Category Archives: Psychology

Very interesting paper: Are the smartest people losing their intelligence?

This is a fascinating new paper by James Flynn (who’s name delivered The Flynn Effect) and Michael Shayer. The paper doesn’t present a smoking gun, but tries to see trends in countries who see a decline in average IQ and countries who don’t see the same decline. But they look deeper than averages on parts of the test, by also looking on which groups in the population are doing worse.

I can share with you the summarizing bullet points:

  • Important national differences, particularly the contrast between Scandinavia and elsewhere.
  • Dutch trends show that IQ gains vary by age which is indicative of the strength of various causal factors.
  • Piagetian trends provide information conventional tests do not: that the largest losses may be at the top of the curve.

Or even the abstract:

The IQ gains of the 20th century have faltered. Losses in Nordic nations after 1995 average at 6.85 IQ points when projected over thirty years. On Piagetian tests, Britain shows decimation among high scorers on three tests and overall losses on one. The US sustained its historic gain (0.3 points per year) through 2014. The Netherlands shows no change in preschoolers, mild losses at high school, and possible gains by adults. Australia and France offer weak evidence of losses at school and by adults respectively. German speakers show verbal gains and spatial losses among adults. South Korea, a latecomer to industrialization, is gaining at twice the historic US rate.

When a later cohort is compared to an earlier cohort, IQ trends vary dramatically by age. Piagetian trends indicate that a decimation of top scores may be accompanied by gains in cognitive ability below the median. They also reveal the existence of factors that have an atypical impact at high levels of cognitive competence. Scandinavian data from conventional tests confirm the decimation of top scorers but not factors of atypical impact. Piagetian tests may be more sensitive to detecting this phenomenon.

But honestly, there are so many nuances in the article that both these summaries don’t do justice. I think this 2 parts of the conclusion are the most important elements of the paper.

Excerpt 1:

Nations that are candidates for IQ decline give evidence that ranges from beyond dispute to fragmentary. The strongest comes from Scandinavia as a whole, Britain (Volume and Heaviness), and Germany (spatial). Nordic data cover vocabulary, similarities, analogies, shapes, metal folding, number series, geometrical figures, and letter matrices. The pivotal year for all of these nations seems to be about 1995. Data from France and Australia await further studies but cannot be dis- missed. The US is strange. All ages plow on unaffected as yet. Black gains are larger than white but white gains are still robust (Flynn, 2012a). The quick developing world (Korea) and the slow developing world will of course continue to gain for some time.

These trends come as no surprise. Flynn has argued that industrialization may eventually pay diminishing returns in developed nations. Until very recently, we have enjoyed a more favorable ratio of adults to children in the home, more and better schooling, more cognitively demanding jobs, and better health and conditions of the aged. These caused large IQ gains for several generations. However, the same factors can turn from positive to mixed or even negative. The number of children in the home has reached a minimum (and indeed there are more solo-parent homes), middle class parents have used up the tricks that make the pre-school environment cognitively enriching, we appear to have reached a limit in terms of enhanced schooling and the number we keep in school into adulthood, the economy may be producing fewer cognitively demanding jobs in favor of more service work; however, we may continue to improve the health of the aged.

Excerpt 2 (bold by me):

The Piagetian results are particularly ominous. Looming over all is their message that the pool of those who reach the top level of cognitive performance is being decimated: fewer and fewer people attain the formal level at which they can think in terms of abstractions and develop their capacity for deductive logic and systematic planning. They also reveal that something is actually targeting that level with special effect, rather than simply reducing its numbers in accord with losses over the curve as a whole. We have given our reason as to why the Piagetian tests are sensitive to this phenomenon in a way that conventional tests are not.

Massive IQ gains over time were never written in the sky as something eternal like the law of gravity. They are subject to every twist and turn of social evolution. If there is a decline, should we be too upset? During the 20th century, society escalated its skill demands and IQ rose. During the 21st century, if society reduces its skill demands, IQ will fall. Nonetheless, no one would welcome decay in the body politic, or among the elite who at present represent our best thinkers. Although it might be argued that the character of the electorate will be enhanced if it contained fewer lawyers and more plumbers and service workers.

It is always possible that our schools and universities will graduate more young people who read and become more critically astute. This in itself would put a limit on IQ losses on Vocabulary, Information, and most Verbal tests, and on accepting the stereotypes that cloud moral reasoning and political prudence.

 

 

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Is there a link between working memory and physical exercise?

There have been numerous studies that make a link between physical exercise and learning, but this new study looks a bit deeper as it shows a positive relationship between the brain network associated with working memory — the ability to store and process information relevant to the task at hand — and healthy traits such as higher physical endurance and better cognitive function. (note: relationship doesn’t necessarily mean causal relation…) But it does seem mens sana in corpore sano.

From the press release:

These traits were associated with greater cohesiveness of the working memory brain network while traits indicating suboptimal cardiovascular and metabolic health, and suboptimal health habits including binge drinking and regular smoking, were associated with less cohesive working memory networks.

