Asylum Claims and Other Numbers at the Border

There’s a lot in the news right now about border crossing, immigration and asylum claims, and I’m seeing all sorts of numbers being thrown around on Twitter. I wanted to do a quick round up of some numbers/sources to help people wade through it.

First up, every month US Customs and Border Patrol publishes the number of apprehensions they have at the Southern US Border and how that compares to the last 5 years. They do this relatively close to real time, we have the numbers for May, but not yet for June. If you want to know why you’re seeing so much in the news, take a look at this graph:

So with 4 months left to go in the fiscal year, we’re already 100,000 over the highest year on that chart. To give some context to that though, apprehension numbers have actually been relatively low for the last few years. They peaked at 1.6 million in the late 90s/early 2000s. However, there have been some changes to the makeup of that group….family crossings. Vox published this chart based on the CBP data that shows how this has changed:

I couldn’t find what those numbers were during the last spike, but it seems to be a record high.

So now what about asylum claims? Recently acting DHS Secretary Kevin McAleenan said the 90% of asylum seekers were skipping their hearings, but others were claiming that actually 89% show up. That’s a MASSIVE discrepancy, so I wanted to see what was going on.

First up, the 89% rate. The DOJ publishes all sorts of statistics about asylum hearings, and in this massive report they showed the “in absentia” rates for asylum decisions (page 33):

So for FY17, asylum claimants were at their decision hearing 89% of the time.

So where did the “90% don’t show up” claim come from? Reading the full context of McAleenan’s quote, it appears that he was specifically referencing a new pilot program for families claiming asylum. From what I can tell the pilot program is not published anywhere, so it’s not possible to check the numbers.

So is it plausible it jumped from 11% to 90%? I tend to doubt it, but it’s important to note the lag time here. The last published DOJ numbers are from FY2017, but those are for hearings that took place in FY2017. The average wait time for hearings in these cases for these cases is enormous….727 days so far in 2019.  These wait times are climbing, but if you toggle the graph around, we can see that the wait time back in 2015 was nearly two years:

So essentially those with decisions in FY2017 probably filed in FY2015. And a lot has happened to the stats since then. First, here are the number of applications over the last few years:

So compared to 2015, the number of applications have tripled but the number of approvals has barely budged. We don’t yet know what that will do to the percentage of people who show up, but it seems very plausible that it could increase the absentee rate. Additionally, because family migration is increasing so rapidly, it’s not clear what that will do to the numbers. Regardless, McAleelan’s reference was specifically to that group, so it was only a subset of the numbers that were previously reported. Still, 90% seems awfully high.

Complicating things further of course is the fact that this was a “pilot program”. That means it could have selected just one country or point of entry. One of the more interesting fact sheets from the DOJ site was the rate of asylum approvals by country. In the past few years, here are the top countries (page 29 of this report):

The rates of granting asylum from each of these countries were wildly different in 2018 though. Chinese asylum seekers were 53% granted, El Salvador was 15%, Honduras was 14%, Guatemala was 11%, Mexico was 6%. It seems plausible that a pilot program might have just been addressing those that arrive at the southern border, so it’s possible that individual countries have different profiles.

Overall, it’s clear that the data on this topic is worth watching.

Twitter and Sundry

I finally got a vacation this week, which means I spent not a lot of time near a computer but had a decent amount of time to scroll through Twitter. A few good accounts I found:

Any other good ones I missed?

Speaking of good accounts to follow, apparently one of the first papers focused on a prominent (and anonymous) Twitter account was published, with this one on the role of Neuroskeptic in calling out scientific ethical breeches. Only paper I’ve ever seen where the conflict of interest statement included “…was banned from commenting by Leonid Schneider at his blog “forbetterscience”.

Finally, Neuroskeptic also follows up on an analysis done by Susan Fiske of who research methods blogs go after and how often.  A few years ago Fiske had caused a kerfluffle when she referred to many science/research methods bloggers as “methodological terrorists” and defended the replication crisis. Her new paper looks at 41 bloggers and categorized which other researchers they talked about most often. Interesting findings: 3 out of the top 4 talked about researchers resigned (Diederik StapelBrian Wansink and Jens Förster), , and the #1 guy is pretty notorious. Other interesting note: there was no clear gender bias in who got talked about. Men were more likely to critique other men, and men who got named were posted about more often. However, it’s not particularly clear what this means about bias, as a few large cases of misconduct got a LOT of coverage, and Bem seems to have become the go to for bad methods/good researcher examples.

