How to increase children’s patience in 5 seconds

A single act increases adults’ compliance with researchers. The same act makes students more likely to volunteer to solve math problems in front of others. Moreover, it makes four-year-olds more patient. What sounds like a miracle cure to everyday problems is actually the oldest trick in the book: human touch.

How do researchers know this? Here is one experiment. In a recently published study (Leonard et al., 2014), four and five year old children were asked to wait for ten minutes in front of candy. The experimenter told them to wait before eating the candy because he had to finish paperwork. How long would children wait before calling the experimenter in because they wanted to eat the candy earlier? Four-year-olds waited for about six minutes while five-year-olds waited for about eight minutes. The task was similar to the classic Marshmallow test shown in the video.


The positive effect of touch

However, it all depends on whether the experimenter gave children a friendly touch on the back during the request to wait. If she did, four-year-olds waited for seven minutes (versus 5 minutes without touch) and five-year-olds waited for nine minutes (versus seven minutes without touch). A simple, five-second-long touch made four-year-olds behave as patiently as five-year-olds. It’s surprising how simple and fast the intervention is.

Touch across the ages

This result nicely fits into a wider literature on the benefits of a friendly touch. Already back in the eighties Patterson and colleagues (1986) found that adults spent more time helping with the tedious task of scoring personality tests if they were touched by the experimenter. Interestingly, the touch on the shoulder was hardly ever reported as noteworthy. In the early noughties Gueguen picked this effect up and moved it to the real world. He showed that touch also increases adults’ willingness to help by watching after a large dog (Gueguen & Fisher-Loku, 2002) as well as students’ willingness to volunteer to solve a math problem in front of a class (Gueguen, 2004).

The reason underlying these effects remains a bit mysterious. Does the touch on the back reduce the anxiety of being faced with a new, possibly difficult, task? Does it increase the rapport between experimenter and experimental participant? Does it make time fly by because being touched feels good? Well, time will tell.

Touch your child?

There are obvious sexual connotations related to touching people, unfortunately this includes touching children. As a result, some schools in the UK have adopted a ‘no touch’ policy: teachers are never allowed to touch children. Research shows that such an approach comes at a cost: children behave less patiently when they are not touched. Should society deny itself the benefits of people innocently touching each other?


Guéguen N, & Fischer-Lokou J (2002). An evaluation of touch on a large request: a field setting. Psychological reports, 90 (1), 267-9 PMID: 11898995

Guéguen, N. (2004). Nonverbal Encouragement of Participation in a Course: the Effect of Touching Social Psychology of Education, 7 (1), 89-98 DOI: 10.1023/B:SPOE.0000010691.30834.14

Leonard JA, Berkowitz T, & Shusterman A (2014). The effect of friendly touch on delay-of-gratification in preschool children. Quarterly journal of experimental psychology (2006), 1-11 PMID: 24666195

Patterson, M., Powell, J., & Lenihan, M. (1986). Touch, compliance, and interpersonal affect Journal of Nonverbal Behavior, 10 (1), 41-50 DOI: 10.1007/BF00987204


Music training boosts IQ

There are more and more brain training companies popping up which promise the same deal: improved intelligence. While there are doubts about their results, another sort of brain training has existed since the beginning of humanity: music. The evidence for its effectiveness is surprisingly strong.


Music Lesson, 1936

Brain training in the 1930’s.

Over the years, researchers have noticed that people who have taken music lessons are better on a wide range of seemingly unconnected tasks. Just look at this impressive list:


Mathematics (across many different tasks; Vaughn, 2000)
Reading (understanding a written text; Corrigall & Trainor, 2011)
Simon task (quickly overcoming an easy, intuitive response in order to do a task right; Bialystok & DePape, 2009)
Digit Span (repeating a long list of random digits; Schellenberg, 2011)
Simple Reaction Time (pressing a button as soon as possible; Hughes & Franz, 2007)


None of these tasks has anything to do with music classes. What is it that makes music lessons correlate with them? It could just be the socio-economic background: the more well-off or well-educated the parents the better the education of their children, including their music education (e.g., Corrigall et al., 2013). However, one can adjust for these differences with statistical tricks and the general picture is that the family background cannot fully explain the advantage musically trained children have on all sorts of tasks (e.g., Corrigall & Trainor, 2011; Schellenberg, 2011). If not family background, then what is underlying the music children advantage?


