Small World of Words

I've been asked to encourage people to take part in an online psychology study called The Small World of Words

I get a lot of this, and I usually don't respond to such requests, but this one looks pretty interesting.

The project aims to collect the world's biggest word association database. You see a series of words and you just have to type in the first three words that pop into your head.

Here's some more about it:

On average, an adult knows about 40,000 words. Researchers in psychology and linguistics are interested in how these words are represented mentally. In this large-scale study we aim to build a network that captures this knowledge by playing the game of word associations. You can help us with this project by participating in this short and fun study.

The study consists of giving the first three words that come to mind for a list of 14 items.
All ages and nationalities are welcome, but please note that we do require all participants to be fluent English speakers.

It's the sheer scale of this that makes it cool. They've got some 60,000 participants, and over a million associations already, but they're aiming for almost 300,000 people - which would make it not just the biggest word association study ever, but the biggest psychology study of all time, as far as I know.

It only takes about 2 minutes to complete and it's actually quite revealing. Out of 14 words I managed to associate a full 3 of them with 'pain', which disturbed me somewhat.

So take a look and spread the word (associations)...

Are Porn Stars Happier?

Women who appear in porn are happier than other women, enjoy sex more - and have lots more of it.

So says a new paper with the pulls-no-punches title of Pornography Actresses: An Assessment of the Damaged Goods Hypothesis

Researchers James Griffith and colleagues sampled 177 American adult actresses, and an equal number of other women of the same age, gender and relationship status. The results were pretty clear: the actresses said they started having sex earlier; had far more partners with an average of 75 vs. 5 in their lifetime (and that's not including on camera).

They were a lot more likely to be bisexual (67% vs 7%!), enjoyed sex more, and reported slightly higher levels of sexual satisfaction, happiness and self-esteem.

On the other hand, they were more worried about STDs and took more drugs (50% had tried ecstasy, 40% cocaine and 27% methamphetamine.)

Finally - and the authors emphasize this - they were no more likely than other women to have suffered childhood sexual abuse. They're not 'damaged goods' as that horrible phrase has it.

So. Well. This study is clearly going to become a hot potato, or rather a political football in The Great Porn Debate, so let's take a calm look at it.

In any survey the fundamental question is - are the respondents representative examples? Or were the porn actresses who filled out the questionnaire atypically happy? Were the comparison women unusually miserable?

We really have no way of knowing. The controls were recruited from a university and an airport, which is pretty sensible although it might introduce some bias. The actresses came via adverts placed in an L.A. clinic specifically for the adult movie industry, the now-defunct AIMHF. That seems like a selective sample - but the clinic reportedly catered to most, if not all, stars in LA because all performers had to get monthly HIV tests there.

Ultimately, though, we don't know how representative they were.

Next up, it was all self-report. So the reports might have been wrong. However, that's a feature of all survey studies, especially those about such things as happiness. It's hard to see a way around this. It's also not clear what bias it would introduce into the results. It could be that the porn actresses were motivated to exaggerate their happiness in a bid to defend their industry, which I suspect will be a common criticism - but that assumes they're happy enough with it to want to defend it, so it's somewhat circular.

Finally, and most importantly in my view, L.A. porn stars are not your average pornstars. The American professional adult movie industry is the biggest, most regulated, and most 'mainstream' in the world. Sadly elsewhere the degree of exploitation, coercion, poverty and abuse among people who end up in porn is a lot higher.

Basically, I can't see anything obviously wrong with this study as far as it goes, but all it shows is that American porn actresses are in fairly good shape. Most women in porn, however, are not American.

Griffith JD, Mitchell S, Hart CL, Adams LT, and Gu LL (2012). Pornography Actresses: An Assessment of the Damaged Goods Hypothesis. Journal of sex research PMID: 23167939

Migraines On Twitter

People talk about migraines on Twitter more on weekdays than weekends and holidays - and the peak time of day for the horrible headaches is 7 in the morning.

The working-day effect on migraines has been reported before - perhaps a reflection of stress or, less charitably, people wanting a day off work... although some people suffer weekend migraines.