Still, super interesting work and good for Fiske for doing it. Gotta respect someone who gets mad, then gets data. I look forward to this being expanded on in the future.

Vaccination Rates by County, State and Around the World

There’s a lot in the news recently about vaccination rates, both in the US and in other countries. After seeing a few comments on Twitter this week about the topic, I got curious about the exact numbers.

First off, it’s important to note that for all the press coverage of the measles outbreak, vaccine exemptions are not evenly distributed across the country. For example, here’s just my state broken down by county. The map on the left is those with exemptions, the one on the right is those without exemptions not meeting requirements. Functionally, the vaccination rate is likely 100%-(the number on the left+the number on the right).


Now not everyone on the right may be missing their vaccinations, for some it may be paperwork. The Boston suburbs probably do well because most working parents have been providing vaccination documentation to day cares for years prior to this.

So how does Massachusetts compare to the country? Well, the CDC puts together a rather awesome interactive map for Kindergarten vaccination rates here. This map shows something interesting. Per the NYTs graphic of the measles outbreak, Washington, New York and Michigan have seen the largest measles outbreaks in the country. However, New York actually has one of the highest vaccination rates in the country at 97.5%. This suggests that it’s not just having a high vaccination rate, but where the unvaccinated are located that causes outbreaks. For example, in Massachusetts the exemption rates are highest on Martha’s Vineyard, a wealthy spread out community with not many year round residents. The other counties with higher rates of exemptions are not close geographically. In New York City though, it’s groups living in close proximity with low rates that are getting hit by the outbreak. This leads to high overall vaccination rates by state, yet still record setting outbreaks in targeted communities.

Now how about worldwide? Well, after working on their childhood vaccination program for years, Mexico actually now has a higher rate of children vaccinated against measles than the US (96% vs 92%). Interestingly, a similar number of people doubt vaccination safety in both countries. According to Our World in Data, France and Russia have the most vaccine skeptics:

Using Our World in Data again though, apparently vaccine skepticism doesn’t always correlate with not getting vaccinated. Both France and Russian have >95% measles vaccination rates.

I thought all this was interesting because overall, many people believe that fewer children are vaccinated than actually are. For example, Americans estimated that only 35% of the worlds children were vaccinated against measles, when in reality 85% are. While knowing that rates are high can sometimes convince people that it doesn’t matter as much if they get their kids vaccinated, thinking many people aren’t vaccinated can sometimes convince people that it’s not important to do so. “Everybody’s doing it” is an effective slogan for a reason.


Quote for Election Season

Life is a bit chaotic this weekend, but as we head towards what looks to be a rather drawn out election season, here’s a quote to keep in mind:

“The public’s ‘opinion’ on almost any issue will be a function of the question asked.”
-Neil Postman, Technopoly (as found on Twitter)

The exact wording here is important…”a function of” does not mean the question fully makes the opinion, but rather that it transforms it in ways that can often be predicted. A good thing to remember when you see headlines saying “the public supports ______” or “low public support for _______”.

Addiction Nation: Recovery and Hope

This post is part of a series about my brother’s upcoming book Addiction Nation: What the Opioid Crisis Reveals about Us, discussing some of the science and stats he used throughout the books. Read the intro post here, part 1 here, part 2 here, part 3 here, or (best of all) pre-order the book on Amazon here. Only 2 more days until the release!

We’ve spent the last few weeks looking at a lot of areas of addiction, but (much like your book) I wanted to end this series on a positive note….talking about recovery and hope. Of course one of the biggest reasons people want to read about addiction is precisely to find hope, so I think it’s a good place to end. Sound good?

Tim: Awesome! I wanted to note one other hopeful thing up front. There are some pretty terrible treatment programs out there. I didn’t get into the corruption or the number of facilities that don’t use evidence-based treatment methodologies. They really do have low success rates. 

One critical thing to look at is how specific studies define “success.” If they only definition of “success” is total abstinence for a person’s entire life (or even just the length of the study) then a lot of numbers are going to look pretty grim.  But, if success is defined by decreasing overdoses, a reduction in harmful behavior or even just using less of the substance, then there is a lot of reason to hope. 

