Bishopblog catalogue (updated 26th Sept 2014)

Source: http://www.weblogcartoons.com/2008/11/23/ideas/

Those of you who follow this blog may have noticed a lack of
thematic coherence. I write about whatever is exercising my mind at the time,
which can range from technical aspects of statistics to the design of bathroom
taps. I decided it might be helpful to introduce a bit of order into this
chaotic melange, so here is a catalogue of posts by topic.

Language impairment, dyslexia and related disorders

The common childhood disorders that have been left out in the cold (1 Dec 2010)
What's in a name? (18 Dec 2010)
Neuroprognosis in dyslexia (22 Dec 2010)
Where commercial and clinical interests collide: Auditory processing disorder (6 Mar 2011)
Auditory processing disorder (30 Mar 2011)
Special educational needs: will they be met by the Green paper proposals? (9 Apr 2011)
Is poor parenting really to blame for children's school problems? (3 Jun 2011)
Early intervention: what's not to like? (1 Sep 2011)
Lies, damned lies and spin (15 Oct 2011)
A message to the world (31 Oct 2011)
Vitamins, genes and language (13 Nov 2011)
Neuroscientific interventions for dyslexia: red flags (24 Feb 2012)
Phonics screening: sense and sensibility (3 Apr 2012) What Chomsky doesn't get about child language (3 Sept 2012) Data from the phonics screen (1 Oct 2012)
Auditory processing disorder: schisms and skirmishes (27 Oct 2012)
High-impact journals (Action video games and dyslexia: critique) (10 Mar 2013) Overhyped genetic findings: the case of dyslexia (16 Jun 2013) The arcuate fasciculus and word learning (11 Aug 2013) Changing children's brains (17 Aug 2013)
Raising awareness of language learning impairments (26 Sep 2013) Good and bad news on the phonics screen (5 Oct 2013)
What is educational neuroscience? (25 Jan 2014)
Parent talk and child language (17 Feb 2014)
My thoughts on the dyslexia debate (20 Mar 2014)
Labels for unexplained language difficulties in children (23 Aug 2014)
International reading comparisons: Is England really do so poorly? (14 Sep 2014)

Autism

Autism diagnosis in cultural context (16 May 2011)
Are our ‘gold standard’ autism diagnostic instruments fit for purpose? (30 May 2011)
How common is autism? (7 Jun 2011)
Autism and hypersystematising parents (21 Jun 2011) An open letter to Baroness Susan Greenfield (4 Aug 2011)
Susan Greenfield and autistic spectrum disorder: was she misrepresented? (12 Aug 2011)

Psychoanalytic treatment for autism: Interviews with French analysts (23 Jan 2012)
The ‘autism epidemic’ and diagnostic substitution (4 Jun 2012)
How wishful thinking is damaging Peta's cause (9 June 2014)

Developmental disorders/paediatrics

The hidden cost of neglected tropical diseases (25 Nov 2010)
The National Children's Study: a view from across the pond (25 Jun 2011)
The kids are all right in daycare (14 Sep 2011) Moderate drinking in pregnancy: toxic or benign? (21 Nov 2012) Changing the landscape of psychiatric research (11 May 2014)

Genetics

Where does the myth of a gene for things like intelligence come from? (9 Sep 2010)
Genes for optimism, dyslexia and obesity and other mythical beasts (10 Sep 2010)
The X and Y of sex differences (11 May 2011)
Review of How Genes Influence Behaviour (5 Jun 2011)
Getting genetic effect sizes in perspective (20 Apr 2012) Moderate drinking in pregnancy: toxic or benign? (21 Nov 2012) Genes, brains and lateralisation (22 Dec 2012) Genetic variation and neuroimaging (11 Jan 2013) Have we become slower and dumber? (15 May 2013) Overhyped genetic findings: the case of dyslexia (16 Jun 2013)

