Eur Child Adolesc Psychiatry (2014) 23:247–255 DOI 10.1007/s00787-013-0483-x
REVIEW
Translation gone awry: differences between commonsense and science Michael Rutter • Tytti Solantaus
Received: 16 March 2013 / Accepted: 3 October 2013 / Published online: 19 October 2013 Ó Springer-Verlag Berlin Heidelberg 2013
Abstract A general assumption is that science is just organised commonsense. It is noted that translation involves a two-way pathway between basic laboratory science and patient care, and that some scientific findings have implications for prevention rather than treatment. A succinct critique follows on the key features that differentiate science and commonsense. The main part of the paper discusses six rather different examples of translation that went awry because people treated science and commonsense as equivalent. Examples based on empirical evidence of translation going awry include (i) the claim that only early intervention can bring lasting benefits; (ii) the claim that the main policy goal for children should be the elimination of all stresses; (iii) the claim that exposure in utero to maternal smoking causes ADHD and conduct disturbance; (iv) the claim that tax benefits should be used to encourage couples to marry; (v) the effects of profound institutional deprivation are similar to those of any adversity; and (vi) environmental effects are largely independent of genetic influences. Much of science is ‘unnatural’ in the sense that technical tools (such as imaging or DNA) are employed, or because animal models are used, or because unusual comparisons are made. Science cannot be based solely on an inductive process; rather, there must be some
M. Rutter and T. Solantaus are joint first authors. M. Rutter (&) MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, de Crespigny Park, Denmark Hill, PO 80, London SE5 8AF, UK e-mail: [email protected] T. Solantaus National Institute for Health and Welfare, University of Tampere, Helsinki, Finland
form of experiment and the testing of two or more alternative explanations. Translation needs to be based on top quality science and an appreciation that even the best science needs to take account of multiple strategies and multiple evaluations. Keywords Induction Hypotheses Animal models Imaging Genetics Translation Abbreviation G9E Gene-environment interaction
Translation There is a widespread and entirely reasonable wish to translate scientific discoveries into patient benefits (see [46], but the assumption that the interplay between science and practice is merely a translational pathway from basic laboratory science to patient care is simplistic [55, 77]. First, there are numerous examples of the starting point being a clinical observation, as with the foetal alcohol syndrome, in which the clinical observation of particular malformations in the offspring of mothers with chronic alcoholic problems led to laboratory studies using animal models. Second, some scientific findings have implications for prevention rather than treatment. Doll and Hill’s [17, 18] evidence that smoking markedly increased the risk for lung cancer is the best known example of this kind. Another example is the findings of intergenerational transmission of mental illness [83], which call for preventive efforts for families and children [86]. Third, in many cases, translation relies on an extended multi-step pathway involving several quite different types of science. The lipid story on cholesterol effects on coronary artery disease and the benefits
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from statins is the most obvious example here [87, 88]. Fourth, this multi-step pathway frequently extends over a very long time period [19] and it follows that a key issue concerns the decision of when the scientific evidence is sufficiently solid for it to be reasonable to proceed with translation [1]. In that connection it has to be realised that a decision not to act constitutes an act. There are penalties for both acting too soon and not acting soon enough. In the remainder of this essay, we focus on the fruits of science in terms of understanding causal processes, but it is obvious that the findings are equally relevant to translation matters. In particular, there is a great need for hypothesis-based bridging studies that constitute experimental clinical medicine as shown by ‘proof of principle’ research.
Method Characteristics of good science Medawar [49, 50] provided a witty, but scathing, critique of the idea that there is one pathognomonic scientific method and he also argued that scientific papers are fraudulent in the sense that they misleadingly imply that scientific discovery is just an inductive process that begins with simple unbiased observations and that these lead inevitably to deduced explanatory hypotheses. They do not because no observations are unbiased; they are influenced by our expectations of what we should observe. Even more crucially, however, it is not logically possible to arrive with certainty to a generalisation that contains more information than the observations upon which the generalisation was based. He argued that what was distinctive about science were three features: (1) a concern to test for possible invalidations or falsifications [57, 58], (2) an attempt to reduce findings to some simplifying explanatory process; and (3) a focus on testing causal inferences [28]. The last would usually involve some sort of experimental approach. In the case of psychology and psychopathology there would often be the need to use ‘natural experiments’ that pull apart variables that ordinarily go together [65, 68]. The combination of these features led Wolpert [97] to argue that science is inherently ‘unnatural’ and not at all simply organised commonsense—thereby taking issue with distinguished writers such as Thomas Huxley and Alfred Whitehead who claimed the opposite. Wolpert gave numerous telling examples—mainly from laboratory science or physics—showing the differences between science and commonsense. Commonsense is based only on inductive reasoning stemming from observations rather than experimental testing. By contrast, science requires some form of experimental testing and some contrasting of alternative explanations or mechanisms. Commonsense
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suffers from the limitations in what people can observe—as shown by the historical example of assuming that the earth is flat because it appears to be so when we look out of the window. The same applies to the belief that the earth is the centre of the universe. However, the key point here is that in society today there is an inadequate appreciation of the numerous sources of systematic bias in commonsense reasoning [36]. Here we follow Wolpert’s arguments but do so from fields relevant to psychology and psychopathology. However, first we need to note the views of other scientists [72]. Thus, Merton [51] proposed that three main features characterised good quality science. First, a search for principles that could be generalised beyond the sample studied. Ordinarily, this would require research that spans several samples. It cannot be done by inductive reasoning alone. Second, a conceptualisation of the meaning or mechanism thought to underlie the findings or observations. This is where hypotheses come into the frame. Medawar expressed this in terms of telling a story—thus emphasising the difference in approach needed for creating a hypothesis and for testing it. Both are essential elements of science. Note that hypotheses are not the same as predictions (despite numerous researchers treating them as if they were). There is no interest in knowing whether the researcher guessed the results correctly; the interest must lie in the putting forward of some sort of underlying meaning or mechanism. Merton’s [51] third criterion was an attitude of scepticism—a norm of questioning, challenging and considering alternative counter-explanations that must be examined against the proposition being put forward. The criteria suggested many years later by the US National Research Council [53] differed in detail but provide much the same message as did also the British Academy Working Group Report [6] report on Social Science and Family Policies. Against that background we turn to six rather different instances in which it seems that translation has gone awry because people have treated science and commonsense as equivalent. The first four are examples where the translation process has been fairly straightforward from scientific findings to decision making and general understanding. The last two are examples of more complicated research processes involving misleading inferences made by both scientists and decision makers.