Füssli: Liegende Nackte und Klavierspielerin

Brain training in the 18th century. I am referring to the left lady.

Another contender is a common factor making some people good on all sorts of seemingly unrelated tasks and other people bad on nearly any task. This factor is called ‘g’ or general intelligence. An indeed, people who have enjoyed a musical education score higher on intelligence tests than people who did not. This has been shown across the globe: North America (Schellenberg, 2011), Europe (Roden et al., 2013), Asia (Ho et al., 2003†). The consistency across age groups is also impressive: 6-11 year olds (Schellenberg, 2006), 9-12 year olds (Schellenberg, 2011), 16-25 year-olds (Schellenberg, 2006). So, what holds these tasks and music education together is general intelligence. But that just opens up the next question: what causes this association between general intelligence and music lessons?
Music lessons cause higher intelligence
The most exciting possibility would be if music lessons actually caused higher intelligence. In order to make such a claim one needs to take a bunch of people and randomly assign them to either music lessons or some comparable activity. This random assignment ensures that any previous differences between music and non-music children will be equally distributed across groups. Random chance assignment at the beginning of the experiment ensures that any group differences at the end must be due to the whether children took music lessons during the experiment or not. Glenn Schellenberg did exactly this experiment with over 100 six-year-olds in Toronto (2004). Over a period of one year the children who learned to play the keyboard or to sing increased their IQ by 7 points. Children who were given drama lessons instead or simply no extra-curricular activity only increased by 4 points (likely because they started school in that year). A similar study which recently came out of Iran by Kaviani and colleagues (2013) replicates this finding. After only three months of group music lessons, the six-year-old music children increased their IQ by five points while children who were not assigned to music lessons only improved by one point. Across studies music lessons boost IQ.
It is worth reiterating how impressive this effect is. It has been found across three different music teaching approaches (standard keyboard lessons, Kodály voice lessons, Orff method). It has been replicated with two different sorts of intelligence tests (Wechsler and Stanford-Binet) as well as most of their subscales. It even came up despite the cultural differences between testing countries (Canada, Iran).
The take-home message couldn’t be any clearer. Music lessons are associated with intelligence not just because clever or well-off people take music lessons. A musical education itself makes you better across many tasks generally and on IQ tests specifically. No other ‘brain training’ has such a strong evidence base. Music is the best brain training we have.


Eros and a youth

Ancient Greek brain training. I am referring to the gentleman on the right.


Bialystok E, & Depape AM (2009). Musical expertise, bilingualism, and executive functioning. Journal of experimental psychology. Human perception and performance, 35 (2), 565-74 PMID: 19331508

Corrigall KA, Schellenberg EG, & Misura NM (2013). Music training, cognition, and personality. Frontiers in psychology, 4 PMID: 23641225

Corrigall, KA, & Trainor, LJ (2011). Associations Between Length of Music Training and Reading Skills in Children Music Perception: An Interdisciplinary Journal,, 29 (2), 147-155 DOI: 10.1525/mp.2011.29.2.147

Ho YC, Cheung MC, & Chan AS (2003). Music training improves verbal but not visual memory: cross-sectional and longitudinal explorations in children. Neuropsychology, 17 (3), 439-50 PMID: 12959510

Hughes CM, & Franz EA (2007). Experience-dependent effects in unimanual and bimanual reaction time tasks in musicians. Journal of motor behavior, 39 (1), 3-8 PMID: 17251166

Kaviani H, Mirbaha H, Pournaseh M, & Sagan O (2013). Can music lessons increase the performance of preschool children in IQ tests? Cognitive processing PMID: 23793255

Roden, I, Grube, D, Bongard, S, & Kreutz, G (2013). Does music training enhance working memory performance? Findings from a quasi-experimental longitudinal study Psychology of Music DOI: 10.1177/0305735612471239

Schellenberg EG (2004). Music lessons enhance IQ. Psychological science, 15 (8), 511-4 PMID: 15270994

Schellenberg, EG (2006). Long-Term Positive Associations Between Music Lessons and IQ Journal of Educational Psychology, 98 (2), 457-468 DOI: 10.1037/0022-0663.98.2.457

Schellenberg EG (2011). Examining the association between music lessons and intelligence. British journal of psychology, 102 (3), 283-302 PMID: 21751987

