Posts filed under Risk (222)

The Herald said, on Friday “Fewer workers stoned on the job”

Information from the New Zealand Drug Detection Agency showed 81,410 on-site drug-screening tests were carried out last year, 16 per cent up from the previous year.

But only 5.5 per cent of tests showed the presence of drugs, down from 6.4 per cent in 2013

As usual, there’s no mention of the fact that NZDDA is just one of the private companies offering drug testing services. It took me a long time to realise this, until I was tipped off by a news story advertising one of their competitors.

Presumably NZDDA don’t think their customers choose them at random, and with no real reason for wanting testing. If customers were behaving even a little rationally you’d expect an expansion of drug testing to pull in lower-risk employees. If we look at the actual number of positive tests, using the quoted figures, it was about 4480 last year and about 4490 in the previous year. Given no change in the number of positive tests and a 1 percentage point change in the proportion of positive tests, from a single company, there’s not a lot of numerical evidence for an increase in number of workers with detectable cannabis in their systems.

More importantly, there’s no evidence whatsoever for the ‘stoned on the job’ headline: absolutely no information is given about this. One of the big problems with cannabis testing is that there is no useful biochemical assay for being stoned. Detectable levels persist long after impairment is over, and even when you’re actually stoned there is not a good relationship between drug concentration and impairment.  This is a real problem for Washington and Colorado, which have legalised cannabis and need to set driving laws. In contrast to alcohol, if you actually care about safe driving and cannabis, it’s really hard to get a useful and objective test.

The story ends with two examples of disasters. In one, cannabis was definitely ruled out as a contributing factor; in the other, the conclusion was only that “it could not be excluded”. The NZDDA  press release is at Scoop, and despite how the story reads, there is surprisingly little text in common.

From a mostly left-wing (ie, NZ middle-of-the-road) group of US civil-rights organisations, but at least some of it will also appeal to libertarians. If you think this sort of thing is interesting/important a good place to find more is mathbabe.org.

Technological progress should bring greater safety, economic opportunity, and convenience to everyone. And the collection of new types of data is essential for documenting persistent inequality and discrimination. At the same time, as new technologies allow companies and government to gain greater insight into our lives, it is vitally important that these technologies be designed and used in ways that respect the values of equal opportunity and equal justice. We aim to:

1. Stop High-Tech Profiling. New surveillance tools and data gathering techniques that can assemble detailed information about any person or group create a heightened risk of profiling and discrimination. Clear limitations and robust audit mechanisms are necessary to make sure that if these tools are used it is in a responsible and equitable way.
2. Ensure Fairness in Automated Decisions. Computerized decisionmaking in areas such as employment, health, education, and lending must be judged by its impact on real people, must operate fairly for all communities, and in particular must protect the interests of those that are disadvantaged or that have historically been the subject of discrimination. Systems that are blind to the preexisting disparities faced by such communities can easily reach decisions that reinforce existing inequities. Independent review and other remedies may be necessary to assure that a system works fairly.
3. Preserve Constitutional Principles. Search warrants and other independent oversight of law enforcement are particularly important for communities of color and for religious and ethnic minorities, who often face disproportionate scrutiny. Government databases must not be allowed to undermine core legal protections, including those of privacy and freedom of association.
4. Enhance Individual Control of Personal Information. Personal information that is known to a corporation — such as the moment-to-moment record of a person’s movements or communications — can easily be used by companies and the government against vulnerable populations, including women, the formerly incarcerated, immigrants, religious minorities, the LGBT community, and young people. Individuals should have meaningful, flexible control over how a corporation gathers data from them, and how it uses and shares that data. Non-public information should not be disclosed to the government without judicial process.
5. Protect People from Inaccurate Data. Government and corporate databases must allow everyone — including the urban and rural poor, people with disabilities, seniors, and people who lack access to the Internet — to appropriately ensure the accuracy of personal information that is used to make important decisions about them. This requires disclosure of the underlying data, and the right to correct it when inaccurate.

As an example, consider this Chicago crime risk profiling system. Is it worrying? If so, why; if not, why not?

From a randomised trial of four different sets of information about vaccine benefits (via Brendan Nyhan)

Parents were randomly assigned to receive 1 of 4 interventions: (1) information explaining the lack of evidence that MMR causes autism from the Centers for Disease Control and Prevention; (2) textual information about the dangers of the diseases prevented by MMR from the Vaccine Information Statement; (3) images of children who have diseases prevented by the MMR vaccine; (4) a dramatic narrative about an infant who almost died of measles from a Centers for Disease Control and Prevention fact sheet; or to a control group.