Neuroscience

Neuroprognosis in dyslexia (22 Dec 2010) Brain scans show that… (11 Jun 2011) 
Time for neuroimaging (and PNAS) to clean up its act (5 Mar 2012)
Neuronal migration in language learning impairments (2 May 2012)
Sharing of MRI datasets (6 May 2012)
Genetic variation and neuroimaging (1 Jan 2013) The arcuate fasciculus and word learning (11 Aug 2013) Changing children's brains (17 Aug 2013)
What is educational neuroscience? ( 25 Jan 2014) Changing the landscape of psychiatric research (11 May 2014)

Statistics

Book review: biography of Richard Doll (5 Jun 2010)
Book review: the Invisible Gorilla (30 Jun 2010)
The difference between p < .05 and a screening test (23 Jul 2010)
Three ways to improve cognitive test scores without intervention (14 Aug 2010)
A short nerdy post about the use of percentiles (13 Apr 2011)
The joys of inventing data (5 Oct 2011)
Getting genetic effect sizes in perspective (20 Apr 2012) Causal models of developmental disorders: the perils of correlational data (24 Jun 2012) Data from the phonics screen (1 Oct 2012)Moderate drinking in pregnancy: toxic or benign? (1 Nov 2012) Flaky chocolate and the New England Journal of Medicine (13 Nov 2012) Interpreting unexpected significant results (7 June 2013) Data analysis: Ten tips I wish I'd known earlier (18 Apr 2014) Data sharing: exciting but scary (26 May 2014)
Percentages, quasi-statistics and bad arguments (21 July 2014)

Journalism/science communication

Orwellian prize for scientific misrepresentation (1 Jun 2010)
Journalists and the 'scientific breakthrough' (13 Jun 2010)
Science journal editors: a taxonomy (28 Sep 2010)
Orwellian prize for journalistic misrepresentation: an update (29 Jan 2011)
Academic publishing: why isn't psychology like physics? (26 Feb 2011)
Scientific communication: the Comment option (25 May 2011)
Accentuate the negative (26 Oct 2011)
Publishers, psychological tests and greed (30 Dec 2011)
Time for academics to withdraw free labour (7 Jan 2012)
Novelty, interest and replicability (19 Jan 2012)
2011 Orwellian Prize for Journalistic Misrepresentation (29 Jan 2012)
Time for neuroimaging (and PNAS) to clean up its act (5 Mar 2012)
Communicating science in the age of the internet (13 Jul 2012) How to bury your academic writing (26 Aug 2012)
High-impact journals: where newsworthiness trumps methodology (10 Mar 2013)
Blogging as post-publication peer review (21 Mar 2013) A short rant about numbered journal references (5 Apr 2013) Schizophrenia and child abuse in the media (26 May 2013) Why we need pre-registration (6 Jul 2013)
On the need for responsible reporting of research (10 Oct 2013)
A New Year's letter to academic publishers (4 Jan 2014)

Social Media

A gentle introduction to Twitter for the apprehensive academic (14 Jun 2011)
Your Twitter Profile: The Importance of Not Being Earnest (19 Nov 2011)
Will I still be tweeting in 2013? (2 Jan 2012)
Blogging in the service of science (10 Mar 2012) Blogging as post-publication peer review (21 Mar 2013)
The impact of blogging on reputation ( 27 Dec 2013) WeSpeechies: A meeting point on Twitter (12 Apr 2014)

