Cost Effectiveness of Mindfulness Based Stress Reduction

The Problem

The WHO estimates that depression and anxiety together account for 75,000,000 DALYs annually, making up ~5% of total DALYs. In “Measuring the Impact of Mental Illness on Quality of Life”, I argue that there is good reason to think that the system used to generate these estimates severely underestimates the impact of mental illness, and thus the true damage may be much higher. To try to get an estimate on the harms of mental health and the benefits of alieviating mental health problems, I did a preliminary cost-effectiveness analysis of Mindfulness Based Stress Reduction (MBSR).

The Intervention

MBSR is an eight week class that uses a combination of mindfulness, body awareness, and yoga to improve quality of life and perhaps physical health for a variety of conditions.

MBSR was created by Jon Kabat-Zinn at the University of Massachusetts in the 1970s, but has spread widely since then. The exact extent of this spread is hard to measure because no official registration is required to teach mindfulness and many classes and books claim to be mindfulness inspired. For the purpose of this evaluation I looked only at things that were officially MBSR or adhered very closely to the description.

Cost of MBSR

Herman, et al. (2017) estimated the marginal cost of an MBSR class participant at $150. The first three hits on google (run in an incognito browser but suspiciously near the location from which I ran the search) for MBSR listed a cost of $395-$595, $275-$425, and $350. The difference between the top of the range and the marginal cost indicates that the high end of that range probably covers all of the costs involved with MBSR (space rental and instructor time for eight weeks of classes plus one eight hour retreat) and then some, so I will use $600 as the ceiling on costs and $150 as the floor.

MBSR has an unusually high time ongoing cost (one hour per day). To model this, I included a range of DALYs as a cost, ranging from 0 (indicating no cost) to 1/24 (as if the participant were dead for that hour). It is unclear how the one hour duration was chosen and I could not find any studies on the comparative impact of different lengths of meditation; it’s quite plausible one could get the same results in less time. For the purpose of this document I used the official program, because it was the most consistently studied.

Cost Effectiveness Analysis of MBSR

Both depression and anxiety are measured with a variety of clinical surveys. To estimate impact, I assumed that the top score on each survey caused a DALY loss equal to severe depression/anxiety, as estimated by the World Health Organization, and that a drop of N percentage points led to a drop of disability weight * N. For example, a drop of 8 points on an 80 point scale of anxiety (disability weight of severe anxiety: 0.523) causes a gain of .0523 DALYs.

For a survey of papers showing potential impact, see this spreadsheet. The estimates range from 2% to 11%, clustered around 7%.

I have created a Guesstimate model to estimate the impact of MBSR. Results were quite promising. On a randomly selected guesstimate run, the average cost was $290/DALY, with a range from $43/DALY to $930/DALY. This is close to but better than Strong Mind’s $650/DALY and overlaps with estimates of antimalarial treatment ($8.15-$150/DALY). Note that the MBSR estimate may understate the impact due to systemic biases in how DALYs are calculated. However it may also overstate the impact, as medical studies tend to overstate intervention impacts for a variety of reasons.

The model makes no attempt to account for co-morbid disorders. Individuals with depression and anxiety would likely see higher benefits, since the same hour of meditation would impact both.

Caveats

All of the effectiveness studies cited were done on developed world citizens with only mild to moderate mental illnesses. Most were middle aged, and access to MBSR implies a minimum SES bar. It is possible that more severe depression is not amenable to MBSR, or that it is amenable and shows a larger absolute change because there is farther to improve.

I could find no studies on MBSR in the developing world, although since mindfulness meditation was originally created before there was such a thing as the developed world, there is a higher than typical chance that its usefulness will survive cultural translation.

All of the studies referenced had small sample sizes. They all show a consistent effect, but it’s possible publication bias is keeping negative studies out of view.

Official MBSR has an unusually high time cost compared to medication and therapy. The costs are high both upfront (eight weeks of classes and an all day retreat) and ongoing (one hour of meditation/day). Some patients may be able to get the benefits of MBSR with less time; others may not be able to practice at all due to the time demands.

 

For more on this see my shallow review of mental health .