Results Examples of translation going awry Only early intervention can bring lasting benefits The scientific basis for this claim has a very distinguished pedigree in Donald Hebb’s [27] book proposing age-
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dependent plasticity of the nervous system. During the 1950s and 1960s this was followed by experimental evidence from rodent studies that enrichment of the environment could lead to structural changes in the brain in juvenile rats [2]. Because the early research on the effects of environmental enrichment and deprivation was undertaken immediately post weaning at 25 days of age, it would seem to follow, first, that early interventions could lead to lasting brain changes and, second, that this was because the interventions occurred during a period of rapid brain growth. The Hubel and Wiesel findings [32] on the importance of early visual input for the normal development of the visual cortex appeared to confirm the claim on early intervention. This commonsense inference was also seemingly supported by the various human studies of interventions in the early years leading to cognitive gains [8]. The policy recommendation followed that resources be taken away from older children and adolescents and transferred for use in the early years [31]. The argument had three main roots. First, prevention is more effective than cure; second, lasting benefits must come from changes in the brain; and, third, that brain development is maximal in the first 3 years (in humans). Nevertheless, the commonsense application of the science was mistaken. The Hubel and Wiesel findings, showing a critical period for visual impact, have been amply confirmed [4], but the critical period for this particular form of experience-expectant biological programming [25] does not apply generally [75]. Most crucially, although the early rodent studies of the effects of environmental enrichment and deprivation were performed with juveniles, later ones included both younger and older adults with findings that were broadly similar in pattern at all ages [62]. That is, the particular brain changes and the specific parts of the brain affected were the same at all ages, even though the magnitude of effects was often larger in juveniles and the brain effects occurred more rapidly. In addition, a large scale prospective structural brain imaging study on humans [24] as well as post-mortem findings [33] have shown that brain development continues right into adult life, with adolescence constituting a period of particular change [82]. Even more crucially, there are neural changes resulting from environmental influences in adult life. This was shown, for example, by the evidence that taxi drivers in London (who had to pass the rigorous ‘knowledge’ exam regarding routes) had a larger posterior hippocampus than controls [45]. Similarly, musicians were found to show neural differences associated with intensive practice [21, 35]. An experimental study of juggling [20] confirmed that experiences truly caused the neural changes. Other research has similarly shown behavioural changes as a result of experiences in adult life—such as the effects of marriage in leading to a reduction in crime [80] or
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beneficial effects of US military service in individuals from a disadvantaged background who entered the Army when young [81]. Note that the evidence also indicates that risk experiences may also begin for the first time in adolescence or adult life [7, 40]. Finally, it has been found that the benefits of early intervention tend to be contingent on the interventions continuing into the school years [8]. Putting all the scientific evidence together, it is clear that the early intervention claim is mistaken. It may be important to intervene early because the early years come first and may influence later experiences but later experiences can be very influential in affecting both behaviour and brain structure. Moreover, most lasting benefits from positive early experiences fade with time unless the positive experiences continue [14]. The situation is closely paralleled in the field of social development. It has been argued that secure attachment in infancy constitutes a powerful influence on later social development but although long-term longitudinal studies confirm the importance of social experiences, they, also, find very little prediction from infancy [26]. The commonsense claims were misleading because they failed to take into account the totality of the evidence from both human studies and animal models. The main policy goal for children should be the elimination of all stresses This commonsense assertion is based on the extensive evidence that the experience of stress causes very substantial mental health risks [40]. Moreover, the use of natural experiments (such as twin studies and twins discordant for the experience of abuse [39] has indicated that this is highly likely to reflect a causal influence. Furthermore, it has been found that even minor adversities can have important ill-effects and that their occurrence may sensitize the individual to become even more vulnerable to later stress experiences [69–71]. It is easy to understand why this has led both policy and practice to focus only on risk and elimination of risk. It has led informed parents to make extensive efforts to shield their children from stress. Once again, however, the totality of the scientific evidence suggests that an elimination of all stress may not be in children’s best interests. In the first place, dealing successfully with challenge is an essential feature of normal development [78]. Clinical and epidemiological evidence show that successful coping with stresses can be strengthening [71]. For example, Elder [22] showed this in terms of adolescents taking on unusual responsibilities during the time of the 1930s economic depression. Lyons’ experimental research with squirrel monkeys [44] led to the same conclusion. Brief weekly separations led to improved
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physiological functioning and greater resistance to stress. Note should be taken of the parallel with infections. Resistance to infection comes about through exposure to infections (either naturally or through immunization) and not through their avoidance. Similarly, the behavioural treatment of phobias shows that avoidance of the feared object or situation makes it more likely that the phobia will persist [47, 59]. There is also a parallel with asthma in which the avoidance of infections increases the risk for asthma and other forms of atopic disease [48, 54, 95]. It might be supposed that the appropriate inference should be that minor stress may be a good thing but severe stress and adversity is always detrimental. However, the evidence shows that even terrible experiences may sometimes be strengthening provided children can cope successfully [93]. Conversely, for unusually susceptible children, even milder stresses may carry risks. Perhaps, the main lesson should be that challenge is good and the focus needs to be on fostering successful coping in children and families in adversity. This should also be a goal in preventive interventions. The claim that exposure in utero to maternal smoking causes ADHD and conduct disturbance This example is somewhat different in that the claim came from researchers. At first sight, the claim seems well based. Careful statistical control for possible confounding variables was undertaken to ensure that the statistical association might be causal. A bringing together of the findings from several studies convincingly showed an apparently true effect of smoking exposure in the womb on ADHD [43]. The plausibility of the claim was much strengthened by the evidence from animal models, as well as human epidemiological studies that there was a true effect in lowering the birth weight (thus providing a physiological basis). Nevertheless, the Academy of Medical Sciences [1] report clearly indicated the major difficulties involved in statistical control of confounding variables. Most crucially, three different types of natural experiment (the assisted conception design, the comparison of siblings from different pregnancies and the Children of Twins (CoT) design) all showed that the association was probably largely a reflection of genetic mediation rather than environmental risk mediation [90]. The assisted conception design neatly illustrates what is involved. Pregnancies using sperm donation do not remove the genetic link between mother and child, whereas egg donation does. A comparison of the two showed that the maternal smoking effect was found only in the former—indicating that most (but not necessarily all) of the association reflected genetic mediation. The commonsense claim was plausible but almost certainly misleading.