Of the working week, Tuesdays saw the most migraines, while Fridays were the least bad. About 80% of Twitter migraine mentions came from women - which matches the fact that women are at higher risk.

That's according to a little study just published that used a public database of tweets, timeu.se, that Neuroskeptic readers may remember.

In fact, an author of this study said in an email to me that it was actually inspired by one of my posts... but I'm aware that telling you that, combined with the previous post, means I'm in danger of blowing my own trumpet or 'disappearing up my own arse' as we say in the UK. So rest assured that this will be the last such self-referential piece for at least... a day or two.

Linnman, C., Maleki, N., Becerra, L., and Borsook, D. (2012). Migraine Tweets - What can online behavior tell us about disease? Cephalalgia DOI: 10.1177/0333102412465207

Questionnaire Extremism and National Character

"Personality differences" between people from different countries may just be a reflection of cultural differences in the use of 'extreme' language to describe people.

That's according to a very important paper just out from an international team led by Estonia's René Mõttus.

There's a write up of the study here. In a nutshell, they took 3,000 people from 22 places and asked them to rate the personality of 30 fictional people based on brief descriptions (which were the same, but translated into the local language). Ratings were on a 1 to 5 scale.

It turned out that some populations handed out more of the extreme 1 or 5 responses. Hong Kong, South Korea and Germany tended to give middle of the road 2, 3 and 4 ratings, while Poland, Burkina Faso and people from Changchun in China were much more fond of 1s and 5s.

The characters they were rating were the same in all cases, remember.

Crucially, when the participants rated themselves on the same personality traits, they tended to follow the same pattern. Koreans rated themselves to have more moderate personality traits, compared to Burkinabés who described themselves in stronger tones.

Whether this is a cultural difference or a linguistic one is perhaps debatable; it might be a sign that it is not easy to translate English-language personality words into certain languages without changing how 'strong' they sound. However, either way, it's a serious problem for psychologists interested in cross-cultural studies.

I've long suspected that something like this might lie behind the very large differences in reported rates of mental illness across countries. Studies have found that about 3 times as many people in the USA report symptoms of mental illness compared to people in Spain, yet the suicide rate is almost the same, which is odd because mental illness is strongly associated with suicide.

One explanation would be that some cultures are more likely to report 'higher than normal' levels of distress, anxiety - a bit like how some make more extreme judgements of personality.

So it would be very interesting to check this by comparing the results of this paper to the international mental illness studies. Unfortunately, the countries sampled don't overlap enough to do this yet (as far as I can see).

Mõttus R, et al (2012). The Effect of Response Style on Self-Reported Conscientiousness Across 20 Countries. Personality and Social Psychology Bulletin PMID: 22745332

More Depressed Than Average?

Whether we think of ourselves as "depressed" or "anxious" depends on what we think about other people's emotional lives, rather than our own, according to an important paper just published: Am I Abnormal? Relative Rank and Social Norm Effects in Judgments of Anxiety and Depression Symptom Severity

The work appears in the obscure Journal of Behavioural Decision Making, which is downright criminal. It deserves to be in the British Journal of Psychiatry ... and it's not often I think that about a paper.

In the first experiment, the authors quizzed people how many days per month they felt “depressed, sad, blue, tearful” or had “excessive anxiety about a number of events or activities.” They then asked them a series of questions designed to work out how they thought other people would answer than question. So they could work out where each individual thought they ranked within the general population, in terms of depression or anxiety symptoms.

Take a look. The top panel shows someone who felt depressed on 5 days a month, but believed this put him in the most depressed 70% of people. The second person felt depressed twice as often, but she thought she was below average.

 

They found that perceived rank was strongly correlated with whether people thought they "had depression" or "had anxiety" - much more strongly than actual frequency of symptoms. "Having depression" meant "being more depressed than other people".

That's just a correlation and doesn't prove causation, but in the second experiment, they randomly assigned people to get different versions of a survey which manipulated perceived rank, and they confirmed that rank was indeed associated with how "disabling" they felt a given level of symptoms would be.

Now, this is just common sense, in a way. Of course whether you think of yourself as abnormal will depend on what you think of as normal - that's what "abnormal" means. We understand ourselves in the context of other people.