Measuring the Impact of Mental Illness on Quality of Life

Introduction

I am currently evaluating multiple interventions aimed at mental illness. In order to compare these to each other and interventions in other areas, it is important to make an estimate of severity of the problem and of the impact of interventions. Several standard systems for evaluating health interventions exist, each of which has strengths and weaknesses. How accurate/useful are these systems for mental illness?

Death Rate

Mental illness has a death toll (primarily from suicide and overdoses) that can be compared to deaths from physical ailments. Death has the advantage of being a binary state subject to very little measurement error or differing definitions across culture. However it is an imperfect proxy for suffering inflicted by mental illness. Depending on culture one country may have a higher depression rate but lower suicide rate. A country with better medical services may have a worse drug problem but fewer deaths from overdoses. Cause of death is subject to manipulation. Mortality is also a very poor measure of anxiety, since anxiety is almost never the immediate cause of death (although it may shorten lifespan).

Disability Adjusted Life Years

Disability adjusted life years (DALYs) are an attempt to use a single number to express the health of a population. The calculation method can vary from study to study; for purposes of this post I will be referring only to the methods used in the Global Burden of Disease 2010 (hereafter GBD 2010) study.

Aggregated DALYs for a population are calculated by multiplying the [disability prevalence] x [disability weight] x [years until remission or death]. Some surveys (but not all) include further discounts for age, assuming that a year lived as a 70 year old is less valuable than a year lived as a 25 year old. This is known as age-weighting. Disability weight is calculated by asking individuals to compare two scenarios and rate which person seems “healthier.” GBD 2010 surveyed approximately 14,000 individuals from five countries (Bangladesh, Indonesia, Peru, the United Republic of Tanzania and the United States of America) and offered a web based survey as well, which was eventually taken by approximately 16,000 people. Previous versions of the GBD exclusively used the evaluations of health care practitioners.

Because they are only are a measure of health, DALYs are not a good measure of suffering. For example, a loved one dying is an obvious cause of suffering via grief, but has no impact on the DALY metric of the survivors. DALYs also deliberately exclude the availability of mitigations: vision impairment has the same DALY cost regardless of the availability of corrective lenses (Voight & King, 2010). These choices make DALYs highly legible and comparable, at the cost of excluding many things one might care about. Additionally, “Healthy” is a highly ambiguous term, which many cultures consider to refer only to physical health. This suggests that if one cares about suffering, or includes mental health in their definition of health, DALYs are likely to severely underrate the impact of mental illness.
Quality Adjusted Life Years

QALYs are explicitly designed to evaluate quality of life, not just health. Instead of choosing which of two individuals is healthier, survey participants may choose which situation they would rather live in (e.g., five years of blindness or four years of deafness), what risk of death they would accept in order to cure an ailment (e.g. 10% risk of death for surgery to restore function to your leg), or “how bad does this sound to you on a scale of 1-100?”

QALYs are noticeably better than DALYs for measuring the impact of mental illness, in that everyone agrees mental illnesses lower quality of life. However there is still concern that they underestimate the impact because people are bad at imagining themselves in different situations, and bad at imagining mental illness in particular. Dolan (2008) argues that any rating based on trade-offs is inherently weak, because humans are so bad at remembering the past and anticipating the future. He favors using ratings of subjective well being from people currently suffering from a condition. Brazier, et al. (2008) cites data that the general public rates mental health issues as less important than physical health, less so than those who suffer from mental illness (Brazier (2008), which if true would lead to an underestimate of the cost of mental illness. Meanwhile De Wit, Busschbach, and De Charro (2000) argue that people underestimate their ability to adapt to situations, and thus all QALY cost estimates are overestimates. Michael Plant argues that this applies only to physical ailments, and that this leads people to underestimate the severity of mental illness relative to physical illness.

Issues Comparing DALYs/QALYs for Mental Illness with Other Illnesses

The cost-effectiveness estimates for malaria nets are based solely on the averted physical suffering. In order to truly compare malaria QALYs with depression QALYs, we must take into consideration the mental health toll of malaria. This turns out to be a very complicated question that can’t be answered without getting into moral ontology, which is beyond the scope of this document.

For a very, very crude idea of the effect on bednets on suffering, see this guesstimate model, which lets you estimate the mental illness cost of malaria from mourning and mental-health related side effects. Ultimately the DALY/$ (guesstimated in the range of 10^-3 and 10 ^-5) are insignificant next to the DALY/$ gain from deaths averted (in the range of 10^-1).

