Global Childhood Poverty and Neuroscience Workshops

Anna Meaney

How does socioeconomic status affect brain development, and can neuroscience aid in the effort to alleviate global child poverty?  As Dr. Martha Farah, the director of the Penn Center for Neuroscience & Society, says: “We’re not here because we want more photogenic brains on an MRI.  We don’t really care about their brains as an end in itself.  We care about their lives and the neuroscience is only interesting insofar as it tells us something about that.”  A working group with diverse research backgrounds put on the Global Childhood Poverty and Neuroscience workshops to attempt to shed some light on issues pertaining to brain development, neuroscience, and child poverty. Included in the first workshop was Dr. Martha Farah; Dr. Sebastian Lipina, a visiting academic from the National Council of Research (CONICET) in Argentina; and Dr. Allyson Mackey from Penn Psychology.

Dr. Farah presented research showing the widening gap in academic performance between children of higher and lower socioeconomic status (SES). A 2009 study by Stevens et al. looked at the effect of SES on attention by simultaneously playing two different stories in each participant's ear while asking them to attune to only one of the stories.  Participants with lower parental education attainment had a harder time focusing their attention on one of the stories.  Why does this difference exist? It is possible that this difference stems from higher unpredictability in lower SES households, where it could be more advantageous to have one’s attention spread out and attuned to many different things at once.  However, this finding can also mean that kids from lower SES backgrounds have trouble paying attention to just one thing, which can be a problem in a busy classroom.

Dr. Farah also discussed a Demir et al. paper from 2015 that looked at brain activity correlated with better math performance.  It was found that better math performance was correlated with activity in verbal regions of the brain in children from higher SES backgrounds.  However, for children from lower SES backgrounds, visual and spatial areas of the brain were correlated with better math performance.  This finding provided evidence that SES is associated with the way the brain processes information, which can have numerous practical implications about the way math can best be taught to kids from lower SES backgrounds, such as demonstrating math visually rather than verbally describing how something works.  Together, these studies look beyond just gaps in test scores and provide evidence for specific learning differences in children from varying SES backgrounds.

Dr. Mackey corroborated Dr. Farah's presentation by discussing how children from a lower SES background are more likely to be exposed to a number of risk factors that impact brain development, and how low SES exacerbates those risks.These include physical risks (e.g. pesticides, lead) as well as physiological risks (e.g. sleep disruption, lack of exercise, poor medical care, malnutrition). Additionally, there are psycho-social elements such as discrimination, eviction, crime, incarceration, unstable families, addiction, and low quality schools.  All of these factors are stressors on child brain development.

For the workshop, Dr. Mackey particularly discussed how stress and sleep deprivation can lead to changes the brain.

Evidence suggests that early life stress alters the reward system in mice (Peña et al. 2017). Mice who were stressed in early life and then encountered social stress in adulthood developed depression-like behaviors (Peña et al. 2017).  While mice and humans are different, children who have experienced more stressful life events have weakened connectivity between certain areas of the brain, potentially indicating a weakening level of neuroplasticity in children, which can make it increasingly difficult to learn new things (Park et al in prep).

Sleep is another domain in which low SES can exacerbate risk factors associated with brain development. Children from lower SES households are at a higher risk for poor sleep quality compared to children from higher SES households (Buckhalt et al 2011).  For kids from lower SES, sleep loss is associated with a great reduction in cognitive performance.  Sleep disturbances are also associated with reduced whole brain volume and dorsolateral prefrontal thickness, an area that is important in complex problem solving and decision making. (Kocevska et al 2016).

However, for children from higher SES who do not see the same reduction as those who experience sleep loss and are of lower SES, this is not the case.  Parents who are concerned about how sleep quality might be affecting their child’s brain development can track their child’s sleep to help determine if there are poor sleep conditions at home.  There are also specific steps that can be taken for parents who want their children to sleep better, such as making sure the child has a consistent bedtime and limiting media use around bedtime.  