This is the first study to establish the link between working memory and physical health and lifestyle choices.

The results of the study will be published online in Molecular Psychiatry.

The research team took brain scans of 823 participants in the Human Connectome Project (HCP), a large brain imaging study funded by the National Institutes of Health, while they performed a task involving working memory, and extracted measures of brain activity and connectivity to create a brain map of working memory. The team then used a statistical method called sparse canonical correlation to discover the relationships between the working memory brain map and 116 measures of cognitive ability, physical and mental health, personality, and lifestyle choices. They found that cohesiveness in the working memory brain map was positively associated with higher physical endurance and better cognitive function. Physical traits such as high body mass index, and suboptimal lifestyle choices including binge alcohol drinking and regular smoking, had the opposite association.

“Working memory accounts for individual differences in personal, educational, and professional attainment,” said Sophia Frangou, MD, PhD, Professor of Psychiatry at the Icahn School of Medicine at Mount Sinai. “Working memory is also one of the brain functions that is severely affected by physical and mental illnesses. Our study identified factors that can either support or undermine the working memory brain network. Our findings can empower people to make informed choices about how best to promote and preserve brain health.”

Abstract of the study:

Working memory (WM) is a central construct in cognitive neuroscience because it comprises mechanisms of active information maintenance and cognitive control that underpin most complex cognitive behavior. Individual variation in WM has been associated with multiple behavioral and health features including demographic characteristics, cognitive and physical traits and lifestyle choices. In this context, we used sparse canonical correlation analyses (sCCAs) to determine the covariation between brain imaging metrics of WM-network activation and connectivity and nonimaging measures relating to sensorimotor processing, affective and nonaffective cognition, mental health and personality, physical health and lifestyle choices derived from 823 healthy participants derived from the Human Connectome Project. We conducted sCCAs at two levels: a global level, testing the overall association between the entire imaging and behavioral–health data sets; and a modular level, testing associations between subsets of the two data sets. The behavioral–health and neuroimaging data sets showed significant interdependency. Variables with positive correlation to the neuroimaging variate represented higher physical endurance and fluid intelligence as well as better function in multiple higher-order cognitive domains. Negatively correlated variables represented indicators of suboptimal cardiovascular and metabolic control and lifestyle choices such as alcohol and nicotine use. These results underscore the importance of accounting for behavioral–health factors in neuroimaging studies of WM and provide a neuroscience-informed framework for personalized and public health interventions to promote and maintain the integrity of the WM network.

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Do smarter people have better connected brains?

It is an interesting question if it is possible to see if a person is smart or not in a brain scan, although I sure do not hope we will start scanning the brains of pupils before entering school. Still, while differences in intelligence so far have mostly been attributed to differences in specific brain regions. However, this new study suggests that smart people’s brains are also wired differently to those of less intelligent persons.  In intelligent persons, certain brain regions are more strongly involved in the flow of information between brain regions, while other brain regions are less engaged.

From the press release:

Understanding the foundations of human thought is fascinating for scientists and laypersons alike. Differences in cognitive abilities — and the resulting differences for example in academic success and professional careers — are attributed to a considerable degree to individual differences in intelligence. A study just published in Scientific Reports shows that these differences go hand in hand with differences in the patterns of integration among functional modules of the brain. Kirsten Hilger, Christian Fiebach and Ulrike Basten from the Department of Psychology at Goethe University Frankfurt combined functional MRI brain scans from over 300 persons with modern graph theoretical network analysis methods to investigate the neurobiological basis of human intelligence.

Already in 2015, the same research group published a meta-study in the journal Intelligence, in which they identified brain regions — among them the prefrontal cortex — activation changes of which are reliably associated with individual differences in intelligence. Until recently, however, it was not possible to examine how such ‘intelligence regions’ in the human brain are functionally interconnected.

Earlier this year, the research team reported that in more intelligent persons two brain regions involved in the cognitive processing of task-relevant information (i.e., the anterior insula and the anterior cingulate cortex) are connected more efficiently to the rest of the brain (2017, Intelligence). Another brain region, the junction area between temporal and parietal cortex that has been related to the shielding of thoughts against irrelevant information, is less strongly connected to the rest of the brain network. “The different topological embedding of these regions into the brain network could make it easier for smarter persons to differentiate between important and irrelevant information — which would be advantageous for many cognitive challenges,” proposes Ulrike Basten, the study’s principle investigator.

In their current study, the researchers take into account that the brain is functionally organized into modules. “This is similar to a social network which consists of multiple sub-networks (e.g., families or circles of friends). Within these sub-networks or modules, the members of one family are more strongly interconnected than they are with people from other families or circles of friends. Our brain is functionally organized in a very similar way: There are sub-networks of brain regions — modules — that are more strongly interconnected among themselves while they have weaker connections to brain regions from other modules. In our study, we examined whether the role of specific brain regions for communication within and among brain modules varies with individual differences in intelligence, i.e., whether a specific brain region supports the information exchange within their own ‘family’ more than information exchange with other ‘families’, and how this relates to individual differences in intelligence.”