Financial Cost

Illness (mental or physical) can exact an enormous physical toll on sufferers, in both cost of treatment and lost productivity. Productivity loss is more difficult to measure than death and thus not as precise a metric, but it is significantly more objective and comparable across ailments than DALYs or QALYs. For more information on the productivity costs of mental illness, see this post.

A second issue is that using productivity loss as a metric will bias interventions towards people with higher potential incomes, which is the opposite of most people’s instincts.

Conclusions

None of these measurements met my goals of being easy to measure and capturing the entire impact of mental illness. This is not surprising, since even the impacts of physical ailments are hard to measure. The only clear conclusion is that QALYs are better than DALYs for any purpose I can think of. Of the options available, death and financial cost are the most objective, easiest to measure, and easiest to compare to other ailments, but lose a lot of data around suffering. QALYs capture that data, but are still of questionable suitability for comparing to other ailments.

Impact of Depression and its Treatment on Productivity

Introduction

One argument for prioritizing treatment of mental illness is that the secondary effects (such as higher productivity and improved health-related behavior) may be especially impactful. Illnesses like depression and addiction are incredible drains on productivity, which can be reversed with treatment. In this essay I investigate the productivity cost of untreated (or unsuccessfully treated) mental illness and the impact of treatment on productivity.

How Bad is it?

World Health Organization Data

Alonso, et al. (2011) surveyed workers to determine how many days they missed work due to a variety of chronic illnesses, including depression and anxiety. Their sample included 63,000 people spread across 24 countries, with a range of cultures and income levels. Across all countries, the following disorders caused the average person with that disorder to lose the following days of work. Note that comorbidity is common and days-missed are additive- e.g. a person with depression and generalized anxiety in a lower income country would miss 26.6 days of work.
Days of Productivity Lost to Illness

Lower income countries Medium income countries Higher income countries All countries
Additional days Additional days Additional days Additional days
Mean s.e Mean s.e. Mean s.e. Mean s.e.
Depression 13.1 5 14.7 4.1 4.1 3.2 9 2.5
Bipolar disorder 36.5 15 23.2 9.6 9.6 5.8 17.3 4.9
Panic disorder 24.3 12.9 17.7 5.5 11.7 4.1 14.3 3.5
Specific phobia −6.6 5.2 4.2 4.7 6.7 3.3 3.9 2.5
Social phobia 5.7 10 9 8.4 7.5 2.9 7.3 2.8
GAD 13.5 9.1 24.6 8.4 7.6 4.9 7.7 3.6
Alcohol abuse −2.8 7.2 8.2 5 −0.3 4.5 1.9 3.2
Drug abuse 14.7 13.9 3.9 12.2 1.2 5.5 2.5 4
PTSD 15.3 11.3 −1.1 9.5 16.2 4 15.2 3.5
Insomnia 5.7 5.3 4.6 5.4 9.4 3.2 7.9 2.7
Headache or migraine 10 3.6 6.5 3.3 4.5 2.1 7.1 1.5
Arthritis 6.1 4.4 0.8 5 1.8 2.4 2.7 1.8
Pain 0.9 3.1 11 2.4 19.6 2.1 14.3 1.5
Cardiovascular 2.7 6.7 1 3.6 7.2 2.7 5.7 2.1
Respiratory 10.7 3 −1.1 2.6 0.9 1.4 2.6 1.3
Diabetes 4 6.4 0.5 5.6 9.6 3.8 8.6 2.8
Digestive −4.3 4.8 −0.4 4 16.6 4.8 7.6 3
Neurological 33.7 23 18.6 7 15.3 7.4 17.4 5.8
Cancer 19.4 17.9 −4.2 12.9 6.9 3.6 5.5 3.5

 

[Note that negative numbers mean the condition is associated with an increase in number of days worked.]

Alonso, et al (2011) did not attempt to measure workers who attended work but were less productive due to illness (presenteeism), or control for average number of days of work for a given country.