But this common sense is maybe not so common nowadays; you can read a hundred papers about the chemistry, genetics or causes of "depression" without a consideration of what "depression" (i.e. "abnormal" as opposed to "normal" mood) is.

The implications are big. Here's my main concern. Right now a lot of people think that promoting the idea that mental illness is very common is a good idea. Their stated goal is that by 'normalizing' mental illness, we'll destigmatize it. This will both help the mentally ill to cope, and encourage people to talk about their own mental health and get help.

All very nice. I've accused such campaigns of being based on dodgy stats, but this paper suggests that such campaigns could end up having exactly the opposite effect from that intended - they could lead to under-diagnosis, and increased stigma.

Suppose being depressed or anxious becomes seen as more 'normal'. According to these data, this will make people who are depressed or anxious less likely to seek help, for any given level of symptoms. Change people's perceptions of other people, and you'll change how they see themselves.

Worse, normalizing distress could - paradoxically - make those who do seek help seem more abnormal. Think about it: if depression and anxiety are normal, surely only an abnormal person would need special help to deal with them.

It's a small step from this to the idea that mental illness is mere personal weakness, laziness, attention-seeking, or scrounging. 'What's your problem? Everyone feels down or worried sometimes... most of us just deal with it.' If everyone is mentally ill, then no-one is really mentally ill... so the "mentally ill" must have something else wrong with them. Not very nice.

I'm not sure if this has happened, or will ever happen, but it's something to think about.

Melrose, K., Brown, G., and Wood, A. (2012). Am I Abnormal? Relative Rank and Social Norm Effects in Judgments of Anxiety and Depression Symptom Severity Journal of Behavioral Decision Making DOI: 10.1002/bdm.1754

Bigender - Boy Today, Girl Tomorrow?

An interesting report in (believe it or not) Medical Hypotheses - Alternating gender incongruity: A new neuropsychiatric syndrome providing insight into the dynamic plasticity of brain-sex.

Bigender individuals report alternating between male, female, and (sometimes) mixed gender states. Case and Ramachandran - that's V.S. Ramachandran of phantom limb fame - write:

Under the transgender umbrella, a distinct subset of "Bigender" individuals report blending or alternating gender states. It came to our attention that many (perhaps most) bigender individuals experience involuntary alternation between male and female states, or between male, female, and additional androgynous or othergendered identities ("Multigender")...

But almost no-one's studied the bigender phenomenon -

A survey of the transgender community by the San Francisco Department of Public Health found that about 3% of genetic males and 8% of genetically female transgendered individuals identified as bigender. To our knowledge, however, no scientific literature has attempted to explain or even describe bigenderism; a search of PsychInfo and PubMed databases returned zero results... the study of this condition could prove illuminating to scientific understanding of gender, body representation, and the nature of self.

No scholarly paper would be complete without some elaborate new jargon, of course -

For the purposes of our research we are calling this condition "alternating gender incongruity" (AGI). We seek to establish AGI as a nosological entity based in an understanding of dynamic brain representations of gender and sex.

So they designed a survey (details in the paper) and sent it to members of a bigender internet forum. The forum had 600 members, although many were lurkers; they got a total of 39 replies. So it's a highly self-selected sample, then, but that's inevitable I think. Here's what they had to say -

Of the 32 alternating bigender respondents included [some were excluded for diagnoses of DID etc], 11 were anatomically female (identified as female at birth)... One respondent identified as intersex, but only for reasons of androgynous facial appearance...

10/32 respondents agreed that their gender switches were "predictable." The period of gender switches was highly variable, ranging from multiple times per day to several times per year. A majority (23/32) of respondents, however, reported that their gender switched at least weekly [with 14 saying it switched at least once per day].

What are the switches like? Some respondents are quoted -

"I still have the same values and beliefs, but a change in gender is really a change in the filter through which I interact with the world and through which it interacts with me."

"My voice usually ends up being higher than other times, I’ll be more emotional, my views on things like politics tend not to change, but how I react to certain things does. Like if I’m in male mode and I see someone crying I’ll think more along the lines of, 'Man up...' while if I’m in girl mode I’ll think more along the lines of ‘Oh sweety!’"

