Before setting out on a project to supply one’s unborn child with an awesome developmental environment, it is pertinent to ask the following question:
What’s the point?
“What a dumb question!” the affronted reader scoffed at his/her computer screen. “If we can take for granted the assumption that we want our children to grow into happy, competent and well-adjusted adults, then how can anyone question the ‘point’ of trying to be a good parent?!?”
Well, dear reader, even if one accepts (which I do) that parents have a duty to create the best future that they can for their children, it is nevertheless perfectly reasonable to question whether parents have the ability to influence their children’s development. How do we know that parents have any effect at all on the lives that their children will lead 10, 20, 30 or 60 years down the line? How do I know, in other words, that all of my (planned) effort to give Dahlia a bright future will not be entirely futile?
I don’t mean this in an esoteric/fatalistic “it’s all in the hands of fate” way. I’m alluding to a number of prominent developmental researchers who genuinely believe that the role of parents and their choices in influencing children’s development is pretty close to zero. And these guys aren’t just nutters on the outer fringes of Developmental Psychology – they are respected academics with plenty of empirical evidence from which to draw support. But before I introduce you to these lovely people, a little (actually, a lot of) background is required. Please be warned – major digression is up ahead.
A few decades ago, it was very trendy for social science researchers to use correlational research to study of variables that were often claimed to play causal roles in driving important developmental outcomes. The research literature sagged with the weight of study after study documenting statistical relationships between a range of environmental factors and child characteristics. Parental involvement in criminal activities, it was found, correlates with offspring criminal behaviour; over-controlling parents are more likely to have depressed children; family social status correlates with children’s agreeableness (a personality trait); children who grow up in houses with more books develop into more proficient readers; right wing and racist parents tend to have kids that are more right wing and racist than average – the list is endless.
Many researchers and some lay-people took the view that these intergenerational correlations were attributable to the influence of parents’ behaviour on the development of their children. Criminal parents are generally abusive and violent, so their kids, being more messed-up than average as a consequence, go on to commit more crimes. Over-controlling parents prevent their children from seeking rewarding experiences, thereby inducing a state of helplessness that heightens their sensitivity to depression for life. Etcetera Etcetera. You, I, or uncle Bob could speculate about hundreds of plausible causal pathways from parenting styles to child outcomes covering each of the aforementioned correlations. The problem is that, as anyone with at least half a neuron’s worth of statistical knowledge will be aware, causation cannot necessarily be inferred from causation.
Consider some examples. Ice cream sales and homicide rates correlate – peaks in purchases of ice creams tend to co-occur with increased activity among the homicidal maniac community. This is not because the taste of deliciousness makes people murderously angry. Nor is it because murderous anger makes people want to taste something delicious. It is because heat makes people murderously angry, and it also causes them to want ice-cream. In other words, ice-cream consumption and murder have no causal connection to each other; rather, a third factor (heat) has a simultaneous causal influence on both, leading to their statistical covariation in the absence of a direct causal link.
As such, correlational findings can rarely be taken as definitive evidence for a proposed causal relationship. If variable A correlates with variable B, then it could be that A causally influences B – but it could also be the case that B causally influences A, or that variable C has a causal influence on both A and B. Correlational information alone is insufficient to disambiguate between these alternatives.
In the case of intergenerational correlations like those described above, there are likewise a number of possible explanations, only some of which involve causal relationships. You might think that criminal parents abuse their children more and thereby cultivate little versions of their criminal selves. But it might equally be the case that criminal parents tend to live in poor neighbourhoods, and that growing up in such neighbourhoods causes their children to become involved in crime. It may be that some criminal behaviour is influenced by genetic factors, in which case the children of criminal parents would be expected to inherit a genetic profile that disposes them towards crime. Similarly, you might think that children who grow up in houses with plenty of books develop greater reading proficiency for an obvious reason: they have more exposure to engaging written material. But again, there are plenty of other plausible explanations for the “number of books in house – child reading proficiency” correlation. Parents with genes that confer reading ability would be expected to both purchase more books and to pass their genes on to their children. Well-read children and book abundance would then co-occur without having influenced one another.
To facilitate causal inferences about the factors that affect development, correlational designs that simply measure different variables are therefore insufficient. When it comes to assessing the causal influence of an environmental factor, randomised control trials are the gold standard. These essentially involve assembling a sample of children and randomly assigning some to a treatment condition (in which the child’s environment is altered in a way that is expected to be beneficial) or a control condition (in which the child’s environment is not altered). For instance, a sample of 100 children who attend normal day-care centres could be recruited, and 50 of them could be randomly transferred to a day-care centre of higher quality (treatment condition) whilst the others remain in their current day-care centre (control condition). In this case, day-care quality would be called the independent variable – the variable whose causal impact is being tested. The researchers would then measure other variables of interest (e.g. IQ) from all of the children in the two conditions. These would be dependent variables – variables whose capacity to be causally influenced by the independent variable is being tested. Note that since each child receives either a beneficial intervention or no intervention at all, no harm will be caused to any of the participants as a consequence of the research.