Chrisholm, et al. (2016) attempted to estimate the economic impact of depression and anxiety, including the cost of lost productivity, using primarily the data above. They estimate that treatment for depression leads to a 5% increase in attendance (in any country) and 5% increase in productivity while present. This implies a normal worker has 180 working days in high income countries and 260 in low income countries, which is low (see OECD data), meaning the 5% estimate for absenteeism is too high. However I believe their estimate for presenteeism is much too low. Just the diagnostic criteria of depression suggests more than a 5% drop in productivity.

 

Comparison to Sleep Deprivation

The effects of depression can be similar to sleep deprivation, in part because depression can cause either insomnia or a need for excess sleep, and in part because both produce a “brain fog” (weirdly, sleep deprivation may also treat depression). Given the paucity of information on the relationship between depression and productivity and the abundance of information on the relationship between sleep and productivity, I turned to sleep deprivation as a model for the effects of depression on productivity, contingent on a given a worker making it to their job. The following are mostly small studies but unsurprisingly all show sleep deprivation having a large negative impact on productivity.

 

Kessler, et al. (2011) estimate that insomnia causes presenteeism equivalent to 7.8 days of missed work per year, an estimated financial loss of $2,280 per person. This used the WHO Health and Work Performance Questionnaire, which relies entirely on workers self-reports of their productivity relative to co-workers. It is also designed only to measure whether someone is more or less productive than average, not the magnitude of the difference.

 

Gibson & Shrader (2014) estimated that a one hour increase in average nightly sleep led to a 16% increase in wages (on average, $6,000). I will use that as my lower bound for the benefits of treating depression. I assume the actual increase productivity is larger than the increase in wages, because some of the benefit is captured by the employer. If we assume the employer and employee capture equal value, this implies an actual productivity increase of 32%. And if we assume depression is equivalent to 2-3x the cost of missing one hour of sleep, that is almost a halving of productivity (note that for actual sleep, the costs of missed sleep probably increase exponentially). This study is especially promising because it is rather large and used a natural experiment (distance from timezone line) to establish study conditions.

 

What Does Treatment Accomplish?

Strong Minds

[When not otherwise stated, data comes from Strong Mind’s 2015 report.]

Strong Minds is an NGO in Africa that runs 12 week group therapy classes in Uganda. Their three month month program produces a noticeable drop in depression.

Strong Minds monitors its effect on depression using a modified version of the PHQ-9 (Patient Health Questionnaire- 9). The scale of this test is unknown, making it hard to evaluate the absolute improvement, but lower scores are relatively better (less depression) than higher scores. This questionnaire is an accepted tool for monitoring severity of depression.

Of women participating in Strong Mind’s 12 week pilot program, 92% had reduced scores on the PHQ-9; 11% of the control group had reduced scores. Most of the other effects reported in Strong Mind’s report are given in absolute terms, with no reference to the control group. Based on the reduction in PHQ-9 scores, I will assume 88% of any result is due to participation in the program. Key results:

  • 15 percentage point increase in participation in primary occupation (79% -> 94%).
  • 40 percentage point reduction in families going 24 hours without a meal (53% -> 13%).
  • 17 percentage point reduction in medical care visits (58% -> 41%). This is likely to understate the improvement in health, as some participants probably had physical problems they had previously been too depressed to treat.
  • 18 percentage point increase in families sleeping in protected shelters (65% -> 83%).
  • 10 percentage point increase in school attendance (33% -> 43%).

Income is not reported in this study. The authors do not say this explicitly, but it is common in developing world studies to examine consumption, because income is so variable.

Qualms about data: the study recorded 46 variables, of which less than 10 were reported in their report (not all of which made it into this report). The report included different metrics from phase one studies (eating 3 meals/day, ability to save any amount of income).  Given that it appears this data was still collected in phase two, the absence of results in the report raises concerns about cherry picking. I included this study despite my qualms because so little data was available about the effect of treatment of depression in developing countries.

Cost: $240/12 women in the program = $20/person. This is almost certainly an underestimate of even the marginal cost of the program.

Schoenbaum, et al.

In The Effects of Primary Care Depression Treatment on Patients’ Clinical Status and Employment, researchers reported that six months after their intervention (treatment for depression by a primary care physician, in the USA), 24% (vs 70% in control group) were depressed, and 72% (vs 54%) were employed.