Academic life

An exciting day in the life of a scientist (24 Jun 2010)
How our current reward structures have distorted and damaged science (6 Aug 2010)
The challenge for science: speech by Colin Blakemore (14 Oct 2010)
When ethics regulations have unethical consequences (14 Dec 2010)
A day working from home (23 Dec 2010)
Should we ration research grant applications? (8 Jan 2011)
The one hour lecture (11 Mar 2011)
The expansion of research regulators (20 Mar 2011)
Should we ever fight lies with lies? (19 Jun 2011)
How to survive in psychological research (13 Jul 2011)
So you want to be a research assistant? (25 Aug 2011)
NHS research ethics procedures: a modern-day Circumlocution Office (18 Dec 2011)
The REF: a monster that sucks time and money from academic institutions (20 Mar 2012)
The ultimate email auto-response (12 Apr 2012)
Well, this should be easy…. (21 May 2012) Journal impact factors and REF2014 (19 Jan 2013)  An alternative to REF2014 (26 Jan 2013) Postgraduate education: time for a rethink (9 Feb 2013) High-impact journals: where newsworthiness trumps methodology (10 Mar 2013)
Ten things that can sink a grant proposal (19 Mar 2013)Blogging as post-publication peer review (21 Mar 2013) The academic backlog (9 May 2013) Research fraud: More scrutiny by administrators is not the answer (17 Jun 2013) Discussion meeting vs conference: in praise of slower science (21 Jun 2013) Why we need pre-registration (6 Jul 2013)
Evaluate, evaluate, evaluate (12 Sep 2013)
High time to revise the PhD thesis format (9 Oct 2013)
The Matthew effect and REF2014 (15 Oct 2013)
Pressures against cumulative research (9 Jan 2014)
Why does so much research go unpublished? (12 Jan 2014) The University as big business: the case of King's College London (18 June 2014)
Should vice-chancellors earn more than the prime minister? (12 July 2014)

Replication and reputation: Whose career matters? (29 Aug 2014)


 

Celebrity scientists/quackery

Three ways to improve cognitive test scores without intervention (14 Aug 2010) What does it take to become a Fellow of the RSM? (24 Jul 2011)
An open letter to Baroness Susan Greenfield (4 Aug 2011)
Susan Greenfield and autistic spectrum disorder: was she misrepresented? (12 Aug 2011)
How to become a celebrity scientific expert (12 Sep 2011) The kids are all right in daycare (14 Sep 2011) 
The weird world of US ethics regulation (25 Nov 2011)
Pioneering treatment or quackery? How to decide (4 Dec 2011) Psychoanalytic treatment for autism: Interviews with French analysts (23 Jan 2012) Neuroscientific interventions for dyslexia: red flags (24 Feb 2012)

Women

Academic mobbing in cyberspace (30 May 2010)
What works for women: some useful links (12 Jan 2011)

The burqua ban: what's a liberal response (21 Apr 2011) C'mon sisters! Speak out! (28 Mar 2012)
Psychology: where are all the men? (5 Nov 2012)
Men! what you can do to improve the lot of women ( 25 Feb 2014) Should Rennard be reinstated? (1 June 2014)

Politics and Religion

Lies, damned lies and spin (15 Oct 2011) A letter to Nick Clegg from an ex liberal democrat (11 Mar 2012)
BBC's 'extensive coverage' of the NHS bill (9 Apr 2012)
Schoolgirls' health put at risk by Catholic view on vaccination (30 Jun 2012)
A letter to Boris Johnson (30 Nov 2013)
How the government spins a crisis (floods) (1 Jan 2014)






Humour and miscellaneous

Orwellian prize for scientific misrepresentation (1 Jun 2010)
An exciting day in the life of a scientist (24 Jun 2010)
Science journal editors: a taxonomy (28 Sep 2010)
Parasites, pangolins and peer review (26 Nov 2010)
A day working from home (23 Dec 2010)
The one hour lecture (11 Mar 2011)
The expansion of research regulators (20 Mar 2011)
Scientific communication: the Comment option (25 May 2011)
How to survive in psychological research (13 Jul 2011)
Your Twitter Profile: The Importance of Not Being Earnest (19 Nov 2011)
2011 Orwellian Prize for Journalistic Misrepresentation (29 Jan 2012)
The ultimate email auto-response (12 Apr 2012)
Well, this should be easy…. (21 May 2012)
The bewildering bathroom challenge (19 Jul 2012) Are Starbucks hiding their profits on the planet Vulcan? (15 Nov 2012) Forget the Tower of Hanoi (11 Apr 2013) How do you communicate with a communications company? ( 30 Mar 2014)
Noah: A film review from 32,000 ft (28 July 2014)

Changing the landscape of psychiatric research:

What will the RDoC initiative by NIMH achieve?