The beauty of randomised control trials is that they allow inferences to be made about the causal impact of the independent variable on the dependent variable(s). A significant difference between, for example, the mean IQ scores of the children in the treatment and control conditions could be used to infer (with high confidence) a causal influence of day-care quality on IQ. Since children were assigned randomly to the treatment and control conditions, there is a limit to how much we would expect children in the two conditions to differ purely as a result of chance. It would be unlikely for any two groups of children to be identical in terms of mean IQ, but it would also be unlikely for them to differ substantially in terms of mean IQ unless there is something causing them to differ. A significant mean IQ difference between the treatment and control groups would therefore allow us to infer that the factor that defines the two conditions (in this case day-care quality) had a causal influence on the children’s IQ.
Importantly, no ambiguities arise with regard to the direction of causality. The assignment to treatment or control condition was determined entirely by the researchers (who made their allocation based on chance), and we can therefore be absolutely sure that no other variables were responsible for determining the quality of day-care that the children received. Thus, the statistical relationship between day-care quality and IQ cannot be attributed to the fact that high IQ children are more likely to be assigned to receive higher-quality day-care, because the assignment was based on chance alone (not on IQ or anything else). Likewise, there can be no third variable affecting both day-care quality condition and IQ, because we know that the former was entirely determined by the researchers and not by any other variables. Thus, randomised control trials permit the evaluation of the causal influence of environmental factors (e.g. day-care quality) on important developmental outcomes (e.g. IQ).
Unfortunately, randomised control trials are expensive, impractical and often impossible to implement within the constraints of a civilised ethical system – for instance, you can’t randomly assign some children to be abused and some to be free from abuse in order to determine the consequences of abuse. Moreover, one of the most important influences on development – a person’s genes – cannot be randomly manipulated by researchers; a person’s genes are established before conception and remain stable throughout their life. Fortunately, people have come up with some pretty clever methods for assessing the extent to which a given trait or behaviour is subject to genetic influence. I’m going to briefly explain the two most common methods (the ones that you’ll find in any bog standard behavioural genetics textbook), but there are loads.
Before I do, however, it is probably important to clarify what is meant by the term “genetic influence” and “individual variation”. Individual variation refers to the extent to which individuals within a given population differ in terms of their score on a particular trait. For example, if everybody in a particular population is between 1.71m and 1.72m in height, the individual variation in height would be less compared to a situation in which people’s heights vary massively from 0.5m to 2.5m.
Genetic influence refers to the extent to which individual variation in a given trait or behaviour is caused by genetic variation. For instance, if I say that 50% of individual variation in IQ is attributable to genetic variation, this means that the total variation in IQ observed between different individuals would be 50% less if, hypothetically, we all had the same genes. In other words, the fact that we all have different genes (some of which push IQs up and some of which push IQs down) causes our IQs to vary by twice as much as they otherwise would.
This is an important point to note because it differs from lay people’s instinctive understanding of what is meant by “genetic influence”. Lay people typically assume that if a trait is subject to genetic influence, then it follows that there exist specific genetic variants that can cause people to be high or low on the trait (such as a “gay gene” or a “crime gene”). This is inaccurate for two main reasons. First, it is very rare for variants of a single gene to exert a large effect on traits or behaviour. Rather, it is almost always the case that many, many different genetic variants all exert very small individual effects, with the result that the cumulative effect of all the numerous different genes that influence a trait may be very high. Secondly, whilst genetic factors can increase the likelihood of certain developmental outcomes, they cannot guarantee a particular developmental outcome. For instance, a child with numerous genetic variants that confer high IQ will be more likely to actually develop an above-average IQ than a randomly selected member of the population. However, the child’s genes do not guarantee that this will happen, because it will always be possible for an environmental factor to prevent the development of a high IQ. For example, if the child is hit by an inter-continental ballistic missile (an environmental factor), he or she is unlikely to develop a high IQ on account of being dead. Thus, genetic influence should be thought of as a process that increases the likelihood of certain outcomes as a function of a person’s genetic profile, not as a process that guarantees that certain developmental outcomes will transpire.
Having clarified (I hope) what is meant by “genetic influence”, we can now explore the two principle techniques that are used in behavioural genetics to facilitate the estimate thereof for traits and behaviours of interest.
The twin method
The twin method involves recruiting samples of identical (Monozygotic, or MZ) and non-identical (Dizygotic, or DZ) twins. MZ twins share 100% of their DNA, whereas DZ twins share, on average, only 50% of their DNA. By examining the degree of similarity observed within MZ and DZ twin pairs for a particular trait or behaviour, it is possible to make inferences about the effect of genetic factors
Let’s say you want to assess the extent to which genetic factors influence a person’s IQ. You would find 20 MZ twin pairs and 20 DZ twin pairs (the numbers here are purely for explanatory purposes and have no methodical relevance). Within each pair, you randomly assign one twin the label “twin 1” and the other the label “twin 2”, and you measure each twin’s IQ (giving you 80 different IQ scores). Making separate calculations for the MZ and DZ subsamples, you assess the correlation between the IQs of the twin 1s and their corresponding twin 2s.  Let’s say that you find a pattern looking something like the one depicted in these graphs:
In these graphs, each dot represents a single pair of twins. The dot’s position on the X axis denotes the IQ of twin 1 within the pair, and the dots position on the Y axis denotes the IQ of twin 2 within the pair. For example, the red dot on the MZ graph represents a twin pair in which twin 1 has an IQ of 112.5 and twin 2 has an IQ of 114. As can be seen, the IQs of the twin pairs in both the MZ and DZ groups are correlated, but the correlation is stronger for the MZ twins – knowing the IQ of twin 1 would enable us to make a better guess of twin 2’s IQ if we were looking at the MZ sample as opposed to the DZ sample.