Another thing I didn’t get to dive into is “spontaneous remission” or when a person recovers from an addiction without any professional treatment. It happens a lot more than you would expect. This means that increasing access to treatment is really important but we can also save a lot of lives by trying to keep people alive long enough for that spontaneous remission to occur. 

Ooooh….defining success metrics clearly. I like it.

Okay, so first up, last week we talked about the Rat Park study, and you mentioned a study that often gets brought up with that one. It’s a 1974 study called “How Permanent Was Vietnam Drug Addiction?“, and it looked at the rates of addiction among American soldiers in Vietnam as they were leaving Vietnam, then got back in touch with them after they got home. The results are here:

The most often quoted statistic (and the one you use in the book) is the amazing drop from 20% reporting an addiction issue to just 1% reporting an issue a year later. It’s an incredible statistic, made stronger by the fact that this study had a very low non-response rate (<5%) and that urine testing backed up the self reported usage. You quote the study as saying:

There have been no studies of addict populations in this country that show anything like the 95 percent remission rate after ten months, which is what a drop from 20 percent addicted while in Vietnam to 1 percent after Vietnam suggests.

I can see why that stat gets all the headlines, but one of the things I found most interesting about this study when I dove in to it was that there’s actually a lot more in it for us to think about. You weren’t able to get in to it in the book, but I found their breakdown of the subgroups within that group fascinating:

So basically 85% of soldiers returned to their pre-Vietnam status. 8% who had used before Vietnam actually stopped using after returning from Vietnam, and 7% who weren’t using before started using and never stopped.

Now the authors throw in a caveat here that just because these veterans stopped using narcotics doesn’t mean they didn’t pick up another problem (alcoholism, barbiturates, etc), and they note that those who continued their addiction tended to have a much bigger problem than they did before going to Vietnam. However, even with those notes, this does fly in the face of the idea that using narcotics will always lead to a permanent addiction problem with that particular substance.

Tim: Absolutely. There is a good reason to believe that this is the norm, not the exception. This is why “heroin-assisted treatment” has been pretty well documented to be effective in the long term. It reduces other health risks, like Hep C and HIV, provides consistent dosage and reduces drug-related crimes. While some people will just keep using indefinitely, a lot of others will experience spontaneous remission or eventually decide to engage in another kind of treatment. 

It also indicates that there are almost certainly people who might be more “situational” addicts, and we may need to treat them differently from those whose addictions seem more persistent. Looking at your story, one could call you a “situational” addict, don’t you think? Any thoughts on this?

Tim: The Vietnam study was actually the inspiration for Bruce Alexander’s “Rat Park.” I think Alexander would argue that almost everyone is a “situational” in their addictions. 

I wouldn’t want to create a strict duality but think this a better category for a spectrum, how big a role does your situation play? For alcohol consumption, there are a lot of folks who have problematic consumption levels that could be classified as alcoholism throughout college and into their twenties and early thirties. But, they eventually change their behavior in a way that is often triggered by major life events.  

But, in Switzerland, about 20% of people have continued using since the beginning of the heroin-assisted treatment program. This remaining population would probably be covered by life trauma, mental illness and some other genetic factors. 

While I focus a lot on environmental and social factors for addiction, you can’t escape some sort of genetic predisposition. Even if it isn’t necessarily for “addiction” but a bodily response to certain substances. 

For example, both us were prescribed opiates in high school/college for oral surgery. You took them and felt terrible. As soon as you could, you moved to ibuprofen because the narcotics made you feel sick. I finished the entire bottle, even though my surgery was less significant because I really enjoyed how they made me feel. 

That’s true. I get incredibly nauseous when I take opioids and have refused them ever since that surgery. Taking enough of them to get addicted would be a downright struggle for me.

Okay, to tease out one last part of that study, I found the entire idea that 8% of the men had a problem before they went to Vietnam but came back and stopped using totally fascinating. That’s pretty much the reverse of what we tend to think about with addiction….that traumatic events must always make it worse. With addiction though, we know this isn’t always the case. As you say in your book:

As discussed earlier, over time, severe addiction reduces the amount of gray matter in the part of our brain most responsible for higher-level reasoning and self-control. A 2013 study of the brains of those struggling with cocaine addiction suggests something interesting. Within a few months of sobriety, that gray matter began to return. Within six to twelve months, the gray matter had returned to baseline levels and was about the same as those who had never been addicted. But soon after that is when the most amazing thing happened: those areas began to form an even greater level of density than for those who had never used cocaine.