The study shows that in more intelligent persons certain brain regions are clearly more strongly involved in the exchange of information between different sub-networks of the brain in order for important information to be communicated quickly and efficiently. On the other hand, the research team also identified brain regions that are more strongly ‘de-coupled’ from the rest of the network in more intelligent people. This may result in better protection against distracting and irrelevant inputs. “We assume that network properties we have found in more intelligent persons help us to focus mentally and to ignore or suppress irrelevant, potentially distracting inputs,” says Basten. The causes of these associations remain an open question at present. “It is possible that due to their biological predispositions, some individuals develop brain networks that favor intelligent behaviors or more challenging cognitive tasks. However, it is equally as likely that the frequent use of the brain for cognitively challenging tasks may positively influence the development of brain networks. Given what we currently know about intelligence, an interplay of both processes seems most likely.”

There are 3 studies linked to this insight:

  1. Kirsten Hilger, Matthias Ekman, Christian J. Fiebach, Ulrike Basten. Intelligence is associated with the modular structure of intrinsic brain networksScientific Reports, 2017; 7 (1) DOI: 10.1038/s41598-017-15795-7
    This is the most relevant abstract:

    General intelligence is a psychological construct that captures in a single metric the overall level of behavioural and cognitive performance in an individual. While previous research has attempted to localise intelligence in circumscribed brain regions, more recent work focuses on functional interactions between regions. However, even though brain networks are characterised by substantial modularity, it is unclear whether and how the brain’s modular organisation is associated with general intelligence. Modelling subject-specific brain network graphs from functional MRI resting-state data (N = 309), we found that intelligence was not associated with global modularity features (e.g., number or size of modules) or the whole-brain proportions of different node types (e.g., connector hubs or provincial hubs). In contrast, we observed characteristic associations between intelligence and node-specific measures of within- and between-module connectivity, particularly in frontal and parietal brain regions that have previously been linked to intelligence. We propose that the connectivity profile of these regions may shape intelligence-relevant aspects of information processing. Our data demonstrate that not only region-specific differences in brain structure and function, but also the network-topological embedding of fronto-parietal as well as other cortical and subcortical brain regions is related to individual differences in higher cognitive abilities, i.e., intelligence.

  2. Ulrike Basten, Kirsten Hilger, Christian J. Fiebach. Where smart brains are different: A quantitative meta-analysis of functional and structural brain imaging studies on intelligenceIntelligence, 2015; 51: 10 DOI: 10.1016/j.intell.2015.04.009
  3. Kirsten Hilger, Matthias Ekman, Christian J. Fiebach, Ulrike Basten. Efficient hubs in the intelligent brain: Nodal efficiency of hub regions in the salience network is associated with general intelligenceIntelligence, 2017; 60: 10 DOI: 10.1016/j.intell.2016.11.001

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New study shows: ‘Fake news’ = incorrect, but hard to correct.

#Fakenews is nothing new, despite some president claiming he invented it. But also because of that certain president there is a present surge of attention for the topic of ‘fake news’. This study by De Keersmaecker and Roets published in Intelligence adds some interesting insights on how people with lower cognitive abilities react to fake news in contrast to people with higher cognitive abilities:

  • When people learn their attitudes are based on false information, they adjust them.
  • People low (vs high) in cognitive ability adjust attitudes to lesser extent.
  • Adjusted attitudes remained biased for people low in cognitive ability.

This excerpt from the conclusion sums it up quite clearly:

In line with our expectations, results indicated that individuals with lower (versus higher) levels of cognitive ability were less responsive to this corrective new information, and the initial exposure to the incorrect information had a persevering influence on their attitudes. Specifically, when individuals with lower levels of cognitive ability learnt that their attitudes towards a target person were partly based on negative information that was incorrect, they did adjust their evaluation about the target person, but to a lesser degree than individuals with higher levels of cognitive ability. Importantly, the adjusted attitudes of individuals with lower levels of cognitive ability were still more negative compared to the evaluations of their counterparts who were never exposed to the incorrect negative information. Contrary, individuals with higher levels of cognitive ability made more appropriate attitude adjustments. In particular, after learning that the negative information was false, they adopted attitudes that were similar to those who had not received false information.

Noteworthy, these effects of cognitive ability on attitude adjustment were obtained regardless of whether or not we controlled for open mindedness (i.e., need for closure) and authoritarianism as potential confounding variables. This indicates that the obtained effects are genuine cognitive ability effects and that making appropriate adjustments of initial social impressions is indeed directly affected by cognitive ability.