Vaughn, K (2000). Music and Mathematics: Modest Support for the Oft-Claimed Relationship Journal of Aesthetic Education,, 34 (3/4), 149-166 DOI: 10.2307/3333641



† Effect only marginally significant (0.05<p<0.1)



1) By Franklin D. Roosevelt Presidential Library and Museum [Public domain], via Wikimedia Commons

2) By Johann Heinrich Füssli: Liegende Nackte und Klavierspielerin, via Wikimedia Commons

3) attributed to the Penthesilea Painter, between circa 460 and circa 450 BC, via Wikimedia Commons

Is ADHD different around the globe? The role of research cultures

An illness is an illness wherever you are. Perhaps this is true for organic diseases but the cultural background can play a tremendous role in the progression and even diagnosis of mental disorders (see e.g., David Dobbs recent post at Wired). However, what has been neglected is an appreciation of how culture affects the research underlying the diagnosis and treatment of psychological disorders. As a consequence, our view on the disorder can change.

Attention deficit hyperactivity disorder shows how culture can exert quite some effect on psychiatric research. In a 2007 meta-analysis by Polanczyk and colleagues prevalence rates were found to differ markedly between geographic regions, but not in the way you might expect. As opposed to the myth of ADHD as an American social construct, European and North American ADHD rates were not significantly different. But both were significantly different to the prevalence rates in Africa and the Middle East.
ADHD in school

One case of ADHD. Or perhaps two. Depends where we are.

However, Polanczyk and colleagues state that this is most likely due to different criteria for diagnosis and study inclusion. For example, while the diagnostic system published by the World Health Organisation is quite strict, the one published by the American Psychiatric Association is more liberal. Depending on which one the researchers adopt, the same person could be part of the ADHD group in one study and the control group in another one.
These different inclusion criteria appear to bias international comparisons. The severe restrictions on ADHD diagnosis in Middle Eastern studies can increase the apparent ADHD severity and social problems. Don’t be surprised then if you read that Middle Eastern ADHD kids fare worse in life than their American counterparts.
Beyond different inclusion criteria, the focus of studies can differ by geographic region. In a recent review, Hodgkins et al. (2012) showed that about half of North American and European ADHD studies sampled adults. East Asian researchers, on the other hand, were mainly interested in adolescents and only sampled adults in about a third of studies. Will this result in ADHD as a potentially life long disease in the Western view while the Easten perspective sees it as part of the transition to adulthood? If so, researchers could be partly to blame for this difference.
Finally, what life consequences a ADHD diagnosis entails is differently researched. While East Asians are mainly interested in effects on self-esteem, Europeans focus more on antisocial behaviour. North American researchers, on the other hand, measure drug abuse and addiction outcomes more than their European or East Asian counterparts. A single headline grabbing result could forever associate inattentive kids with drug abuse. Don’t expect this result to emerge in Asia, it is likely to be found in the US.
This is not to say that ADHD, its prevalence in different age groups or its life consequences are entirely determined by research agendas. Evidence is still needed to support diagnosis or treatment. However, whether anyone ever looked for this evidence is dependent on culture. Across the world research cultures, i.e. strategies to get scientific evidence, differ. Don’t be surprised then if evidence based psychiatry differs as well.

Hodgkins P, Arnold LE, Shaw M, Caci H, Kahle J, Woods AG, & Young S (2011). A systematic review of global publication trends regarding long-term outcomes of ADHD. Frontiers in psychiatry / Frontiers Research Foundation, 2 PMID: 22279437

Polanczyk G, de Lima MS, Horta BL, Biederman J, & Rohde LA (2007). The worldwide prevalence of ADHD: a systematic review and metaregression analysis. The American journal of psychiatry, 164 (6), 942-8 PMID: 17541055

1) By CDC ( [Public domain], via Wikimedia Commons


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Risk vs. Opportunity across the life-span: Risky choices decline with age

Risk taking is somewhat enigmatic. On the one hand, risky choices in every day life – like drug abuse or drink driving – peak in adolescence. Never again in life is the threat to die from easily preventable causes as great. On the other hand, in laboratory experiments this risky choice peak in adolescence is absent. Instead, the readiness to take a gamble simply goes down the older you are. How can we explain this paradox? Perhaps, we should look at a tribe in the Amazon rain forest for answers.