You got this from a study called “Dissociated Grey Matter Changes with Prolonged Addiction and Extended Abstinence in Cocaine Users“, which contained this very cool graphic:

So basically, substance use can get bad in a hurry because many substances actually erode the very parts of the brain that normally help us avoid doing impulsive things. Prolonged abstinence actually reinforces those parts of the brain beyond the baseline levels. As the study says:

If addiction can be characterized as a loss of self-directed volitional control , abstinence and its maintenance may be characterized by a reassertion of these aspects of executive function. Current cocaine users demonstrate reduced GM in brain regions critical to executive function, such as the anterior cingulate, lateral prefrontal, orbitofrontal and insular cortices. In contrast, the group of abstinent CD users reported here show elevations in GM as a function of abstinence duration that exceeds control levels after 36 weeks, on average, of abstinence.

They do note (as all good studies do) that they don’t really know causality here either. It could be that these addicts had above-average levels of grey matter beforehand (they were not measured pre-addiction) or it could be that recovery caused them to grow more grey matter than they originally had. It could be a little of both. It’s pure anecdote, but based on what I’ve seen out of successful recovered addicts I’ve known, I’d say the change is real.  How about you? On a personal level, do you feel addiction and recovery changed your brain at all?

Tim: My struggle would be classified as a relatively mild opioid use disorder. While the addictive process at work certainly would have changed my brain it would have been less significant than if it had gone on for years or decades. Since the initial change was not as substantial I don’t think my process of recovery likely changed things as much. 

I have been amazed that whenever I talk with someone who is also open about their recovery, there is often a sense of connection because there are different truths we’ve realized about ourselves that creates a kind of bond. 

Three thoughts related to that. 

First, I wanted to tell my story because early detection matters. If you are able to see what is happening and get support early on, recovery won’t be as difficult. I think a lot of people end up letting an addiction progress because of the shame and stigma that surrounds it. Admitting you are feeling out of control seems like a life and world ending admission. That makes it harder to do. 

Second, I do think this journey has led me to a place of diving deeper into the techniques of cognitive behavioral therapy. My research in that area made me realize how important those tools can be for improving my outlook and life more broadly. Writing a book about opioid addiction made me reflect on my alcohol consumption. It isn’t problematic at the moment but if I was to continue to drink 1-2 more alcoholic beverages a week for the next 10-20 years, there could be significant negative effects. So, I’ve started using what I’ve learned to be more thoughtful about the role alcohol plays in my life. 

Third, has been a deepening of my own spiritual and religious practices including various forms of meditation and prayer. Mindfulness training is now integrated into a lot of different recovery practices. Even though I don’t feel a day to day tug towards opioid usage, I’ve tried to dig into these practices that could provide some anchoring because I am now well aware how easily the addictive process can kick up. 

Alright, well that wraps up the series! If you want to see more from my brother, take a look at his book/author page here or buy the book and get it on Tuesday! Anything else you want to say to the nice people Tim?

Thanks for reading and I’m sure I’ll be back some time soon!

Agreed! You didn’t put it in the book, but I’d love to dig more in to the research around some of the heroin assistance programs. Crazy stuff.

Thanks for posting brother, and thank you so much for letting me opine on your work. It’s been an honor to go through so much of this journey with you, both the addiction part and the book writing part. I’m proud of you on both counts, and can’t wait to see what’s next in your journey.

Addiction Nation: Controversial or Disputed Research

This post is part of a series about my brother’s upcoming book Addiction Nation: What the Opioid Crisis Reveals about Us, discussing some of the science and stats he used throughout the books. Read the intro post here, part 1 here, part 2 here, or (best of all) pre-order the book on Amazon here.

Okay, so last week you heard about how Tim had to change a few things around when we read the actual research. Today I wanted to talk about a few pieces of research that were included in the book that have some controversy around them. While there’s only so much you can fit in a book, we thought the blog might be a good place to expand a little on some of the studies quoted. How does that sound brother?