Abstract of the study:

The present experiment (N = 390) examined how people adjust their judgment after they learn that crucial information on which their initial evaluation was based is incorrect. In line with our expectations, the results showed that people generally do adjust their attitudes, but the degree to which they correct their assessment depends on their cognitive ability. In particular, individuals with lower levels of cognitive ability adjusted their attitudes to a lesser extent than individuals with higher levels of cognitive ability. Moreover, for those with lower levels of cognitive ability, even after the explicit disconfirmation of the false information, adjusted attitudes remained biased and significantly different from the attitudes of the control group who was never exposed to the incorrect information. In contrast, the adjusted attitudes of those with higher levels of cognitive ability were similar to those of the control group. Controlling for need for closure and right-wing authoritarianism did not influence the relationship between cognitive ability and attitude adjustment. The present results indicate that, even in optimal circumstances, the initial influence of incorrect information cannot simply be undone by pointing out that this information was incorrect, especially in people with relatively lower cognitive ability.

 

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How to raise IQ? Education! (a new meta-analysis)

This morning Stuart Ritchie shared a preprint of a new meta-analysis he made together with Elliot Tucker-Drob and the theme is very relevant in many of the present discussions about education: the link between IQ and education. An important insight from the conclusion:

…the results support the hypothesis that education has a causal effect on intelligence test scores. The effect of one additional year of education—contingent on study design, inclusion of moderators, and publication bias correction—was estimated from approximately one to five points on the standard IQ scale.

And this is also important:

The results reported here indicate strong, consistent evidence for effects of education on intelligence. Although the effects—on the order of a few IQ points for a year of education— might be considered small, at the societal level they are potentially of great consequence. A crucial next step will be to uncover the mechanisms of these educational effects on intelligence, in order to inform educational policy and practice.

Still important questions remain. Ritchie and Tucker-Drob mention several, but I personally find this question very relevant for further research:

…are there individual differences in the magnitude of the educational effect? One possibility is the “Matthew Effect” (Stanovich, 1986), whereby children at greater initial cognitive (or socioeconomic) advantage benefit more from additional education than those at lower advantage. Another possibility is that education acts as an “equalizer”, such that those at lower levels of initial advantage benefit most (Downey, von Hippel, & Broh, 2004). Indeed, some evidence of an equalizing effect was reported in a single study by Hansen, Heckman, & Mullen (2004).

Read the abstract:

Intelligence test scores and educational duration are positively correlated. This correlation can be interpreted in two ways: students with greater propensity for intelligence go on to complete more education, or a longer education increases intelligence. We meta-analysed three categories of quasi-experimental studies of educational effects on intelligence: those estimating education-intelligence associations after controlling for earlier intelligence, those using compulsory schooling policy changes as instrumental variables, and those using regression-discontinuity designs on school-entry age cutoffs. Across 142 effect sizes from 42 datasets involving over 600,000 participants, we found consistent evidence for beneficial effects of education on cognitive abilities, of approximately 1 to 5 IQ points for an additional year of education. Moderator analyses indicated that the effects persisted across the lifespan, and were present on all broad categories of cognitive ability studied. Education appears to be the most consistent, robust, and durable method yet to be identified for raising intelligence.

 

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A new form of self-harm: cyberbullying yourself

I hadn’t heard this one before, according to this new paper a new form of self-harm in youth has emerged and is cause for concern. The behavior: ‘digital self-harm’ or ‘self-trolling,’ where adolescents post, send or share mean things about themselves anonymously online. The concern: it is happening at alarming rates and could be a cry for help. This new FAU study is the first to examine the extent of this behavior and is the most comprehensive investigation of this understudied problem and I was quite surprised to see that in a big sample 6% actually did this kind of self-harm.

From the press release:

Adolescents harming themselves with cuts, scratches or burns has gained a lot of attention over the years not just because of the physical damage and internal turmoil, but also because it has been linked to suicide. More recently, a new form of self-harm in youth has emerged and is cause for concern, warns a researcher and bullying expert from Florida Atlantic University.

The behavior: “digital self-harm,” “self-trolling,” or “self-cyberbullying,” where adolescents post, send or share mean things about themselves anonymously online. The concern: it is happening at alarming rates and could be a cry for help.

A new FAU study is the first to examine the extent of this behavior and is the most comprehensive investigation of this understudied problem.

“The idea that someone would cyberbully themselves first gained public attention with the tragic suicide of 14-year-old Hannah Smith in 2013 after she anonymously sent herself hurtful messages on a social media platform just weeks before she took her own life,” said Sameer Hinduja, Ph.D., study author, a professor in FAU’s School of Criminology and Criminal Justice in the College for Design and Social Inquiry, and co-director of the Cyberbullying Research Center. “We knew we had to study this empirically, and I was stunned to discover that about 1 in 20 middle- and high-school-age students have bullied themselves online. This finding was totally unexpected, even though I’ve been studying cyberbullying for almost 15 years.”

Hinduja and his collaborator from the University of Wisconsin-Eau Claire, Justin W. Patchin, Ph.D., recently published results of their study in the Journal of Adolescent Health.

They used a nationally representative sample of 5,593 middle and high school students between the ages of 12 and 17 years old living in the United States to find out how many youth participated in digital self-harm, as well as their motivations for such behavior. They also examined if certain correlates of offline self-harm also applied to digital forms of self-harm.