©CartoonStock.com

There's a lot wrong with current psychiatric classification. Every few years, the American Psychiatric Association comes up with a new set of labels and diagnostic criteria, but whereas the Diagnostic and Statistical Manual used to be seen as some kind of Bible for psychiatrists, the latest version, DSM5, has been greeted with hostility and derision. The number of diagnostic categories keeps multiplying without any commensurate increase in the evidence base to validate the categories. It has been argued that vested interests from pharmaceutical companies create pressures to medicalise normality so that everyone will sooner or later have a diagnosis (Frances, 2013). And even excluding such conflict of interest, there are concerns that such well-known categories as schizophrenia and depression lack reliability and validity (Kendell & Jablensky, 2003).



In 2013, Tom Insel, Director of the US funding agency, National Institute of Mental Health (NIMH), created a stir with a blogpost in which he criticised the DSM5 and laid out the vision of a new Research Domain Criteria (RDoC) project. This aimed "to transform diagnosis by incorporating genetics, imaging, cognitive science, and other levels of information to lay the foundation for a new classification system."



He drew parallels with physical medicine, where diagnosis is not made purely on the basis of symptoms, but also uses measures of underlying physiological function that help distinguish between conditions and indicate the most appropriate treatment. This, he argued, should be the goal of psychiatry, to go beyond presenting symptoms to underlying causes, reconceptualising disorders in terms of neural systems.



This has, of course, been a goal for many researchers for several years, but Insel expressed frustration at the lack of progress, noting that at present: "We cannot design a system based on biomarkers or cognitive performance because we lack the data". That being the case, he argued, a priority for NIMH should be to create a framework for collecting relevant data. This would entail casting aside conventional psychiatric diagnoses, working with dimensions rather than categories, and establishing links between genetic, neural and behavioural levels of description.



This represents a massive shift in research funding strategy, and some are uneasy about it. Nobody, as far as I am aware, is keen to defend the status quo, as represented by DSM.  As Insel remarked in his blogpost: "Patients with mental disorders deserve better". The issue is whether RDoC is going to make things any better. I see five big problems.



1. McLaren (2011) is among those querying the assumption that mental illnesses are 'disorders of brain circuits'. The goal of the RDoC program is to fill in a huge matrix with new research findings. The rows of the matrix are not the traditional diagnostic categories: instead they are five research domains: Negative Valence Systems, Positive Valence Systems, Cognitive Systems, Systems for Social Processes, Arousal/Regulatory Systems, each of which has subdivisions: e.g. Cognitive Systems is broken down into Attention, Perception, Working memory, Declarative memory, Language behavior and Cognitive (effortful) control. The columns of the matrix are Genes, Molecules, Cells, Circuits, Physiology, Behavior, Self-Reports, and Paradigms. Strikingly absent is anything about experience or environment.



This seems symptomatic of our age. I remember sitting through a conference presentation about a study investigating whether brain measures could predict response to cognitive behaviour therapy in depression.  OK, it's possible that they might, but what surprised me was that no measures of past life events or current social circumstances were included in the study. My intuitions may be wrong, but it would seem that these factors are likely to play a role. My impression is that some of the more successful interventions developed in recent years are based not on neurobiology or genetics, but on a detailed analysis of the phenomenology of mental illness, as illustrated, for example, by the work of my colleagues David Clark and Anke Ehlers. Consideration of such factors is strikingly absent from RDoC.



 2. The goal of the RDoC is ultimately to help patients, but the link with intervention is unclear. Suppose I become increasingly obsessed with checking electrical switches, such that I am unable to function in my job. Thanks to the RDoC program, I'm found to have a dysfunctional neural circuit. Presumably the benefit of this is that I could be given a new pharmacological intervention targeting that circuit, which will make me less obsessive. But how long will I stay on the drug? It's not given me any way to cope with the tendency of checking the unwanted thoughts that obtrude into my consciousness, and they are likely to recur when I come off it.  I'm not opposed to pharmacological interventions in principle, but they tend not to have a 'stop rule'. 



