Just weeks before the new diagnostic manual is released, NIMH cites “lack of validity” and says “patients with mental disorders deserve better.”
In a surprising announcement just weeks before the scheduled release of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), the US government’s mental health research arm has announced plans to stop using DSM categories in its work.
The National Institutes of Mental Health (NIMH) is the single largest funder of mental health research in the world. In his announcement last week explaining the decision, NIMH Director Thomas Insel wrote that “Symptoms alone rarely indicate the best choice of treatment.” While diagnositic categories based on clusters of symptoms — like the categories in the DSM — provide a common language that mental health care providers and researchers can use, these categories are more about that consistency in usage (i.e., reliability) than they are about clinical or research validity. Such symptom-based diagnosis, Insel argued, is now outdated in most other areas of medicine.
So NIMH is scrapping DSM categories when funding future research and is developing its own framework to “transform diagnosis by incorporating genetics, imaging [such as the PET scan pictured above], cognitive science, and other levels of information to lay the foundation for a new classification system,” according to Insel. For now, the new classification system is just a framework for research. But the clear intention is to make the DSM obsolete.
As a family therapist, I find the DSM-5 categories to be both useful and limited in the ways Insel described. They are a good tool for communicating with other professionals, but not especially useful for clients, beyond establishing that others may have similar suffering. I like the idea of a new classification system for mental disorders based on biology and verifiable laboratory tests (indeed, I think it’s overdue), and think it quite likely that such a system will strongly support systemic and relational therapies. The brain is a social organ, after all, and therapy creates verifiable physiological changes in the brain.
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Your comments are welcomed. You can post them in the comments below, by email to ben[at]bencaldwell[dot]com, or on my Twitter feed.
Stanley, one of the developers of the popular PREP program, offers a more optimistic view of the Building Strong Families study’s Oklahoma City data.
I posted last week about the disappointing 3-year results of the Building Strong Families study, a major study of relationship education involving more than 5,000 families at nine sites around the country.
Scott Stanley, one of the developers of the PREP relationship education course and a (quite deservedly) well-respected name in relationship and marriage research, wrote me in response, offering a more optimistic look at the site-specific data from the study’s Oklahoma City location. He kindly granted permission for me to post his letter, in its entirety, here. The emphasis added is mine and I’ve plugged in some links, but otherwise left his writing unchanged:
Just read your post on BSF in OK. You raise important points like those raised by others.
I wanted to argue the other side a bit, particularly about the Oklahoma finding at 36 months in the BSF study. I won’t take the space to do it fully in this comment, but I would refer your readers to a blog post I did on the 36 month findings in light of a similar critique by Andrew Cherlin in the last week of 2012. The piece (my blog piece) links to Cherlin’s critique and several other interesting pieces that your readers may appreciate. Andrew Cherlin has read my piece on his critique, and I believe he has changed his mind about the importance of the stability finding in OK at 3 years out. (see links here and below)
The key point is simply this: As I explain in my piece, what you refer to a small difference in family stability is actually a 20% increase in family stability for these most vulnerable families 3 years later (49% in the program group vs. 41% in the control group, of families where the children born lived continuously with both parents over the three year follow-up period, which is a 20% improvement of the intervention group over the control group).
What you, as so many others, are likely unaware of is that the evidence for most government social programs (or other programs for that matter) is dismal (I also make this point in my piece). I give some suggestions for how people can look such things up in my piece as well.
This OK BSF finding is actually rather extraordinary, and it is unlike findings in most all evaluations of government programs, especially evaluations of initial efforts–it is significant, relatively large (this is not a small difference on such an outcome in a policy study), and it is on what is easily argued the single most important type indicator relevant to this study context and family policy. It is also not at all unusual to get earlier impacts on things that can change more immediately that may (as in this case) set up longer term, more important outcomes.
You may not be impressed with that finding, but there are those who know government evaluations quite well who find it remarkable. However, it is true that among people who have been critics of these fledgling efforts, the desire has clearly mostly been to focus on the pooled results across sites where the story is not positive.
In addition to the points I make in my blog in commenting on Andrew Cherlin’s piece, I would add these points here about the finding you dismiss: This impact on a hard indicator of an outcome (family stability) of prime interest three years after the intervention (1) happened in the only program to deliver a substantial dose of intervention to a high percentage of couples in the intervention group, (2) happened in the only program to have many significant impacts on relationship quality variables at the intermediate stage of evaluation, and (3) happened in the only site that also had a stability findings at the prior time point.