The fact that the correlation is higher in the MZ sample allows us to infer a genetic influence on IQ. Since the members of both MZ twin pairs and DZ twin pairs grow up in the same household as their co-twin, greater similarity within MZ pairs relative to DZ pairs cannot be attributed to the impact of the family environment. Rather, the only potential causal factor that is shared to a greater extent within MZ twin pairs relative to DZ twin pairs is genes – MZ twin pairs share 100% of their genes whilst DZ twin pairs share, on average, 50% of their genes. As such, the fact that MZ twin pairs are more similar to each other in terms of IQ than DZ twin pairs can only be due to the increased genetic relatedness of the former. In this way, the collection of data from samples of MZ and DZ twins can enable to formulation of estimates about extent to which a given trait or behaviour is subject to genetic influence.
Twin studies can also allow us to make inferences about the impact of the shared-family environment (i.e. environmental factors that make children growing up in the same house more similar) on development. It is best to avoid too much statistical detail here – suffice to say that a causal role in shaping the development of a given trait can be ascribed to the shared family environment when the correlation among DZ twin pairs is more than half of the corresponding correlation among MZ twin pairs.
In the real world, studies like the one described above have indeed been conducted and generally indicate that about 70% of the variability in IQ between individuals can be attributed to genetic factors. In other words, if we lived in a hypothetical universe where everybody had the same genes, then the extent to which IQ would vary across individuals would be 70% less than in the current universe (Plomin & Spinath, 2004). Whoa!
Before I move on to describing a second method for assessing genetic and environmental influences on traits and behaviour, a few points must be noted with regard to the twin method in order to avoid giving a deceptively rosy picture of their capacity to adjudicate the intellectual arena between nature and nurture.
A.) Parents may instinctively treat MZ twin pairs in a more similar manner to DZ twin pairs, meaning that increased similarity among the former could be due to environmental, rather than genetic factors
B.) MZ twins are not actually 100% genetically identical – the genome of each twin within an MZ pair will contain a few novel mutations unique to that individual, which calls into question one of the key assumptions of the twin method.
C.) People often conform to the opinions and behaviour of others, particularly others who share their physical and dispositional characteristics. This could mean that members of MZ twin pairs mimic the behaviour and personality of their co-twin to a greater extent than members of DZ twin pairs, which could cause correlations among MZ twin pairs to increase in the absence of any genetic influence on the trait or behaviour under investigation.
D.) Twins in general may not be representative of the single-birth population. As such, estimates of the genetic and environmental contributions to traits and behaviours in twin samples may not be applicable to everyone else.
E.) MZ twins may share a more similar pre-natal environment than DZ twins. This could mean that greater MZ vs. DZ similarity could be attributable to pre-natal, not genetic, factors.
F.) Etcetera etcetera.
And now, we can talk about the adoption method.
The Adoption Method
The adoption method involves recruiting samples of children who were adopted into families to which they are not biologically related. Any similarity between the child and their adoptive family can only be attributed to the influence of the family environment, because the child has no genetic relationship with their adopted family. For instance, if children adopted into wealthy families develop higher IQs than children adopted into poorer families, we can infer that family wealth has a causal impact on the child’s IQ. In a typical family, it might be possible to argue that common genetic factors are responsible for conferring high IQ and high earning capacity, such that parents who are genetically disposed to be wealthy pass on IQ-enhancing genes to their children. However, such an explanation can be ruled out in the case of adoptive families, because in these families there is no biological relationship between children and parents and, thus, no mechanism for the transfer of IQ-enhancing genes. Thus, similarities between adopted children
Conversely, any similarity between the adopted child and their biological family can be attributed to the influence of genetic factors. Since the child never has contact with their biological family, the only thing capable of exerting a common influence on both the child and his/her biological relatives is shared genetic material. Thus, by examining the degree of similarity between adopted children and their biological and adopted families, it is possible to obtain evidence pertaining to the role of genetic and environmental factors in influencing a particular trait or behaviour.
By now, I would imagine that anyone who has bothered to read this far down is probably thinking something along the lines of “get to the point, please”. Well, I’m nearly there. You see, studies that have employed the adoption and twin methods describe above present what might be interpreted as a rather bleak and pessimistic view of parents’ capacity to alter the course of their children’s development. Basically, the existing body of evidence from twin and adoption suggests that, overall, the shared family environment has little to no influence on a wide range of important developmental outcomes. This would seem to suggest that parents have very little influence on their children’s futures.