A group of psychologists from Duke University led by David Paulsen looked at risk taking in the laboratory. Participants had the choice between either a guaranteed mediocre reward (say, four coins) or a gamble with a 50/50 chance of getting a low (e.g., two coins) or a high (e.g., six coins) reward. This is reminiscent of many choices we face in life: do you prefer ‘better safe than sorry’ or ‘high risk/high gain’? As you can see in their figure below, Paulsen and colleagues found adolescents to be greater risk seekers than adults. No matter how risky the gamble, adolescents choose it more often compared to adults.
risk taking across age groups

‘Better save than sorry’ vs. ‘High risk – high gain’

Paradoxically, children are even more risk prone than adolescents. Moreover, the riskier the gamble the greater the difference to older people. Paulsen and colleagues have trouble explaining why risky choices in the laboratory do not show an adolescent peak which so many real world behaviours show. Could it have to do with laboratory risk being clearly defined while real world risk is unknown? Is it peer influencing which drives real world riskiness but is absent in the laboratory? Is there more thrill in real risk taking while lab experiments are so boring that thrill seeking doesn’t come into play?
Perhaps. However, one explanation – which I, personally, found totally obvious – is not even discussed. Risky choices decline with age, true. But the opportunity to make risky choices increases with age. In Western society there are both explicit laws as well as implicit norms that prevent children from the opportunity to take risks. Take as an example alcohol abuse. Many people perceive a party without alcohol as mediocre. With alcohol, however, you take a gamble between doing something very regrettable (read, low reward) or having the time of your life (read, high reward).
Amazon rainforest

Where to test an alternative explanation: the real world.

How does this play out across the life span? It is inconceivable to serve beers at children’s birthday parties. However, the older you are the more you choose yourself what is served at your parties. When you are a young adolescent this increased risk taking opportunity meets a still high (but declining) risk taking readiness and you get wasted.
So, with age, risk taking goes down because the opportunities to take risks do not get more after a certain age while the readiness to take these risks still declines. The outcome would be a peak in real life risk taking at adolescence despite a linear decline in risky choices, i.e. exactly the observed pattern.
This interaction between risk taking opportunities and risk taking readiness is nicely illustrated by a native American tribe Dan Everett described in his very readable book Don’t Sleep, There are Snakes. The Pirahã do not have the Western notion of childhood. Everett writes that ‘children are just human beings in Pirahã society, as worthy of respect as any fully grown human adult. They are not seen as in need of coddling or special protections.’ (p.89). As a consequence, ‘there is no prohibition that applies to children that does not equally apply to adults and vice versa’ (p.97).
What does this mean for child alcohol consumption on the infrequent occasions when alcohol is available to the tribe? This episode gives the answer (p. 98):
Once a trader gave the tribe enough cachaça [alcohol] for everyone to get drunk. And that is what happened. Every man, woman and child in the village got falling-down wasted. Now, it doesn’t take much alcohol for Pirahãs to get drunk. But to see six-year-olds staggering with slurred speech was a novel experience for me.
So, perhaps this solves the paradox. The laboratory results were unrealistic by Western standards because they gave children a choice which they usually do not have: sure reward or gamble? Once you look at societies that do give children this choice you see that the laboratory results line up better with real life.
There is much to be learned by going beyond the laboratory and looking at the real world. The entire real world.


Everett, D. (2008). Don’t sleep, there are snakes. London: Profile Books

Paulsen, D.J., Platt, M.L., Huettel, SA, & Brannon, E.M. (2012). From risk-seeking to risk-averse: the development of economic risk preference from childhood to adulthood. Frontiers in psychology, 3 PMID: 22973247



1) as found in Paulsen et al. (2012)

2) By Jorge.kike.medina (Own work) via Wikimedia Commons






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Infants choose their teachers