The link to my comment on Andrew Cherlin’s piece is here: http://slidingvsdeciding.blogspot.com/2013/01/family-stability-and-relationship.html [There is also a full disclosure comment at the end of that blog piece.]
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My thanks to Dr. Stanley for his thoughtful email and the permission to repost it here.
Your questions and comments are similarly welcomed. You can post them in the comments below, by email to ben[at]bencaldwell[dot]com, or on my Twitter feed.
I’ve mentioned here in the past that estimates of the divorce rate are notoriously difficult to make well. There’s some inherent guesswork involved, unless you just wait for an entire annual cohort of marriages to reach either death or divorce. And that would take a long time. To simply compare a given year’s number of marriages with that year’s number of divorces is to compare different cohorts, making estimates of the divorce rate done that way wildly inaccurate.
Instead, demographers and social scientists do the best-educated guesswork they can based on past data and current trends. (Government data does not do forward-looking prediction, but rather focuses on divorces that have already occurred.) As new divorce-rate studies are released, you can keep up with them on the Divorce Statistics and Studies Blog. Reasonable people can disagree about the best scientific ways to determine the divorce rate, and there is probably some value to several different approaches. So news reporters, talking to scientists, will sometimes come up with different numbers, and that’s okay. They tend to wind up in that least the same neighborhood. (That neighborhood, by the way, projects the divorce rate for people getting married this year in the low 40s, percentage-wise.)
What is not okay — what shows rather extreme laziness in news reporting — is to ask a scientific question of someone who is in no place to answer it, and then not bother to check the accuracy of their statement. What’s even worse is when that person can directly benefit from providing misinformation.
So it went with CNBC.com in September, when reporter Cindy Perman opened her story about affairs (reprinted by USA Today) by providing an estimate of the divorce rate — a measurable, objective, scientific thing — helpfully volunteered by the director of the American Academy of Matrimonial Lawyers.
The problems with this are so obvious that I’m stunned the article was printed. I don’t even blame the lawyer, at least not any more than I blame spokespeople from the National Association of Realtors for suggesting that any economic news, good or bad, means it’s a great time to buy a home. They’re lying, but that’s their job. I just wish reporters would subject those claims to actual scrutiny.
It’s a topic taken on quite well by Tara Parker-Pope in her book For Better, which dissects the science surrounding a number of elements of marriage and divorce.
Any time you see the lazy and wrong estimate that half of all marriages end in divorce, go ahead and — nicely — say something to correct it. I suppose as a couples therapist I might also benefit from inflating the divorce rate, but I’d rather let facts speak for themselves — and I think effective, widely-available therapy would bring down the divorce rate even further. It would save us all some money, too.
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If you know of egregious repeat offenders with the half-of-all-marriages-end-in-divorce nonsense, email examples to me at ben[at]bencaldwell.com, post a comment below, or send me a link to it on Twitter. Of course, other comments are always welcome.
Newlywed couples, once thought to consistently experience a quick drop in satisfaction, actually often remain just as happy (or close to it) over time, according to a recent study. For couples who do get worse, the reasons can be evident early on. The study’s author comments.
According to a study published late last year in Family Process, the rapid decline in marital satisfaction following a couple’s wedding — generally thought to be quite normal — is actually something many couples manage to avoid. The “average” couple experiences a drop because for some couples, satisfaction declines precipitously. But many couples, including the most satisfied, actually remain fairly stable in their marital happiness.
Justin Lavner and Thomas Bradbury at UCLA monitored the progression of marital satisfaction over time among 232 couples, starting soon after the couples were married. They found that couples’ progressions in happiness clustered into five different groups. For the three groups who started out the most satisfied, they tended to stay at about the same level (or decline only minimally) in the four years after their wedding day. For the two groups who started married life less satisfied, things tended to get significantly worse with time — dragging down the population average. As might be expected, among those five groups, divorce rates varied significantly, with the groups whose satisfaction declined over time far more likely to split up.
I asked Lavner a number of questions via email about the study and its implications. The following has been edited for length and clarity. My questions are in bold, and Lavner’s responses are in plain text.
BC: How would you describe your findings in plain language, and what surprised you the most?
JL: We set out to examine one of the most often-cited “facts” about marriage — that satisfaction declines as marriage goes on. We wondered whether this average pattern obscured different patterns that couples experience, and if so, what factors characterized people who had different patterns and how these patterns related to later divorce rates.