Summary

Translating these productivity impacts into dollars is difficult because we can’t assume they hit all incomes equally, however the WHO estimates that in aggregate depression and anxiety together cost one trillion dollars US/year in lost productivity worldwide, slightly more than 1% of total GDP. On an individual level, there is no satisfying answer here. Depression has a very broad definition: the worst cases can destroy all productivity. The typical case destroys somewhere between 5% and 50% of productivity. Treatment of depression can restore that lost productivity in some but not 100% of participants.  

 

Areas for Further Investigation

I used sleep deprivation to generate heuristics for how damaging depression might be, with the answer being “quite bad”. Those numbers are even more accurate for estimating the effect of sleep deprivation. Because the scope of this paper was limited to economic effects stemming from workplace productivity, I have left out many other costs of sleep deprivation, including health costs and developmental damage to children. Given the costs and prevalence of sleep deprivation, sleep-promoting interventions, especially in children and adolescents, may be a promising area for intervention.

Epistemic Spot Check: A Guide To Better Movement (Todd Hargrove)

Edit 7/20/17: See comments from the author about this review.  In particular, he believes I overstated his claims, sometimes by a lot.

 

This is part of an ongoing series assessing where the epistemic bar should be for self-help books.

Introduction

Thesis: increasing your physical capabilities is more often a matter of teaching your neurological system than it is anything to do with your body directly.  This includes things that really really look like they’re about physical constraints, like strength and flexibility.  You can treat injuries and pain and improve performance by working on the nervous system alone.  More surprising, treating these physical issues will have spillover effects, improving your mental and emotional health. A Guide To Better Movement provides both specific exercises for treating those issues and general principles that can be applied to any movement art or therapy.

The first chapter of this book failed spot checking pretty hard.  If I hadn’t had a very strong recommendation from a friend (“I didn’t take pain medication after two shoulder surgeries” strong), I would have tossed it aside.  But I’m glad I kept going, because it turned out to be quite valuable (this is what triggered that meta post on epistemic spot checking).  In accordance with the previous announcement on epistemic spot checking, I’m presenting the checks of chapter one (which failed, badly), and chapter six (which contains the best explanation of pain psychology I’ve ever seen), and a review of model quality.  I’m very eager for feedback on how this works for people.

Chapter 1: Intro (of the book)

Claim: “Although we might imagine we are lengthening muscle by stretching, it is more likely that increased range of motion is caused by changes in the nervous system’s tolerance to stretch, rather than actual length changes in muscles. ” (p. 5). 

Overstated, weak.  (PDF).  The paper’s claims to apply this up to 8 weeks, no further.  Additionally, the paper draws most (all?) of its data from two studies and it doesn’t give the sample size of either.

Claim:  “Research shows the forces required to deform mature connective tissue are probably impossible to create with hands, elbows or foam rollers.” (p. 5). 

Misleading. (Abstract).  Where by “research” the Hargrove means “mathematical model extrapolated from a single subject”.

Claim:  “in hockey players, strong adductors are far more protective against groin strain than flexible adductors, which offer no benefit” (p. 14).

Misleading. (Abstract) Sample size is small, and the study was of the relative strength of adductor to abductor, not absolute strength.

Claim: “Flexibility in the muscles of the posterior chain correlates with slower running and poor running economy.” (p. 14).

Accurate citation, weak study.  (Abstract) Sample size: 8.  Eight.  And it’s correlational.

[A number of interesting ideas whose citations are in books and thus inaccessible to me]

Claim:  “…most studies looking at measurable differences in posture between individuals find that such differences do not predict differences in chronic pain levels.”  (p. 31). 

Accurate citation.  (Abstract).  It’s a metastudy and I didn’t track down any of the 54 studies included, but the results are definitely quoted accurately.

 

Chapter 6: Pain

Claim: “Neuromatrix” approach to pain means the pattern of brain activity that create pain, and that pain is an output of brain activity, not an input (p93).

True, although the ability to correctly use definitions is not very impressive.

Claim: “If you think a particular stimulus will cause pain, then pain is more likely.  Cancer patients will feel more pain if they believe the pain heralds the return of cancer, rather than being a natural part of the healing process.” (p93).

Correctly cited, small sample size. (Source 1, source 2, TEDx Talk).

ClaimPsychological states associated with mood disorders (depression, anxiety, learned helplessness, etc) are associated with pain (p94).

