Category: Summer Team Impact Project

Physiological Data Associated with Linguistic Racism

Author(s): Pamela Benitez, Elizabeth Kwari, McKenna Olsen, Susan Pham, Sara Razavi

Mentor(s): Nathalia Peixoto, Volgenau School of Engineering

This project focuses on testing the correlation between linguistic racism and anxiety using physiological data. In this experiment, participants consisted of two groups, native English speakers (NES) and non-native English speakers (NNES). Each group had 5 participants, with a total of 10 participants. In the pre-experiment phase, participants were required to fill out two surveys. The first survey was on social anxiety and the second survey was on their emotional state. In addition, participants were exposed to a 25-minute video. The video was organized into 4 sections: (1) listening to 10 min. of relaxing music, (2) 10 min. Relating to linguistic racism, (3) second time taking their emotional state survey, and (4) listening to 5 min. of relaxing music. The hypothesis is that when NNES are exposed to linguistic racism, anxiety-like symptoms will occur such as an increase in heart rate and body temperature. Another part of our hypothesis is that non-native English speakers will be more stressed or sad after watching the linguistic racism video. To find this correlation, quantitative data was collected using E4s and Muse 1. Other data analysis will include participants’ survey results before and after watching the linguistic racism video. The qualitative data results that will be more focused on is comparing the participants’ results in their emotional state, specifically their changes before and after watching linguistic racism.

Hello everyone, we are one of the groups taking part in the STIP (Summer Team Impact Project) program for the summer of 2022. Our group consists of five members that helped with research and running experiments throughout the entirety of the summer. These members include Susan Pham, Elizabeth Kwari, Sara Razavi, Pamela Benitez, & McKenna Olsen.

While there are many that view being different as something good, being unique, there are just as many people that also degrade others for being different too. Words like foreigner, second class, alien, etc. are just some examples of direct forms of the prejudice that many had experience in today’s society. However, it does not just stop at direct comments. There are numerous ways that society subtly expresses racism whether it be certain words and actions, but not enough research has been done to show that this an actual problem. Our group’s project hopes to bring more awareness to the topic of linguistic racism and show that such subtle forms of racist words and actions do have a significant impact on an individual’s psyche, shown through their physiological signals.

Before we begin an overview of our group’s research, it is important to first understand what exactly linguistic racism is.

Linguistic racism is a type of prejudice individuals may have towards others based on the way they speak, accent or dialect they have, or their repertoire. Linguistic racism can be expressed in a variety of ways but is often done through the form of explicit verbal attacks such as mocks, slurs, and name-calling.

Not only does linguistic racism affect an individual by making them feel embarrassed because of their way of speaking, but it can also affect them on a deeper level, going as far as affecting the individual’s mentally. There are studies to suggest it may lead to increases in anxiety, depression, and insecurity about their language skills. Because of this, victims of linguistic racism may feel that they have reduced opportunities for self-representation and require increased effort to try and mask their accents.

And this brings us back to our group’s overall objective and research question relating to this project. Our objective is to investigate experimental methods to capture physiological data related to anxiety and linguistic racism. Our research question is how did our team test the correlation between linguistic racism and anxiety?

Based on some previous studies that have researched on detecting social anxiety with E4 data. E4 Empatica watches were used to collect physiological data and only heart rate, electrodermal activity, and skin temperature can be used as social anxiety indicators.

Our first trial procedure consists of a few steps. First, participants wore E4 watches while watching a video. Second, the video itself had three sections, the first section of listening to soothing music for 10-minute, second session of watching a 3-minute video on racism, then listening to soothing music again for 10-minute. Lastly, E4 data was synched to the E4 connect website.

The results shown from the first trial did not capture what we were looking for. Our hypothesis is that heart rate will increase when the participant is exposed to linguistic racism. In both of these graphs, both the participants from the non-native English speaker group showed a consistent heart rate pattern the whole time watching the video and listening to relaxing music. It is important to note that the decrease in skin temperature was due to the room temperature the participants were in.

Based on the first trial methods errors, our final trial procedure is much more structured and thorough. First, participants wore E4 watches and the muse 1 headband. Next, participants took 2 surveys on personal anxiety and emotional level. The second step included the participant listening to 10 minutes of soothing music, then watching a 6-minute video on linguistic racism, and then listening to 5 minutes of soothing music once again. Participants pressed the E4 button to mark their event of transitioning between listening and watching the video. Afterwards participants retook the emotional level survey.

Results from the second trial show that when the participant is watching the 6-minute video about linguistic racism, there is a slight increase in heart rate.

Tying it back to our hypothesis, it is predicted that participants would show an increase of heart rate when exposed to linguistic racism. What the researchers are looking for is a correlation between an increase in heart rate and frontal cortex activity. In the E4 graph, during the linguistic racism video section, there was an increase in heart rate. With the muse graph, we can associate not only that the heart rate was increasing, but the participant’s frontal cortex was active when watching the linguistic racism video. This correlation can show that the participant was either angry, anxious, or stressed.

Some issues we have encountered were technical related problems of data collection. Some participants showed weaker physiological responses and that the Muse 1 headband had issues streaming onto the muse app. Another issue is that the first trial setting had a lot of background noises and the room temperature would be on the cold side. Lastly there was the issue of lack of relatability. Some participants in both the native English-speaking group and non-native English-speaking group showed no reaction when watching the linguistic racism video.

Here is our bibliography

A Special thanks to George Mason University and the OSCAR Office for this research opportunity. Thank you to all the team members who have worked hard in this project, and Susan, who is the project manager of this group. Special thanks to Dr. Zhang and Dr. Park for supervising us and thank you to Venkat and Nathalia for supporting us.

College of Humanities and Social Science College of Science Summer Team Impact Project

Investigating the Reliability of an Empatica E4 for In-the-Field Experiments

Author(s): Pamela Benitez, Susan Pham

Mentor(s): Nathalia Peixoto, Electrical and Computer Engineering Department

E4 Empatica watches are a helpful tool that allows researchers to capture several data points with real-time streaming and visualization graphs. These devices are currently validated under non-movement conditions, however, few studies note that there is little data on how accurate an E4 watch is when participants are not sitting still or are in ambulatory settings. As a result, our team decided to test the accuracy of Empatica (E4) watches over long periods, and when performing hard physical activity. Participants wore the watch for 8 – 12 hours daily, for 5 days. During these 5 days, participants followed their routine and performed tasks such as carrying groceries, eating, and exercising. Once five days had passed, researchers pulled HRV data points consisting of 5-minute sessions from each day-to-day trial. By looking at the data points in Microsoft Excel, and comparing them to the premade graphs the E4 Connect website offered, researchers were able to quantitatively count the number of times the E4 did not accurately read the HRV data. Out of 300 data points, the E4 stopped working approximately 146 times. The results of this experiment ultimately indicate that the E4 is not a practical tool to use underneath motion conditions.

Hi everyone, welcome to our STIP project for summer 2022. This summer, Susan Pham and I worked together to determine the reliability of an E4 for in-field experiments. We hope you enjoy our presentation.

So our project centered around determining the accuracy of an E4 watch under strong motion conditions. We know that an E4 is quite reliable when a participant is staying still, however when we were conducting our literature review for other projects, we noted that many studies suggest that there is not enough research to prove that the E4 is reliable for experiments where the participants move around, or perform strenuous activities. So we asked the question, how reliable is it when a participant is in motion? This summer, our to see if the E4 still maintains its gold standard status for experiments that involve strong movements, such as exercising or simply wearing an E4 in day-to-day activities.

So to start off, what is an E4? An E4 is a wristband that measures several physiological indicators of stress in real-time, including electrodermal activity, which is related to sweat gland activity. Blood volume pulse, which helps the watch derive the heart rate variability (which is basically just a measure in variation between each heartbeat), and your external skin temperature. An increasement of any of these signals would give an indication that a person is stressed, or emotionally aroused. Here’s a quick demonstration on what the E4 looks like, and how it works.

This is the E4. As you can see, it’s quite a bulky watch. To use it, first, you remove the back charging panel. When you want to turn it on, you press the small circular button that’s on the front portion of the watch. This should cause the watch to emit blue blinking light. This means that the E4 is in discovery mode, and it’s ready to be paired to the streaming app. To put it on, you just wrap the band around your arm and make sure the sliver nodes press against your wrist firmly. Let’s see exactly how the watch connects to the streaming app.