This being Ramachandran, the paper also touches on left handedness, brain hemispheres, phantom genitals and more, but it's fair to say that all this is pretty speculative -

In myth, art, and tradition throughout the world the left side of the body (and hand) – and therefore the right hemisphere – is regarded as more "feminine" – intuitive and artistic. One wonders therefore whether gender alternation may reflect alternation of control of the two hemispheres. Such alternation is seen to a limited extent even in normal individuals but may be exaggerated (and more directly involve the gender aspect) in AGI...

Personally, what I find most interesting about this is the question of what would have happened to 'bigender' people before the term 'bigender' came along; it seems to be newer, and certainly less widely used, than 'transgender'/'transsexual'.

Would they have been identified as transgender? Maybe... but maybe not. Would they have had any label at all?

Case, L., and Ramachandran, V. (2012). Alternating gender incongruity: A new neuropsychiatric syndrome providing insight into the dynamic plasticity of brain-sex Medical Hypotheses, 78 (5), 626-631 DOI: 10.1016/j.mehy.2012.01.041

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

Take Your Placebos, Or Die

People who take their medication as directed are less likely to die - even when that "medication" is just a sugar pill.

This is the surprising finding of a paper just published, Adherence to placebo and mortality in the Beta Blocker Evaluation of Survival Trial (BEST). 

BEST was a clinical trial of beta blockers, drugs used in certain kinds of heart disease. The patients were aged about 60 and they all suffered from heart failure. Everyone was randomly assigned to get a beta blocker or placebo, then followed up for 3 years to see how they did.

Here's the big finding: in the placebo group of 1174 patients, the people who took all of their placebo pills on time (the good adherers), were significantly less likely to die than the patients who missed lots of doses. People who took over 75% as directed were 40% less likely to die than those with less than 75% adherence:

That's pretty interesting. The pills were placebos - they can't have had any benefit. So what's going on?

It gets even better. You might be tempted to write off these results as obvious: "Clearly, people who follow the study instructions are just 'healthy' people in other ways - maybe they take more exercise, eat better, etc. and that's what protects them."

Certainly, that's what I'd have said.

But what's remarkable is that when the authors corrected the statistics for all the confounding variables they measured - including things like age, gender, ethnicity, smoking, body mass index and blood pressure - it barely changed the effect. Some of the factors did correlate with adherence, but not in a way that it could explain the adherence effect on mortality.

This isn't the first study to find this effect. The authors themselves have already reported it, as have other researchers going back decades (many of which also tried, and failed, to explain it through confounding factors.) They say that it's unlikely to be a case of publication bias.

So what we have is a large effect, which cannot be causal, yet which can't be explained by any obvious confounds. Logically then, it must be the result of a confound (or more than one) that aren't obvious.

This is an important lesson. It's common for someone to do a study and find an interesting / scary / controversial correlation between two things. Often one is some kind of lifestyle factor, diet, environmental exposure, or whatever, and the other is some nasty disease. "And it wasn't explained by confounds!", such studies often conclude.

What the placebo adherence effect demonstrates is that there may be confounds no-one has thought of. They might even be impossible to measure. And if these mystery confounds can literally kill you, they can probably cause all kinds of other effects too.

In other words this illustrates the truism that correlation is not causation - not even when you're really sure it is...

Pressman, A., Avins, A., Neuhaus, J., Ackerson, L., and Rudd, P. (2012). Adherence to placebo and mortality in the Beta Blocker Evaluation of Survival Trial (BEST) Contemporary Clinical Trials DOI: 10.1016/j.cct.2011.12.003

Men and Women - Alien Personalities?

How different are men and women? Are they from two different planets?

In the cleverly-titled The Distance Between Mars and Venus, the authors argue that personality-wise, the differences between men and women have been underestimated by previous studies because they used simplistic statistics.

Traditional studies of gender and personality have given some men and some women a personality quiz, and calculated the average male and female scores on the different aspects of personality.