In particular, intervention 4 is a popular and sensible idea, and it has occurred to people from Benjamin Franklin to Kiwi parents and the Herald. However:

RESULTS: None of the interventions increased parental intent to vaccinate a future child. Refuting claims of an MMR/autism link successfully reduced misperceptions that vaccines cause autism but nonetheless decreased intent to vaccinate among parents who had the least favorable vaccine attitudes. In addition, images of sick children increased expressed belief in a vaccine/autism link and a dramatic narrative about an infant in danger increased self-reported belief in serious vaccine side effects.

This research is depressing from the point of view of science communication. The problem is that the message goes in two apparently opposite ways.  One conclusion is that increasing trust in science and medicine is the only solution, which would require more public contact and communication, and openness about uncertainty.  The other conclusion is that a public health advertising campaign is a treatment, and like any other treatment it should be evaluated for safety and effectiveness before it’s applied to the population, an approach that seems to imply a reduction in open and unfiltered communication.

I don’t think the contradiction is unavoidable; I think more communication about research process — who are we and what do we actually do — will help, but also that advertising, whether government-funded or pushed by PR departments, is actually dangerous.  If we overstate claims about the biochemical effects of compounds in chocolate, or the number of deaths prevented by lowering the blood alcohol limit, why should we be trusted on important issues?

This is what it looks like when a country does manipulate its official statistics (from Ezequiel Tortorolli, via Tom Pepinsky and Xavier Marquez).

The black line is Argentina’s official federal inflation rate. The red line is the average of the rates for the 18 provinces, which are the fainter wiggly lines.

[Update: Argentina has just announced a new inflation index that’s supposed to be non-bogus. It will take a while to convince people.]

Two headlines a month apart on the BBC news website, one of the world’s most respected sources for serious news

The older one, “Schizophrenia: talking therapy offers ‘little benefit’” is based on a summary of 50 randomised trials.

The newer one, “Schizophrenia: Talking therapies `effective as drugs‘”, is based on a report from a pilot study of 74 people that compared cognitive behavioural therapy to no treatment, not to drugs.  It doesn’t mention the earlier story.

Ezra Klein, who’s one of the United States’ top political and economic journalists, has just left the Washington Post to start a new web-based publication.  He writes

New information is not always — and perhaps not even usually — the most important information for understanding a topic. The overriding focus on the new made sense when the dominant technology was newsprint: limited space forces hard choices. You can’t print a newspaper telling readers everything they need to know about the world, day after day. But you can print a newspaper telling them what they need to know about what happened on Monday. The constraint of newness was crucial.

The web has no such limits. There’s space to tell people both what happened today and what happened that led to today.

For health and science stories there should be room for less newness and more context even on paper, since only a tiny minority of the most interesting stories are covered. But even if you can’t explain why today’s headline is different, you can at least notice that it’s the opposite of what you said a month ago.

[update: I lost the credit to Dean Rutland and Ben Goldacre for the picture in editing. My apologies to them.]

The Herald has a headline “Dry January may not have been as good for your health as you thought“, and lead

For many people, the beginning of February marks the end of a month of abstinence from their favourite tipple.

But as we bid a perhaps too enthusiastic farewell to Dry January, one expert is saying that last month’s good intentions may have done more harm than good.

Now, ‘Dry January’ almost certainly has done no real harm or good to readers of the Herald, since it’s a UK thing, and it would be quite hard for British alcohol consumption to have much impact on NZ health.  The story, amazingly, hasn’t even been edited to mention the NZ analog, FebFast, which has just started on Saturday.

With that out of the way, the point of the story is that moderate levels of alcohol consumption are probably beneficial to health, and so giving up alcohol for a month does more harm than good. While it’s nice to see the J-curve acknowledged in the media, it’s unlikely to apply here. If you have any real reason to join the ‘Dry January’ campaign, you’re probably drinking enough to be on the unhealthy side of the curve (like many people in NZ), and the health risks go up fairly fast with increased consumption.  If giving up alcohol for a month does you any good, except in the wallet, it’s likely to do quite a bit more good than harm. It’s true that drinking moderately without a month off would be even better, but that’s not the intervention at issue.

It’s also worth noting that the benefits claimed for beer in the story include its silicon content. That’s a fairly reliable sign of desperation in nutrition claims; it’s not clear that anyone has ever been short of silicon.