True, (source), although it doesn’t look like the study is trying to establish causality.

ClaimMany pain-free people have the kinds of injuries doctors blame pain on (p95).

True, many sources, all with small sample sizes.  (source 1, source 2, source 3, source 4, source 5)

Claim: On taking some cure for pain, relief kicks in before the chemical has a chance to do any work (p98)

True.  His source for this was a little opaque but I’ve seen this fact validated many other places.

Claim: we know you can have pain without stimulus because you can have arm pain without an arm (p102).

True, phantom limb pain is well established.

Claim: some people feel a heart attack as arm pain because the nerves are very close to each other and the heart basically never hurts, so the brain “corrects” the signal to originating in the arm (p102).

First part: True.  Explanation: unsupported.  The explanation certainly makes sense, but he provides no citations and I can’t find any other source on it.

Claim: Inflammation lowers the firing threshold of nociceptors (aka sensitization) (p102).

True (source).

Claim: nociception is processed by the dorsal horn in the spine.  The dorsal horn can also become sensitized, firing with less stimulus than it otherwise would.  Constant activation is one of the things that increases sensitivity, which is one mechanism for chronic pain (p103).

True (source).

Claim: people with chronic pain often have poor “body maps”, meaning that their mental model of where they are in space is inaccurate and they have less resolution when assessing where a given sensation is coming from (p107).

Accurate citation (source).  This is a combination of literature review and reporting of novel results.  The novel results had a sample of five.

Claim: The hidden hand in the rubber hand illusion experiences a drop in temperature (p109).

Accurate citation, tiny sample size (source).  This paper, which is cited by the book’s citation, contains six experiments with sample sizes of fifteen or less.  I am torn between dismissing this because cool results with tiny sample sizes are usually bullshit, and accepting it because it is super cool.

Claim: “a hand that has been disowned through use of the rubber hand illusion will suffer more inflammation in response to a physical insult than a normal hand.” (p. 109).

Almost accurate citation (source).  The study was about histamine injection, not injury per se.   Insult technically covers both, but I would have preferred a more precise phrasing.  Also, sample size 34.

Claim: People with chronic back pain have trouble perceiving the outline of their back (p. 109). 

Accurate citation, sample size six (pdf).

Claim:  “Watching the movements in a mirror makes the movements less painful [for people with lower back pain].” (p. 111). Better Movement. Kindle Edition.

Accurate citation, small sample size (source).

Model Quality

Reminder: the model is that pain and exhaustion are a product of your brain processing a variety of information.  The prediction is that improving the quality of processing via the principles explained in the book can reduce pain and increase your physical capabilities.

Simplicity: Good.  This is not actually simple model, it requires a ton of explanation to a layman.  But most of its assumptions come from neurology as a whole; the leap from “more or less accepted facts about neurology” to this model is quite small.

Explanation Quality: Fantastic.  I’ve done some reading on pain psychology, much of which is consistent with Guide…, but Guide… has by far the best explanation I’ve read.

Explicit Predictions: Good, kept from greatness only by the fact that brains and bodies are both very complicated and there’s only so much even a very good model can do.

Useful Predictions: Okay. The testable prediction for the home-reader is that following the exercises in the back of the book, or going to a Feldenkrais class, will treat chronic pain, and increase flexibility and strength.  Since the book itself admits that a lot of things offer short term relief but don’t address the real problem, helping immediately doesn’t prove very much.

Acknowledging Limitations: low. (Note: author disputes this, and it’s entirely possible he did and I forgot).  GTBM doesn’t have the grandiose vision of some cure-all books, and repeatedly reminds you that your brain being involved doesn’t mean your brain is in control.  But there’s no sentence along the lines of “if this doesn’t work there’s a mechanical problem and you should see a doctor.”

Measurability: low.  This book expects you to put in a lot of time before seeing results, and does not make a specific prediction of the form they will come in.  Worse, I don’t think you can skip straight to the exercises.  If I hadn’t read the entire preceding book I wouldn’t have approached them in the correct spirit of attention and curiosity.

Hmmm, if I’d assigned a gestalt rating it would have been higher than what I now think is merited based on the subscores.  I deliberately wrote this mostly before trying the exercises, so I can’t give an effectiveness score.  If you do decide to try it, please let me know how it goes so I can further calibrate my reviews to actual effectiveness.