Let’s check out the streaming app for the E4. As you can SEE, the app is called E4 realtime. To connect to the watch, we click on connect e3 and start streaming. Once we do that, we confirm which watch we want to use. The app will then show its acquisition of the physiological signals. As you can see, it takes a few seconds to get the app properly connected to the watch, and for it to begin working. It takes a bit longer, around 7 seconds or so, for the watch to accurately determine the Heart rate variability. The e4 can be a little finicky in determining this, which is why it does take a few seconds. However, if we press on the back button, we’ll be able to see other physiological indicators that we talked about previously, such as eda, temperature. We can even see the duration of the session, and how much battery life the watch itself has. If we want to stop streaming, we simply click on the stop streaming button. We click on yes, and as you can see in the sync section, the app states that the data is uploading. Once it reaches 100 percent and states the data was uploaded, this means that we’ll be able to see our data on the E4 Connect website later.

So now that you have a good idea of what the E4 looks like, and how it works, it’s important to know the mythology we used for our experiment. we decided to see if we could quantitatively determine the accuracy for the E4, when a participant is in movement. To do this, we compared the data gathered from an experiment where participants are sitting still and watch a video while wearing the e4, to an experiment where the participants are actively moving in day-to-day life and are wearing the e4 for a period of 8 to 12 hours .

Here’s a data set from both of our experiments. On the right is the experiment where the participants were sitting sill, whereas on the left is when participants are in motion. As you can see, there is a clear difference. The data graph from when the participant is sitting still, which is on the right, is consistent the heart rate is clear and steady.
In contrast, the heart rate when the participant is going about their day-to-day life is shaky and inconsistent. The long flatline indicates that the E4 was not able to read the HRV correctly, and the sudden decreases in heart rate are the result of the E4 not being able to connect to the streaming app, most likely due to motion. Just by looking at this, it’s clear, that the E4 is not very reliable when the participant is moving.

To quantitatively determine how accurate the E4 was for our motion experiments, we looked at the raw HRV data for the day-to-day experiments. The total session lasted an hour, but we randomly chose a section of 5 minutes from the total hours. From those 5 minutes, we looked at the raw HRV, and the E4 graph, and counted how many flat lines and zeroes there were in that duration of 5 minutes. We counted these flatline and zeroes as these would have given indications that the E4 had stopped accurately recording. We then added the total number of flatlines and zeroes and divided that by the total number of data points, which was 300. Performing these calculations gave us an accuracy rate of 46%, which means that this isn’t a device you want to use if you’re going to perform any experiments with hard physical activity.

So undeniably, E4 watches are useful research tools that allow researchers to capture physiological signals accurately. However, based on our test results, the watch gives too many unreliable readings when the participant is in motion. This has allowed us to conclude that the E4 is not the ideal equipment to use in experiments that involve long durations of wear, or that involve hard movement.

Here is the bibliography for this project on the reliability on empatica E4 watches for in-the-field experiment

Lastly, Thank you to George Mason’s OSCAR office for allowing us to work in this research opportunity. Thank you to Dr. Chaplin for supervising us. And Thank you to Venkat and Nathalia for supporting and guiding us throughout this summer’s program.

College of Education and Human Development Summer Team Impact Project

The Effect of Age and Years of Service on Firefighter Fitness

Author(s): Arasta Wahab

Mentor(s): Joel Martin, Marcie Fyock-Martin; Kinesiology

C:UsersarastOneDriveDocuments9. Summer 2022ResearchPoster Presentation.mp4

The firefighter (FF) profession is a demanding job that requires cardiorespiratory fitness, muscular strength, and endurance. Evidence indicates that muscular fitness and body composition are related to the ability to perform their occupational duties. The purpose of this study is to assess the relationship between age and years of service on FF fitness. 96 professional firefighters volunteered for the study. Body composition was assessed via bioelectrical impedance analysis. The fitness assessment was 30 minutes and consisted of pull-ups, push-ups, curl-ups, and 3-minute step test. In the regression model, examining influence of age and years of service on pull-ups was statistically significant (R2 = 0.04, F(2, 269) = 6.104, p < 0.01). The regression model for pull-ups reveals that years of service was a significant predictor (β = -0.08, p < 0.001). The model investigating the influence of age and years of service on curl-ups was statistically significant (R2 = 0.03, F(2, 269) = 3.625, p < 0.03). The regression model for curl-ups shows that age was a significant predictor (β = -0.35, p < 0.03). For push-ups, the regression model was not significant for age and years of service (R2 = 0.01, F(2, 269) = 1.605, p < 0.20). The regression model for step-ups was not significant (R2 = 0.004, F(2, 269) = 0.556, p < 0.57). The model for body fat percentage was statistically significant (R2 = 0.04, F(2, 269) = 5.489, p < 0.01). The regression model for body fat percentage reveals that age was a significant predictor (β = 0.77, p < 0.001). There is a decline in the number of pull-ups, curl-ups, and increase in body fat percentage. These findings suggest that promoting FF fitness may help address the decline in body composition, cardiorespiratory fitness, and muscular fitness that comes with age and years of service.[/expand] [expand title="Audio Transcript"]Hello, my name is Arasta Wahab, and I am a senior at George Mason University majoring in Kinesiology. This summer 2022 I was involved in OSCAR's Impact Project where my supervisors, peers, and I conducted research on firefighters. My poster is about ‘The Effect of Age and Years of Service on Firefighter Fitness.' To introduce my topic, the firefighter profession is a physiologically demanding job that requires cardiorespiratory fitness, muscular strength, and endurance. Due to the high physical nature of this occupation, it may be advantageous to have greater levels of fitness. Consequently, the National Fire Protection Association has placed a minimum standard of 42 ml/kg/min for cardiorespiratory fitness. Despite these recommendations, about 70% of fire departments do not require firefighters to meet this level of aerobic capacity. Furthermore, current evidence indicates that upper body fitness, and body composition are all related to the ability of firefighters to perform their occupational duties. Better understanding the effects of age and years of service on firefighters may lead to improved fitness and occupational performance. The purpose of this study is to assess the relationship between age and years of service on firefighter fitness. For methods of retrospective studies, the total sample of participants were 96 firefighters. The demographics consisted of all males, a median age of 52 years old, years of service of 9 years, and a body fat of 26%. For fitness parameters, body composition was assessed via bioelectrical impedance analysis. The duration of the fitness assessment was 30 minutes and consisted of pull-ups, push-ups, curl-ups, and a 3-minute step test. For statistical purposes, linear regression models were used to examine the influence of age and years of service on fitness measures. Looking at the results table, it displays the effect of age and years of service on firefighter fitness. The variables consisted of body fat percentage, pull-ups, push-ups, curl-ups, and step-ups. Below are the models of age and years of service. In the regression model, examining influence of age and years of service on pull-ups, curl-ups, and body fat percentage was statistically significant. The regression model for push-ups and step-ups were not statistically significant. In conclusion, as these individuals progress into their career, there is a decline in the number of pull-ups, number of curl-ups, and increase in body fat percentage. However, due to the low variance there may be other variables that may influence firefighter performance. These findings suggest that the promotion of firefighter fitness may help address the decline in body composition, cardiorespiratory fitness, and muscular fitness that comes with age and years of service. With further research, the effects of age and years of service on firefighter fitness can be used to target their specific needs. Guidance and implementing health programs may provide a call to action for engagement in physical activity. And here are my references for the articles I have used. Thank you and I hope you enjoyed my presentation.[/expand]

College of Visual and Performing Arts Summer Team Impact Project

Recovery Room

Author(s): Taylor Dinh, McKenna Olsen

Mentor(s): Nathalia Peixoto, College of Science

https://www.youtube.com/watch?v=G5AGI_-VDfw

Recovery for patients with substance use disorders (SUD) is a long and difficult path. Treatment, and encouragement to stay committed to recovery is also difficult to find and afford. When there are so few low-cost treatments and coping mechanisms for recovery, the road to recovery can be bleak, especially when the possibility of recovery seems like a pipe dream. We, the researchers, wish to create a virtual space where people suffering from SUD can be reassured of their doubts in themself and in the concept of recovery. The “room” for support that we created is a virtual space that is a visual novel. A visual novel is traditionally a term used in the video game industry, used to describe a video game that is mostly text based with user input in order to change the story. We used a visual novel engine called Renpy in order to make this recovery room. Renpy uses Python as its coding language, and it simplifies text and string display inputs so that the player can simply click on the window to read forward or move backwards in the text. We utilized the button system to be able to add reassuring quotes to each option of distress (categorized by the type of problem). We can categorize this visual novel we created as a “serious game.” Serious games are games meant for educational purposes, or with the intent of being used in the field.

Hello, my name is Taylor Dinh, I’m a part of the George Mason Summer Team Impact Project for 2022. The project that I chose to work on this summer is a serious game in Renpy. I worked on the programming aspect of this project while my partner, McKenna Olsen, worked on the website and literature review. Our project was created in order to try to create personalized digital spaces that can give participants words of encouragement in order to reaffirm their commitment to recovery from substance use disorder.