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Tax benefits should be used to encourage couples to marry The relevant scientific background is the finding that the break-up rate associated with cohabitations is substantially higher than those associated with married couples in the UK and in the USA [41]. This has led to the inference that strong incentives should be provided for marriage, including the introduction of tax benefits [96]. At first sight this seems a justifiable commonsense inference from the scientific evidence but it is not, for several different reasons. First, cohabiting couples are widely heterogeneous. Some are individuals who have made a committed relationship but have decided not to marry but, also, there are many who are living together without any kind of longterm commitment [41]. Second, there is evidence of substantial selection into marriage—meaning that the differences between married and cohabiting couples are likely to reflect who chooses to get married rather than marriage as a circumstance [16]. Third, Australian evidence indicates that it is dubious whether financial incentives actually make much difference to whether or not people choose to get married [6]. Fourth, most crucially, marriages in the USA are more likely to break down than cohabitations in Scandinavia [13]. Fifth, marital breakdown may, dependent on circumstances, either improve the situation for children or make it worse [15, 61]. We may conclude that stable, loving family relationships are indeed beneficial for children but these do not necessarily have to involve marriage and the findings in America make it quite clear that, at least in that country, marriage is not necessarily associated with stable longlasting relationships. The effects of profound institutional deprivation are similar to those from any adversity This example differs from the first four examples for three rather different reasons. First, the initial science base was weak because it relied on findings regarding different forms of stress and adversity other than institutional deprivation [29, 30, 85, 91], and on findings about the physical recovery of children experiencing profound deprivation including subnutrition [84]. The problem with the first is that it involved assuming that institutional deprivation would have effects that were no different from other forms of stress and adversity. That was a most uncertain generalisation. The problem with the second is that the studies concerned physical growth and cognition, there being no measures of social functioning. The second unusual feature of this example is that none of the findings of the actual effects of profound institutional deprivation on outcome were predictable on either the basis
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of commonsense or the limited research evidence at the start. It might be supposed, on commonsense grounds, that although there were individual differences in response to adversity, these would be either absent or at least much less in the case of really profound and prolonged adversities. The study of institutional deprivation, however, showed that that was not the case [79]. There was no appreciable narrowing of the range of responses with the most severe and prolonged deprivation. The third unusual feature is that the inappropriate and misleading inferences were made by scientists as well as by policy makers. Thus, many studies mainly used questionnaire measures such as the CBCL which included no measures that could have picked up particular abnormalities as actually found. Similarly, the meta-analysis undertaken by van IJzendoorn and Juffer [94] was not only based on cross-sectional measures but also did not include measures of the features later found to be important. The English and Romanian Adoptees (ERA) Study followed children from the age of 4 years, shortly after adoption, up to age 15 years (in some cases later than that) [73, 74, 79]. The findings showed that there were no measurable ill-effects if the institutional deprivation did not last beyond the child’s age of 6 months. However, there was a marked rise in the rate of serious deficits if the deprivation lasted to the age of 6–12 months or later [42]. All the deficits concerned highly unusual behavioural patterns and not at all the usual range of emotional and behavioural disturbances that had been expected. It had been assumed that deprivation would result in an increase in all forms of psychopathology, but this was not the case with profound institutional deprivation, unless there was also one of the unusual patterns. These unusual patterns included quasi-autistic features, disinhibited attachment, and inattention/overactivity, as well as cognitive impairment. Commonsense, as well as previous research, suggested that the effects of the institutional deprivation should, to a considerable extent, fade away with time. In fact, the findings showed that the effects were as strong at 15 years as they had been at 11 years and at 6 years—there being no diminution over time. Because uncertainties as to whether these unusual patterns might be more a function of subnutrition than psychosocial deprivation, further analyses were done on the group who showed no evidence of subnutrition, as indexed by physical growth [74]. The evidence was clear-cut in showing that, if anything, the findings were even more striking in the absence of subnutrition. The findings also showed a difference between the effects of subnutrition and ‘pure’ psychosocial deprivation with respect to head growth (which other research has shown is a good index of brain growth). Whereas the subnourished group showed markedly diminished head growth even
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when the deprivation had not lasted beyond 6 months, there was no diminution in head growth in the ‘pure’ psychosocial deprivation group until the deprivation had lasted longer than that. During the years between 4 and 15 years there had been a substantial catch-up in head growth but at 15 years it still fell well short of what occurred in non-deprived populations. Policy makers had no better basis for their inferences but they assumed that ordinary services would know what to do with any problems presented by the children after adoption into UK families. Also, they assumed that recovery was likely to be swift if it was going to take place. Accordingly, there were no tailored services provided in the UK for families after the adoption of children from profoundly depriving institutions in Romania. Environmental effects are largely independent of genetic influences The last example, in common with the institutional deprivation example, initially included no satisfactory basis for scientific inferences. There was evidence that individuals differed markedly in their response to both acute stress and serious adversity [66]. Also, scientific reasoning (although not commonsense) suggested that genetic influences might play a part in susceptibility to the environment [63]. However, the main genetic thinking focussed on genes that provided a liability to disorder, rather than on genes affecting environmental vulnerability. Indeed, the broad message from quantitative behavioural genetics was that gene–environment interactions were sufficiently uncommon and sufficiently weak that they could safely be disregarded in statistical analyses [56]. That was based on twin studies in which there was no information on the individual genes and not much information on specific environments. There were scientists who queried these negative claims on the grounds that gene–environment interactions were likely to involve specific genes and specific environments, rather than anonymous genes and anonymous environments [76]. The situation became transformed when advances in molecular biology made it possible to identify individual genes crucial to studying gene–environment interaction (G9E) systematically and through better evidence on the environmental mediation of certain risk effects [64, 67]. The first human evidence came from epidemiological/ longitudinal studies. Using data from the Dunedin study, Caspi and colleagues [9–11] showed marked G9E effects. This research was distinctive in using biological scientific evidence to select genes that might be involved in environmental susceptibility and in choosing environments where there was good evidence of substantial environmentally mediated risk effects. The findings showed