Tim: Perfect! This was another tricky area of wading through a lot of conflicting information. One thing that I don’t think your readers will be surprised by is that the reason some of these studies are controversial is not always about the studies themselves but the claims or coverage that comes out of them.

For example, the claim “environmental factors play a role in addiction” isn’t controversial. What is controversial is when a study is used, or it’s author claims, that they have demonstrated that environment is ALL or most of what matters.

My general standard was to imagine a reader diving into a specific study in more detail. As they read, would they feel like they were learning nuance and adding texture? Or would the feel like they were misled?

That sounds like a pretty reasonable standard to me! And yes, “blame the journalist” has been a catchphrase on this blog since the very beginning. Coverage of studies can certainly skew perception of the study in ways authors never intended.

Alright, first up, a study I’ve actually blogged about before “Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century“. Before we get to the meat of this, I gotta point out brother, you actually got the name of this study wrong in your citation list. You called it “Rising morbidity and mortality, US Whites”. I mean I know I’m the only one who’s gonna read through all your citations, but GET. IT. TOGETHER. Luckily for you the author, journal, year, and DOI number were all correct, so I’ll let this one slide.

Edited even before Tim could reply: I actually just figured out how this happened. On the study page I just linked to if you click “citation manager” it changes the name of the study to the one Tim used

I take it all back brother, you’re okay.

Tim: Oh dear readers… You have no idea how sweet this is. I tried to find an emoji for the feelings you feel when your sister who is always right isn’t right but I just couldn’t find one that could encapsulate how great I feel right now. 

Okay, okay, simmer down here kiddo. I actually was right. The name of the paper you used in your citation list isn’t the one it was published under. I was just clarifying that your error wasn’t your fault.

Anyway, your quote in the book about this study (Chapter 7) is this:

After decades  of declining mortality rates – primarily because of gains in treating cancer and heart disease – the likelihood of a white person dying between the ages of forty-five and fifty four has gone up. A similar trend has not been seen in any of the world’s wealthiest nations……The change was driven was driven almost entirely by drug -and alcohol-related liver disease, and suicides.

You use the study above to support this quote, and you accurately state what the study concluded. However, there have been a few follow ups that I blogged about here.

First, Andrew Gelman questioned the findings of the initial study, citing cohort effects as possible confounders. Then, another study came out that suggested that the overdose increase was real, but not the suicide rate increase.  Then in 2018 the CDC released a report that showed that suicide rates were at a 50-year peak. They didn’t specifically quantify based on race, but they did show that rural areas (which tend to be whiter) were more vulnerable.

There’s a lot going on here, but I think overall it seemed like a reasonable quote for you to leave in. I’d say one of the big challenges of editing a non-science book for scientific accuracy is how to explain things like this without derailing the whole book. The point of your chapter was supposed to be Despair and Acedia, not demographic trends.  It seemed like the initial study got enough right that it was worth quoting, but I still feel like we’re refining the details. Personally, I would have put more of that in, but I know you had space limitations.  Any thoughts on this?

Tim: More got cut from this book than made it in the final copy. Final word count is around 70,000 and I left 100,000 words on the cutting room floor. That isn’t just rewrites but all the sections and chapters that didn’t make the final cut. It is tough to figure out how much space you can dedicate to the nuances or follow ups of specific studies.  

And with the specific details of which “deaths of despair” were most responsible, it gets pretty complicated. My guess is there will be some back and forth about this for a while because of how hard it is to feel confident in how deaths are categorized.  

There is a real human somewhere who needs to go through and catalog cause of death. And, whether or not someone died by suicide or via an accidental overdose is a line that is not always clear. Social norms or even the kind of reporting forms used can influence how these numbers are counted. 

We will also likely see studies in the future that see what sort of effects the high overdose rate will have on those who might have died later from alcohol-related health issues or by suicide. The main question there being whether or not these deaths are concentrating when in previous cohorts they would have spread more evenly over several decades. 

The lines are blurry enough for me that I felt the overall point about “deaths of despair” stands even as researchers try to parse out in greater detail what is going on. 

Alright, next up we have the infamous Rat Park study. From the work of Bruce Alexandar, this is one of the most quoted studies on addiction. Basically, the researchers put rats in empty cages with morphine and noted that the rats became addicted very quickly. They then put them in a nice environment and discovered that they rarely got addicted to morphine. This study is often used to prove that when it comes to addiction, environment matters more than exposure to drugs.