 

You might like this book if…

…you suffer from chronic pain or musculoskeletal issues, or find the mind-body connection fascinating.

This post supported by Patreon.

Review: The Dueling Neurosurgeons (Sam Kean)

If you like this blog, you might like…

I originally intended The Tale of the Dueling Neurosurgeons for epistemic spot checking, but it didn’t end up feeling necessary.  I know just enough neurobiology and psychology to recognize some of its statements as true without looking them up, and more were consistent enough with what I knew and what good science and good science writing looks like; interrogating the book didn’t seem worth the trouble.  I jumped straight to learning from it, and do not regret this choice.  The first thing I actually looked up came 20% of the way into the book, when the author claimed the facial injuries of WWI soldiers inspired the look of the Splicers from BioShock.*

[*This is true. He used the word generic mutant, not the game-specific term Splicer, but I count that under “acceptable simplifications for the masses”.  Also, he is quicker to point out that he is simplifying than any book I can remember.]

At this point it may be obvious why I think fans of this blog will really enjoy this book, beyond the fact that I enjoyed it.  It has a me-like mix of history (historical color, “how we learned this fact”, and “here’s this obviously stupid alternate explanation and why it looked just as plausible if not more so at the time”*), actual science at just the right level of depth, and fun asides like “a lot of data we’ve been talking in this chapter on phantom limbs about comes from the Civil War.  Would you like to know why there were so many lost limbs in the Civil War?  You would?  Well here’s two pages on the physics of rifles and bullets.”**

[*For example, the idea that the brain was at all differentiated was initially dismissed as phrenology 2.0.

**I’m just going to assume you want the answer: before casings were invented, rifles had a trade off between accuracy and ease of use.  Bullets that precisely fit the barrel are very hard to load, bullets smaller than the barrel can’t be aimed with any accuracy.  Some guy resolved this by creating bullets that expanded when shot.  But that required a softer metal, so when the bullet hit it splattered.  This does more damage and is much harder to remove.]

I am more and more convinced that at least through high school, teaching science independent of history of science is actively damaging, because it teaches scientific facts, and treating things as known facts damages the scientific mindset.  “Here is the Correct Thing please regurgitate it” is the opposite of science.  What I would really love to see in science classes is essentially historical reenactments.  For very young kids, give them the facts as we knew them in 18XX, a few competing explanations, and experiments with which to judge them (biased towards practical ones you know will give them informative results), but let them come to their own conclusions.  As they get older, abandon them earlier and earlier in the process; first let them create their own experiments, then their own hypotheses, and eventually their own topics.  Before you know it they’re in grad school.

The Dueling Neurosurgeons would be a terrible textbook for the lab portion of that class because school districts are really touchy about inducing brain damage.  But scientists had a lot of difficulty getting good data on the brain for the exact same reason, and Dueling Neurosurgeons is an excellent representation of that difficulty.  How do we learn when the subject is immensely complex and experiments are straightjacketed?  I also really enjoyed the exploration of  the entanglement between what we know and how we know it.  I walked away from high school science feeling those were separable, but they’re not.

You might like this book if you:

  • like the style of this blog. In particular, entertaining asides that are related to the story but not the point. (These are mostly in footnotes so if you don’t like them you can ignore them).
  • are interested in neurology or neuropsychology at a layman’s level.
  • share my fascination with history of science.
  • appreciate authors who go out of their way to call out simplifications, without drowning the text in technicalities.

You probably won’t like this book if you:

  • need to learn something specific in a hurry.
  • are squeamish about graphic descriptions of traumatic brain damage.
  • are actually hoping to see neurosurgeons duel.  That takes up like half a chapter, and by the standards of scientists arguing it’s not very impressive.

The tail end of the book is either less interesting or more familiar to me, so if you find your interest flagging it’s safe to let go.

This post supported by patreon

Dreamland: bad organic chemistry edition

I am in the middle of a post on Dreamland (Sam Quinones) and how it is so wrong, but honestly I don’t think I can wait that long so here’s an easily encapsulated teaser.