Now as you can see here, we have our website for our project, and in which you can see there is a brief explanation of our project as well as explanations as to how Renpy works. You can even download our serious game through the builds. We have builds for both Mac and Windows computers. Explanations as to what Renpy is and common misunderstandings as to what each function means and how to fix them. Then, we have our game itself, which you can access through the Renpy launcher. All you have to do is select your game, and then hit “launch project;” however, if you were to download the game through the builds tab, you do not need Renpy in order to access this.

So, what is our project? Well, we used Renpy, a visual novel engine that runs using Python, in order to create a program that we call The Recovery Room. This room has a user interface that allows the participant to interact, as you can see here you can press the start button and click to move forward and you can receive encouragement based on what problem you are facing that day. The long-term possibilities for this project are that professionals in the industry can learn to create their own recovery rooms for their patients, together with their patients in order to create a therapeutic and personalized app that runs with minimal coding that way the patient can access it on their phone if they need it or if they need a reminder of their goal of recovery. The audio, the images and the text can all be altered to better suit the patient’s needs.

Thank you for listening to my presentation on our recovery room and listening to our hard work this summer.

College of Humanities and Social Science Summer Team Impact Project

“The mental health services in here are poor”: Resident Perceptions on Mental Health Services Provided in Restricted Housing

Author(s): Shelby Rothberg, Kristina Wheeler

Mentor(s): Taylor Hartwell, Criminology, Law, and Society

Many residents experience symptoms of mental illness while being housed in solitary confinement units, yet little is known about the mental health services provided to them, and how effective the residents find these services to be. This research investigates how the residents placed in solitary confinement units perceive the mental health services provided to them while they are housed in these units. Using 106 interviews collected from six different prisons, our findings suggest that most residents view these mental health services as being an overall negative experience, with residents citing a lack of treatment or ineffective treatment. These findings show that mental health services in solitary confinement units are lacking and more effective treatment is needed.

Title Slide:
-Hi, I am Shelby Rothberg
-I am Kristina Wheeler
-And we are Criminology, Law, and Society Majors at George Mason University. For our Summer Team Impact Project, we worked with the Center for Advancing Correctional Excellence!, also known as ACE!, on their Solitary Confinement Project. This project has been ongoing for the past five years, with two of those including teams of undergraduate and graduate research assistants visiting seven different prisons and solitary confinement units where they conducted interviews with residents and staff. For our project this summer, Kristina and I investigated residents’ perceptions of the mental health services provided to them in solitary confinement.
Literature Review
-In the prisons included in this study, solitary confinement units are called RHUs, or restricted housing units. RHUs are commonly referred to as a “prison within a prison”. A resident may be placed in an RHU as either a voluntary or involuntary removal from the general population. While in the RHU, residents are placed in a locked cell, either alone or with another prisoner, and are unable to leave their cell for a majority of the day. We began our project by diving into the previous literature regarding the mental health of residents in solitary confinement units. Much of the previous literature on this subject can be summarized by the following key findings. First, in 2005 Rhodes found that 20-25% of residents in solitary confinement units included in their study showed strong evidence of having a mental illness. Next, Haney concluded in 2006 that prisoners held in solitary confinement for long periods of time are at an increased risk of mental illness symptoms, especially long-term impulse-control disorder and clinical depression. In 2020 Dellazizzo et al., concluded that mental illness is a contributing factor to a resident’s placement in solitary confinement. Finally, in their 2008 study, Lovell found that 45% of residents included in their study that were being housed in solitary confinement units suffered from psychological breakdowns, marked psychological symptoms, brain damage, or serious mental illness. These findings all suggest that long-term solitary confinement may lead to declining mental health and symptoms of mental illness. They also suggest that many residents in these solitary confinement units have a preexisting mental illness before they were placed within these units, and their placement may lead to worsening symptoms of their mental illness. With this understanding that solitary confinement leads to declining mental health and that many residents in these units have symptoms of mental illness also comes a gap in knowledge regarding the mental health services provided to these residents, and more importantly the residents’ perceptions of the mental health services that are provided to them while they are in the solitary confinement units.
Research Question
-This gap in knowledge leads to our main research question for our summer project: What are residents’ in solitary confinement units’ perceptions of the mental health services provided to them while they are being housed in the RHU? This then leads into another question we investigated which was: Do residents feel that the mental health services provided to them in the RHU are effective or ineffective? Another question we would like to explore in the future is: what are RHU residents” thoughts about psychological staff in RHUs?
Data Collection/Methods
-To answer these questions, we coded and analyzed resident interviews that had been previously collected by the ACE! team. Our study site included six different male state prisons that each had their own RHU. The data collection process took place over two years beginning in 2017. In the first year, the team spent two days in each of the three prisons. In the second year, the team spent four days in each of the four prisons. The team consisted of 6 undergraduate research assistants, 3 masters students, 2 PhD students, and 3 faculty members. The data collected included two hundred and nine total resident interviews, one hundred and six of which were included in our current project. 103 interviews were excluded as they did not reference mental health services. Our research process began by closely reading through all of the resident interviews. We then used the coding software program Atlas.ti to code the interviews for mental health and mental health services. From here, interviews that included any mention of mental health services in RHUs were used in this study. Preliminary analysis was then conducted to determine residents’ perceptions of the mental health services that were provided to them.
Findings
-Here are our findings. Overall in our research, there were more negative perceptions of mental health, rather than positive perceptions of service. In total, there were 274 instances where the resident stated their negative perception, and 36 instances where the resident said something positive about the mental health services provided. There were two major recurring themes in the data such as the 76 residents who said that they believed there were not enough services or a lack thereof, and the 71 residents who stated that the psych services provided were ineffective and not beneficial. We have also provided quotes from the data to give examples of the residents perceptions such as, “There are no checkups to even see if anyone needs to get any medication provided to them”, “They (CO’S) do not talk about what is actually happening”, and “The mental health services in here are poor. There is really no one for you to talk to. They just give you medication when you just need to talk to someone.”
Discussion
-For theoretical implications we wanted to expand the literature on mental health services in RHU’s using the data provided. Practical implications include residents that may have useful suggestions for improving the effectiveness of treatment for themselves or in group therapy settings. Correctional institutions should consider adding more psych services for residents as well. Some RHU’s may be lacking the employees that are needed. For our future research we have three things we would like to research. The first research question is “What are RHU residents’ perceptions of psychological staff in RHUs?”. The second thing we would like to inquire in-depth is into mental health services (e.g.,how correctional officers/psych staff implement the psych programs, how correctional staff enforce attendance, etc.). Lastly a more in-depth inquiry into psych programming (e.g., examine perceptions of psych programs among program participants; conduct ethnographic field observations of psych programs).
Final Slide
-Thank you for listening to our presentation

College of Public Health Summer Team Impact Project

Role of Urban Built Environment of Breast Cancer Mortality Health Disparities

Author(s): Kai Barner, Ha Dao, Abigail Kokkinakis, Alexandra Diaz Merida, Amanda Webber

Mentor(s): Taylor Anderson, Geography & Geoinformation Science; Travis Gallo, Environmental Science and Policy; Mariaelena Pierobon, Biohealth

Breast cancer is the second-leading cause of cancer-related death among women in the United States, but mortality rates vary across the population. Previous studies use individual and county level data to examine the association between breast cancer mortality and various socio-demographic and environmental variables. However, global regression models assume spatial stationarity meaning that associations between explanatory variables and breast cancer mortality are the same across geographic space and scales. Therefore, the objective of the study is to use county-level data that describes the social and built environment across the contiguous United States to explain breast cancer mortality rates, as reported in the Surveillance, Epidemiology, and End Results (SEER) database, using a multi-scale geographically weighted regression model (MGWR) that accounts for spatial heterogeneity. We compare our MGWR model with a baseline global linear regression model (OLS). The MGWR outperformed the global linear regression model with an adjusted R2 of 0.91, explaining about 43% more variance than the OLS. The R2 for each county is high in the western part of the US and decreases towards the east. In comparison to global linear regression, MGWR had the same overall trends in terms of relationships between explanatory variables and mortality. For example, as mammogram screenings, health food index, and primary healthcare physician ratio increased, breast cancer mortality decreased. However, MGWR reveals spatial heterogeneity associated with the magnitude and direction of each relationship across counties. Such an approach allows for greater consideration of where certain variables are most influential in breast cancer mortality allowing for location-specific interventions.