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relative specificity with respect to outcomes. Thus, the 5HTT transporter promoter gene showed a G9E with respect to the liability to depression but not to antisocial behaviour. Conversely, the MAOA gene showed G9E with respect to antisocial outcomes but not depression. However, as in the whole of good science, the topic needed to be investigated using a variety of diverse methodologies— including human experimental studies [34, 52] and animal models [12, 89]. When all of this research was put together there were several rather surprising G9E findings1. First, the G9E applied to adversities as severe as gross maltreatment and not just acutely stressful life events. Indeed, the G9E was mainly seen with maltreatment and was only marginally significant with respect to acute stresses [37]. The human experimental approach (in which genetic findings were combined with brain imaging, following a fearful stimulus, in order to examine the effects on neural structure and function), indicated that the G9E applied to individuals without psychopathology. In other words, the G9E had to apply to pathways that operated in all of us and not just in patients with depression, antisocial behaviour or schizophrenia. The Karg meta-analysis also indicated that the pathways involving G9E extended from early childhood to adult life and not so much to immediate effects. Thus, the effects of G9E were most evident with maltreatment in early childhood and outcomes in late adolescence or early adult life. Finally, although initially conceptualized in terms of responsivity to seriously adverse environments, evolutionary considerations suggested that the genes probably concerned environmental susceptibility generally and not just responses to adverse environments [3, 5, 23]. Although the evidence is as yet incomplete, the empirical research findings have generally supported this supposition. For the most part, geneticists (both quantitative and molecular) have accepted that the findings overwhelmingly support the notion that G9E may be quite common. It is true that a few remain resistive to accepting the evidence (e.g., [60]) but their arguments are based on a biased selection of findings [92]. Non-scientific commentators have, for the most part, tended either to discuss resilience (i.e., the phenomenon of relative resistance to stress and adversity) without paying attention to G9E or to assume that the main value of the findings was to identify individuals for whom serious adversity did not matter because they were resistant to its 1
We make no attempt to review all the evidence here as this has been done elsewhere (Caspi et al. 2010; Rutter, in press)—finding that G9E claims are supported by much research using samples other than the Dunedin study and also using human experiments and animal models.
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effects [98]. However, the G9E findings matter because they carry the potential to identify causal pathways for both the effects of genes and the effects of environments and because the phenomenon applies to all of us and not just to patients with disorders. Moreover, there is growing evidence that those individuals who are most vulnerable to adversity may also be most responsive to the positive effects of therapeutic interventions [38]. The problem relating to G9E is, however, not so much that people made misguided and misleading commonsense assumptions but, rather, that the scientific evidence itself has been lacking until relatively recently.
Conclusions Perhaps the first point to note is that, as Wolpert [97] argued, much of the science was ‘unnatural’ in the sense that technical tools were used (as with the DNA findings and the use of brain imaging in the study of G9E), or because animal models were employed (as with the studies of early experience), or because unusual comparisons were made (as with the contrasting findings on prenatal smoking exposure for pregnancies involving egg donation as against sperm donation). Probably, too the same applies to the contrasting effects of marriage within and between cultures. However, our focus has been primarily on the differences between commonsense and science in the approach to understanding the mechanisms. Commonsense (like early science) tends to rely on an inductive approach in which natural observations are followed by a logical reasoning of what these might mean. By contrast, science requires some form of experiment (either a natural experiment or a contrived intervention experiment) and the testing of two or more alternative explanations or mechanisms. This may, or may not, involve induction, but commonsense differs in having to rely only on induction rather than experiments. What this entails, as explained by Medawar [49, 50], is both the creation of a possible ‘story’ (i.e., hypotheses) and the consequent testing of the story (i.e., the experiments). Not infrequently, the first testing shows that the hypothesis is only partially supported. That requires, then, a modification of the ‘story’ and a further experimental testing. In short, science involves both a process within a particular design, and the use of multiple different research strategies (Table 1). We need to turn, lastly, to consider how and why the misguided claims, and hence the translation going awry, came about. Four reasons seem to apply. First, sometimes there was not an adequate basis for scientific conclusions. This would apply to both the G9E and the effects of institutional deprivation. Second, the situation might be an unfamiliar one. This was obviously the case in relation to
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Table 1 Key reasons for Translation Going Awry Early interventions
Removal of all stress
Maternal smoking
Tax benefits for marriage
Inadequate basis for scientific conclusions Situation unfamiliar
9
Selectively biased alteration to the science
9
Ideology/excessive adherence to theory
9
9
institutional deprivation but perhaps, to some degree, it also applied to the effects of prenatal exposure to maternal smoking. Third, those making the commonsense claims gave selectively biased attention to only part of the science. That applies to most of the examples but it is best illustrated by the use of only the early rodent findings (on juveniles) on environmental deprivation, ignoring the later rodent findings on adults. Finally, ideology or strong adherence to a background theory shaped supposedly commonsense recommendations as in the case of both marriage and early preventive interventions. Of course, although not discussed by us here, commonsense claims are often correct and are found to be supported by science. We have focussed exclusively on the fairly frequent occasions when commonsense and science pull in different directions. We are definitely not arguing that commonsense has no place in policy and practice. Indeed, in an era of bureaucratic control (which is sometimes mindless), commonsense is very necessary in deciding how changes are brought about. It is just that commonsense is not a good guide to the likely effects of particular policies. We are also not suggesting that politics should be based only on science (see [6]) indeed, provided that it pays attention to evidence, values have to shape policies. Finally, it would be nice to be able to argue that all scientists are fully honest and dispassionate in their claims. Regrettably, ambitions, financial considerations, and pressures from employers or funding agencies mean that ex cathedra claims by scientists should always be treated with extreme caution. In some of the examples we considered, scientists were open to criticism for their biased use of scientific findings. The need, always, is to pay attention to the evidence, and that is where science has an essential place. Moreover, translation needs to be based on particularly high quality research that involves a sensitivity to the clinical situation as well as to science. Multiple research strategies will be required and multiple evaluations will usually be involved. Conflict of interest
None.
