Wednesday, 26 June 2013

Accuracy vs. Stigma: Is There a Conflict?

Another day another paper (1) examining the links between stigma and the public understanding of mental health problems. The paper (a series of meta-analyses) concludes that "biogenetic explanations" can exacerbate stigma by increasing people's "pessimism" about the outcome of psychological disorders. On Twitter Keith Laws questioned the implications of the message:

Those who responded to this question on Twitter pointed out correctly that it is "absurd" and morally problematic to ignore or suppress the truth about the cause of mental disorder in favour of the narrative you want to tell. I agree, but these answers don't do justice to the most interesting possible ramifications of the research. In their conclusion to the paper, the authors make it fairly clear that they are not advocating the promotion of inaccurate accounts:
"Mental health professionals should not misinform their clients and the public by withholding information about the biogenetic factors that underpin psychological problems." (emphasis mine)
Unfortunately, the waters muddy somewhat when it comes to describing what they are advocating:
"However, our findings indicate that this must be done with considerable caution. Explanations that invoke biogenetic factors may reduce blame but they may have unfortunate side-effects, and they should not be promoted at the expense of psychosocial explanations, which appear to have more optimistic implications." 
What the second half of this passage sadly misses, in its haste to decry the dominance of "biogentic factors", is that the best explanations of the causes of mental health problems would accurately communicate the complexity of genetic causation. It is this complexity that can easily get lost in public debate and everyday healthcare. Having a genetic predisposition to a particular problem doesn't always mean the same thing in the public imagination as it does in reality.

Biology is one determinant of our thoughts, feelings and behaviour; at the same time we retain some quantity of agency (possibly itself biologically determined, but let's steer clear of that philosophical rabbit hole for now), which we are able to exercise to change them. This capacity is not limitless and it varies with the nature of mental health problems, but it is real. People are changed, to some degree, by how they think of themselves (this is what is meant by Ian Hacking's idea about the "Looping Effects of Human Kinds") and if they weren't, there would be no point in any psychotherapeutic intervention.

We can't know very much from this paper about the nature of the disorders or the explanations that are being studied, but it does raise two possibilities that should be further explored. When people with mental health diagnoses attribute their problems to "bio-genetic causes" they may be 1. failing to do justice to the richness of what this really means and 2. buying into an unwarranted therapeutic pessimism that impacts on prognosis.

I'd be among the first to point out that this sort of research gets hijacked and over-simplified by well-meaning advocacy groups who just want to replace one narrative with another, but the fact remains that what it means for genes to have an impact on behaviour is frequently misunderstood. Highlighting the potential public health ramifications of overly simple, overly certain forms of understanding is an important part of public science communication.

1: Kvaale, E. P., Haslam, N., & Gottdiener, W. H. (2013). The ‘side effects’ of medicalization: A meta-analytic review of how biogenetic explanations affect stigma. Clinical Psychology Review.


  1. Thanks for addressing my essay question Huw!
    Just a few observations about the Kvaale et al meta analysis:

    The authors declare that: Biogenetic explanations reduce blame, but induce pessimism about recovery. By contrast, biogenetic explanations do not affect desire for distance and a very small effect on dangerousness is eliminated because publication bias.
    So, biogenetic accounts have the positive effect of reducing blame, but the 'seemingly' negative effect of pessimism about recovery.

    It is a very mixed picture, but contrary perhaps to you, I think they are advocating a political over scientific priority viz the explanations that are given to patients - they wildly speculate that biogenetic accounts "could seriously impede the recovery process" - with no evidence at all presented!