Top of Form

Abigail G Kokkinakis0:09

Hello everyone. The objective of this study is to examine the association between the urban built environment and sociodemographic variables and breast cancer mortality using an approach that will capture spatial heterogeneity and those associations. According to the American Cancer Society, breast cancer is most common cancer in American females. One in eight females will be diagnosed with breast cancer and their lifetime, and one in 39 females will die from breast cancer. A lot of studies look at individual level, social demographic data, and regression techniques. However, these regression techniques assume spatial stationarity which ignores local heterogeneities and associations between variables and breast cancer mortality.

Ours created a US model focusing on urban built environment variables without the limitations of most global regression techniques.

We collected Seer data from the most recent five-year interval, which was 2015 to 2019. Note the white space in the map shown. These are the counties that did not have data provided, which was roughly 1/3 of the data.

Ha Dao1:10

Due to privacy reasons, counties with the count of deaths less than 10 were omitted by SEER. Therefore, we decided to assume these missing counts as 9 and calculate the crude rate based on this. Moving forward with data collection and preprocessing. In the beginning of our research, 65 urban-built and social-demographic breast cancer determinants were obtained. Throughout the process of data cleaning and data wrangling, log transformation and scaling were applied on selected variables to reduce skewness and normalize the range of independent variables. Upon running Pearson correlation and Variance Inflation Factor, we removed variables that were highly correlated so we can avoid multicollinearity in the regression model. Lastly, the leap and bounds algorithm was used to find the variables that explain the models best which you can see on the screen here

Amanda A Webber1:59

Our model contained 18 variables. For the sake of time, we’re showing the three most significant variables as well as the variables that have no significance. The three most significant variables are access to mammograms, access to primary care doctors, and percent of population that is uninsured. The variables that are not significant based on their P value are textile manufacturing, commute, radiance, and unemployment.

You can see from this map of our county residuals that predictive accuracy varied across counties and appears spatially correlated. The R square value reflects the amount of variation in the data set that is explained by our model. On a scale from 0 to 1, this models R Square explains roughly 50% of the variation within the data.

Kai Barner2:47

Big picture, this project wanted to account for spatial heterogeneity. A primary limitation of OLS regression is that it assumes that each explanatory variable has the same relationship with the dependent variable across the entire study area. So when one unit change of an explanatory variable occurs, that results in the same change to the dependent variable, no matter the location. Multiscale Geographically Weighted Regression – MGWR – takes location into account by taking the concept of neighborhoods from standard Geographically Weighted Regression and allowing their size, or bandwidth, to vary between different variables in the data set. Multiple scales reflect diversity in distribution and extent of influence.

This project examined data at the county level, so when analyzing the influence of a variable on an individual county, the bandwidth took into account that many neighbors at the same time. There are just over 3100 counties in the continental US, and we can see that some of the neighborhoods actually encompassed all of them. But at the other end of the spectrum, a small bandwidth indicates that the spatial process changes quickly from location to neighboring locations. And we see this with food index, exercise, access to primary health care, and mammograms.

Where our OLS model had an adjusted R-squared of 0.478, our MGWR model explained about 44 percentage points more variance, with an adjusted R-squared of 0.918.

Here we have our MGWR results for mammograms. The mean coefficient is negative 0.14, so the standard behavior nationwide is an inverse relationship. As the number of mammograms increase, breast cancer mortality decreases and we see this norm in cornflower blue. As we move through the purples into magenta, this negative correlation becomes even stronger. But on the other hand, areas in the cyan extend from having a weaker negative correlation to actually having a positive coefficient. In these areas as mammograms increase, breast cancer mortality also increases.

These local differences warrant further examination of other variables and other factors of underlying influence, alluding to the local complexities behind trying to improve breast cancer health outcomes. There is no one-size-fits-all solution.

Alexandra Diaz Merida5:05

Another variable that we looked at was access to exercise, which measures how close an individual is to a location for physical activity. This can be either parks or recreation centers in this map we see that in general there is a negative correlation, which means that the higher the access to exercise opportunities, there is a decrease in breast cancer mortality. Looking at these graphs, we can see which counties need more access to exercise in order to decrease breast cancer mortality.

Similar to access to exercise, we also looked at food index, which is described as how close an individual is to healthy foods and the and the ability to access due to cost barriers. It is also negatively correlated, which again means that the higher the food index, there’s a decrease in mortality. These maps will help inform local governments about breast cancer mortality rates and how improving these variables can decrease mortality.

In summary, MGWR explains the results better than OLS for spatial heterogeneity, providing better explanations for how urban built environment variables affect breast cancer mortality. Thank you.

Kai Barner6:12

Thank you.

Abigail G Kokkinakis6:13

Thank you.

College of Education and Human Development College of Science Honors College Summer Team Impact Project

Firefighter Mobility and Balance: A Descriptive Analysis

Author(s): Victoria Ghanma

Mentor(s): Joel Martin, Marcie Fyock-Martin; Kinesiology

There are no firefighting tests that measure the mobility and balance in firefighters (FFs), so little is known about the mobility and balance in FFs. Knowing more about the mobility and balance in FFs might provide more information on movement related injuries, especially since falls are the primary injury mechanisms in FFs.

PURPOSE: This study aims to explore the mobility and balance of a cohort of firefighters, using the Functional Movement Screen® (FMS) and Y-Balance Test.

METHODS: Thirteen professional firefighters (males=10, females=3, age: 37 ± 9.31 yrs; Height: 180.75 ± 6.16 cm; Weight: 121.72 ± 19.65 kg) volunteered to be part of this study. The wall-sit-and-reach was used to measure flexibility. The mobility of FFs was measured using the Functional Movement Screen® (FMS). The Anterior Y-balance test (YBT) was used to measure lower extremity balance and asymmetries. Test for normality showed the data was not normally distributed, data was normalized with a log10 transformation. All descriptive data is presented in means and standard deviations.

RESULTS: The body fat percent of the firefighters was 38.83 ± 5.11 %. Their fat mass was 47.26 (10.94) kg, and their fat-free mass was 70.34 ± 12.05 kg. The wall-sit-and-reach scores were 25.96 ± 8.76 cm. The YBT (right leg) score was 57.54 ± 7.76 cm and the YBT (left leg) score was 59.08 ± 7.29 cm. The asymmetries found between the two YBTs (right and left) were 3.69 ± 3.10 cm. The total FMS scores were 11.39 ± 1.26.

CONCLUSION: Comparing the data in the present study to a study published that examined service members in the military, we found that the service members had higher YBT scores than the FFs. Also, all FFs scored <14 on the FMS, indicating that the FFs tested were at a higher risk of developing an injury.[/expand] [expand title="Audio Transcript"]Hi, my name is Victoria Ghanma, and I am a sophomore here at George Mason University. This summer team impact project project has taught me a lot, and I was taught how to discover. My project involves First Responders, specifically firefighters. This summer I had the opportunity to closely work with those firefighters and learn more about the firefighting occupation. Firefighters generally take a test called the CPAT, which stands for the candidate physical ability test. This test tests the physical ability of firefighters but it does not test their mobility, also known as movement, or their balance, so we decided to test for those two factors balance and mobility in those firefighters. Before measuring the firefighters' mobility and balance, we took basic anthropometrics using a stadiometer, which is similar to what you see at a hospital when they take your height. We also used a scale to measure weight, and we used the BOD POD to measure for volume displacement to give us factors like body fat percent, fat mass, and fat-free mass. We also measured the firefighters' flexibility using the classic sit and reach box that most of us have used in high school. Then, we measured the firefighters' lower extremity balance using something called the Y balance test, which also tests for asymmetries. The Y balance test was conducted on both legs and the asymmetries between each leg were calculated, calculated by subtracting the difference of the scores of the right leg and the scores of the left leg all absolute valued. We only used the anterior test for the Y balance test. And the other test that we used to measure movement was the functional movement screen shorted to the FMS, and it is used to measure our participants movement. So this test looks at certain movements of firefighters. There are multiple subtests in this test, and they all look at different mobility areas. We have the deep squat, hurdle step, inline lunge, shoulder mobility, active straight leg raise, and a trunk stability push-up and we have the quadruped rotary stability test. For all of those are in the functional movement screen and they measure different things. For the data we collected, we tested for the normality of this data. However, the data was not normally distributed, as we always see in research, so what we did was normalize the data using a log 10 transformation. This way, the descriptive data we gathered could be presented in means and standard deviations. So, in this table you can see our results. You will notice that the firefighters we tested were overweight. You will also notice that they lacked on tasks that require balance and coordination. We compared the firefighter y balance test to other service members in the military, and we found that the service members had an absolute reach mean of 60 centimeters on their left leg compared to Firefighters scoring 59.08 centimeters on their left leg and 59.8 centimeters on the service member's right legs compared to 57.54 centimeters in the firefighters' right leg. Also, looking at the functional movement screen, all our firefighters scored below 14 and anything below a 14 puts the firefighters at a higher risk of developing injuries. So, in our data, all firefighters had an increased injury risk. That's why it may be beneficial for the fire departments to adopt a mobility drill that can be done before each shift. This has been practiced in other countries such as Japan and this way the firefighters may also be warmed up for their calls. So, it would be useful to incorporate it here in the U.S and incorporating a mobility exercise in the firefighters' lives may improve movement and reduce injury risk which may raise their FMS scores. It may also be beneficial to conduct semi-annual screening to keep track of the firefighters' mobility and ensure that they are going in the right track. And, thank you very much for listening to my project and I hope you have a great day.[/expand]