For instance, consider the various studies that have examined used the adoption and twin methods to investigate the genetic and environmental influences on personality development. According to the most widely accepted model of personality, there are five distinct personality traits that define an individual’s idiosyncratic behavioural tendencies, namely openness to experience, extraversion, neuroticism, agreeableness and conscientiousness. Twin studies examining these “Big 5” personality traits indicate that about 45% of the individual variation therein is attributable to genetic variation, with virtually no role played by the shared family environment. In other words, siblings from the same family would generally be more similar to each other in terms of personality that two randomly selected members of the population, but only because of their genetic relatedness and not because of the similar rearing environment that they would both have experienced. Studies using the adoption method reveal similar findings: adopted children have similar personalities to their biological parents, but their similarity to their adoptive relatives is no greater than their mean similarity to a random member of the population.
The story is similar for behavioural genetic studies of schizophrenia, anxiety disorders, cognitive ability in adulthood, susceptibility to addiction, likelihood of falling victim to school bullying, obesity, divorce and plenty of other things. Even a trait like religiosity, which you would think should be almost entirely determined by the religious practices of your parents, is also subject to substantial genetic influence. There are some exceptions: shared environmental factors have been found to exert a substantial influence on people’s tendencies towards criminal behaviour, and twin (but not adoption) studies indicate that the shared family environment influences the risk of falling victim to depression.
What’s more, some intergenerational correlations that were once attributed to the effects of parents on their children have now been shown to be largely due to genetic confounds. For instance, take the finding that children whose parents frequently interact with them in a coercive manner are more likely to display anti-social behaviour. This was once taken to indicate that coercive parenting causes children to behave antisocially. However, a rather famous adoption study casts doubt on this explanation. It was found that adopted children whose biological parents had an elaborate criminal history received more coercive parenting from their adoptive parents compared to other adopted children. Think about that for a moment – the criminal history of the adopted child’s biological parents correlated with the tendency of their adopted parents to behave in a coercive manner. Since the biological parents had no contact with their children, the only way that they could influence these children’s lives was through the genes transmitted to them. In other words, biological parents with criminal histories transmitted genes to their children that enhanced the children’s tendency to engage in aggressive and defiant behaviour; these aggressive and defiant behaviours then evoked hostile reactions from the adopted parents, leading to a correlation between biological parent criminal history and adoptive parent hostility.
The remarkable thing about this finding is that it reveals that variables typically assumed to be causes of developmental outcomes may in fact be consequences of genetically-conferred tendencies that are more common in children who are already prone to develop in a certain way. In other words, children are not merely recipients of the causal inputs provided by their environments; they shape their environments through their own behaviour, which is often under genetic influence.
Some researchers have interpreted these findings as evidence that the influence of parents on children’s development has been heavily overestimated. For instance, in her book “the nurture assumption”, Judith Harris argues that genetic influences on development far outweigh the impact of any factors over which parents are likely to have significant control. She also proposes that children’s peers have more influence on their development than their parents. One example that she uses is language development – the children of immigrant parents learn the new language of their host culture easily from their peers; instead of mimicking their parents’ accents they adopt the (correct) pronunciations that they hear from same-age others.
Personally, I think there is a lot of truth to what Harris says. Evidence for powerful genetic influences on a range of developmental outcomes is very, very strong. Conversely, to my knowledge there is no comparable evidence for the causal role of parenting behaviours in development. As I will show below, there is evidence that parents have some effect on their children’s development across various domains, but data from twin, adoption and other genetically informative studies indicate that this environmental influence is highly unlikely to be greater than the impact of genetic factors.
Moreover, I think Harris is spot on when in pointing to the impact of peer influence on children’s development. Experiments using random assignment demonstrate that children’s aggression smoking, risk-taking and wellbeing is strongly influenced by the behaviour of their peers. Moreover, the fact that adolescent’s rate peer relationships as among their highest concerns in life strongly suggests that they would be highly susceptible to peer pressure. Studies of “peer contagion” reveal that adolescence is a stage in life at which people are particularly prone to the influence of same-age others. When people reach university age, studies examining random assignments to dormitory partners show that people tend to align their alcohol consumption and academic habits to those of their new room-mates, again highlighting the impact of peer influence on important developmental outcomes. Likewise, children’s computer-aided learning has been found to be influenced by the characteristics of the same-age learning partners that they are assigned. More generally, children have been found to mimic the behaviours and problem solving strategies of other children around them from a very young age.
Further evidence for the importance of peers in driving important developmental outcomes comes from studies of bullying in schools. A wide variety of evidence, some of which comes from randomised control trials, shows that being subject to bullying has a highly detrimental impact on children’s development.
So, all in all, there is pretty good evidence that for the roles of both genes and peers in influencing development. Doesn’t this mean, then, that there simply isn’t much influence left for parents to exert?
I’m going to try to make the case below that the answer to this question is “no”. Peers and genes aside, I think there is good reason to believe that the choices the typical parent exerts a strong influence on their children’s development.
I have the power!