Despite all of this research that link SES and brain development, the path from research to policy is a long one.  This reality was demonstrated to the audience with the example of the state’s car seat policy - it took 10 years for Pennsylvania to change the policy regarding car seats for children under 2 years old after a study was published saying children under the age of 2 are 75% less likely to die or be severely injured in a crash if they are sitting rear-facing.

Because it takes so long for science to influence policy, it is important to think about the small steps parents and educators can take now.  Neuroscience can have real world effects that can make a difference in children’s lives, and fortunately, the field is filled with scientists who are committed to thinking about the real-world implications of their research.


About the Author:
Anna is a senior at Vassar College where she studies Neuroscience with a focus on evolution.  She volunteered in The Changing Brain lab this summer.  Anna can be reached at anmeaney@vassar.edu with any questions.   

 

 

The Effect of Effort on Test Scores

Connor Kendzora

Little research has been conducted to assess students’ performance in low-stakes testing situations in comparison to high-stakes situations. Low-stakes tests do not heavily impact the test-taker’s grade in a class or the course of their academic career. On the contrary, high-stakes tests usually do impact the test-taker’s grade or academic career.

Previous studies have only made statistical comparisons using a between-subjects design, meaning that a different sample of students was used for each condition (high-stakes and low-stakes). This leads to more individual differences between groups and, consequently, less statistical power. A comparison using a repeated-measures design, in which the same sample of participants is used for each condition, could be valuable, as it may reveal that students’ performance on low-stakes tests does not actually match the student's’ proficiency in the tested subject, as a result of a deficiency in effort compared to high stakes testing.

Yigal Attali (2016), influenced by past studies that revealed a negative difference in low-stakes scores from high-stakes scores, performed such a comparison, where he used data from an existing study of the effect of extra time on GRE scores by Bridgeman, Cline and Hessinger (2004) in order to determine the effect of effort in low stakes assessments.

Attali measured the participants’ operational scores (the score received on the actual GRE), research scores (score received on the research section, or the extra section of the GRE the participants had been asked to complete), and the amount of effort exerted by each participant during the research section (time taken to complete). The author justified his definition of effort as the amount of time taken to complete the research section by citing that self-report measures are often biased as subjects are often reluctant to admit they did not try their hardest. He argues that the longer a test-taker spends on a test, the fewer short, rapid-guess responses they will give, indicating a larger amount of effort.

Results of statistical analyses showed that the average research score was considerably lower than the average operational score. This was true for both the verbal and quantitative sections. Average time spent on the research section was only 63% of the time spent on the operational section. It was also found that 2% of the research group scored the lowest possible score on their section, compared to only 0.2% in the operational group. This indicates that many test-takers did not perform to their potential by giving less effort on the research section. Attali also checked for effects of motivational filtering, or filtering out scores of students who clearly gave minimal effort on the research section. He accomplished this by examining what the data would look like if minimal effort attempts were removed at increasing intervals. Removing the bottom 18% (in terms of time taken to complete the research section) of test takers greatly decreased the effect of the stakes and increased the correlation between the research scores and operational scores.

In summary, low-stakes test scores and high-stakes test scores can have a strong correlation when filtering out the test-takers who give effort unrepresentative of their ability. This is something to be kept in mind by organizations who seek to draw conclusions about students’ proficiency from low-stakes tests.


About the Author:  
Connor is a Psychology major and incoming senior at California State University, Long Beach. He worked in The Changing Brain Lab during Summer 2017 and currently works as an ABA therapist. Any questions can be emailed to connorkendzora@gmail.com.

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The members of The Changing Brain Lab would like to officially introduce our new blog! We will use this space in order to discuss new research that pertains to our interests, events on campus or in the community that we are involved with, and news regarding our lab. We will be releasing a blog post approximately once every month, so please check back whenever possible to see what our lab has been up to! Information regarding the author of each piece will follow each published post. If you have any questions or comments regarding the papers or events discussed, please feel free to contact our lab at mackeylab@sas.upenn.edu or via phone at (215) 573-1670.