College of Education and Human Development Summer Team Impact Project

Exploring the Correlations Between the Functional Movement Screen and the Oswestry Low Back Pain Questionnaire

Author(s): Rouse Barker, Victoria Ghanma, Joseph Hahn, Hana Khan, Kayleigh Newman, Arasta Wahab

Mentor(s): Joel Martin, Marcie Fyock-Martin; Kinesiology

Law enforcement officers (LEO) work in demanding jobs and are at high risk for developing injuries. Approximately 67.7% surveyed reported experiencing lower back pain (LBP) at some point during the past year. Duty belts, patrol cars, and load carriage all contribute to LBP in LEO. LBP has been demonstrated to limit mobility, which decreases Functional Movement Screen (FMS) score.

PURPOSE: To test whether LEO who receive “at risk for injury” scores on the FMS (score <14), report greater lower back pain according to the Oswestry Low Back Pain Questionnaire (OLBPQ). METHODS: 6 male police officers with LBP, completed the OLBPQ. Officers were then evaluated on performance of the FMS. LEO were separated into two groups, those scoring below and above FMS composite score of 14, FMS-Low and FMS-High, respectively. Independent t-tests and correlation tests were conducted. (r=0.22, p=0.68, Alpha = 0.05) RESULTS: There was no significant difference in OLBPQ between the groups (p=0.74, D=0.28) nor significant differences in FMS scores, except for active straight leg raise. No significant correlations existed between OLBPQ score and FMS (r=0.22, p= 0.68). CONCLUSIONS: The research findings suggested that FMS scores were not indicative of severity of LBP. Mobility didn't appear to change with increased LBP. This indicates that an FMS score of 14 may not be the proper cut off point for determining disability for LEO with a history of LBP. Based on these results, it appears that LBP might be caused by different factors for different people and that mobility is not necessarily indicative of pain intensity. These results were contrary to the expected outcome. One limitation of this study was the small sample size of 6 participants. Future research should be conducted to test if other mobility tests, such as the Y-Balance test, correspond with LBP in LEO.[/expand] [expand title="Audio Transcript"]Hello everyone. My name is Kayleigh Newman and this summer I had the opportunity to work with Dr. Joel Martin, Dr. Marcie Fyock, Megan Sax Van Der Weyden, Mike Toczko and other fellow undergrad student interns. With our OSCAR grant, we worked with two groups, law enforcement officers with backpain and firefighters without back pain. I spent most of time this summer working on the law enforcement officers project. For this study, we were interested to know if there was a correlation between mobility and lower back pain felt by law enforcement officers. Before starting the study, we recognized that lower back pain is more common in police officers and we realized this is due to many factors, including the duty belts these officers wear and how much time they spend driving in patrol cars. Lower back pain often limits mobility, so we wanted to see if this was the case in law enforcement officers as well. Our participants first filled out the Oswestry lower back pain questionnaire which asked them to be very specific about the prevalence and intensity of their lower back pain. We used the FMS, or functional movement screen, to test the mobility of 6 male police officers. The FMS uses 7 different tests to evaluate someone's movement ability, the deep squat, inline lunge, hurtle step, shoulder mobility, straight leg raise, trunk stability push up, and the rotary stability exercise. You can achieve a max score of 21 on the FMS. However, in research, a score of 14 or lower is widely regarded to be the cut off point for being at risk for injury. 3 of the six participants scored below 14 and the other 3 participants scored above 14. These groups were called the FMS-low and the FMS-high groups respectively. Statistical analysis was conducted which provided us with further data to interpret. To our surprise, the results showed that there was no significant differences in the LBP scores between the two groups and that there were no significant correlations between the Oswestry lower back pain score and the FMS. This means that despite what we anticipated, lower back pain did not appear to impact mobility, according to this study. Finally, the results also showed that there were no significant differences in the individual tests on the FMS between the two groups except for one test. The FMS-high group scored significantly higher (meaning they had better mobility) in the active straight leg raise than the FMS-low group. This is an interesting finding because the active straight leg raise tests for hamstring abnormalities and hip problems, which are both risk factors of lower back pain. So, even though the groups were not different in terms of their overall FMS scores or Oswestry lower back pain scores, they were different in terms of the straight leg raise. Overall, the findings suggested that the FMS may not able to indicate lower back pain severity, as mobility didn't change with increased lower back pain. It's quite possible too that an FMS score of 14 is not an accurate cut off point for these types of participants. However, this study did have a limitation in terms of only having 6 participants so far. It is an ongoing study and more participants will be included later, so it may be best to reinterpret the data later once more has been collected. One suggestion for future research is to explore how other mobility tests, such as the Y-Balance test, corresponds with lower back pain in police officers. As I wrap up, I want to thank all of our participants throughout this study who made our research possible as well as all those who worked behind the scenes. I want to than the OSCAR organization, Dr. Martin and Dr. Fyock as well as the grad students, Mike and Megan, who guided us on a daily basis this summer. It has been a great experience working with everyone and learning how to review literature, test subjects, use lab equipment, interpret data, and present data. I look forward to continuing my work on this project and seeing how far we can take it. Thanks again to everyone.[/expand]

College of Humanities and Social Science College of Science Summer Team Impact Project

Economic Effects of COVID-19 Pandemic on GMU Students

Author(s): Brittany Justice, Eve Smith, Huy Tran

Mentor(s): Lawrence Cheskin, Nutrition and Food Studies; Matthew Rossheim, Global and Community Health; Alison Evans Cuellar, Health Administration and Policy; Zimako Chuks , Erika Kennedy , Graduate Assistants

https://youtu.be/TvfyHMW0ROA

Prior research suggests that social determinants such as household and employment insecurity have detrimental impacts particularly to communities who identify as underrepresented and under-resourced. However, it remains unclear as to how economic insecurity has affected marginalized college students during the COVID-19 pandemic. This study aims to assess how economic instability has impacted underrepresented college students during this crisis. Samples were collected using an online screener distributed among undergraduate student groups and organizations to recruit students who have been impacted socially, financially, and academically by COVID-19 pandemic. Individual interviews have been conducted to assess employment conditions during the pandemic such as health and safety when working onsite, benefits or lack thereof, etc., and the effects of these conditions on the participants’ mental health. Responses were collected and organized using Microsoft Excel. Based on preliminary findings, students who identify as Asian or Pacific Islander reported being economically impacted at 75.5%, which is significantly higher than other student groups. This suggests that students who identify as Asian or Pacific Islander at George Mason have faced severe economic effects as a result of this ongoing crisis. In addition, it is also important to notice the significance of COVID-19 and how it impacts other underrepresented student group’s mental health and resilience in terms of academic performance and frequency in reporting mental distress during this unprecedented time.

Huy Tran: 0:04

Hello, and thank you, you all for watching our presentation. My name is Huy Tran, and I am working on a Summer Team Impact Project with Brittany Justice and Eve Smith. Our project’s goal was to answer the question, how were George Mason students economically impacted by the COVID-19 pandemic, and we wanted to learn how different groups of Mason student were financially impacted during the pandemic, and if any student group or demographic was particularly impacted as well. So COVID-19 has really caused major impact on many regions of country around the world, and college student population is also in the equation as well. George Mason University is among top 5% the most diverse colleges. And because of this nature beauty of diversity at George Mason, the impact of COVID-19 also varies in different groups of students as well. During the, during the COVID-19 pandemic, many service facing businesses closed, including restaurants and retail stores. Over 40% of full-time students also work to support themselves and about ¼ students work in the food or personal service jobs, which were heavily impacted by state and federal COVID-19 safety regulations. Students from low income families are more likely to have to work to support themselves, which makes them particularly vulnerable to economic instability during mass layoffs. In addition, soon, from racial minority groups are more commonly work to support themselves. So, the purpose of our project is to gain a better understanding of George Mason students’ experiences and hardships throughout the course of COVID-19 pandemic in order to establish and develop an intervention to mitigate the problems.