9
Profound institutional deprivation
G9E
9
9
9 9
9
9
9
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REVIEW
Translation gone awry: differences between commonsense and science Michael Rutter • Tytti Solantaus
Received: 16 March 2013 / Accepted: 3 October 2013 / Published online: 19 October 2013 Ó Springer-Verlag Berlin Heidelberg 2013
Abstract A general assumption is that science is just organised commonsense. It is noted that translation involves a two-way pathway between basic laboratory science and patient care, and that some scientific findings have implications for prevention rather than treatment. A succinct critique follows on the key features that differentiate science and commonsense. The main part of the paper discusses six rather different examples of translation that went awry because people treated science and commonsense as equivalent. Examples based on empirical evidence of translation going awry include (i) the claim that only early intervention can bring lasting benefits; (ii) the claim that the main policy goal for children should be the elimination of all stresses; (iii) the claim that exposure in utero to maternal smoking causes ADHD and conduct disturbance; (iv) the claim that tax benefits should be used to encourage couples to marry; (v) the effects of profound institutional deprivation are similar to those of any adversity; and (vi) environmental effects are largely independent of genetic influences. Much of science is ‘unnatural’ in the sense that technical tools (such as imaging or DNA) are employed, or because animal models are used, or because unusual comparisons are made. Science cannot be based solely on an inductive process; rather, there must be some
M. Rutter and T. Solantaus are joint first authors. M. Rutter (&) MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, de Crespigny Park, Denmark Hill, PO 80, London SE5 8AF, UK e-mail: [email protected] T. Solantaus National Institute for Health and Welfare, University of Tampere, Helsinki, Finland
form of experiment and the testing of two or more alternative explanations. Translation needs to be based on top quality science and an appreciation that even the best science needs to take account of multiple strategies and multiple evaluations. Keywords Induction Hypotheses Animal models Imaging Genetics Translation Abbreviation G9E Gene-environment interaction
Translation There is a widespread and entirely reasonable wish to translate scientific discoveries into patient benefits (see [46], but the assumption that the interplay between science and practice is merely a translational pathway from basic laboratory science to patient care is simplistic [55, 77]. First, there are numerous examples of the starting point being a clinical observation, as with the foetal alcohol syndrome, in which the clinical observation of particular malformations in the offspring of mothers with chronic alcoholic problems led to laboratory studies using animal models. Second, some scientific findings have implications for prevention rather than treatment. Doll and Hill’s [17, 18] evidence that smoking markedly increased the risk for lung cancer is the best known example of this kind. Another example is the findings of intergenerational transmission of mental illness [83], which call for preventive efforts for families and children [86]. Third, in many cases, translation relies on an extended multi-step pathway involving several quite different types of science. The lipid story on cholesterol effects on coronary artery disease and the benefits
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from statins is the most obvious example here [87, 88]. Fourth, this multi-step pathway frequently extends over a very long time period [19] and it follows that a key issue concerns the decision of when the scientific evidence is sufficiently solid for it to be reasonable to proceed with translation [1]. In that connection it has to be realised that a decision not to act constitutes an act. There are penalties for both acting too soon and not acting soon enough. In the remainder of this essay, we focus on the fruits of science in terms of understanding causal processes, but it is obvious that the findings are equally relevant to translation matters. In particular, there is a great need for hypothesis-based bridging studies that constitute experimental clinical medicine as shown by ‘proof of principle’ research.
Method Characteristics of good science Medawar [49, 50] provided a witty, but scathing, critique of the idea that there is one pathognomonic scientific method and he also argued that scientific papers are fraudulent in the sense that they misleadingly imply that scientific discovery is just an inductive process that begins with simple unbiased observations and that these lead inevitably to deduced explanatory hypotheses. They do not because no observations are unbiased; they are influenced by our expectations of what we should observe. Even more crucially, however, it is not logically possible to arrive with certainty to a generalisation that contains more information than the observations upon which the generalisation was based. He argued that what was distinctive about science were three features: (1) a concern to test for possible invalidations or falsifications [57, 58], (2) an attempt to reduce findings to some simplifying explanatory process; and (3) a focus on testing causal inferences [28]. The last would usually involve some sort of experimental approach. In the case of psychology and psychopathology there would often be the need to use ‘natural experiments’ that pull apart variables that ordinarily go together [65, 68]. The combination of these features led Wolpert [97] to argue that science is inherently ‘unnatural’ and not at all simply organised commonsense—thereby taking issue with distinguished writers such as Thomas Huxley and Alfred Whitehead who claimed the opposite. Wolpert gave numerous telling examples—mainly from laboratory science or physics—showing the differences between science and commonsense. Commonsense is based only on inductive reasoning stemming from observations rather than experimental testing. By contrast, science requires some form of experimental testing and some contrasting of alternative explanations or mechanisms. Commonsense
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suffers from the limitations in what people can observe—as shown by the historical example of assuming that the earth is flat because it appears to be so when we look out of the window. The same applies to the belief that the earth is the centre of the universe. However, the key point here is that in society today there is an inadequate appreciation of the numerous sources of systematic bias in commonsense reasoning [36]. Here we follow Wolpert’s arguments but do so from fields relevant to psychology and psychopathology. However, first we need to note the views of other scientists [72]. Thus, Merton [51] proposed that three main features characterised good quality science. First, a search for principles that could be generalised beyond the sample studied. Ordinarily, this would require research that spans several samples. It cannot be done by inductive reasoning alone. Second, a conceptualisation of the meaning or mechanism thought to underlie the findings or observations. This is where hypotheses come into the frame. Medawar expressed this in terms of telling a story—thus emphasising the difference in approach needed for creating a hypothesis and for testing it. Both are essential elements of science. Note that hypotheses are not the same as predictions (despite numerous researchers treating them as if they were). There is no interest in knowing whether the researcher guessed the results correctly; the interest must lie in the putting forward of some sort of underlying meaning or mechanism. Merton’s [51] third criterion was an attitude of scepticism—a norm of questioning, challenging and considering alternative counter-explanations that must be examined against the proposition being put forward. The criteria suggested many years later by the US National Research Council [53] differed in detail but provide much the same message as did also the British Academy Working Group Report [6] report on Social Science and Family Policies. Against that background we turn to six rather different instances in which it seems that translation has gone awry because people have treated science and commonsense as equivalent. The first four are examples where the translation process has been fairly straightforward from scientific findings to decision making and general understanding. The last two are examples of more complicated research processes involving misleading inferences made by both scientists and decision makers.