We found that although the average pattern is indeed one of declining satisfaction, there are a few different patterns that better characterize newlyweds’ marriages over the first four years, including very high, stable trajectories, as well as marriages that start off low in satisfaction and experience large declines very quickly.
Spouses with negative patterns could be distinguished by a range of factors as early as six months into marriage. These included their personality characteristics, how they interacted with their partners during a 10-minute problem-solving discussion, how much aggression they reported, and how much stress they had in their lives. Importantly, these early patterns related to ten-year divorce rates: couples with the worst trajectories had rates of divorce that were more than four times as high as those couples with the best trajectories!
I think the finding that surprised me the most was how early these differences emerged. All of the factors that distinguished between patterns were found at six months into marriage, and some couples were already dissatisfied by then. To me, this suggests that there is a lot more variability in couples early in their relationships than we had previously thought.
BC: I was amazed at the wide disparity in divorce rates for couples based on their marital satisfaction trajectories. How do you think this data can be used to inform and improve treatment for couples at risk of divorce?
JL: We often hear that satisfaction declines as marriage goes on. While that may be true on average, what’s really powerful about this data is that they highlight how couples vary widely in the likelihood their relationships will deteriorate, and also give us a better idea of what types of characteristics make couples more likely to experience negative marital trajectories. Using this kind of data, we can be more targeted in our relationship education interventions and direct services toward those couples who need them most.
BC: One of your key findings is that for both husbands and wives, Personality, Stress, Aggression, and Positive Affect distinguished trajectory groups. What does this suggest for identification and treatment of at-risk couples? Do we need multiple forms of therapy geared toward couples with different traits?
JL: These findings indicate that those couples with the greatest distress (and at highest risk of divorce) are characterized by a full range of negative personality traits, experience more stress, report more aggression, and demonstrate lower levels of positive affect. This suggests that focusing on any one factor in treatment will not be sufficient: for example, we cannot focus on negative communication without recognizing how couples’ personalities and stressful environments will limit the benefits they can achieve from communication training.
I see this not as evidence that we need multiple forms of therapy geared toward couples with different traits, but more that our interventions need to continue recognizing and addressing the multiple factors that affect couples’ lives. My guess is that it is likely to be quite difficult to fully “match” traits with specific forms of therapy to increase success when there are multiple factors at play.
BC: You mention that the data holds some promise for early identification of at-risk couples, but temper this pretty heavily, saying that “it is nonetheless discouraging because it suggests that the task of strengthening these relationships must address a wide range of possible causes for the distress, some of which may be difficult to modify.” Could you expand on this?
JL: Not only are the couples who go on to experience distress those with multiple risk factors, but some of these risk factors are likely to be quite stable, particularly their personalities and the stress they encounter. We also identify this risk very early in the relationship, which means that by the time couples present for therapy (which they are notoriously slow to do), these distressing circumstances have likely plagued them for several years.
That said, I’m still optimistic about therapy possibly changing these trajectories and ultimately reducing divorce risk for these couples, particularly if intervention occurs early and addresses multiple factors of couples’ lives (as integrative behavioral couple therapy and enhanced models of cognitive behavior therapy now do, among others).
BC: You briefly talk about public policy, suggesting that broad-based marriage promotion programs are not likely to be as successful as programs targeting “the challenging circumstances and chronic stresses likely to impede relationship maintenance.” In your ideal world, what would a program designed to reduce divorce look like?
JL: Ideally relationship education programs need to do more to address the complete gestalt of couples’ circumstances — their particular ways of interacting, their personal histories, and how the contexts they live and work in affect their relationships. How this would play out is still an open question, but could include modules such as personality characteristics and emotion regulation strategies, or work stress and how that affects home life, along with stress management techniques. Special attention needs to be given to recruiting and retaining high-risk couples, as this presents the best opportunity to prevent distress and divorce.
I would also like to see more attention given to factors that can promote relationship stability. These findings indicate that many couples have stable levels of satisfaction over time, so how can we help them maintain and even enhance their relationships? For example, Art Aron and his colleagues (Aron, Normon, Aron, McKenna, & Heyman, 2000) have suggested that participating in novel activities can enhance couples’ relationship quality. Our programs must do more to promote relationship functioning, in addition to helping prevent deterioration in relationships.
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Comments are welcome below. In addition, you can email me at ben[at]bencaldwell.com, or help prevent deterioration in my Twitter feed.