On page 39 Quinones says “Most drugs are easily reduced to water-soluble glucose…Alone in nature, the morphine molecule rebelled.”  I am reasonably certain that is horseshit.  Glucose contains three kinds of atoms- carbon, oxygen, and hydrogen.  The big three of organic chemicals.  Your body is incapable of atomic fusion, so the atoms it starts with are the atoms it ends up with, it can only rearrange them into different molecules.  Morphine is carbon, oxygen, hydrogen, and nitrogen, and that nitrogen has to go somewhere, so I guess technically you can’t reform it into just sugar.  But lots of other medications have non-big-3 atoms too (although, full disclosure, when I spot checked there was a lot less variety than I expected).

This valorization of morphine as the indigestible molecule is equally bizarre.  Morphine has a half-life of 2-3 hours (meaning that if you have N morphine in your body to start with, 2-3 hours later you will have N/2).  In fact that’s one of the things that makes it so addictive- you get a large spike, tied tightly it with the act of ingestion, and then it goes away quickly, without giving your body time to adjust.  Persistence is the opposite of morphine’s problem.

This is so unbelievably wrong I would normally assume the author meant something entirely different and I was misreading.  I’d love to check this, but the book cites no sources, and the online bibliography doesn’t discuss this particular factoid.  I am also angry at the book for being terrible in general, so it gets no charity here.

Talking about controversial things (discussion version)

There is a particular failure pattern I’ve seen in many different areas.  Society as a whole holds view A on subject X.  A small sub-group holds opposing view B.   Members of the sub group have generally put more thought into subject X and they have definitely spent more time arguing about it than the average person on the street.  Many A-believes have never heard of View B or the arguments for it before.

A relative stranger shows up at a gathering of the subgroup and begins advocating view A, or just questioning view B.  The sub-group assumes this is a standard person who has never heard their arguments and launches into the standard spiel.  B doesn’t listen, A gets frustrated and leaves the subgroup, since no one is going to listen to their ideas.

One possibility is that the stranger is an average member of society who genuinely believes you’ve gone your entire life without hearing the common belief and if they just say it slowly and loud enough you’ll come around.*  Another possibility is they understand view B very well and have some well considered objections to it that happen to sound like view A (or don’t sound that similar but the B-believer isn’t bothering to listen closely enough to find out).  They feel blown off and disrespected and leave.

In the former scenario, the worst case is that you lose someone you could have recruited.  Oh well.  If the latter, you lose valuable information about where you might be wrong.  If you always react to challenges this way you become everything hate.

For example: pop evolutionary psychology is awful and people are right to ignore it.  I spent years studying animal behavior and it gave me insights that fall under the broad category of evopsych, except for they are correct.  It is extremely annoying to have those dismissed with “no, but see, society influences human behavior.”

Note that B doesn’t have to be right for this scenario to play out.  Your average creationist or anti-vaxxer has thought more about the topic and spent more time arguing it than almost anyone.  If an ignorant observer watched a debate and chose a winner based on fluidity and citations they would probably choose the anti-vaxxer.  They are still wrong.

Or take effective altruism.  I don’t mind losing people who think measuring human suffering with numbers is inherently wrong.  But if we ignore that entire sphere we won’t hear the people who find the specific way we are talking dehumanizing, and have suggestions on how to fix that while still using numbers.  A recent facebook post made me realize that the clinical tone of most EA discussions plus a willingness to entertain all questions (even if the conclusion is abhorrent) is going to make it really, really hard for anyone with first hand experience of problems to participate.  First hand experience means Feelings means the clinical tone requires a ton of emotional energy even if they’re 100% on board intellectually.  This is going to cut us off from a lot of information.

There’s some low hanging fruit to improve this (let people talk before telling them they are wrong), but the next level requires listening to a lot of people be un-insightfully wrong, which no one is good at and EAs in particular have a low tolerance for.

Sydney and I are spitballing ideas to work on this locally.  I think it’s an important problem at the movement-level, but do not have time to take it on as a project.**  If you have thoughts please share.

*Some examples: “If you ate less and exercised more you’d lose weight.”  “If open offices bother you why don’t you use headphones?”, “but vaccines save lives.”, “God will save you…”/”God isn’t real”, depending on exactly where you are.

**Unexpected benefit of doing direct work: 0 pangs about turning down other projects.  I can’t do everything and this is not my comparative advantage.