Results of the study show that nearly 6 percent of the teens reported that they had anonymously posted something mean about themselves online. Among these, about half (51.3 percent) said they did it just once, about one-third (35.5 percent) said they did it a few times, while 13.2 percent said they had done it many times.

Boys were more likely to participate in this behavior (7 percent) compared to girls (5 percent). Their reasons, however, varied dramatically. Boys described their behavior as a joke or a way to get attention while girls said they did it because they were depressed or psychologically hurt. This finding is especially worrisome for the researchers as there may be more of a possibility that this behavior among girls leads to attempted or completed suicide.

To ascertain motivations behind the behavior, the researchers included an open-ended question asking respondents to tell them why they had engaged in digital self-harm. Most comments centered around certain themes: self-hate; attention seeking; depressive symptoms; feeling suicidal; to be funny; and to see if anyone would react. Qualitative data from the study showed that many who had participated in digital self-harm were looking for a response.

Age and race of the respondents did not differentiate participation in digital self-harm, but other factors did. Teens who identified as non-heterosexual were three times more likely to bully themselves online. In addition, victims of cyberbullying were nearly 12 times as likely to have cyberbullied themselves compared to those who were not victims. Those who reported using drugs or participating in deviance, had depressive symptoms, or had previously engaged in self-harm behaviors offline were all significantly more likely to have engaged in digital self-harm.

“Prior research has shown that self-harm and depression are linked to increased risk for suicide and so, like physical self-harm and depression, we need to closely look at the possibility that digital self-harm behaviors might precede suicide attempts,” said Hinduja. “We need to refrain from demonizing those who bully, and come to terms with the troubling fact that in certain cases the aggressor and target may be one and the same. What is more, their self-cyberbullying behavior may indicate a deep need for social and clinical support.”

Abstract of the study:

Purpose

Despite increased media and scholarly attention to digital forms of aggression directed toward adolescents by their peers (e.g., cyberbullying), very little research has explored digital aggression directed toward oneself. “Digital self-harm” is the anonymous online posting, sending, or otherwise sharing of hurtful content about oneself. The current study examined the extent of digital self-harm among adolescents.

Methods

Survey data were obtained in 2016 from a nationally representative sample of 5,593 American middle and high school students (12–17 years old). Logistic regression analysis was used to identify correlates of participation in digital self-harm. Qualitative responses were also reviewed to better understand motivations for digital self-harm.

Results

About 6% of students have anonymously posted something online about themselves that was mean. Males were significantly more likely to report participation (7.1% compared to 5.3%). Several statistically significant correlates of involvement in digital self-harm were identified, including sexual orientation, experience with school bullying and cyberbullying, drug use, participation in various forms of adolescent deviance, and depressive symptoms.

Conclusions

Digital self-harm is a new problem that demands additional scholarly attention. A deeper inquiry as to the motivations behind this behavior, and how it correlates to offline self-harm and suicidal ideation, can help direct mental health professionals toward informed prevention approaches.

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Reducing racial bias in children (for 2 months)

A new study with young children shows a technique to reduce racial bias in young children (4 to 6 year olds), well the key element is repetition.

From the press release:

We tend to see people we’re biased against as all the same. They are “those people.” Instead of thinking of them as specific individuals, we lump them into a group. Now an international team of researchers suggests that one way to reduce racial bias in young children is by teaching them to distinguish among faces of a different race.

The study, published in the journal Child Development, is the first to show a lasting effect – and in kids young enough to not be too set in their ways.

It is co-authored by researchers from the University of California San Diego, the University of Toronto, the University of Delaware, l’Université Grenoble Alpes in France, and Hangzhou Normal University and Zhejiang Normal University in China.

Two 20-minute sessions with 4- to 6-year-old Chinese children, in which they were trained to identify black male faces as individuals, reduced implicit bias in the children for at least two months.

Key to reducing the bias? The repeat session.

“A single session had minimal immediate effects that dissipated quickly. The lesson didn’t stick. But a second session a week later seemed to act like a booster shot, producing measurable differences in implicit bias 60 days later,” said Gail Heyman, a professor of psychology in the UC San Diego Division of Social Sciences and a senior co-author on the study.

Kang Lee, of the University of Toronto and also a senior co-author, said, “We know from other research that preferences for your own race develop in early childhood. Our method has the advantage of being suitable for very young children, and it also improves children’s ability to recognize faces, which is an important social skill in and of itself.”

First author on the study is Miao K. Qian, of Hangzhou Normal University and the University of Toronto.

The researchers are careful to note that racial bias is complicated. For starters, psychologists think there may be at least two different types of bias: implicit bias, or the extent to which we have subconscious negative and positive associations with different races, and explicit bias, or preferences we’re more aware of and can (if we’re not being guarded) articulate. Implicit bias may have perceptual roots, arising from greater exposure to people of your own race, while explicit bias may be learned socially from adults and peers. Then there’s the question of behavior. How implicit or explicit bias translates into biased behavior is a subject yet to be fully explored.