By Hardeep Singh from Vancouver, Canada (Mohkam Mopping) [CC-BY-2.0 (], via Wikimedia Commons
My father has seen his four children grow up and is still fascinated with the things that children do NOT know. He likens them to a new computer whose hard drive is still void of information and needs to be filled by a user, i.e. by their parents or other care takers. The computer metaphor is a very widely used one in the cognitive sciences. It turns out that for infant learning it is a misleading one. Rather than being like an empty disc which accumulates knowledge, infants act like explorers who use every bit of information they have in order to make sense of the unknown, to evaluate new inputs and ultimately to decide for themselves what to learn.
Zmyj and colleagues have an article in press in the journal Infant and Child Development which illustrates this nicely. 14 month old infants were presented with a new object: a lamp. Ordinarily lamps are switched on with hands (you knew that, right?) but infants were shown videos in which another person switches the lamp on using the head. Will children imitate them and, thus, show evidence for learning in terms of how to use a new object? They will, but it depends on how old the person in the video is. Most infants imitated an adult, less infants imitated a child aged three and a half, even less imitated another infant. This pattern of results makes intuitive sense. Instead of imitating any person blindly, infants trust people more who tend to be more knowledgeable given that they are older.
Previously, Seehagen and Herbert (2011) had found similar results for infants asked to imitate a person building a rattle. However, Zmyj and colleages went further and showed that a different pattern emerges when children see a person use toys in a rather intuitive way. Now, the infant peer was imitated most and the older child or the adult less. Infants appear to imitate people differently depending on whether they want to acquire knowledge (adults have more knowledge than infants) or whether they want to have fun (infants know better how to have fun than adults). Even before their second birthday, children decide for themselves who they turn to for learning.
Infants deciding what to learn? At 14 months they can hardly speak. They just started walking. Toilet training is still an issue. And they should decide for themselves? The aforementioned studies could perhaps be reinterpreted in a less extreme way. Perhaps appearances drive the effect. By 14 months the child could find an adult more like parents and, thus, trust an adult more for learning novel things. It is imaginable that the child identified better with fellow infants when there is nothing to learn and, thus, imitates them more. This argument is not only a bit constructed, it is also contradicted by a bunch of publications contrasting two adults rather than an adult and an infant.
Chow and colleagues presented infants with either an adult who is reliable or an adult who is not. The unreliable adult would express great happiness when looking into a container even though the container is empty. Children may find such an adult a bit odd. His actions do not really match expectations. Chow and colleagues (2008) found infants to be more hesitant in exploring a container which an unreliable informant claimed contained a nice object. They followed a reliable adult’s information faster. The same or a similar manipulation of an adult’s reliability also changes other infant behaviours:
– their looks behind a barrier to see what the adult is going on about (Chow et al., 2008)
– their surprise at seeing the adult look in the wrong direction in order to find an object (Poulin-Dubois and Chow, 2009)
– their imitation of the head movement to switch on the aforementioned new lamp (Poulin-Dubois et al., 2011; Zmyj et al., 2010).
Infants are not like a container which you can fill with knowledge. The computer metaphor of an empty hard drive simply does not hold. Every new bit of information is evaluated in terms of where it comes from. This evaluation itself is driven by what the infant already knows. It is as if children try to coat themselves against unreliable information. Before toddlers have seen their second birthday cake they show a higher level of self-guided learning than parents realise. You better don’t act unreliable in front of them!
Chow, V., Poulin-Dubois, D., & Lewis, J. (2008). To see or not to see: infants prefer to follow the gaze of a reliable looker. Developmental Science, 11, 761-770. doi: 10.1111/j.1467-7687.2008.00726.x
Poulin-Dubois, D., & Chow, V. (2009). The Effect of a Looker’s Past Reliability on Infants’ Reasoning About Beliefs. Developmental Psychology, 45, 1576-1582. doi: 10.1037/a0016715
Poulin-Dubois, D., Brooker, I., & Polonia, A. (2011). Infants prefer to imitate a reliable person. Infant Behavior and Development, 34, 303-309. doi:10.1016/j.infbeh.2011.01.006
Seehagen, S., & Herbert, J.S. (2011). Infant Imitation From Televised Peer and AdultModels. Infancy, 16, 113-136. doi: 10.1111/j.1532-7078.2010.00045.x
Zmyj, N., Buttelmann, D., Carpenter, M., & Daum, M.M. (2010). The reliability of a model influences 14-moth-olds’ imitation. Journal of Experimental Child Psychology, 106, 208-220. doi:10.1016/j.jecp.2010.03.002
Zmyj, N., Daum, M.M., Prinz, W., Nielsen, M., & Aschersleben, G. (in press). Fourteen-month-olds’ imitation of differently aged models. Infant and Child Development. doi: 10.1002/icd.750