When you do this you find that there are differences, but that the standardized effect sizes are fairly small, which means that there is a lot of overlap. Even on measures where men score above women on average, lots of men score below the female average, and vice versa, like this:

Traditional studies of overall gender differences have looked to see the differences between the average man and woman on each personality aspect, and then averaged the differences on each scale to get an "overall difference" score. Which comes out as fairly small.

The authors of the new paper say that this approach fails to capture the true difference and they give a helpful analogy of why:

Consider two fictional towns, Lowtown and Hightown. The distance between the two towns can be measured on three (orthogonal) dimensions: longitude, latitude, and altitude. Hightown is 3,000 feet higher than Lowtown, and they are located 3 miles apart in the north-south direction and 3 miles apart east-west.

What is the overall distance between Hightown and Lowtown? The average of the three measures is 2.2 miles, but it is easy to see that this is the wrong answer. The actual distance is the Euclidean distance, i.e. 4.3 miles – almost twice the "average" value.

The main novel argument of this paper is that if you calculate the distance (technically the Mahalanobis distance) in 'personality space' between men and women then you get a larger value than if you just average the differences on each measure.

The paper also uses a couple of other methods that increase the effect sizes, namely using 15 different personality measures instead of the more common Big 5, and adjusting the differences upwards to take account of the fact that quizzes only imperfectly measure underlying 'latent' personality traits.

I don't want to get into the debate over how valid the underlying data are (a 1993 sample of over 10,000 American adults, used to standardize the 16PF questionnaire). There are lots of technical comments here. I'm going to focus on the distance method.

It's a very interesting approach and certainly raises questions about merits of the old approach, which when you think about it, does seem a bit crude. But I'm not sure that the average person is talking about distance in a hypothetical space when they talk about "personality differences".

As an analogy, consider the dog breeds Labrador and Golden Retriever. These are regarded as being pretty similar kinds of dog. On any given feature, the average differences are small, at least compared to the diversity of other breeds. They're roughly the same size, much the same build, coat type etc.

They are distinct breeds. This surely means that when you take all of the differences together, they define distinct regions of "dog space" (which has dozens or hundreds of dimensions), with little or no overlap.

Yet they are still regarded as similar. "Similar" and "distinct" are not mutually exclusive. In fact, isn't the definition of 'distinct yet similar' that two things separate in some kind of feature-space, but don't differ much on any one measure?

So I would say that these data show that, while men and women may be distinguishable in personality, they could still be similar. This is something of a semantic point but not "merely" semantic: it changes the interpretation of the numbers.

J. S. Hyde, who is most associated with the view that gender differences are small, makes a similar (or do I mean distinct?) point in her comment on the paper:

The gender difference found is along a dimension in multivariate space that is a linear combination of the original variables transformed into latent variables...[but] the resulting dimension here is uninterpretible. What does it mean to say that there are large gender differences on this undefined dimension in 15-dimensional space created from latent variables? The authors call it global personality, but what does that mean?

Her questioning of what the direction along which men and women differ means, is (I think) the same question I'm asking about whether it disproves the idea of "similarity", in the ordinary sense of the term.

Finally, take a step back and the whole debate seems a bit circular because, by definition, "personality" means "things that differ between individual people". Things we are have in common aren't even in the picture. Two groups could differ in personality space but still be very close in the much larger space of "possible creatures". There's no personality trait for 'being human'.

Del Giudice, M., Booth, T., and Irwing, P. (2012). The Distance Between Mars and Venus: Measuring Global Sex Differences in Personality PLoS ONE, 7 (1) DOI: 10.1371/journal.pone.0029265

One in Four Revisited

In a recent Telegraph article, professional contrarian Brendan O'Neill argues against the idea that one in four people experience mental illness - and indeed against the idea that one in four people are bullied, abused or whatever else:

Can it really be true that a quarter of Brits are bullied or beaten up at home or are mentally ill, or is this simply a case of social campaigners exaggerating how bad life is in order that they can continue to make headlines, make an impact, and get funding? I reckon it's the latter. Next time you see the "one in four" figure, be very sceptical – it's probably Dickensian-style doom-mongering disguised as social research, where the aim is to convince us, against the evidence of our own eyes and ears, that loads of the people we encounter everyday are basket cases in need of rescue.