Eve Smith: 2:08

Okay, so now I’m just going to go over the research process that we conducted. So, in our project, researchers interviewed undergraduate Mason students to discuss their experiences during the COVID pandemic. So far, we have collected results from roughly 133 students. These interviews included questions about student’s economic situation, academic performance, health behaviors, and mental health and wellbeing throughout the pandemic. We asked students if they had been working before the pandemic, and if they had lost their jobs, had working hours reduced or were forced to look for new employment during the pandemic.

Eve Smith: 2:45

And based on our results, we discovered that just over half the students we interviewed reported being negatively financially impacted by the pandemic. This included students who lost jobs or had reduced working hours, or students with parents who dealt with job loss or reduced hours. Students also reported leaving their jobs due to safety concerns, being furloughed, or being unable to work for an extended period of time while under quarantine.

Brittany Justice 3:14

For our next steps, we’ll be analyzing economic impact based on students of differing gender, sexual orientation, race, ethnicity, current income and first generation status to see if any groups of students at Mason or particularly impacted by the pandemic.

Brittany Justice: 3:36

Economic insecurity commonly affects student’s academic performance and personal wellbeing. Based on our results, so far, it appears that a large number of Mason students are dealing with negative economic impacts due to the COVID-19 pandemic. The high rates of economic impact demonstrate how important it is for George Mason to work to inform students of financial resources that are available to them from the university or in the students own communities.

Huy Tran: 4:10

Again, thank you for so much for listening.

For more on this topic see:

COVID-19’s Impact on Under-Resourced/Underrepresented College Students and their Peers

COVID-19 Food Security Project

College of Humanities and Social Science Honors College Summer Team Impact Project

Black Lives Next Door – Eleven Oaks Elementary School

Author(s): Rachel Amon, Kyle Buckner, Sydney Hardy, Alexis Massenburg, Sira Thiam

Mentor(s): George Oberle, University Libraries; LaNitra Berger, Office of Fellowships and African and African American Studies; Benedict Carton, History and Art History; Anthony Guidone, Anne Dobberteen, Graduate Assistants

https://youtu.be/9KfjlHABqKo

The Black Lives Next Door Project is focused on locating Black geographies, empowering Black voices, and uncovering the history of the Black community in Fairfax County, Virginia. The focus of this research is Eleven Oaks Elementary School. Even though the school operated from 1955 to 1968, it was still an important piece of Black geography. The scope of the project is to discover the history of the Eleven Oaks school, learn more about the student experience, create a list of faculty present, understand the desegregation process, and map the Black geographies around Eleven Oaks. The school was the pinnacle of the Black community when it was first built because there were seven classrooms instead of just one, but the school still lacked funding and resources. Teachers were heavily relied on to support students and provide resources to compensate for the lack of food, books, and other materials. This fostered a warm and supportive culture at Eleven Oaks, but community members recognized its shortcomings. It was also one of the last schools in Fairfax to be integrated, so the desegregation process was lengthy.