There are psychological interventions that tackle the symptoms and the cognitive processes that underlie them more directly.  Could better knowledge of neurobiological correlates help develop more of these?  I guess it is possible, but my overall sense is that this translational potential is exaggerated – just as with the current hype around 'educational neuroscience'. The RDoC program embodies a mistaken belief that neuroscientific research is inherently better than psychological research because it deals with primary causes, when in fact it cannot capture key clinical phenomena. For instance, the distinction between a compulsive hand-washer and a compulsive checker is unlikely to have a clear brain correlate, yet we need to know about the specific symptoms of the individual to help them overcome them.



3. Those proposing RDoC appear to have a naive view of the potential of genetics to inform psychiatry.  It's worth quoting in detail from their vision of the kinds of study that would be encouraged by NIMH, as stated here:



Recent studies have shown that a number of genes reported to confer risk for schizophrenia, such as DISC1 (“Disrupted in schizophrenia”) and neuregulin, actually appear to be similar in risk for unipolar and bipolar mood disorders. ... Thus, in one potential design, inclusion criteria might simply consist of all patients seen for evaluation at a psychotic disorders treatment unit. The independent variable might comprise two groups of patients: One group would be positive and the other negative for one or more risk gene configurations (SNP or CNV), with the groups matched on demographics such as age, sex, and education. Dependent variables could be responses to a set of cognitive paradigms, and clinical status on a variety of symptom measures. Analyses would be conducted to compare the pattern of differences in responses to the cognitive or emotional tasks in patients who are positive and negative for the risk configurations.



This sounds to me like a recipe for wasting a huge amount of research funding. The effect sizes of most behavioural/cognitive genetic associations are tiny and so one would need an enormous sample size to see differences related to genotype. Coupled with an open-ended search for differences between genotypes on a battery of cognitive measures, this would undoubtedly generate some 'significant' results which could go on to mislead the field for some time before a failure to replicate was achieved (cf. Munafò, & Gage, 2013).



The NIMH website notes that "the current diagnostic system is not informed by recent breakthroughs in genetics". There is good reason for that: to date, the genetic findings have been disappointing. Such associations as are found either indicate extremely rare and heterogeneous mutations of large effect and/or involve common genetic variants whose small effects are not of clinical significance. We cannot know what the future holds, but to date talk of 'breakthroughs' is misleading.



4. Some of the entries in the RDoC matrix also suggest a lack of appreciation of the difference between studying individual differences versus group effects.  The RDoC program is focused on understanding individual differences. That requires particularly stringent criteria for measures, which need to be adequately reliable, valid and sensitive to pick up differences between people.  I appreciate that the published RDoC matrices are seen as a starting-point and not as definitive, but I would recommend that more thought goes into establishing the psychometric credibility of measures before embarking on expensive studies looking for correlations between genes, brains and behaviour. If the rank ordering of a group of people on a measure is not the same from one occasion to another, or if there are substantial floor or ceiling effects, that measure is not going to be much use as an indicator of an underlying construct. Furthermore, if different versions of a task that are supposed to tap into a single construct give different patterns of results, then we need a rethink – see e.g. Foti et al, 2013; Shilling et al, 2013, for examples.  Such considerations are often ignored by those attempting to move experimental work into a translational phase. If we are really to achieve 'precision medicine' we need precise measures.



5. The matrix as it stands does not give much confidence that the RDoC approach will give clearer gene-brain-behaviour links than traditional psychiatric categories.



For instance, BDNF appears in the Gene column of the matrix for the constructs of acute threat, auditory perception, declarative memory, goal selection, and response selection. COMT appears with threat, loss, frustrative nonreward, reward learning, goal selection, response selection and reception of facial communication. Of course, it's early days. The whole purpose of the enterprise is to flesh out the matrix with more detailed and accurate information. Nevertheless, the attempts at summarising what is known to date do not inspire confidence that this goal will be achieved.