Results Examples of translation going awry Only early intervention can bring lasting benefits The scientific basis for this claim has a very distinguished pedigree in Donald Hebb’s [27] book proposing age-
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dependent plasticity of the nervous system. During the 1950s and 1960s this was followed by experimental evidence from rodent studies that enrichment of the environment could lead to structural changes in the brain in juvenile rats [2]. Because the early research on the effects of environmental enrichment and deprivation was undertaken immediately post weaning at 25 days of age, it would seem to follow, first, that early interventions could lead to lasting brain changes and, second, that this was because the interventions occurred during a period of rapid brain growth. The Hubel and Wiesel findings [32] on the importance of early visual input for the normal development of the visual cortex appeared to confirm the claim on early intervention. This commonsense inference was also seemingly supported by the various human studies of interventions in the early years leading to cognitive gains [8]. The policy recommendation followed that resources be taken away from older children and adolescents and transferred for use in the early years [31]. The argument had three main roots. First, prevention is more effective than cure; second, lasting benefits must come from changes in the brain; and, third, that brain development is maximal in the first 3 years (in humans). Nevertheless, the commonsense application of the science was mistaken. The Hubel and Wiesel findings, showing a critical period for visual impact, have been amply confirmed [4], but the critical period for this particular form of experience-expectant biological programming [25] does not apply generally [75]. Most crucially, although the early rodent studies of the effects of environmental enrichment and deprivation were performed with juveniles, later ones included both younger and older adults with findings that were broadly similar in pattern at all ages [62]. That is, the particular brain changes and the specific parts of the brain affected were the same at all ages, even though the magnitude of effects was often larger in juveniles and the brain effects occurred more rapidly. In addition, a large scale prospective structural brain imaging study on humans [24] as well as post-mortem findings [33] have shown that brain development continues right into adult life, with adolescence constituting a period of particular change [82]. Even more crucially, there are neural changes resulting from environmental influences in adult life. This was shown, for example, by the evidence that taxi drivers in London (who had to pass the rigorous ‘knowledge’ exam regarding routes) had a larger posterior hippocampus than controls [45]. Similarly, musicians were found to show neural differences associated with intensive practice [21, 35]. An experimental study of juggling [20] confirmed that experiences truly caused the neural changes. Other research has similarly shown behavioural changes as a result of experiences in adult life—such as the effects of marriage in leading to a reduction in crime [80] or
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beneficial effects of US military service in individuals from a disadvantaged background who entered the Army when young [81]. Note that the evidence also indicates that risk experiences may also begin for the first time in adolescence or adult life [7, 40]. Finally, it has been found that the benefits of early intervention tend to be contingent on the interventions continuing into the school years [8]. Putting all the scientific evidence together, it is clear that the early intervention claim is mistaken. It may be important to intervene early because the early years come first and may influence later experiences but later experiences can be very influential in affecting both behaviour and brain structure. Moreover, most lasting benefits from positive early experiences fade with time unless the positive experiences continue [14]. The situation is closely paralleled in the field of social development. It has been argued that secure attachment in infancy constitutes a powerful influence on later social development but although long-term longitudinal studies confirm the importance of social experiences, they, also, find very little prediction from infancy [26]. The commonsense claims were misleading because they failed to take into account the totality of the evidence from both human studies and animal models. The main policy goal for children should be the elimination of all stresses This commonsense assertion is based on the extensive evidence that the experience of stress causes very substantial mental health risks [40]. Moreover, the use of natural experiments (such as twin studies and twins discordant for the experience of abuse [39] has indicated that this is highly likely to reflect a causal influence. Furthermore, it has been found that even minor adversities can have important ill-effects and that their occurrence may sensitize the individual to become even more vulnerable to later stress experiences [69–71]. It is easy to understand why this has led both policy and practice to focus only on risk and elimination of risk. It has led informed parents to make extensive efforts to shield their children from stress. Once again, however, the totality of the scientific evidence suggests that an elimination of all stress may not be in children’s best interests. In the first place, dealing successfully with challenge is an essential feature of normal development [78]. Clinical and epidemiological evidence show that successful coping with stresses can be strengthening [71]. For example, Elder [22] showed this in terms of adolescents taking on unusual responsibilities during the time of the 1930s economic depression. Lyons’ experimental research with squirrel monkeys [44] led to the same conclusion. Brief weekly separations led to improved
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physiological functioning and greater resistance to stress. Note should be taken of the parallel with infections. Resistance to infection comes about through exposure to infections (either naturally or through immunization) and not through their avoidance. Similarly, the behavioural treatment of phobias shows that avoidance of the feared object or situation makes it more likely that the phobia will persist [47, 59]. There is also a parallel with asthma in which the avoidance of infections increases the risk for asthma and other forms of atopic disease [48, 54, 95]. It might be supposed that the appropriate inference should be that minor stress may be a good thing but severe stress and adversity is always detrimental. However, the evidence shows that even terrible experiences may sometimes be strengthening provided children can cope successfully [93]. Conversely, for unusually susceptible children, even milder stresses may carry risks. Perhaps, the main lesson should be that challenge is good and the focus needs to be on fostering successful coping in children and families in adversity. This should also be a goal in preventive interventions. The claim that exposure in utero to maternal smoking causes ADHD and conduct disturbance This example is somewhat different in that the claim came from researchers. At first sight, the claim seems well based. Careful statistical control for possible confounding variables was undertaken to ensure that the statistical association might be causal. A bringing together of the findings from several studies convincingly showed an apparently true effect of smoking exposure in the womb on ADHD [43]. The plausibility of the claim was much strengthened by the evidence from animal models, as well as human epidemiological studies that there was a true effect in lowering the birth weight (thus providing a physiological basis). Nevertheless, the Academy of Medical Sciences [1] report clearly indicated the major difficulties involved in statistical control of confounding variables. Most crucially, three different types of natural experiment (the assisted conception design, the comparison of siblings from different pregnancies and the Children of Twins (CoT) design) all showed that the association was probably largely a reflection of genetic mediation rather than environmental risk mediation [90]. The assisted conception design neatly illustrates what is involved. Pregnancies using sperm donation do not remove the genetic link between mother and child, whereas egg donation does. A comparison of the two showed that the maternal smoking effect was found only in the former—indicating that most (but not necessarily all) of the association reflected genetic mediation. The commonsense claim was plausible but almost certainly misleading.