Now while I agree this study is interesting, I do have some concerns. Scott Alexander over at Slate Star Codex raised some issues with this study a few years ago with this post. He points out that while some studies have mostly replicated the effect, other studies have not. More than that though, the two things that seemed to most stand out where:

  1. Genetics studies that produce results like this:
  2. The pretty observable fact that the rich and famous still have drug and alcohol problems. As the SSC post points out, Celebrity Rehab with Dr. Drew was canceled by the host after he said “he was tired of the criticism leveled at him after celebrities he treated had relapsed into addiction and died”. Given that celebrities have access to some of the nicest environments in the world, it seems hard to says it’s all about environment.

You nod to the controversy in the book with this note:

Alexander doesn’t deny that a wide range of other factors including genetics, life experience and individual choice plays a role, but he believes they need to be put into the background because of the power of the social forces at play.

That’s a good note, and you devoted a ton of time to the other factors elsewhere in the book. You seemed to end up with a pretty “big tent” view of addiction, acknowledging that pretty much every theory has some truth and value, but none are exactly right. It’s hard to express this in any one chapter though, without constantly caveating yourself. How did you end up feeling about this process? Any general thoughts on how much context people should give to studies like these, where the general premise is probably broadly true, but some of the specifics have questions?

Tim: After reading some of the critiques of this study, I considered taking it out. But then I got annoyed by some of the critics who claimed that the study had NEVER been replicated when it was actually mixed results from replications. 

I read Alexander’s book, The Globalization of Addiction, and felt comfortable that there is a pretty wide body of research establishing significant environmental effects when it comes to addiction. And, in the popular press and general cultural understanding of addiction, I still think these factors are not well understood or well known. 

This is why I included the study about returning Vietnam service members and indigenous populations. Different scientists, different approaches but affirming the same general points. 

I did have another paragraph providing a caveat about the role of poverty and that if wealth were all you needed then you’d never see the same celebrity on MTV Cribs and in the tabloids going off to rehab. But there was a longer section there that didn’t make the cut. 

The best framework isn’t connecting poverty and addiction but stress and addiction. Poverty is just one of the highly stressful experiences common in our world. But so was serving in Vietnam and, while I have no first-hand experience, so is being a celebrity.  

Another interesting area of inquiry is that there is good reason to believe that intermittent access to resources is actually more stressful than a consistent lack of resources. Our bodies respond poorly to highly fluctuating environments. That area of research could have been a whole chapter on its own. The one other area I touch on it is my chapter on the “body” where I look briefly at genetic/epigenetic factors related to addiction. 

Yeah, those are good points. The idea that stress and environment can play a roll in addiction seems pretty clear, though even your own story shows that can be complicated. You got addicted due mostly to large quantities of pain medication prescribed for a real need, but the tumultousness of your life at the time can’t have helped. For any critique of this study, even Scott Alexendar ended up saying the idea that ultimately unhappy people probably do more drugs than happy people seemed to be relatively self evident.  So I think there’s something to this, though clearly it’s not the whole story. Addiction is not something that happens in a vacuum, even if there’s more going on. As they say, genetics loads the gun, environment pulls the trigger.

Alright, so that’s it for this week! Come back next week for our final post, and in the meantime enjoy this picture of me holding the actual book my brother signed for me! GETTING EXCITED!!!!


Addiction Nation: What Hurts, What Helps

This post is part of a series on my brother’s upcoming book Addiction Nation: What the Opioid Crisis Reveals about Us, discussing some of the science and stats he used throughout the books. Read the intro post here, part 1 here, or (best of all) pre-order the book on Amazon here.

Okay, so this week’s post is kind of a big topic. I think it’s fair to say that most of your book is actually about “what hurts and what helps” addiction, so this post is really just to talk about two of the interesting studies you used in the course of all of those chapters. I included one that had a pretty surprising conclusion and two that I know we discussed at length and you ended up doing some rewrites on. Does that sound good?

Tim: Perfect! And this is probably a good time to point out that this book probably took twice as long to write because of you. There are sometimes that authors have a point they want to make and so they start searching around until they can find a study that seems to back up the point they want to make. 