After such a list of objections to RDoC, I do have one good thing to say about it, which is that it appears to be encouraging and embracing data-sharing and open science. This will be an important advance that may help us find out more quickly which avenues are worth exploring and which are cul-de-sacs. I suspect we will find out some useful things from the RDoC project: I just have reservations as to whether they will be of any benefit to psychiatry, or more importantly, to psychiatric patients.



References

Foti, D., Kotov, R., & Hajcak, G. (2013). Psychometric considerations in using error-related brain activity as a biomarker in psychotic disorders. Journal of Abnormal Psychology, 122(2), 520-531. doi: 10.1037/a0032618



Frances, A. (2013). Saving normal: An insider's revolt against out-of-control psychiatric diagnosis, DSM-5, big pharma, and the medicalization of ordinary life. New York: HarperCollins.



Kendell, R., & Jablensky, A. (2003). Distinguishing between the validity and utility of psychiatric diagnoses. American Journal of Psychiatry, 160, 4-12.



McLaren, N. (2011). Cells, Circuits, and Syndromes: A Critical Commentary on the NIMH Research Domain Criteria Project Ethical Human Psychology and Psychiatry, 13 (3), 229-236 DOI: 10.1891/1559-4343.13.3.229



Munafò, M. R., & Gage, S. H. (2013). Improving the reliability and reporting of genetic association studies. Drug and Alcohol Dependence(0). doi: http://dx.doi.org/10.1016/j.drugalcdep.2013.03.023



Shilling, V. M., Chetwynd, A., & Rabbitt, P. M. A. (2002). Individual inconsistency across measures of inhibition: an investigation of the construct validity of inhibition in older adults. Neuropsychologia, 40, 605-619.





This article (Figshare version) can be cited as:

 Bishop, Dorothy V M (2014): Changing the landscape of psychiatric research: What will the RDoC initiative by NIMH achieve?. figshare. http://dx.doi.org/10.6084/m9.figshare.1030210 

Parent talk and child language

© www.CartoonStock.com

There's been a lot in the media lately about the impacts of parental talk on children's language development. Some of it has been opinion, as in this piece in the Daily Telegraph, in which the headline proclaimed that children were "starting school unable to speak". This reflected the views of a head teacher, who claimed that the proportion of children with poor language skills had increased in his lifetime, and that this was the fault of parents who did not have time to talk to their children any more. There is nothing new here: versions of this story pop up every few years or so (here's one from 2003,  and a blogpost on another case from 2011): Editors know that stories about feckless parents sell newspapers: readers love the sense of complacency and moral superiority they induce.



But there is also more evidence-based stuff. Some children do have serious difficulties mastering spoken language, and there is research demonstrating links between parent talk and child language outcomes. We've known since the influential study of Hart and Risley (1995) that there is massive variation in the amount of language children are exposed to at home, and this is predicted by socio-economic status. There are many subsequent studies showing positive associations between aspects of the language that babies and toddlers hear and the rate and complexity of their language development.



When the Guardian ran a piece last week on the latest of these studies, someone tweeted "do we really need a study to demonstrate that?" – to most people it's blindingly obvious that children's language development will be determined by the language that they hear at home. This assumption is shared by many professionals in the field of language development; for instance, in a recent review, Leffel and Suskind (2013) describe poor attainment of children from disadvantaged homes and unambiguously state: "Parent linguistic input lies at the heart of the problem".



Except that it's not so simple. And the complexities become apparent when we look at the type of evidence that we have, which is mostly correlational. Students learn in Psychology #101 that correlation does not equal causation, yet when a causal interpretation seems so obvious to most people, this can get forgotten. I have lost count of the number of times I've seen a study showing that parent talk predicts child language development, where the conclusion drawn by the authors (and press offices and the media) is that limited parental language causes child language problems. No other explanation is even countenanced. Yet if we were well taught in Psychology #101, we would realise that we need to consider alternative explanations for the observed association. The figure below shows three possible causal models; these are not mutually exclusive and so all could play a role.