1 00:00:01.319 –> 00:00:12.120 Alexis Massenburg: Hello everybody, my name is Alexis Massenburg i’m a junior global affairs major at George mason university and I am one of the researchers on the black lives next door summer impacting research project. 2 00:00:12.540 –> 00:00:25.920 Alexis Massenburg: And so what I am sharing my screen is the Omeka website that we created and it kind of just has all the aspects of this project on the website, and so you can scroll through and look at. 3 00:00:26.640 –> 00:00:36.990 Alexis Massenburg: different aspects of this project, different students research and so i’ll be getting to that, I just wanted to give everyone an overview of what this project is about and what my specific research is about. 4 00:00:37.620 –> 00:00:44.790 Alexis Massenburg: Before I go through the website, so the black lives next door summer impact team research project. 5 00:00:45.270 –> 00:00:53.160 Alexis Massenburg: is focused on locating black geographies empowering black voices and uncovering the history of the black community in fairfax county Virginia. 6 00:00:54.030 –> 00:01:03.600 Alexis Massenburg: The primary focus of my research is 11 oaks elementary school and even though it was only operated for about 13 years it was still an important piece of black geography. 7 00:01:04.590 –> 00:01:18.750 Alexis Massenburg: So the project is mostly about learning more about the student experience the history of 11 oaks creating a list of faculty and staff present at the school that’s really important to name these black people that had a big impact on this. 8 00:01:20.490 –> 00:01:32.910 Alexis Massenburg: On this Community understanding the desegregation process and mapping the black geographies around 11 oaks, so the school was the pinnacle of the black Community when it was first built, because it was new it was nice. 9 00:01:34.470 –> 00:01:40.620 Alexis Massenburg: And there were seven classrooms instead of just one, so it was definitely something that people were proud of. 10 00:01:41.070 –> 00:01:54.330 Alexis Massenburg: But it still lacked a lot of funding and resources in relation to the white schools and in fairfax county and because of this teachers were heavily relied on to provide food books materials programming. 11 00:01:55.410 –> 00:02:07.680 Alexis Massenburg: And it created a great culture at 11 oaks it was very warm and inviting and supportive, but it still was coming up short in terms of overall resources and funding. 12 00:02:09.300 –> 00:02:20.070 Alexis Massenburg: And also, it was one of the last schools to be integrated so we’ll definitely be talking about a very lengthy desegregation process and I just want to talk about the types of of evidence that I used. 13 00:02:21.510 –> 00:02:31.080 Alexis Massenburg: I used newspapers journals articles historical maps I primarily went to the fairfax city library, and I was able to. 14 00:02:33.150 –> 00:02:46.320 Alexis Massenburg: Look at the newspapers, through this very old machine I forgot what it was called but I was able to look at the newspapers on these on rolls of film and I looked through different vertical files and. 15 00:02:47.910 –> 00:02:49.440 Alexis Massenburg: different historical. 16 00:02:51.840 –> 00:03:05.340 Alexis Massenburg: Like different historical pamphlets and like announcements and pictures and flyers from old just older fairfax schools to kind of understand the culture and ideas about what’s going on there. 17 00:03:06.870 –> 00:03:18.960 Alexis Massenburg: And also Just to give you a quick overview of my results, I was able to locate the black Community I got a great understanding of the desegregation progress the desegregation process and. 18 00:03:20.520 –> 00:03:26.820 Alexis Massenburg: I learned about what programs are available for students of color and I will save in the future, I would like to work on. 19 00:03:29.280 –> 00:03:41.430 Alexis Massenburg: kind of connecting this project more to George mason university and like what hand or university had or what role we had in the disappearance of the black community in fairfax because it definitely is declining. 20 00:03:43.050 –> 00:03:49.740 Alexis Massenburg: And yeah so now, I will go through my personal page so 11 oaks elementary school. 21 00:03:50.760 –> 00:04:09.810 Alexis Massenburg: So this is the first page is just kind of gives you the overview that I just just gave and so some of the history of the school, you can see that 11 oaks is located on school street so it’s very, very close to where our universities to be this is George mason university right here. 22 00:04:11.550 –> 00:04:27.930 Alexis Massenburg: And so 11 oaks was created through the fairfax rosenwald school in 1952 and the school opened in 1953 and it had seven classrooms a cafeteria 215 students on 6.15 acres. 23 00:04:29.730 –> 00:04:46.710 Alexis Massenburg: But it was closed in June on June 6, 1966 due to desegregation and then it was demolished in 2008 to make room for George mason boulevard, which is very close our school, a lot of expensive houses are located near there, especially on 11 oak street so. 24 00:04:48.660 –> 00:04:52.440 Alexis Massenburg: Definitely can see where these biographies are erased. 25 00:04:53.550 –> 00:04:58.740 Alexis Massenburg: These are some maps, this is what 11 looks looks like Currently, this is the school layout. 26 00:05:00.540 –> 00:05:02.730 Alexis Massenburg: And yeah and some more of the school layout. 27 00:05:03.840 –> 00:05:14.280 Alexis Massenburg: So i’ll get into the next page, which is the student experience, so this is a picture of 11 oaks in their school safety patrol 11 oaks is an elementary school. 28 00:05:16.080 –> 00:05:20.370 Alexis Massenburg: And you know I kind of included some of the previous. 29 00:05:22.200 –> 00:05:36.000 Alexis Massenburg: Black elementary schools and their experiences, because those schools were integrated into 11 oaks so one of the teachers talks about how they only had four pieces of chalk, an old broken X for cutting down wood and. 30 00:05:37.320 –> 00:05:50.910 Alexis Massenburg: How they had hand-me-down books from white schools, and they also did have a hot soup program so that’s just an example of black teachers and black faculty being resourceful and trying to provide for the students in ways that you know they did not have funding for. 31 00:05:53.280 –> 00:06:05.850 Alexis Massenburg: yeah and an interesting quote was that this the cub run school the elementary school that had those pieces of chalk and and hand-me-down books was started by people who came out of slavery, whereas the. 32 00:06:07.020 –> 00:06:16.590 Alexis Massenburg: 11 old school is a rosenwald school and it was funded and it was built by the county so it lasted for a long time it lasted until 2008. 33 00:06:17.610 –> 00:06:22.260 Alexis Massenburg: It was utilized for different purposes so that’s definitely something that’s important to note. 34 00:06:26.460 –> 00:06:27.870 Alexis Massenburg: yeah, so there is definitely. 35 00:06:29.610 –> 00:06:37.830 Alexis Massenburg: A positive culture at 11 oaks but still students were lacking resources and. 36 00:06:39.210 –> 00:06:42.480 Alexis Massenburg: there’s a strong comparison between white schools here I show. 37 00:06:43.560 –> 00:06:52.560 Alexis Massenburg: How someone even quoted that I wanted my child to attend green acres, which is a local white school because it was nicer they had newer books, you can see the difference between. 38 00:06:53.370 –> 00:07:01.260 Alexis Massenburg: The black schools and the white school this, I know, the picture is not that great, but this is a really big school compared to this one so. 39 00:07:02.400 –> 00:07:12.330 Alexis Massenburg: And these are the floor layouts of just 11 oaks right here and green acres right here, they look totally different um you can see that green acres is definitely larger. 40 00:07:13.560 –> 00:07:16.890 Alexis Massenburg: And they’re very close to each other, too, so it kind of. 41 00:07:18.840 –> 00:07:25.410 Alexis Massenburg: is a matter of desegregation and discrimination and then next the teachers and staff. 42 00:07:27.450 –> 00:07:30.780 Alexis Massenburg: So, as I said, the Faculty was very supportive. 43 00:07:32.790 –> 00:07:37.620 Alexis Massenburg: 11 oaks only had one principle, the whole time through the whole entire. 44 00:07:39.180 –> 00:07:44.730 Alexis Massenburg: course of the school her name was Janie R. Howard, and she was strict but she also is. 45 00:07:46.110 –> 00:07:53.040 Alexis Massenburg: very generous and warm and no pupil was ever deprived of a hot lunch and she used her own money to pay for meals. 46 00:07:55.740 –> 00:07:56.250 Alexis Massenburg: and 47 00:07:57.690 –> 00:07:58.890 Alexis Massenburg: Some teachers were. 48 00:08:00.180 –> 00:08:09.750 Alexis Massenburg: Some people recall teachers going and getting their own supplies for students, and here I listed all the names of the teachers, because it’s important to name. 49 00:08:11.760 –> 00:08:17.070 Alexis Massenburg: My people that had a very significant role in the Community and then here I. 50 00:08:19.140 –> 00:08:25.290 Alexis Massenburg: Have a picture of where the teachers went when schools were integrated because 11 oaks was shut down. 51 00:08:26.880 –> 00:08:35.850 Alexis Massenburg: And then here mapping of the black communities, so I had a quote where Warren hunter said that everything Southwest drive was. 52 00:08:36.780 –> 00:08:48.150 Alexis Massenburg: black and segregated so this right here would be everything south of West drive, but you can see that the redistricting lines are kind of breaking up this black Community right here so. 53 00:08:48.540 –> 00:08:55.410 Alexis Massenburg: This is just another instance of black geographies being disrupted and I just wanted to highlight that, in my research, because I think it’s important. 54 00:08:56.850 –> 00:09:01.380 Alexis Massenburg: And then here is the lengthy part the road to desegregation so. 55 00:09:03.930 –> 00:09:08.400 Alexis Massenburg: Even though brown versus Board of education was mandated in 1954. 56 00:09:09.840 –> 00:09:18.150 Alexis Massenburg: There was a huge massive resistance movement led by Harry F byrd which was two different schools, I wanted to integrate. 57 00:09:19.380 –> 00:09:34.800 Alexis Massenburg: And you can see that 11 oaks and fairfax county had no intention of desegregating because the school got a new library into classrooms and 1959 which was five years after the desegregation mandate and. 58 00:09:37.170 –> 00:09:41.520 Alexis Massenburg: It was kind of taking a long time for the school to desegregate. 59 00:09:43.470 –> 00:09:54.300 Alexis Massenburg: And at first they tried to have only the first graders go to science schools and second through six remain segregated but then finally in 1966 11 oaks was used as just a kindergarten. 60 00:09:55.680 –> 00:10:06.840 Alexis Massenburg: And then in 1968 it was fully use for admin Center for administration and all the students were relocated to schools that were integrated and closer to their homes. 61 00:10:08.460 –> 00:10:17.040 Alexis Massenburg: And there are some positive stories some people said they may friends black with black and white, children and they integrated decently. 62 00:10:18.900 –> 00:10:33.600 Alexis Massenburg: And the students were relocated to schools like Burke centreville clifton fairview lorton and West more elementary schools, and here I have some numbers of how many the actual number of black students are integrated into these elementary schools and also. 63 00:10:34.680 –> 00:10:44.460 Alexis Massenburg: An article about desegregation being complete and just showing you the proximity of 11 oaks and green acres they’re very close to each other, but they couldn’t be more different. 64 00:10:46.230 –> 00:10:55.980 Alexis Massenburg: And so, the last thing I have is the programs that are available for students of color so this one was particularly intriguing to me the culturally disadvantaged Program. 65 00:10:56.880 –> 00:11:05.610 Alexis Massenburg: So it kind of was just talking about how students that live in bad areas or slum areas have increased drops in IQ after five or six. 66 00:11:08.010 –> 00:11:13.650 Alexis Massenburg: And so the program was created to help students prepare for first grade. 67 00:11:15.120 –> 00:11:18.330 Alexis Massenburg: And the schools were chosen because they were you know. 68 00:11:19.680 –> 00:11:26.880 Alexis Massenburg: Closer to culturally disadvantaged people, and so you know 11 oaks was one of those schools and then this school was born. 69 00:11:27.720 –> 00:11:32.820 Alexis Massenburg: into the head start program, and so the head start program actually is a very positive Program. 70 00:11:33.510 –> 00:11:45.060 Alexis Massenburg: It wants to equalize students in terms of education nutrition psychology social service health volunteer work and classroom experience and keep in mind, these are preschoolers, so this is very, very. 71 00:11:45.690 –> 00:12:04.260 Alexis Massenburg: Advanced for them, and so they have a couple of goals here just to develop communication skills raise a child children’s level of aspiration promote better health developed teacher understanding so it’s definitely a very positive positive program and, here are some pictures of the Program. 72 00:12:05.310 –> 00:12:18.990 Alexis Massenburg: That we got from a head start book that we found in the fairfax city library, so you can see that this desegregation was off to a pretty decent start after you know the very lengthy waiting period, but overall. 73 00:12:20.910 –> 00:12:23.730 Alexis Massenburg: This was my research on 11 oaks elementary school. 74 00:12:25.560 –> 00:12:38.520 Alexis Massenburg: And the results were pretty good, I was able to map the black community, I was able to learn more about desegregation and learn more about these black communities these teachers, where they lived the students their experiences. 75 00:12:39.570 –> 00:12:47.010 Alexis Massenburg: So yeah This is all on the omeka website and I appreciate your time for watching this video, and thank you.

For more on this topic see:

Black Lives Next Door

Black Lives Next Door: Student Voices Meets School Silence

Black Resistance in Fairfax County

BLND Project: “Back to School”: An Examination of the Forgotten Historic Location

College of Humanities and Social Science Honors College Summer Team Impact Project

Black Lives Next Door

Author(s): Ky Buckner

Abstract:
Black Lives Next Door is a research project dedicated to investigating the relationship between George Mason and the Black community of Northern Virginia. From archival analysis to conducting an oral history interview with a former GMC professor, I both explored new research methods and learned so much about the history of Northern Virginia and my soon-to-be alma mater–George Mason. My two central findings were presented in digital exhibits, using the Omeka platform. One is entitled “Racial Ridicule at George Mason College” and it analyzes the history of racial parody in the GMC student body from 1965-1971. I specifically look at the frequent use of Blackface and analyze an annual “slave auction” held at the college from ’68-’71. The second exhibit is entitled “No Room for Revolutionaries” which explores the controversial dismissal of three faculty members, who were also avid critics of racial discrimination and the Vietnam war.