“We think that reducing implicit racial bias in children could be a starting point for addressing a pernicious social problem,” Heyman said. “But it is not the complete answer to racial discrimination or to systemic, structural racism.”

The researchers worked with 95 children in an eastern city in China. All the kids were Han Chinese and, according to their guardians’ reports, none had direct interaction with any non-Asian people prior to the study. As with most longitudinal studies, there was attrition among participants for a number of reasons, with a final sample, at day 70, of 50.

To measure bias, the researchers used their own Implicit Racial Bias Test (or IRBT), which they’ve validated in a previous paper with subjects in China and Cameroon. The IRBT is a preschool-friendly adaptation of the implicit association test (or IAT). The logic of the two tests is similar: People are quicker to associate positive attributes with members of their own race than with those of another racial category. A difference in response time is taken as a measure of implicit bias. One advantage of the IRBT, the researchers say, is that it uses only pictures instead of words: simple and intuitive smiley and frowny icons that subjects are asked to pair with neutral faces of their own race or a different one.

After measuring the children’s levels of pro-Asian/anti-black bias by calculating how quick they were to pair a frowny or smiley icon with a black male vs. an Asian male face, the researchers assigned them randomly to three different training groups. One group saw black male faces, a second group saw white male faces, and a third group saw Asian male faces. These last two groups were controls to see if learning to differentiate among faces of any race, different from one’s own or the same, produced results that generalized to a third.

Individuation training consisted of learning to identify five different faces that had been numbered 1 through 5, starting with just two faces and working up to five. Training continued until the child correctly matched all five faces with their numerical “names.” This took 20 minutes on average.

There were two training sessions a week apart. A day after each training, children took the implicit racial bias test again. They were tested for bias a final time 60 days after the second training.

The results: Only the training to distinguish among black faces reduced pro-Asian/anti-black bias. Training on white faces or Asian ones didn’t make a difference. Reduction in bias was most significant after the second session and it had a longer-lasting effect than had been documented before.

The researchers are now working with a larger, more diverse group of children in Toronto over a longer term. If their intervention to reduce implicit racial bias is effective in that setting as well, they hope to develop a more consumer-friendly version of their training sessions: a fun, gamified app that could be used in schools and at home.

Abstract of the study:

This study tracked the long-term effect of perceptual individuation training on reducing 5-year-old Chinese children’s (= 95, Mage = 5.64 years) implicit pro-Asian/anti-Black racial bias. Initial training to individuate other-race Black faces, followed by supplementary training occurring 1 week later, resulted in a long-term reduction of pro-Asian/anti-Black bias (70 days). In contrast, training Chinese children to recognize White or Asian faces had no effect on pro-Asian/anti-Black bias. Theoretically, the finding that individuation training can have a long-term effect on reducing implicit racial bias in preschoolers suggests that a developmentally early causal linkage between perceptual and social processing of faces is not a transitory phenomenon. Practically, the data point to an effective intervention method for reducing implicit racism in young children.

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Modern speedreading apps don’t help comprehension

Do you know Tsundoku? It’s a Japanese word to describe the pile of books that lays beside your bed that you should read. It is acquiring reading materials but letting them pile up in one’s home without reading them. If only you could read a bit faster, maybe that could help?

I’m sorry, but the answer seems to be ‘no’ as this new study by Acklin and Papesh shows:

Despite the claims of companies marketing speed-reading tools (e.g., Spritz), our results clearly demonstrated comprehension deficits after rapid presentation of text passages. Consistent with pre- vious research (e.g., Juola et al., 1982), RSVP text presentation led to comprehension scores well be- low those obtained after static reading, regardless of whether the presentation rate was 700 or 1,000 wpm.

The test group wasn’t that big, as forty-two undergraduate psychology students from Louisiana State University with a mean age of 20 years (SD = 2.36) and an average of 14.8 (SD = 1.27) years of education participated in this study for partial course credit. Still the results seem quite damning.

Abstract of the study:

New computer apps are gaining popularity by suggesting that reading speeds can be drastically increased when eye movements that normally occur during reading are eliminated. This is done using rapid serial visual presentation (RSVP), where words are presented 1 at a time, thus preventing natural eye movements such as saccades, fixations, and regressions from occurring. Although the companies producing these apps suggest that RSVP reading does not yield comprehension deficits, research investigating the role of eye movements in reading documents shows the necessity of natural eye movements for accurate comprehension. The current study explored variables that may affect reading comprehension during RSVP reading, including text difficulty (6th grade and 12th grade), text presentation speed (static, 700 wpm, and 1,000 wpm), and working memory capacity (WMC). Consistent with recent work showing a tenuous relationship between comprehension and WMC, participants’ WMC did not predict comprehension scores. Instead, comprehension was most affected by reading speed: Static text was associated with superior performance, relative to either RSVP reading condition. Furthermore, slower RSVP speeds yielded better verbatim comprehension, and faster speeds benefited inferential comprehension.