    Let's have a quick look at Kvaale et als pessimism findings:
    "There was evidence that the findings were heterogeneous (Q = 38.915; p = 0.001; I2 = 61.455). The findings from subgroup analyses (Table 4) suggested that biogenetic explanations induce pessimism among students and community members, whether they are of genetic or other types, in within-subjects designs, and in between-subjects design when contrasted with psychosocial explanations. However, there was no evidence that biogenetic explanations induce pessimism in between-subjects designs when they were contrasted with no explanation or ambiguous/multifactorial explanations. Overall, despite evidence of unexplained heterogeneity in most subgroups, the subgroup analyses show that biogenetic explanations increase prognostic pessimism across most contexts."

    a) 'heterogeneous' is the word - the reported I2 indicates 'large' heterogeneity and this is apparent in the forest plot (their fig 4)
    Indeed, it is obvious in Figure 4, which shows that only 5 of 16 comparisons on pessimism indicate significant pessimism with biogenetic explanations - less than one-third of studies is hardly convincing!

    b) the subgroup analyses show that biogenetic explanations do not induce pessimism for between subject designs when contrasted with no explanation or ambig/multifactorial explanations

    c) significant 'pessimism' is recorded only for within-subject designs (pre-post) and when contrasted with psychosocial explanations

    d) Bennett et al (2008) produced the largest effect size - so I thought to check it...and its quite revealing.
    First, although the genetic explanation fares significantly worse than the 'environmental' account, but the genetic account has a mean above the 12.5 mid-point cut-off - as the authors say "scores below this indicate a negative attitude and scores above 12.5 indicate a positive attitude" - so the biogenetic account is still viewed as 'positive' viz potential for recovery.
    Second, it is difficult to know what the 'genetic' and 'environmental' conditions mean in this study. The environmental and genetic accounts are identical - except that the genetic account also contains the following: "Doctors believe that Simon’s illness occurred due to a
    genetic predisposition towards schizophrenia within his family. He has been living this way for 6 months."

    So, the genetic account = the 'environmental' account plus this info. Interestingly the 'environmental' account offers no explanation at all for the problems.
    Having looked at the largest effect size in the meta-analysis, one might then reasonably doubt its validity or how it is interpreted. Removal of that study could of course reduce the overall effect to ns (I didn’t have time to check any of the other 4 significant studies, but they may be worth further detailed examination)

    Of course, it may be that biogenetic accounts do not increase pessimism at all, but that other (psychological accounts) increase optimism - some might say...with minimal justification!

    1. Presumably there's a danger of response bias here too. Patients encouraged to believe that they have greater control over their symptoms may be more likely to report improvements, but people often like to report that they are 'good'. Providing patient's with a primarily biological explanation of symptoms could just lead to more honest responses.

      Regardless, any attempt to 'manage' patients with different explanations of their illness should only be done with informed consent, which would require an honest description of the available evidence.

  2. Thanks both of you for your comments. Keith, I think you are right, the fact that these authors have chosen, with very little critical discussion, to group these four variables together and call them "stigma" is suggestive of a forgone conclusion looking for an evidence base. The content of their conclusion also points to a prioritisation of one sort of causal narrative over another, with minimal concern for what the evidence says about the truth. My post was an attempt to engage with the most favourable interpretation of their rather murky recommendations; the question of how one frames health information is interesting, and all the more so in disorders of complex cause.

    A detailed examination of their evidence reveals the flaws in an overly simple conclusion about "stigma" and pessimism. In fact, your analysis leaves me feeling more optimistic about people's pessimism; suggesting it is less swayed by the "deterministic" nature of bio-genetic medical explanations than the authors fear. This is just as well given that we can't simply draw on our personal preferences to decide what the truth is about any given problem.

    @eindt, you raise an interesting question about the ethics of the study's recommendations. I'm not sure how one could both obtain informed consent and manage patients' expectations by deliberately distorting the truth; care to elaborate?

    This paper, and the whole field of decision-making in psychology, opens an interesting ethical issue; is it ever OK to mislead patients for their own good? The paper is premised on the bet that the answer is yes; that prognosis in mental health is affected by the nature of causal information. I think there would need to be some pretty convincing evidence about the benefits before I felt such a move was justified, and this ain't it.