Instead, I really wanted to take the time to understand multiple different models and viewpoints for understanding addiction. That meant spending a lot of time with opposing viewpoints. And, when I found a study that I thought was interesting or exciting, I had the specter of my older sister looking over my shoulder reminding me to go back to the source material. 

Unfortunately, there are a lot of people out there who don’t have sisters who wouldn’t mind calling them out publicly for being sloppy with their research. In Chapter 9, I highlight the destructive game of scientific telephone that turned a small letter to the editor in the New England Journal of Medicine into a “landmark study” that Purdue Pharma used to claim that fear of opioid addiction was overblown. 

If only they all had sister’s to give them a healthy dose of neuroticism…

Note to authors: if you’re lacking a sister to keep you honest, I’m available for hire!

Alright first up, the study that was surprising. I would love to take credit for how you introduced this study, but I actually have to admit you did this phrasing all on your own. For some context, this is on page 35 after you talk about how hearing your doctor say that your addiction wasn’t your fault was so valuable to your own recovery. You say a few things about the disease model of addiction, then you say this:

But the disease model isn’t the only way to understand addiction. In fact, there are limitations. At least one study shows that alcoholics who believe their alcoholism is a disease are more likely to relapse than those who don’t.

That was some great context. So many people get concerned with making a strong statement that they forget/ignore counter evidence. At the same time, noting that it was “one study” helps give the reader some useful context about how widely this has been found. Nice job brother!

Tim: This was a big area of learning for me. When I first started learning more about addiction  I thought of there being two opposing camps. The first represented the old outdated model of addiction as a moral failing. Then there was the new wave of scientific research that showed addiction is a disease. 

While the disease model dominates addiction science, I started to read a lot of great authors and researchers who either explicitly argued against that theory or were offering important correctives to it. These folks include Bruce Alexander, Marc Lewis, Carl Hart, William Miller and Maia Szalavitz (who you first introduced me to.) While I don’t always frame what I write as a critique of the disease model, there is a lot that comes from authors and researchers who are doing exactly that. 

A scientific model is a framework that is used to understand a complex phenomenon. Models can have benefits and limitations. In theological language, you can talk about an “icon”. It is an image that points to or is analogous to a reality that transcends it. An “idol” is when you believe that what you are looking is the greater truth itself. 

The study you mention is this one here “What predicts relapse? Prospective testing of
antecedent models“. It was done on 122 alcoholics who entered recovery, then were assessed for a bunch of different things pre-treatment and then every 2 months through a year to see what types of things correlated with relapsing. Here’s the finding you mention:

I highlighted the Bonferroni adjustment part because I think that’s an important note for how rigorous this study was. The authors did a ton of comparisons/correlations to see what factors might be relevant. They highlighted both those that came up as significant (and thus might be worth exploring) but also noted that due to how many correlations they were running they really should have used a higher cutoff. This is a great way of doing initial data analysis on a topic like this and shows they were really interested in getting to the truth. So basically the disease model issue had some initial evidence but needed more study to be proven.

They then pulled all the data to look at just this factor and showed that the disease model belief was associated with relapse at every time point. This gives even more statistical weight to the theory. They also give this caveat:

The direction of causality cannot be determined from these data. It is possible that belief in alcoholism as a loss- of-control disease predisposes clients to relapse, or that repeated relapses reinforce clients’ beliefs in the disease model. In any event, endorsement of traditional disease model precepts was prospectively predictive of relapse.

That seems like a reasonable conclusion, and certainly intriguing. Not sure what we really do with that information though, other than work it in the way you did. Any thoughts?

Tim: I think this speaks to the power of language in our lives. When we, as a society, understand the ways that addiction is like a disease, we are motivated to look at the social, economic and medical factors at play. It motivates all of us to look at the public health possibilities that can make a difference like increasing access to treatment in general, MAT (medically assisted treatment), harm reduction and other social supports. 

However, it is also reasonable to assume that some people might use the language of disease and assume that puts the responsibility for recovery solely on outside factors. JD Vance, in Hillbilly Elegy, describes his own interpersonal frustration with his mother who used disease language to justify her abusive behavior toward her children. 

Maia Szalavitz, in the book you recommended to me, uses the language of addiction as a learning disorder. Recovery isn’t a simple “choice” in the way we normally use the word. But that doesn’t mean there aren’t tactics and strategies a person can learn that help them overcome and compensate for the harm addiction can cause.