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Well, no surprise, but also no cigar: more education linked to better cognitive functioning later in life

This is a strange study. Researchers from the University of California in Berkeley used the data of 196000 Lumosity-users. This is a big group, making the study already interesting, but hold your horses, I do think there are some major issues.

First read this excerpt from the press release and see if you can spot the mistake:

The study, led by University of California, Berkeley, researchers, examined relationships between educational attainment, cognitive performance and learning in order to quantify the cumulative effect of attending school.

Its findings suggest that higher levels of education may help stave off age-related cognitive decline. In addition, the team found that education didn’t have a large impact on novel learning, or learning something new at various points in time.

The work, which reviewed the performance of around 196,000 subscribers to Lumosity online brain-training games, is believed to be the largest to date to evaluate cognitive effects of prior educational experience on past and future performance. Researchers said their findings may be of value to psychologists, sociologists, neuroscientists, education researchers and policymakers.

Grading educational achievement

Conventional wisdom has long accepted that higher education is likely to boost incomes and helps prepare individuals for a workplace with often-changing skill sets. Yet fewer than 40 percent of adults in the United States are expected to graduate from college in their lifetimes, and the percentage declines for more advanced degrees.

Until now, research has been inconclusive about the cognitive impacts of higher education and whether the quantity of schooling can influence the acquisition and maintenance of cognitive skills over time.

The researchers of the paper, which appears in the August 23 edition of PLOS ONE, are Silvia Bunge, a professor of psychology at UC Berkeley professor and at the Helen Wills Neuroscience Institute; Belén Guerra-Carrillo, a graduate student in Bunge’s Building Blocks of Cognition Laboratory and a National Science Foundation Fellow; and Kiefer Katovich, who was a statistician with Lumos Labs while the study was conducted.

Bunge and her team say higher levels of education are strong predictors of better cognitive performance across the 15- to 60-year-old age range of their study participants, and appear to boost performance more in areas such as reasoning than in terms of processing speed.

The study’s findings are consistent with prior evidence that the brain adapts in response to challenges, a phenomenon called “experience-dependent brain plasticity.” Based on the principles of plasticity, the authors predicted improvements in cognitive skills that are repeatedly taxed in demanding, cognitively engaging coursework.

Differences in performance were small for test subjects with a bachelor’s degree compared to those with a high school diploma, and moderate for those with doctorates compared to those with only some high school education.

The researchers noted that people from lower educational backgrounds learned novel tasks nearly as well as those from higher ones.

“The fact that the cognitive tests were not similar to what is learned in school is a strength of the study: It speaks to the idea that schooling doesn’t merely impart knowledge – it also provides the opportunity to sharpen core cognitive skills,” said Bunge.

The researchers analyzed anonymized data collected from around 196,000 Lumosity subscribers in the United States, Canada and Australia who came from a range of educational attainment and diverse backgrounds. Participants complete eight behavioral assessments of executive functioning and reasoning that are unrelated to educational curricula as part of their subscription.

The research team also looked closely at a subset of nearly 70,000 subscribers who finished Lumosity’s behavioral assessments a second time after about 100 days of additional cognitive training. Testing before and after the assessments measured cognitive performance in areas such as working memory, thinking quickly, responding flexibly to task goals and both verbal and non-verbal reasoning.

“Given the size and wide age range of our sample, it was possible to test whether these age effects are influenced by education – and, importantly, to determine how the cognitive effects of educational attainment differ across the lifespan, as one’s experience with formal education recedes into the past and is supplanted by other life experiences,” the team wrote.

Bunge said that collaborating with Lumosity was a golden opportunity to analyze data from around 196,000 participants – an anonymized dataset that would have taken a lifetime to collect in a laboratory.

Did you spot it?  I actually do think education can play a large role in this, but how can the researchers know what the status was of the executive functions before education? Even more: if those executive functions are stable from a certain age on, it’s even more impossible to tell.

But there is another issue, if you take a look at the abstract of the study (italic by me):

Attending school is a multifaceted experience. Students are not only exposed to new knowledge but are also immersed in a structured environment in which they need to respond flexibly in accordance with changing task goals, keep relevant information in mind, and constantly tackle novel problems. To quantify the cumulative effect of this experience, we examined retrospectively and prospectively, the relationships between educational attainment and both cognitive performance and learning. We analyzed data from 196,388 subscribers to an online cognitive training program. These subscribers, ages 15–60, had completed eight behavioral assessments of executive functioning and reasoning at least once. Controlling for multiple demographic and engagement variables, we found that higher levels of education predicted better performance across the full age range, and modulated performance in some cognitive domains more than others (e.g., reasoning vs. processing speed). Differences were moderate for Bachelor’s degree vs. High School (d = 0.51), and large between Ph.D. vs. Some High School (d = 0.80). Further, the ages of peak cognitive performance for each educational category closely followed the typical range of ages at graduation. This result is consistent with a cumulative effect of recent educational experiences, as well as a decrement in performance as completion of schooling becomes more distant. To begin to characterize the directionality of the relationship between educational attainment and cognitive performance, we conducted a prospective longitudinal analysis. For a subset of 69,202 subscribers who had completed 100 days of cognitive training, we tested whether the degree of novel learning was associated with their level of education. Higher educational attainment predicted bigger gains, but the differences were small (d = 0.04–0.37). Altogether, these results point to the long-lasting trace of an effect of prior cognitive challenges but suggest that new learning opportunities can reduce performance gaps related to one’s educational history.