I say "argues against", but he doesn't actually provide any arguments. He just links to the claims and says they're silly.

As Neuroskeptic readers know, I am myself skeptical of the idea that one in four people are mentally ill, but I'm skeptical of it because I've looked at the evidence and it doesn't support that figure. Actually, if you take the available evidence at face value, it says that the true figure for the lifetime prevalence is much higher than one in four. I don't think those figures are very useful however because of various methodological issues.

So in my view we just don't know how many people are mentally ill, largely because we don't have any clear definition of what "mentally ill" means. But that doesn't mean we can just assume that it can't possibly be one in four just because "our own eyes and ears" tell us that most people are not "basket cases".

Much mental illness goes undiagnosed and unnoticed, and I'd imagine also that Brendan O'Neill and the kind of people who read him don't tend to "encounter everyday" people from groups such as the unemployed, the elderly and so forth, in whom the rates are higher.

But even beyond that, it's a silly argument because of selection bias. If you as a healthy person encounter someone everyday, chances are they're not severely ill - mentally or physically - because if they were, they'd be less likely to be around in places for you to encounter. Unless you're a doctor or whatever, you live your life in the world of healthy people.

It's like saying that you don't believe children or the elderly exist, because in your life as a working age adult, you never meet any of them.

Antipsychotics - The New Valium?

Antipsychotics, originally designed to control the hallucinations and delusions seen in schizophrenia, have been expanding their domain in recent years.

Nowadays, they're widely used in bipolar disorder, depression, and as a new paper reveals, increasingly in anxiety disorders as well.

The authors, Comer et al, looked at the NAMCS survey, which provides yearly data on the use of medications in visits to office-based doctors across the USA.

Back in 1996, just 10% of visits in which an anxiety disorder was diagnosed ended in a prescription for an antipsychotic. By 2007 it was over 20%. No atypical is licensed for use in anxiety disorders in the USA, so all of these prescriptions are off-label.

Not all of these prescriptions will have been for anxiety. They may have been prescribed to treat psychosis, in people who also happened to be anxious. However, the increase was accounted for by the rise in non-psychotic patients, and there was a rise in the rate of people with only anxiety disorders.

The increase was driven by the newer, "atypical" antipsychotics.

Whether the modern trend for prescribing antipsychotics for anxiety is a good or a bad thing, is not for us to say. The authors discuss various concerns ranging from the side effects (obesity, diabetes and more), to the fact that there have only been a few clinical trials of these drugs in anxiety.

But what's really disturbing about these results, to me, is how fast the change happened. Between 2000 and 2004, use doubled from 10% to 20% of anxiety visits. That's an astonishingly fast change in medical practice.

Why? It wasn't because that period saw the publication of a load of large, well-designed clinical trials demonstrating that these drugs work wonders in anxiety disorders. It didn't.

But as Comer et al put it:

An increasing number of office-based psychiatrists are specializing in pharmacotherapy to the exclusion of psychotherapy. Limitations in the availability of psychosocial interventions may place heavy clinical demands on the pharmacological dimensions of mental health care for anxiety disorder patients.

In other words, antipsychotics may have become popular because they're the treatment for people who can't afford anything better.

These data show that antipsychotics were over twice as likely to be prescribed to African American patients; the poor i.e. patients with public health insurance; and children under 18.

Comer JS, Mojtabai R, & Olfson M (2011). National Trends in the Antipsychotic Treatment of Psychiatric Outpatients With Anxiety Disorders. The American journal of psychiatry PMID: 21799067

Britain's Not Getting More Mentally Ill

There's a widespread belief that mental illness is getting more common, or that it has got more common in recent years.

A new study in the British Journal of Psychiatry says: no, it's not. They looked at the UK APMS mental health surveys, which were done in 1993, 2000 and 2007. Long-time readers will remember these.

The authors of the new paper analyzed the data by birth cohort, i.e. when you were born, and by age at the time of the survey. If mental illness were rising, you'd predict that people born more recently would have higher rates of mental illness at any given age.