Final thought on this one is that addiction comes in lots of different shapes and sizes. One direction I hope addiction research goes is not just asking, does this work for a general population? But, are there specific kinds of addictions and backgrounds that make specific approaches, language, and treatment more effective?

For example, Bill Wilson was a relatively wealthy banker who should have “had it made” but lost everything for a while because of his alcoholism. There is a whole category of people, like him, who might need to start with addiction as a disease and learning their own powerlessness. 

But what about those who had an addiction with roots in an abusive childhood in which they always experienced themselves as powerless and their world as out of control? Maybe the place they would need to start is with their own agency. 

That’s a good point. We often think of treatment as “working for people” or “not working for people”, but the effect may not be consistent across all populations. This actually an excellent intro to the next study I wanted to talk about….

There were two studies that we probably discussed more than almost any others: “The forest and the trees: relational and specific factors in addiction treatment” and “Effect of Counselor Expectations on Alcoholic Recovery“. I objected to your initial framing of the findings in these, and you ended up changing how you presented them. In these two studies, it was found that counselor empathy and counselor’s belief that the client was going to succeed impacted the outcomes for the addict. In the first study, they showed that treatment approach mattered less than the counselors “accurate empathy” level, and the second found that when counselors were told the addict was likely to succeed (on a scale that was actually randomly assigned) they did better.

Now normally this point is just made as a sort of “counselors, be better” without any further nuance. When I dug in to the papers though, I got concerned that there was a pretty big caveat. In another paper that reviewed the findings of the previous two papers (Rediscovering Fire: Small Interventions, Large Effects) the authors point out that this effect didn’t come from changing the behavior of some or even most counselors. Instead, they said:

Therapists’ experimentally induced expectancies about their clients
become self-fulfilling prophecies in treatment outcomes (Leake & King, 1977), and patient retention rates are predictable even from the tone of voice a doctor uses when talking about alcoholics (Milmoe, Rosenthal, Blane, Chafetz, & Wolf, 1967). At least two studies suggest that therapist effects may reflect the impact of a relatively small number of counselors whose clients show particularly poor outcomes (McLellan, Woody, Luborsky, & Goehl, 1988; Project MATCH Research Group, 1998). In our first study of therapist effects (Miller et al., 1980), clients seen by counselors low in empathy fared worse than those given brief intervention and sent home with self-help materials.

So basically it’s not your average counselor who needs to change, it’s actually your burnt out or otherwise low performing ones who may need to be addressed. You added this caveat to both your citations (Chapters 19 and 21), and I think it’s a stronger point for it. It’s amazing how often these two things get cited without the nuance, so I’m kinda proud you got it in there. How did you feel about it?

Tim: Annoyed. I had to go back and rewrite stuff because of you and your pesky attention to detail and facts. 

This is an area where at first I was worried that the study would somehow lose rhetorical power but the caveat, but it actually deepens the point. The important change isn’t large scale training to get a counselor from an 8 to a 9 on the empathy scale. It is a broader scale distinction between someone who is clearly burned out and has stopped caring with those who are generally empathetic and trying. This specificity in the research actually led me to want to make two broader points more strongly. 

First, I write a lot about empathy and understanding for those who struggle with addiction. This study points to the need to support those who work every day with those who struggle with addiction. First responders, medical staff, social workers and so many others on the front line are getting burned out. We need to make sure they are supported. The work they are doing isn’t easy. 

Second, while I’m going well beyond the bounds of the study now, I think it illustrates the importance of societal attitudes toward addiction. If struggling with addiction continues to be a “Scarlett A” that marks a person for life, then we create a world in which that addiction is more likely to stay with a person for life. If our fundamental assumption is that redemption and growth is always possible and that struggle and setback is not a curse of the few but a description of what it means to be human, then we are creating a world where recovery is more likely to be a reality. 

I’m glad you ended up feeling that way about it. I think that with many scientific findings, the nuanced truth is often more interesting than the initial simple point you were going for. Life is messy, so is the data, as I always say. (Actually I think I made that up just now, but I like it and it may be my new thing.)

Alright, I think we’re done here! Next week we have even more debating to do, as we’re going to cover two studies that actually have produced a lot of debate in the popular press. Hope you’ll join us!