First, let me make a point about the evidence from twin studies mentioned above, which indicates that important variables such as personality are subject to little to no influence from the “shared family environment”. What this means is that there are no environmental factors causing children raised in the same household to be more similar to each other – the only reason siblings are more similar to each other than two random members of the population is because of their genetic relatedness. One might be tempted to infer that this means that parents have no impact on their children’s personality or susceptibility to mental illness. If parents’ behaviour did have an effect on their children’s development, then we would expect children of the same family (who are presumably exposed to the same parenting behaviour) to be similar to each other for reasons other than genetic relatedness.
However, the “presumably” of the previous sentence is in fact a very tenuous one, because evidence indicates that parents often treat their different children in very different ways. So the presence of a significant effect of parenting behaviour would not necessarily function to make siblings within the same household more similar to each other. As such, evidence from twin studies indicating that the shared family environment explain a negligible portion of the individual variation in many important traits should not be taken as evidence that parents don’t matter.
Moreover, when it comes to adoption studies, there is evidence that environmental factors linked to the family have an important impact on development. For instance, Wicks et al. (2010) found that children adopted into families that had higher socio-economic status (SES) were at less risk of later developing schizophrenia compared to children adopted into low SES families. Wicks et al. (2010) also found that the effect of adoptive family SES was greatest for children who had a schizophrenic biological parent – in other words, the increase in risk faced by children adopted into low (vs. high) SES families was particularly great for children who had a biological parent with schizophrenia. This is an example of gene-environment interaction, which refers to the process whereby the effect of an environmental variable (in this case family SES) on a dependent variable (child risk of schizophrenia) depends on a genetic variable (child’s genetic disposition to experience schizophrenia, as indexed by status of biological parent). The key point, however, is that Wicks et al.’s (2010) data clearly showed that the characteristics of the adoptive environment were important for children’s later development. Likewise, Duyme et al. (1999) found that children adopted into high SES families grew to have higher IQs relative to children adopted into low SES families.
Further evidence for the importance of the family environment in development comes from a range of randomised control trials examining the impact of interventions aimed at improving parents’ interactions with their children. One study of which I am particularly fond randomly assigned parents to either watch several episodes of the parenting show “families” (which depicts the implementation of desirable parenting practices) or to a “waiting list” control condition. Children of the parents in the “families” condition exhibited a significant decline in behavioural problems, indicating that the parenting practices taught by the television series had a beneficial impact on the children. A wide range of other parenting interventions have also been shown to have beneficial consequences for the children involved. There is therefore good evidence that the ways in which parents interact with their children can have important effects of the way those children develop.
It’s worth mentioning the work of Michael Rutter at this point. Rutter is among many researchers analysing data from samples of Romanian adoptees who were adopted shortly after the fall of the tyrannical (and Western-backed) Ceausescu regime in 1989. As infants, these children were raised in orphanages under conditions of horrific deprivation: numerous babies were placed in single cots with no access to toys and rare attention from adults. Malnourishment was common and in some instances there may have been as many as 50 or 60 children per adult caregiver. Rutter et al. have published several studies over the years comparing UK-born adoptees to people who grew up in these Romanian orphanages before being adopted in the UK.
A number of interesting findings have emerged over the years. First, a large improvement in the Romanian group in terms of body weight, head circumference and IQ was observed shortly after adoption in the UK, indicating that part of the effects of early deprivation were amenable to recovery. Secondly, a range of social, cognitive and neurobiological impairments have been found to persist among the Romanian group, who have now entered adulthood. Thirdly, Romanian-born individuals who were adopted before reaching 6 months of age do not differ significantly in their cognitive, emotional or biological profiles from UK-born adoptees, indicating that the detrimental effects of severe early deprivation only persist in the long term if the deprivation lasts for more than 6 months. Fourthly, many of the individuals who spent the longest amount of time (more than 24 months) in the Romanian orphanages have grown into healthy, happy and well-functioning adults, indicating that even severe, prolonged childhood deprivation does not make subsequent developmental problems inevitable. 
There are few key points here, particularly from the point of view of an aspiring parent. It’s quite remarkable that the Romanian orphans who were adopted before 6 months displayed no observable long term impairments as a consequence of their severe early deprivation. My wife and I recently read a parenting book written very stern paediatrician, who informed us in no uncertain terms that breast feeding is an absolute must up until 6 months of age (no exceptions!) and that even a single bottle feed would risk irreparably and permanently harming our baby. The fact that 5 months of exposure to the horrific conditions of a Romanian orphanage (which certainly did not come with a readily available supply of breast milk) was not sufficient to generate permanent impairment makes me very sceptical about the paediatrician’s claims.
Of course, there are some caveats that need to be noted in the interpretation of the above findings. The Romanian adoptees were compared to UK-born adoptees, so this was not a randomised control experiment. That is, children were not randomly assigned to either experience or to not experience severe deprivation before adoption. Rather, their experience of severe deprivation was determined by their pre-existing life circumstances: their country of birth and the circumstances of their parents. This means that there may have been factors that varied systematically between Romanian and UK born adoptees (aside from severe deprivation) that generated or masked differences between them. For instance, the hardships of communist Romania forced many children from “typical” families into orphanages (Beckett et al., 2006), whereas in the UK, adopted children tend to come from families who are particularly disadvantaged (Plomin et al., 2013). The UK-born adoptees, having been born to particularly disadvantaged parents, may therefore have been at greater genetic risk for various developmental problems relative to the Romanian-born adoptees. This could have masked some of the detrimental effects of early deprivation in the Romanian sample, because it would have meant that they were compared with an artificially low standard. As such, the absence of significant developmental differences between UK adoptees and Romanian orphans who were adopted into the UK before 6 months of age does not necessarily permit the inference that early deprivation is developmentally inconsequential when remedied prior to 6 months.