Different Models to account for association between parent talk and child language

Model A is the one that is typically assumed by most people: parent talk to children boosts their language development, and accordingly, if a child has poor language skills, this is likely to be caused by inadequate talk from parents.



In Model B, the association goes in the other direction. Poor language in the child leads to less talk from the parent. This could occur if, for instance, parents are discouraged from talking to a child who is unresponsive and appears not to understand. Consider too, this recent study looking at outcomes of infants in a special care baby unit . Children who were exposed to more adult language in hospital had better language outcomes; however, as the authors noted, "It could be that parents and caregivers have more opportunity to talk to infants who are less sick."



Model C explains the association without postulating a direct link from parental talk to child language. Instead it sees both of these as outcomes of some other cause. This could be an environmental factor, such as poor diet, or a genetic risk that is shared by parents and their children.



It is the job of researchers to try and find evidence to establish the relative importance of these different causal routes. In the case of child language, this is not just a theoretical exercise: it potentially makes a difference to the kinds of intervention that are likely to be effective in helping children. In particular, if model A is the main explanation for the association, then we should be able to boost poor child language by encouraging reticent parents to interact more like talkative parents. This is unlikely to be effective if model B explains the association. And if model C applies, then we would need to either modify the third factor (X) itself, or clarify how it operated in order to alter its association with poor outcomes in children.



I am concerned about the near-universal acceptance of model A as the sole explanation, because there are two lines of evidence that go against it. First, we can to some extent disentangle the impact of socioeconomic disadvantage and parental talk if we study children whose parents produce little spoken language input because they have a congenital hearing impairment. Some profoundly deaf parents have children with normal hearing. In the past there was concern about such children: how would they learn spoken language if their parents produced little intelligible speech? In fact, the studies that were done obtained unexpectedly positive results, leading to the conclusion that although young children clearly need some exposure to spoken language in order to learn to speak, they could develop normal language on the basis of exposure to other adults outside the home and language on TV (Schiff-Myers, 1988).



The second line of evidence comes from studies that disentangle genetic and environmental influences by considering language development in twins. If parental talk is an important determinant of child language, then we would expect twins growing up together in the same home to resemble each other. However, if model A is all-important, we would not expect the genetic relationship between the twins to have any effect. But it does make a difference, and on many language measures this effect is quite substantial. So we find that twins do resemble each other in general, but that resemblance is quite a bit higher if the twins are genetically identical (monozygotic) than if they are fraternal (dizygotic, and sharing around half their DNA for genes that vary between people).



I remember being struck when I first did twin studies of children's language difficulties at how different two twins growing up in the same family could be – provided they were non-identical. It was, however, unusual to find identical twin pairs where one had a significant language problem and the other was unaffected. The overall pattern of results tells us that the child's genetic makeup plays a role in determining their language development (Bishop, 2006).



So what has this to do with models A, B and C? Quite simply, the twin data support a version of model C: given that genes affect language development, we expect parents (who share around half their genes with their children) to resemble their children. We already know that parents of children with language impairments are more likely than other parents to have some kind of language or literacy problem themselves (Barry et al, 2007). This doesn't affect everyone: of course there are many literate and articulate parents whose children have language difficulties. But on balance, these kinds of difficulties run through generations, and we therefore expect to see an association between limited language ability in parents and language difficulties in their children. Note that a genetic account will also predict that language difficulties in children will predominate among those of lower social-economic status: parents who themselves are language-impaired are likely to have low levels of educational attainment and poor occupational prospects.