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Tax benefits should be used to encourage couples to marry The relevant scientific background is the finding that the break-up rate associated with cohabitations is substantially higher than those associated with married couples in the UK and in the USA [41]. This has led to the inference that strong incentives should be provided for marriage, including the introduction of tax benefits [96]. At first sight this seems a justifiable commonsense inference from the scientific evidence but it is not, for several different reasons. First, cohabiting couples are widely heterogeneous. Some are individuals who have made a committed relationship but have decided not to marry but, also, there are many who are living together without any kind of longterm commitment [41]. Second, there is evidence of substantial selection into marriage—meaning that the differences between married and cohabiting couples are likely to reflect who chooses to get married rather than marriage as a circumstance [16]. Third, Australian evidence indicates that it is dubious whether financial incentives actually make much difference to whether or not people choose to get married [6]. Fourth, most crucially, marriages in the USA are more likely to break down than cohabitations in Scandinavia [13]. Fifth, marital breakdown may, dependent on circumstances, either improve the situation for children or make it worse [15, 61]. We may conclude that stable, loving family relationships are indeed beneficial for children but these do not necessarily have to involve marriage and the findings in America make it quite clear that, at least in that country, marriage is not necessarily associated with stable longlasting relationships. The effects of profound institutional deprivation are similar to those from any adversity This example differs from the first four examples for three rather different reasons. First, the initial science base was weak because it relied on findings regarding different forms of stress and adversity other than institutional deprivation [29, 30, 85, 91], and on findings about the physical recovery of children experiencing profound deprivation including subnutrition [84]. The problem with the first is that it involved assuming that institutional deprivation would have effects that were no different from other forms of stress and adversity. That was a most uncertain generalisation. The problem with the second is that the studies concerned physical growth and cognition, there being no measures of social functioning. The second unusual feature of this example is that none of the findings of the actual effects of profound institutional deprivation on outcome were predictable on either the basis
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of commonsense or the limited research evidence at the start. It might be supposed, on commonsense grounds, that although there were individual differences in response to adversity, these would be either absent or at least much less in the case of really profound and prolonged adversities. The study of institutional deprivation, however, showed that that was not the case [79]. There was no appreciable narrowing of the range of responses with the most severe and prolonged deprivation. The third unusual feature is that the inappropriate and misleading inferences were made by scientists as well as by policy makers. Thus, many studies mainly used questionnaire measures such as the CBCL which included no measures that could have picked up particular abnormalities as actually found. Similarly, the meta-analysis undertaken by van IJzendoorn and Juffer [94] was not only based on cross-sectional measures but also did not include measures of the features later found to be important. The English and Romanian Adoptees (ERA) Study followed children from the age of 4 years, shortly after adoption, up to age 15 years (in some cases later than that) [73, 74, 79]. The findings showed that there were no measurable ill-effects if the institutional deprivation did not last beyond the child’s age of 6 months. However, there was a marked rise in the rate of serious deficits if the deprivation lasted to the age of 6–12 months or later [42]. All the deficits concerned highly unusual behavioural patterns and not at all the usual range of emotional and behavioural disturbances that had been expected. It had been assumed that deprivation would result in an increase in all forms of psychopathology, but this was not the case with profound institutional deprivation, unless there was also one of the unusual patterns. These unusual patterns included quasi-autistic features, disinhibited attachment, and inattention/overactivity, as well as cognitive impairment. Commonsense, as well as previous research, suggested that the effects of the institutional deprivation should, to a considerable extent, fade away with time. In fact, the findings showed that the effects were as strong at 15 years as they had been at 11 years and at 6 years—there being no diminution over time. Because uncertainties as to whether these unusual patterns might be more a function of subnutrition than psychosocial deprivation, further analyses were done on the group who showed no evidence of subnutrition, as indexed by physical growth [74]. The evidence was clear-cut in showing that, if anything, the findings were even more striking in the absence of subnutrition. The findings also showed a difference between the effects of subnutrition and ‘pure’ psychosocial deprivation with respect to head growth (which other research has shown is a good index of brain growth). Whereas the subnourished group showed markedly diminished head growth even
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when the deprivation had not lasted beyond 6 months, there was no diminution in head growth in the ‘pure’ psychosocial deprivation group until the deprivation had lasted longer than that. During the years between 4 and 15 years there had been a substantial catch-up in head growth but at 15 years it still fell well short of what occurred in non-deprived populations. Policy makers had no better basis for their inferences but they assumed that ordinary services would know what to do with any problems presented by the children after adoption into UK families. Also, they assumed that recovery was likely to be swift if it was going to take place. Accordingly, there were no tailored services provided in the UK for families after the adoption of children from profoundly depriving institutions in Romania. Environmental effects are largely independent of genetic influences The last example, in common with the institutional deprivation example, initially included no satisfactory basis for scientific inferences. There was evidence that individuals differed markedly in their response to both acute stress and serious adversity [66]. Also, scientific reasoning (although not commonsense) suggested that genetic influences might play a part in susceptibility to the environment [63]. However, the main genetic thinking focussed on genes that provided a liability to disorder, rather than on genes affecting environmental vulnerability. Indeed, the broad message from quantitative behavioural genetics was that gene–environment interactions were sufficiently uncommon and sufficiently weak that they could safely be disregarded in statistical analyses [56]. That was based on twin studies in which there was no information on the individual genes and not much information on specific environments. There were scientists who queried these negative claims on the grounds that gene–environment interactions were likely to involve specific genes and specific environments, rather than anonymous genes and anonymous environments [76]. The situation became transformed when advances in molecular biology made it possible to identify individual genes crucial to studying gene–environment interaction (G9E) systematically and through better evidence on the environmental mediation of certain risk effects [64, 67]. The first human evidence came from epidemiological/ longitudinal studies. Using data from the Dunedin study, Caspi and colleagues [9–11] showed marked G9E effects. This research was distinctive in using biological scientific evidence to select genes that might be involved in environmental susceptibility and in choosing environments where there was good evidence of substantial environmentally mediated risk effects. The findings showed