Nevertheless, data from the Romanian adoptees has clearly demonstrated that early deprivation or receipt of inadequate adult care is detrimental to later development. For instance, Almas et al. (2016) found that orphans who were randomly selected to be taken out of their existing childcare institution and placed in the care of a foster family developed higher IQs relative to their peers who remained in institutional care. Because this study randomly selected children to be taken out of foster care, its results permit causal inference with respect to the causal impact of institutional vs. foster care on IQ.
So, all in all, there is pretty good evidence that parenting has at least some causal impact on children’s development. The surprising lack of impairment among Romanian adoptees who were adopted prior to six months of age notwithstanding, this seems to indicate that parenting is not, in fact, futile.
A Non-Linear relationship?
I should note one important fact that is often overlooked in the debate surrounding the importance of parenting practices on child development, namely the fact that much of the hard evidence for the causal influence of parenting comes from studies that have used samples of atypically disadvantaged children. Understandably, researchers tend to be more interested in finding ways to improve outcomes for children growing up in very difficult circumstances rather than children who already have quite bright prospects. Thus, much of the existing research that has employed randomised control trials to assess causal influences on child development has tended to focus on the capacity of a factor or factors of interest to improve outcomes for children in high-risk groups. For instance, there have been plenty of randomised control trials examining interventions aimed at the parents of young people at high risk of behavioural emotional, cognitive and social problems. However, relatively few studies involve interventions designed to improve developmental outcomes for children who are already at relatively low risk.
This raises the possibility that the relationship between parenting quality and child outcomes may be non-linear. It may be that improvements in parenting quality confer benefits to children only up to a point; past this point, the impact of additional improvements in parenting quality may confer diminishing benefits to the child. In other words, having OK parents may be much, much better than having awful parents, but having amazing parents may only be slightly better than having OK parents (see figure 2 for a graphical representation of this statistical relationship). For example, let’s say that parenting quality can be quantified in terms of how frequently a parent reads to their child, and that the quality of a child’s development outcomes can be quantified in terms of their reading ability. It may be that reading to one’s child for 1 hour a week dramatically improves their reading ability relative to 0 hours per week of reading. But reading to them for 2 hours a week may only slightly increase their reading ability relative to 1 hour of reading per week, the benefit of 3 hours of parental reading relative to 2 hours may be even less. For every additional hour of parental reading per week, the benefit in terms of the child’s reading ability may continuously diminish (i.e. there may be diminishing returns to parents’ investment in their children).
If this was the case, then a literature bias in favour of utilising disadvantaged samples in RCT studies would lead to an overly optimistic impression of the extent to which parents can influence the ways in which their children develop. For instance, if an RCT reveals that, among disadvantaged families, reading to one’s children improves their literacy abilities, we cannot necessarily assume that the result will extrapolate to non-disadvantaged families. In non-disadvantaged families, children are likely to be read to more regularly than in disadvantaged families, even in the absence of any interventions designed to encourage parental reading. As such, according to the above conjecture, the benefit conferred on these children by any further increases in parental reading may be minimal. Their parents may already read to them so frequently that further increases in reading time yield little to no additional benefit. Thus, the magnitude of the effect of parental reading estimated on the basis of studies using disadvantaged samples would not extrapolate to advantaged families.
There is some evidence that this “diminishing returns” principle is indeed applicable to many aspects of child development. For instance, in their review of a wide range of family-based interventions, Engle et al. (2011) concluded that interventions tend to be more effective when directed at the most disadvantaged children. Using samples of twins from high and low socio-economic status families, Turkeimer et al. (2003) found that the family environment has a significant impact on IQ for poorer children, but that variation in IQ across wealthy children is largely attributable to genetic factors. This indicates that improvements in the family environment may be capable of improving IQ in children who are disadvantaged, but that wealthier children tend to already have highly cognitively stimulating home environments, such that further improvements therein would have no impact on their IQ. Furthermore, a number of studies have shown that the relationship between parental wealth and child educational attainment is non-linear, with increases in parental wealth associated with greater increases in child educational attainment at lower regions of the wealth distribution. The same non-linear relationship has been found between parent and child education in developing countries.
Research on Romanian adoptees also appears to support the diminishing returns principle. Adoptees who were taken from the extreme deprivation of Romanian orphanages to well-functioning UK families experienced a drastic improving in cognitive, emotional and physical functioning. However, Beckett et al. (2006) failed to find an effect of adopted parent educational level on any of the developmental outcomes measured for the Romanian adoptees. This suggests that being raised in a typical UK home is much better than being raised in a Romanian orphanage under Ceausescu, but that once you make it into a UK home, you have already reached an upper region of the parenting quality distribution wherein further increases in parenting quality (as indexed by parental education) have minimal impact. In other words, the effect of improvements in a child’s rearing environment may diminish as the rearing environment increases in quality.