The headline finding: there was no cohort effect, implying that rates of mental illness aren't changing. There was a strong age effect: in men, rates peak at about age 50; in women the data is rather messy but in general the rate is flat up to age 50 and then it falls off, like in men. But there's no evidence that those born recently are at higher risk.

The only exception was that men born after 1950 were at somewhat higher risk than those born earlier as shown by the "break" on the graph above. The effect for women was smaller. The most recent cohort, those born after 1985, were also above the curve but there was only one datapoint there, so it's hard to interpret.

We also get a rather cute graph showing how life changes with age:

As you get older, you get less irritable and, if you're a woman, you'll worry less. But sleep problems and, in men, fatigue, increase. Overall, 50 is the worst age in terms of total symptoms. After that, it gets better. Well, that's nice to know. Or not, depending on your age.

Overall, the authors say:

Our finding of subsequently stable rates contradicts popular media stories of a relentlessly rising tide of mental illness, at least for men. Stable prevalence in the male population, together with peaking of the prevalence of common mental disorder at about age 50 years, indicates that a large increase in projected rates of poor mental health is unlikely in the male population in the near future....

Trends in women are less clearly identified, with considerable increases in the prevalence of sleep problems, but no clear increase or even some decrease in other measures. Further research is needed to relate these age and cohort differences to drivers of mental health such as employment status and family composition.

Caution's warranted, though, because the APMS data were based on self-reported symptoms of mental illness assessed by lay interviewers. As I've argued before, self-report is problematic, but this is true of almost all of these kinds of studies.

More unusual is that this study didn't attempt to assign formal diagnoses, it just looked at total symptoms on the CIS Scale; a total of 12 or more was considered to indicate "probable disorder".

Purists would say that this is a weakness and that you ought to be making full DSM-IV diagnoses, but honestly, it's got its own problems, and I think this is no worse.

Finally, this study only looked at "common mental disorders" i.e. depression and various kinds of anxiety symptoms. Things like schizophrenia and bipolar disorder weren't included, but from what I remember they're not rising either.

Spiers N, Bebbington P, McManus S, Brugha TS, Jenkins R, & Meltzer H (2011). Age and birth cohort differences in the prevalence of common mental disorder in England: National Psychiatric Morbidity Surveys 1993-2007. The British journal of psychiatry : the journal of mental science, 198, 479-84 PMID: 21628710

The Media and Numbers: "It's Complicated".

According to everyone in the British media, 25% of young men are worried about the amount of porn they watch online and men watch an average of 2 hours per week.


Says who? The BBC apparently "teamed up with doctors from the Portman Clinic", a London specialist mental health hospital, to do the study. The actual survey was done online by a certain market research company, which I am not going to name, because they've already got free advertising in every newspaper.

What does this tell us about pornography? Nothing. Dr Petra Boynton explains why in a long and excellent deconstruction. In order to properly interpret these results, we'd need to know lots of details about the study design, which we weren't told. Of course this doesn't stop us from going ahead and interpreting them improperly. 25%! 2 hours. Ooh, that's a lot. Is it? This online porn, eh. Tut tut.

So, sure, 25% could be The True Proportion Of Men Who Worry About Online Porn. Or it might not be. Or the whole question might be so fraught as to be meaningless. The point is, we don't know, we cannot possibly know from the limited amount of information we were given, and we weren't meant to know, because numbers like these are essentially pornographic themselves - they're just for show.

Numbers very rarely make a good news story. When you look into it, the vast majority of them only make sense to people who know all of the background, and by definition, if you have to spend a few pages explaining the background, it's not a good news story. A good news story is one which anyone who can read can immediately understand, and get angry/scared/amused by.

Yet journalists also love numbers because everyone knows, on some level, that numbers matter. The very fact that a story has numbers in it, makes that story better. Indeed, very often, there would be no story without them. Someone doing a survey and finding some numbers can make a news story out of nothing. "Modern online pornography worries some people and is a complicated issue" isn't news; "25% of men..." is news.