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relative specificity with respect to outcomes. Thus, the 5HTT transporter promoter gene showed a G9E with respect to the liability to depression but not to antisocial behaviour. Conversely, the MAOA gene showed G9E with respect to antisocial outcomes but not depression. However, as in the whole of good science, the topic needed to be investigated using a variety of diverse methodologies— including human experimental studies [34, 52] and animal models [12, 89]. When all of this research was put together there were several rather surprising G9E findings1. First, the G9E applied to adversities as severe as gross maltreatment and not just acutely stressful life events. Indeed, the G9E was mainly seen with maltreatment and was only marginally significant with respect to acute stresses [37]. The human experimental approach (in which genetic findings were combined with brain imaging, following a fearful stimulus, in order to examine the effects on neural structure and function), indicated that the G9E applied to individuals without psychopathology. In other words, the G9E had to apply to pathways that operated in all of us and not just in patients with depression, antisocial behaviour or schizophrenia. The Karg meta-analysis also indicated that the pathways involving G9E extended from early childhood to adult life and not so much to immediate effects. Thus, the effects of G9E were most evident with maltreatment in early childhood and outcomes in late adolescence or early adult life. Finally, although initially conceptualized in terms of responsivity to seriously adverse environments, evolutionary considerations suggested that the genes probably concerned environmental susceptibility generally and not just responses to adverse environments [3, 5, 23]. Although the evidence is as yet incomplete, the empirical research findings have generally supported this supposition. For the most part, geneticists (both quantitative and molecular) have accepted that the findings overwhelmingly support the notion that G9E may be quite common. It is true that a few remain resistive to accepting the evidence (e.g., [60]) but their arguments are based on a biased selection of findings [92]. Non-scientific commentators have, for the most part, tended either to discuss resilience (i.e., the phenomenon of relative resistance to stress and adversity) without paying attention to G9E or to assume that the main value of the findings was to identify individuals for whom serious adversity did not matter because they were resistant to its 1
We make no attempt to review all the evidence here as this has been done elsewhere (Caspi et al. 2010; Rutter, in press)—finding that G9E claims are supported by much research using samples other than the Dunedin study and also using human experiments and animal models.
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effects [98]. However, the G9E findings matter because they carry the potential to identify causal pathways for both the effects of genes and the effects of environments and because the phenomenon applies to all of us and not just to patients with disorders. Moreover, there is growing evidence that those individuals who are most vulnerable to adversity may also be most responsive to the positive effects of therapeutic interventions [38]. The problem relating to G9E is, however, not so much that people made misguided and misleading commonsense assumptions but, rather, that the scientific evidence itself has been lacking until relatively recently.
Conclusions Perhaps the first point to note is that, as Wolpert [97] argued, much of the science was ‘unnatural’ in the sense that technical tools were used (as with the DNA findings and the use of brain imaging in the study of G9E), or because animal models were employed (as with the studies of early experience), or because unusual comparisons were made (as with the contrasting findings on prenatal smoking exposure for pregnancies involving egg donation as against sperm donation). Probably, too the same applies to the contrasting effects of marriage within and between cultures. However, our focus has been primarily on the differences between commonsense and science in the approach to understanding the mechanisms. Commonsense (like early science) tends to rely on an inductive approach in which natural observations are followed by a logical reasoning of what these might mean. By contrast, science requires some form of experiment (either a natural experiment or a contrived intervention experiment) and the testing of two or more alternative explanations or mechanisms. This may, or may not, involve induction, but commonsense differs in having to rely only on induction rather than experiments. What this entails, as explained by Medawar [49, 50], is both the creation of a possible ‘story’ (i.e., hypotheses) and the consequent testing of the story (i.e., the experiments). Not infrequently, the first testing shows that the hypothesis is only partially supported. That requires, then, a modification of the ‘story’ and a further experimental testing. In short, science involves both a process within a particular design, and the use of multiple different research strategies (Table 1). We need to turn, lastly, to consider how and why the misguided claims, and hence the translation going awry, came about. Four reasons seem to apply. First, sometimes there was not an adequate basis for scientific conclusions. This would apply to both the G9E and the effects of institutional deprivation. Second, the situation might be an unfamiliar one. This was obviously the case in relation to
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Table 1 Key reasons for Translation Going Awry Early interventions
Removal of all stress
Maternal smoking
Tax benefits for marriage
Inadequate basis for scientific conclusions Situation unfamiliar
9
Selectively biased alteration to the science
9
Ideology/excessive adherence to theory
9
9
institutional deprivation but perhaps, to some degree, it also applied to the effects of prenatal exposure to maternal smoking. Third, those making the commonsense claims gave selectively biased attention to only part of the science. That applies to most of the examples but it is best illustrated by the use of only the early rodent findings (on juveniles) on environmental deprivation, ignoring the later rodent findings on adults. Finally, ideology or strong adherence to a background theory shaped supposedly commonsense recommendations as in the case of both marriage and early preventive interventions. Of course, although not discussed by us here, commonsense claims are often correct and are found to be supported by science. We have focussed exclusively on the fairly frequent occasions when commonsense and science pull in different directions. We are definitely not arguing that commonsense has no place in policy and practice. Indeed, in an era of bureaucratic control (which is sometimes mindless), commonsense is very necessary in deciding how changes are brought about. It is just that commonsense is not a good guide to the likely effects of particular policies. We are also not suggesting that politics should be based only on science (see [6]) indeed, provided that it pays attention to evidence, values have to shape policies. Finally, it would be nice to be able to argue that all scientists are fully honest and dispassionate in their claims. Regrettably, ambitions, financial considerations, and pressures from employers or funding agencies mean that ex cathedra claims by scientists should always be treated with extreme caution. In some of the examples we considered, scientists were open to criticism for their biased use of scientific findings. The need, always, is to pay attention to the evidence, and that is where science has an essential place. Moreover, translation needs to be based on particularly high quality research that involves a sensitivity to the clinical situation as well as to science. Multiple research strategies will be required and multiple evaluations will usually be involved. Conflict of interest
None.
9
Profound institutional deprivation
G9E
9
9
9 9
9
9
9
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