Perhaps this provides room for a mid-way position with regard to the importance of parents as causal contributors to development: parenting is not futile, in the sense that abusing or neglecting one’s children will be extremely likely to cause them permanent harm. But once you have already reached the stage of being an adequate parent, then making an effort to further improve your parenting practices may be of minimal benefit to your children.
However, I would not have started this blog if I believed this to be true. Whilst it is almost certainly the case that variation in parenting practices makes more of a difference at the lower end of the parenting quality distribution, this does not mean that parenting becomes inconsequential once you reach the upper portions of the distribution. There are plenty of RCTs showing that improvements in parenting practices can be of benefit to children who are likely to already be receiving high quality parenting.Moreover, parenting is a multifaceted process that comprises many different domains of activity (e.g. discipline, provision of nutritious food, guidance in mastering important cognitive milestones etc.). For many of these domains, there is no evidence that the relationship between parenting practices and child outcomes is non-linear, and there is even evidence that the effects of improvements in care-giving are more pronounced at the upper portions of the caregiving quality distribution.
Furthermore, it is important to note that interventions targeting disadvantaged children have an obvious advantage, which I call the “low-hanging fruit” advantage. For instance, consider the issue of malnutrition, which can be devastating for those that it affects. In a developed country, one generally has to be a pretty awful parent to allow one’s children to suffer from malnutrition (although in some instances parents obviously cannot be blamed for such things). So simply by providing one’s children with a basic level of nutrition, one can avoid the serious issues that would be expected to affect the children of highly neglectful parents. Thus, by moving from “extremely neglectful” to “quite neglectful (but not neglectful enough to induce malnutrition)”, a parent can confer a huge benefit to their child. Better still, a parent might not only try to ensure that their child is not malnourished, but they may even encourage their children to eat healthy foods whilst avoiding unhealthy foods. But this would be more challenging – children generally favour sweet, fatty and unhealthy foods over broccoli and cabbage, and it therefore takes a great deal of effort, commitment and skill on the part of parents to raise a healthy eater. Moreover, the increased parental effort that is required yields a diminished return: the health gap between unhealthy eaters and malnourished eaters is much wider than the gap between unhealthy eaters and healthy eaters.
In other words, avoiding malnutrition can be classified as a goal that is analogous to low-hanging fruit: you have to be a pretty bad parent (or a pretty bad fruit-picker) not to attain it. But you have to be a much more committed parent (or be prepared to climb much higher) to obtain to the high-hanging fruit, namely a child who is a healthy eater. Moreover, the low-hanging fruit are the juiciest – the most serious problem is the one that is easiest and cheapest to prevent. As one ascends the fruit tree, the additional gains afforded by the extra fruit diminish. Of course, anyone who reaches the upper levels of the fruit tree will already have picked the lower-hanging fruit, so it is always better to be higher up. The point remains, however, that the gain achieved by additional ascent reduces as one’s starting height increases.
This is true in many other areas of child-development as well. It’s easy to give your infant some form of pleasant human contact some of the time, but providing highly stimulating and engaging interactions a lot of the time is much more difficult. Meanwhile, the devastating effects of severe social deprivation relative to mere social impoverishment are much greater than the effects of social impoverishment relative to social enrichment. Thus, the low-hanging fruit (providing some social contact) are much juicier than the high-hanging fruit (providing optimal social contact). The same is true of many aspects of parenting.
Children who have highly motivated parents are therefore only likely to have small problems that are very difficult to ameliorate, whereas children with less motivated parents are likely to have more serious problems that are easier to ameliorate. Thus, interventions aimed at children whose parents have been less successful in creating favourable rearing environments can target the low-hanging fruit. They can tackle the easily-resolved-but-serious problems, achieving high gain at relatively low cost. Conversely, an intervention aimed at children raised in more favourable environments will have to target the high-hanging fruit. These children’s parents are likely to have solved most of the serious, easily-resolved problems that their children face, meaning that any intervention will have to expend relatively more resources resolving relatively less serious problems in order to be of benefit these children. Consequently, interventions targeting disadvantaged children are likely to generate higher effect sizes than interventions targeting non-disadvantaged children.
Whilst this explains why the effectiveness of family interventions varies as a function of social (dis)advantage, it does not mean that the high-hanging fruit are not worth the effort involved in their attainment. They may be more difficult to reach, but they still confer benefits on one’s children. So, as far as I am concerned, trying to improve one’s parenting is worth the effort at all regions of the parenting quality distribution.
 Permit me to present an early qualification to avoid sounding horrendously arrogant from hereon in: when I criticise or praise certain parenting practices, and when I outline my intention to follow parenting practices that I deem to be “awesome”, I do not seek to convey any value judgements about myself or others. My comments about the favourability or lack thereof of certain parenting characteristics refer to the empirically documented impact of the characteristics themselves, not to the parents who possess them. I recognise that many parental characteristics that influence a child’s development are impossible or very difficult for parents to control (e.g. parent socio-economic status; parental divorce; parental death; parental exposure to disease). When it comes to comments about my own plans to provide a favourable rearing environment for Dahlia, I speak of nothing more than intentions. Dahlia is yet to be born and, as such, I have no idea how successful these intentions will be. In short, I don’t mean anything I write to sound judgemental.