Well, pointing is one way of describing it. Not a really big effect and so maybe again not really suggesting that much is another way as it’s a bit different from what they used earlier on to explain why their data and study is so interesting:

“The fact that the cognitive tests were not similar to what is learned in school is a strength of the study: It speaks to the idea that schooling doesn’t merely impart knowledge – it also provides the opportunity to sharpen core cognitive skills,”

Yeah, but this isn’t the case for the pre- en posttest of the Lumosity-bit in this study, and certainly not if you look to previous recent research rhat has shown this tool has no effect on decision-making and no effect on cognitive function beyond practice effects on the training tasks.

So what we have here is a big dataset, with no way to check if the people didn’t lie, with a big selection-element (they choose to use a brain training tool) and without any information about their functioning before they took education. But ok, we have a big dataset.

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Almost all cognitive abilities are positively related, also in adolescence

If you believe in talents, than you might think that missing one talent can be compensated by being better in another field. Sadly, often some have more than others as  almost all cognitive abilities are positively related. A new study confirms this as it shows that cognitive abilities – in this case vocabulary and matrix reasoning – seem to reinforce each other in adolescence and for young adults.

From the press release:

One of the most striking findings in psychology is that almost all cognitive abilities are positively related – on average, people who are better at a skill like reasoning are generally also better at a skill like vocabulary. This fact allows scientists and educational practitioners to summarize people’s skills on a wide range of domains as one factor – often called ‘g’, for ‘general intelligence’. Despite this, the mechanisms underlying ‘g’ and its development remain somewhat mysterious.

“What this so-called ‘g-factor’ means is still very much up for debate,” explains researcher Rogier Kievit of the Cognition and Brain Science Unit at the University of Cambridge. “Is it a causal factor, an artefact of the way we create cognitive tests, the result of our educational environment, a consequence of genetics, an emergent phenomenon of a dynamic system or perhaps all of these things to varying degrees?”

In a new study, scientists from Cambridge, London, and Berlin led by Kievit directly compared different proposed explanations for the phenomenon of ‘g’ and how it develops over time.Data was used from a Wellcome-funded longitudinal cohort (NSPN), where 785 late adolescents, ages 14 to 24, were tested on two occasions approximately 1.5 years apart. They focused two subtests reflecting key domains of ‘g’, namely fluid reasoning (solving abstract puzzles) and vocabulary (knowing the definitions of words). Their findings are published in Psychological Science, a journal of the Association for Psychological Science.

The team observed that the best explanation for the improvement in skills over time was the so-called ‘mutualism’ model. This model proposes that cognitive abilities help each other during development: In other words, better reasoning skills allow individuals to improve their vocabulary more quickly, and better vocabularies are associated with faster improvement in reasoning ability.

These findings are crucial to our understanding of cognitive abilities, as they suggest that small differences early on in childhood may lead to larger differences later on, and help partially explain how ‘g’ arises.

The work has implications for important outcomes in adolescence.

“Our findings may be relevant for early detection of developmental challenges,” says Kievit. “Often screening tests for difficulties focus only on individual outcomes (i.e., ‘Is a child achieving the desired level on some test?’), but studying the dynamics between cognitive domains is likely to paint a richer, more accurate picture of the expected trajectory of development.”

And the findings may also shed light on more long-term life outcomes.

“General cognitive ability is strikingly predictive of various important life outcomes ranging from academic and professional success, to mental and physical health and even longevity – to understand why this is so, we must better understand what this g-factor really is,” Kievit explains.

The researchers note that their observations regarding links between cognitive abilities are exciting, but they do not address whether the relationships are directly causal in nature.

“We hope to further tease apart the underlying mechanisms in future work,” Kievit concludes.

Abstract of the study:

One of the most replicable findings in psychology is the positive manifold: the observation that individual differences in cognitive abilities are universally positively correlated. Investigating the developmental origin of the positive manifold is crucial to understanding it. In a large longitudinal cohort of adolescents and young adults (N = 785; n = 566 across two waves, mean interval between waves = 1.48 years; age range = 14–25 years), we examined developmental changes in two core cognitive domains, fluid reasoning and vocabulary. We used bivariate latent change score models to compare three leading accounts of cognitive development: g-factor theory, investment theory, and mutualism. We showed that a mutualism model, which proposes that basic cognitive abilities directly and positively interact during development, provides the best account of developmental changes. We found that individuals with higher scores in vocabulary showed greater gains in matrix reasoning and vice versa. These dynamic coupling pathways are not predicted by other accounts and provide a novel mechanistic window into cognitive development.

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