The Herald reports on a nice comparison of Accident Compensation Commission claims rates for cycling and other activities. Michael Chieng, an Auckland medical student, found that the risk of a ACC claim was 35 times higher per rugby game than per two hour cycle ride, with cycling also safer than skiing and horseriding.  The health benefits of cycling are almost certainly greater than the risks, which is why helmet laws aren’t very good public health interventions.

It’s still a bit unfortunate that cycling was compared only to recreational activities, not to other ways of getting from point A to point B. I’m pretty sure that it’s less safe than walking or riding a bus. Also, unlike rugby and skiing, cycling in New Zealand is a lot more dangerous than it should be.

Sadly, I do have to point out, yet again, that there is not only no link to the research, there doesn’t even seem to be a source to link to.

That is, how to gamble in a way that over a course of a year, gives you a higher chance at a larger payout than playing NZ Lotto each week and hoping for Division 1. We all know you can’t “beat Lotto” in the usual sense of improving your odds of winning.

In the ordinary Saturday Lotto, you pick 6 numbers out of 40, and if all 6 are correct (which they aren’t) you win $1 million. The chance of winning is 1 in 3838380 per ‘line’. Suppose you play the minimum of 4 lines, for $6, each week for a year. The chance of winning in a year is one in 18453.75. That is, on average you’d expect to win once in every 18453 years and 9 months.

Alternatively, suppose you save up the $6 per week, and then at the end of the year go to a casino and play roulette.  Put it all on a single number.  If you win, put it all on a single number again, and then if you win,  put it all on a ‘double street’ of six numbers.  Your chance of winning (in double-zero roulette) is 1 in 9145.33, and if you win you will make $2426112.

So, you get twice the chance of winning as you would have for Lotto division 1, and more than twice the payout. The expected return is 85%, much better than the 56% that NZ Lotteries returns (averaged over all its games, annual report).  Does that mean it’s a good idea? No. Not even slightly.  You have a 37 in 38 chance of turning up with $300 and losing it in a few minutes. If you don’t, you have a 37 in 38 chance of losing $7500 in the next few minutes, and if you don’t, you have about an 85% chance of losing more than quarter of a million dollars.   This strategy makes your losses obvious, which makes gambling no fun. And you still only win once every 91 centuries.

Enjoyable gambling, including Lotto, is based on making your losses less obvious by masking them with small wins and stretching them out over time. Of course, that’s also what makes gambling, including Lotto, potentially addictive.

A maths-free article on data mining and surveillance, from the New York Review of Books

Using techniques ranging from supermarket loyalty cards to targeted advertising on Facebook, private companies systematically collect very personal information, from who you are, to what you do, to what you buy. Data about your online and offline behavior are combined, analyzed, and sold to marketers, corporations, governments, and even criminals. The scope of this collection, aggregation, and brokering of information is similar to, if not larger than, that of theNSA, yet it is almost entirely unregulated and many of the activities of data-mining and digital marketing firms are not publicly known at all.

The Sydney Morning Herald has a story on the impact of plain packaging for cigarettes in Australia.  Cancer researchers in Sydney found a big spike in calls to Quitline after the packaging change, and interpreted this as evidence it was working

The researchers said although the volume of calls to Quitline was an ”indirect” measure of people’s quitting intentions and behaviour, it was more objective than community surveys where people can answer questions in a socially desirable and biased way.

On the other side, tobacco companies say there hasn’t been any actual fall in smoking.

”In November 2013, a study by London Economics found that since the introduction of plain packaging in Australia there has been no change in smoking prevalence … What matters is whether fewer people are smoking as a result of these policies – and the data is clear that overall tobacco consumption and smoking prevalence has not gone down,” he said.

In this setting you might reasonably be concerned that either side is putting their results in fancy packaging. So what should you believe?

In fact, the claims are consistent with each other and don’t say much either way about the success of the program.  If you look at the research paper, they found an increase peaking at about 300 calls per week and then falling off by about 14% per week. That works out to be a total of roughly 2000 extra calls attributed to the packaging change, ie, just over half a percent of all smokers in Australia, or perhaps a 10% increase in the annual Quitline volume. If the number of people actively trying to quit by methods other than Quitline also goes up by 10%, you still wouldn’t expect to see much impact on total tobacco sales after one year.

The main selling point for the plain packaging (eg) was that it would prevent young people from starting to smoke. That’s what really needs to be evaluated, and it’s probably too early to tell.

[Update: Of course, other countries that were independently considering changing their policies shouldn’t wait for years just because Australia started first. That would be silly.]

[Update: the Quitline data are just for NSW; so perhaps 1.5% of smokers]