So what we end up with is lots of news stories which have numbers in them, but which don't, actually, tell us anything about the world, which is what numbers are supposed to do. Numbers to most of the media are like an attractive trophy wife. They like to be seen with them in public. But deep down they're not all that attached.

Who Gets Autism?

According to a major new report from Australia, social and family factors associated with autism are associated with a lower risk of intellectual disability - and vice versa. But why?


The paper is from Leonard et al and it's published in PLoS ONE, so it's open access if you want to take a peek. The authors used a database system in the state of Western Australia which allowed them to find out what happened to all of the babies born between 1984 and 1999 who were still alive as of 2005. There were 400,000 of them.

The records included information on children diagnosed with either an autism spectrum disorder (ASD), intellectual disability aka mental retardation (ID), or both. They decided to only look at singleton births i.e. not twins or triplets.

In total, 1,179 of the kids had a diagnosis of ASD. That's 0.3% or about 1 in 350, much lower than more recent estimates, but these more recent studies used very different methods. Just over 60% of these also had ID, which corresponds well to previous estimates.

There were about 4,500 cases of ID without ASD in the sample, a rate of just over 1%; the great majority of these (90%) had mild-to-moderate ID. They excluded an additional 800 kids with ID associated with a "known biomedical condition" like Down's Syndrome.

So what did they find? Well, a whole bunch, and it's all interesting. Bullet point time.

• Between 1984 to 1999, rates of ID without ASD fell and rates of ASD rose, although there was a curious sudden fall in the rates of ASD without ID just before the end of the study. In 1984, "mild-moderate ID" without autism was by far the most common diagnosis, with 10 times the rate of anything else. By 1999, it was exactly level with ASD+ID, and ASD without ID was close behind. Here's the graph; note the logarithmic scale:
  

• Boys had a much higher rate of autism than girls, especially when it came to autism without ID. This has been known for a long time.
  
• Second- and third- born children had a higher rate of ID, and a lower rate of ASD, compared to firstborns.
  
• Older mothers had children with more autism - both autism with and without ID, but the trend was bigger for autism with ID. But they had less ID. For fathers, the trend was the same and the effect was even bigger. Older parents are more likely to have autistic children but less likely to have kids with ID.
  

• Richer parents had a strongly reduced liklihood of ID. Rates of ASD with ID were completely flat, but rates of ASD without ID were raised in the richer groups, though it was not linear (the middle groups were highest. - and effect was small.)
  

To summarize: the risk factors for autism were in most cases the exact opposite of those for ID. The more “advantaged” parental traits like being richer, and being older, were associated with more autism, but less ID. And as time went on, diagnosed rates of ASD rose while rates of ID fell (though only slightly for severe ID).

Why is this? The simplest explanation would be that there are many children out there for whom it's not easy to determine whether they have ASD or ID. Which diagnosis any such child gets would then depend on cultural and sociological factors - broadly speaking, whether clinicians are willing to give (and parents willing to accept) one or the other.

The authors note that autism has become a less stigmatized condition in Australia recently. Nowdays, they say, a diagnosis of ASD may be preferable to a diagnosis of "just" "plain old" ID, in terms of access to financial support amongst other things. However, it is also harder to get a diagnosis of ASD, as it requires you to go through a more extensive and complex series of assessments.

Clearly some parents will be better able to achieve this than others. In other countries, like South Korea, autism is still one of the most stigmatized conditions of childhood, and we'd expect that there, the trend would be reversed.

The authors also note the theory that autism rates are rising because of some kind of environmental toxin causing brain damage, like mercury or vaccinations. However, as they point out, this would probably cause more of all neurological/behavioural disorders, including ID; at the least it wouldn't reduce the rates of any.

These data clearly show that rates of ID fell almost exactly in parallel with rates of ASD rising, in Western Australia over this 15 year period. What will the vaccine-vexed folks over at Age of Autism make of this study, one wonders?

Leonard H, Glasson E, Nassar N, Whitehouse A, Bebbington A, Bourke J, Jacoby P, Dixon G, Malacova E, Bower C, & Stanley F (2011). Autism and intellectual disability are differentially related to sociodemographic background at birth. PloS one, 6 (3) PMID: 21479223