This kind of genetic explanation for parent-child similarities has a lot of evidential support, but people are very reluctant to accept it. If you propose that genes may play a role in children's developmental difficulties, people will tend to assume that you have a political agenda aligned with the Third Reich, with a goal of identifying a genetic underclass who should not be helped because they are just 'made that way'. This reflects a wrong-headed genetic determinism that is at odds with contemporary understanding of how genes work. Genes do not determine your fate: their impact is likely to vary according to the environment, and by modifying environments we may alter outcomes. Unlike in model A, though, model C predicts that sensitivity to specific environments may depend on one's genes. The arguments have been cogently put in a recent book by Asbury and Plomin (2013), who lament the way in which genetic influences on children's development have been ignored in favour of a political stance that blames educational and developmental difficulties on either poor parenting or poor teaching. If, as has been repeatedly shown, there is evidence that genes are important in influencing children's language development, then we may be squandering our intervention resources by ignoring this fact.



The bottom line is that we need more research. Well-conducted randomized controlled trials on the impact of modifying parent input have been thin on the ground to date, and have not generated impressive evidence of efficacy (see my earlier blogpost) . Obviously, it's early days, and I'd cheer on others who are attempting such research. Results may depend on the nature of the intervention, the aspects of language that are assessed, and the type of population the intervention is used with. My suggestion is that rather than denying the reality of genetic effects, we should be conducting research to find out what kinds of input are most effective for children who are at genetic risk. It is possible that rather than more language input, they may do best with a different kind of language input, specifically tailored to take into account their cognitive strengths and weaknesses. We are a long way from understanding how best to do this, and meanwhile, ingenious and dedicated practitioners are working hard to tackle the very real problems that some children experience. My message is simply that to lay the blame for these difficulties at the door of parents, and to anticipate that problems can be readily overcome by encouraging parents to talk more to their children may be oversimplistic.



To finish, I cannot resist adding my favourite quote from Richard Dawkins, which focuses on mathematics rather than language learning, but gets to the nub of inappropriate concerns about genetic explanations:



People seem to have little difficulty in accepting the modifiability of "environmental" effects on human development. If a child has had bad teaching in mathematics, it is accepted that the resulting deficiency can be remedied by extra good teaching the following year. But any suggestion that the child's mathematical deficiency might have a genetic origin is likely to be greeted with something approaching despair: if it is in the genes "it is written", it is "determined" and nothing can be done about it: you might as well give up attempting to teach the child mathematics. This is pernicious rubbish on an almost astrological scale ..... What did genes do to deserve their sinister juggernaut-like reputation? Why do we not make a similar bogey out of, say, nursery education or confirmation classes? Why are genes thought to be so much more fixed and inescapable in their effects than television, nuns, or books? 

Richard Dawkins (1982) The extended phenotype, Oxford University Press (p. 13) 

References 

Asbury, K., & Plomin, R. (2013). G is for genes: The impact of genetics on education and achievement. Chichester: Wiley Blackwell.

Barry, J. G., Yasin, I., & Bishop, D. V. M. (2007). Heritable risk factors associated with language impairments. Genes, Brain and Behavior, 6, 66-76.

Bishop, D. V. M. (2006). What causes specific language impairment in children? Current Directions in Psychological Science, 15, 217-221.

Caskey, M., Stephens, B., Tucker, R., & Vohr, B. (2014). Adult talk in the NICU with preterm infants and developmental outcomes Pediatrics DOI: 10.1542/peds.2013-0104

Hart, B., & Risley, T. R. (1995). Meaningful differences in the everyday experience of young American children. Baltimore, MD: Paul H. Brookes Publishing Co.

Leffel, K., & Suskind, D. (2013). Parent-directed approaches to enrich the early language environments of children living in poverty. Seminars in Speech and Language, 34(4), 267-277. doi: 10.1055/s-0033-1353443
Schiff-Myers, N. (1988). Hearing children of deaf parents. In D. Bishop & K. Mogford (Eds.), Language development in exceptional circumstances (pp. 47-61). Edinburgh: Churchill Livingstone.



This article (Figshare version) can be cited as:
Bishop, Dorothy V M (2014): Parent talk and child language. figshare.
http://dx.doi.org/10.6084/m9.figshare.1030407