 Moffitt, 2005
 Butterfield, 1996; 2002
 Parker, 1983
 Furnham & Cheng, 2015
 Payne, Whitehurst and Angel, 1994
 Not that all forms of right wing ideology involve racism; Duriez and Soenens, 2009
 Thornberry, 1996
 Parrot, Silk and Conduit, 2003
 This phrase assumes far too much functional specificity within the human brain, but I think it sounds nice. Also, half a neuron is a dead neuron.
 Aside from the fact that the deceptive marketing of ice cream to children to the extreme detriment of their health is, arguably, murder – but that is for another post.
 See Mota et al., 2006 for example of something like this
 Unless, of course, the environmental alteration that is applied transpires to be unintentionally harmful (e.g. the “higher-quality day-care centres turn out to be not so high quality after all). The risk of such an eventuality must be assessed by an ethics committee – if the risk of any participants being harmed is deemed to be unacceptably high, then the research will be unlikely to receive ethical approval and will therefore be prevented from taking place.
 Strictly this is not actually true. All humans are almost entirely genetically identical – 99.9% of the DNA of one human will be identical to that of any other human. When we say that DZ twins share 50% of their DNA, we mean that even if you zoom in to focus only on the 0.1% of sites on the human genome where any two given people can differ, then the two members of a given DZ twin pair will have the identical DNA at 50% of these sites (this is an average – some DZ twin pairs may be more genetically similar; others may be less genetically similar). MZ twins have the same DNA at 100% of these sites (although, as we shall see later, even MZ twins are not totally genetically identical to each other).
 Statistical correlation and its application to twin research is a bit too complicated to explain fully in the current post, but for anyone interested see here.
 Remember, this means that if we had a magic button that would make everybody’s genes the same, the amount of individual variation in each of the big 5 personality traits would be reduced by 45%.
 Vernon, Villani, Vickers and Harris, 2008; Jang, Livesley and Vernon, 1996; Plomin and Caspi, 1990; Johnson, Vernon & Feiler, 2008; Krueger and Johnson, 2008
 Vukasovic and Bratko, 2015
 Tienari et al., 2003; Wicks, Hjern and Dalman, 2010
 Ask, Torgersen, Seglem and Waaktaar, 2014; Rapee, Schniering and Hudson, 2009
 Bergen, Gardner and Kendler, 2007; Haworth et al., 2010; Briley and Tucker-Drob, 2013
 Agrawal & Lynskey, 2013
 Ball et al., 2008
 Silventoinen et al., 2010
 McGue and Lykken, 1996
 D’Onfrio et al., 1999
 Frisell, Pawitan, Langstrom & Lichtenstein, 2012; Rhee and Waldman, 2002
 Rice, 2009; McAdams et al., 2015
 Brannigan et al., 2002
 O’Conner et al., 1998
 Moffitt, 2005
 Harris, 1998
 Johnson and Newport, 1989
 Turkheimer, 2016
 Dishion et al., 1999; Bandura, Ross and Ross, 1963
 Thomas et al., 2013
 Gardner & Steinberg, 2005
 Witvliet et al., 2009
 Westenberg et al., 2004
 Dishion and Tipsord, 2011
 Zimmerman, 2003; Kermer and Levy, 2002
 Fafchamps & Mo, 2015
 Haun et al., 2013
 Clarkson et al., 2016; Espelage et al., 2015; Olweus & Limber, 2007
 Caspi et al., 2004
 Sanders et al., 2000; see also Sanders et al., 2008
 Calam et al., 2008; Carta et al., 2013; Guttentag et al., 2014
 Rutter et al., 1999
 Kennedy et al., 2016
 Kumsta et al., 2016
 Beckett et al., 2006
 FYI, my wife and are planning on breastfeeding, but we are doubtful of all the weird and wonderful claims about its benefits. Based on the available evidence (which, surprisingly, is extremely scarce when it comes to randomised control trials), we think that breastfeeding probably has mild benefits relative to bottle feeding. I’ll discuss this more in a later post.
 Diamond & Lee, 2011
 Sheldon & King, 2001
 Hutchings et al., 2007
 Perry, 2014
 Keen et al., 2010
 Cates et al., 2016
 Diamond & Lee, 2011
 By parenting quality, I mean an aggregate of all the parenting variables that impact children in ways that are generally considered to be important.
 Karagiannaki, 2012
 Blunch, 2012
 Rutter et al., 1999; Beckett et al., 2006
 I’m assuming that more educated parents are generally “better” parents in the sense that they provide a more developmentally beneficial rearing environment; this is a fair assumption to make (Lundberg et al., 2014).
 Engle et al., 2011
 Lakes et al., 2004; Morawska & Sander, 2009
 Beijersbergen et al., 2012
 Finch et al., 2015
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