Transcript:
This summer I worked on the Black Lives Next Door research team. Over the past three months, we investigated the historical relationship between George Mason and the Black community of Northern Virginia. While GMU presently touts itself as a beacon of global diversity among southern institutions, it’s history was far from inclusive. Part of what motivated our faculty leaders — Dr. Berger, Dr. Carton, and Dr. Oberle –ì to form this group was a report released in 1971 by the Virginia State Advisory Committee to the National Civil Rights Commission, entitled “George Mason: For all the people?” After examining a bevy of evidence, the report ultimately concluded that “George Mason College was conceived of, by, and for the white community of Northern Virginia.”
Before we began our research, we undertook a two-week session with readings on Mason‚Äôs history and relevant theoretical texts, as well as having multiple guest speakers. We read from authors such as Katherine McKittrick, focusing specifically on her concept of Black Geographies as holding unique spatial, political, and historical importance. We also read the aforementioned Civil Rights report, as well a dissertation on Mason‚Äôs development as a college. Dr. Wendi Manuel-Scott spoke with us multiple times, as did Dr. Marsha Chatelin from Georgetown University. We also met with Brittney Falter from Special Collections, who showed us how to access the university archives.
That’s where my research began–flipping through manilla folders on the second floor of Fenwick. I was browsing the documents C. Harrison Mann — a former member of GMC’s advisory committee –had saved, uncertain what I would find. On the first appointment I made at the archives, I found meeting minutes where they discussed the dismissal of a professor named Robert Houston for being a “ringleader” stirring up trouble on campus, specifically citing his participation in a protest against racial discrimination. I was intrigued and as I learned more, I found other incidents of professors being controversially dismissed.
Jim Shea, former philosophy professor at GMC, was most known for his absolute opposition to the draft and Vietnam war. He also actively criticized racial discrimination at GMC and sought to alter recruitment policies, alongside another professor who was dismissed named Larry Leftoff. Leftoff taught Math and him, Shea, as well as Houston became the focus of my research. In the archives, the university has an oral series history. Fortunately, Shea had already been interviewed which proved to be an invaluable source for my research. However, neither Houston nor Leftoff had an oral history. They would be worth talking to if I could find them, I thought. I googled around for them, combed phone books and white pages, and even scrolled through every ancestry website I could find. I ended up finding a phone number for Leftoff and a page for Houston on WikiTree. After speaking with my faculty mentors, they advised me to reach out so I did. I spoke with Leftoff on the phone for an hour, discussed our research and he was excited to speak more at length. We made plans to set up a formal interview, but I lost contact with him after he sent a final e-mail explaining that he needed a few days to respond because he was preparing for a hurricane. I haven‚’t heard from Leftoff since. Houston, on the other hand, replied to my message through WikiTree — an ancestry website — impressed that I had found him and agreed to be interviewed. I ended up conducting an oral history interview with him, lasting an hour and a half long, which will be added to the university archives. In addition, Houston mentioned that he had gathered some materials that may be relevant to my research and forwarded documents, pamphlets, and pins from his time at Mason, which will also be added to the University’s archives.
At the conclusion of our research, our team created a digital exhibit to present our findings. We used a software called Omeka, which uses html to generate webpages. I ended up creating two different exhibits, one entitled “Racial Ridicule at George Mason College” and the other entitled “No Room for Revolutionaries.” Racial Ridicule explores what I found when looking at copies of the student yearbook from Mason in the 60s, where white students frequently employed Blackface at beauty competitions and parties. One of my most stunning finds was that from 1968-1971 GMC held a charity “slave auction” and it entailed pretty much exactly what it sounds like, students owned other students for a day. No Room for Revolutionaries explores the cases of Shea, Leftoff, and Houston, showing that they were dismissed primarily for their political beliefs — specifically being outspoken against institutional racism and the Vietnam war — rather than their ability to teach. This summer was a unique experience for me because it’s the first time I’ve almost exclusively interacted with primary evidence. Usually, I’m reading other people analyze sources, whereas I was able to make my own interpretations on documents I found. I learned so much and improved my research and writing immeasurably. As far as I understand, the faculty leaders intend to renew this project and I would totally recommend anyone interested to apply.

For more on this topic see:

Black Lives Next Door – Eleven Oaks Elementary School

Black Lives Next Door: Student Voices Meets School Silence

Black Resistance in Fairfax County

BLND Project: “Back to School”: An Examination of the Forgotten Historic Location

College of Education and Human Development College of Public Health College of Science Honors College Summer Team Impact Project

Supporting STEM Education in K-12 Schools Through Physical Education

Author(s): Lainey Borresen, Chelsea Flores, Abigail Kokkinakis, Mia Wilborne, Kara Wright, Safa Yosufzai

Mentor(s): Dominique Banville, School of Education; Nancy Holincheck, School of Education; Risto Marttinen, School of Education; Vernise Ferrer, Stephanie Stehle, Graduate Assistants

Summer Team Impact Project
Supporting STEM Education in K-12 Schools Through Physical Education

Undergraduate Research Assistants : Kara Wright, Chelsea Flores, Elaine Borresen, Mia Wilborne, Abby Kokkinakis & Safaa Yosufzai

Abstract :
Our goal for this Summer Team Impact Project is to present a unit plan and activities for physical education instruction while integrating STEM content. Our hope is that this integration can also pique interest in activities for those who may not usually be as engaged during PE. In the literature review we discovered that teachers require detailed guidelines on how to include STEM, newly updated resources and more. Students require real world applications and connections to the STEM content. Research assistants were paired up to create three unit plans focusing on different grade levels. Using Virginia Standards of Learning, we sought to combine relevant science topics for K-12 students with games to develop their basketball, pickleball and softball skills. This plan is flexible, for teachers to use this unit plan in its entirety, or as they see fit. A basketball unit plan was composed for grade 5, highlighting the scientific method, phases of matter and more. A pickleball unit plan was composed for grade 7, highlighting environmental science, solar systems, ecosystems and more. A softball unit plan was composed for grade 9, highlighting physical science, physics, biomechanics and more. Undergraduate students analyzed interviews of current PE teachers to determine themes and barriers to integrating STEM. Some of the main barriers or concerns addressed in these interviews were shortage of time available to teachers, lack of knowledge or confidence in STEM topics and creativity in integrating the STEM knowledge. Each unit plan consists of lead-up games, activities, ancillary materials and more.

• [collectively] Hi!
• My name is Kaye, and I am a Physical Education major.
• My name is Chelsea, and I’m a Physical Education major.
• My name is Lainey, and I’m a Nursing major.
• I’m Mia, and I’m a Chemistry major.
• I’m Safa, and I’m currently a Community Health major.
• I’m Abby, and I’m an Environmental Science major.
• So, the purpose of our research is to integrate STEM concepts into K through 12 physical education. So, we’re using basketball for fifth grade, pickleball for seventh grade, and softball for ninth grade.
• So, we used the first few weeks of our research to do a literature review, where we found a lot of PE teachers had trouble integrating STEM concepts into their PE classes, for they didn’t want to lose movement time, and they didn’t necessarily know how. So we are creating unit plans to show them how and give examples.
• During our literature review, we found out that many countries who have integrated STEM into PE classes have used creative methods and new activities. But, there’s not been any form of integration of STEM into PE in the United States. So, our research and lesson plans will help other states, as well as other counties in Virginia.
• Fifth grade focused on basketball, and scientific method, and phases of matter.
• Grade seven focused on pickleball. And, our SOLs were mainly around Life Science so we were able to integrate environmental science, environmental harm, solar systems, predator and prey, natural selection in our pickleball activities.
• Ninth grade had softball, where we focused on physical science, biomechanics, and physics.
• In order to get teachers’ perspective on STEM and integration in physical education, our team had the opportunity to interview about nine teachers who taught middle school or elementary. The interviews took about two weeks to complete, and here are some of the findings.
• So, there are some challenges to integration, from being able to condense the STEM topic to overcoming the perception of what STEM in PE entails. So, these are some of the concerns that teachers expressed.
• So, some teachers were comfortable with STEM integration in PE to some extent, and some of them had already done so. But, most of them mentioned that they needed further guidance in order to successfully integrate STEM in PE lessons.
• Some teachers mentioned that not every physical education class is standard on the amount of time, so the lack of time was a major concern around teachers.
• Other barriers to integration was that some teachers felt that integrating STEM into their curriculum is mainly them learning the new technology. And, also, dealing with the county’s bureaucracy, and how much freedom they would have in order to integrate STEM into their PE lessons. So, some of them were concerned about the county’s bureaucracy, mainly.
• The creativity of managing- in bridging the gap. PE teachers touched on methods that could help student engagement in PE, and also expressed hope for enhancement of lessons that STEM integration can bring.
• Ranking STEM areas. Each teacher had a unique perspective about how difficult it was to integrate science, technology, and engineering, and mathematics. But, almost all of them seemed to agree that engineering would be the most challenging to integrate in PE lessons.
• The standards of learning. So, teachers emphasized that it’s important for them to incorporate SOLs into lessons, and sort of keep the validity of the program.
• [collectively] Thank you OSCAR for letting us be a part of this project.