Category: Undergraduate Research Scholars Program (URSP) – OSCAR

Laser-Induced Graphene–Nanoparticle Platforms for Plasmonic Enhanced Photosensing

Author(s): Ali Kabli

Mentor(s): Pilgyu Kang, Mechanical Engineering

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Abstract

This project explores the potential for enhancing the performance of Laser-Induced Graphene (LIG) using metallic nanoparticles (NPs) as a platform for fabricating photosensors with enhanced sensitivity. The main question being addressed is can a Laser-Induced Graphene–Palladium nanoparticle (LIG-PdNP) nanocomposite enhance sensor sensitivity through plasmonic and interfacial effects? Research has been conducted in the past regarding the use of LIG as the functional material in a photosensor, and the rationalization behind using these metallic NPs in a nanocomposite material is to improve the sensitivity of the sensor by improving the photoresponsivity. This is due to the introduction of plasmonic effects from the NPs, which allows for the photocurrent to flow more efficiently. The main novelty behind this particular project’s approach lies in the synthesis of the nanocomposite, where classic means would have the NPs deposited on the LIG surface creating point contacts. The synthesis technique being explored here involved a one-step synthesis via precursors and a polymer substrate, which creates a “seamless interface” between the components of the functional material. This interface allows for the electrons to flow freely between the LIG and NPs, enhancing the photoresponsivity of the device. Two devices were compared, one with 0wt% of PdNPs, and another with 30wt% PdNPs in order to observe any improvements in the performance of the devices when hit with a blue laser (448.2nm wavelength). Future research regarding this project includes using NPs with higher plasmonic effects such as gold or silver, as well as refining the geometric footprint and patter of the sensor itself to increase performance further.

Audio Transcript

Hello everyone, my name is Ali Kabli and today I’m going to present to you my undergraduate research project, Laser Induced Graphene Nanoparticle Platforms for Plasmonic Enhanced Photosensing. This project was advised by Dr. Pilgyu Kang from the Department of Mechanical Engineering.

So to give a brief background and introduction, past research has been done by Dr. Kang and his group, utilizing laser-induced graphene, or LIG, as a sensing element in photosensors. Now, these sensors operate based on the premise of photosensitivity. You basically shine a laser of some known wavelength at the sensor, which will induce some photocurrent. The change in photocurrent can be observed and used for sensing purposes. We want to improve the sensitivity of these devices by introducing metallic nanoparticles, or NPs, to increase the plasmonic effects and photoresponsivity of these devices. Now, for the purposes of this project, the specific nanoparticles that were used were palladium. However, any metal that has known plasmonic effects can be used.

For the purposes of this presentation, or project, we proposed a novel nanocomposite synthesis technique, which resulted in a seamless interface between the LIG and the nanoparticles. Traditional methods would have you deposit these nanoparticles on the surface of the LIG, or whatever substrate you’re using, which results in a point contact between the particles and the bulk surface. The downside to this is the fact that that point contact doesn’t allow for the most efficient flow of electrons. However, through a one-step synthesis technique using precursors and polymer substrate, we are able to integrate these nanoparticles within the surface of the laser-induced graphene itself, allowing the electrons to flow seamlessly.

So, the main question that we were answering with this research project was, can a laser-induced graphene palladium nanoparticle nanocomposite enhance sensor sensitivity through plasmonic and interfacial effects? The plasmonic effects, once again, coming from the fact that we’re using these metallic nanoparticles, and the interfacial effects coming from the seamless interface through our unique synthesis technique.

The methods and procedure for this project involved the actual synthesis of our nanocomposite using the one-step technique. Then we would fabricate the photosensor device using the synthesized nanocomposite. It should be mentioned that the scale of this sensor was 500 millimeters by 500 milliliters, which is actually quite large given the nanoscale. It’s very, very large. So that may have resulted in the data being slightly skewed, which is an improvement that we will go over at the end of this presentation. Then we collected optical data regarding the photoresponsivity of the device by hooking it up to an optical testing apparatus where we would shine a laser on and off at known intervals. The laser’s wavelength was known for the purposes of this project. We were using a blue laser, 448.2 nanometers of wavelength, and we would plot the resulting photocurrent as a function of time. The long-term goals of this project are to one day harness these nanocomposites as a platform for plasmonically enhanced PEC or photoelectrochemical gas sensors.

Now here’s just a brief snapshot of the results. We see on the left side a comparison between the photocurrent resulting from a 30 weight percent nanoparticle nanocomposite and on the right side we have the photocurrent resulting from just pure LIG. As you can see the scale on the left side is in microamps, and the scale on the right side is in nanoamps, which means that we were able to show a drastic improvement, three orders of magnitude to be exact.

In conclusion, the experiment was a huge success in proving that plasmonic effects could enhance the sensitivity of these devices. However, more work is still needed in the future. We can refine the geometry and footprint of the sensor itself so that it’s a lot smaller than 500 by 500 millimeters. We can also test other nanoparticles with known greater plasmonic effects, such as gold or silver. And we can also play around with different laser parameters, focusing the laser’s beam more, increasing the wavelength, etc.

Some acknowledgements. Of course, my advisor, Dr. Pilgyu Kang, Graham Harper, who aided in data collection on this project, and Philip Acatrinei, for being an indispensable help in data collection and in setting up the experiment itself. He actually programmed the software that we were using to collect the data. So without him, this project would not have been possible. Thank you.

College of Engineering and Computing College of Humanities and Social Science Honors College Making and Creating OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR Winners

A Robotic Cat for Examining Camera Clarity and Privacy in Human–Robot Interaction

Author(s): Alexia De Costa

Mentor(s): Eileen Roesler, Department of Psychology

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Abstract

This project presents the Bioinspired Automated Robotic Cat (BARC), a functional companion robot designed to support research in human–robot interaction and privacy-aware design. BARC features camera-based facial detection, expressive gaze behaviors, audio responses, and various soft and rigid materials to mimic a household cat. Because camera systems can enhance interaction while raising privacy concerns, the ongoing study compares peoples’ responses under two conditions: a clear, high-quality camera filter and a blurred, low-clarity camera filter. Using surveys and observation of touch behavior, the study examines how camera clarity shapes engagement and perceived privacy, informing the design of social robots that are effective while respecting user comfort.

Audio Transcript

Have you ever wondered what a robot actually sees when it looks at you?
Today, social and service robots are becoming increasingly common, and many rely on cameras for facial recognition and user engagement. But as useful as cameras are, they also raise important questions: Do they make people feel watched? Can a robot feel friendly while still respecting privacy?

These questions lie at a key intersection in human–robot interaction, that robots need perception to understand us, yet high-resolution sensing can make people uncomfortable. So I wanted to explore a central challenge: can we reduce privacy concerns without making interactions less enjoyable? And does being transparent about what a robot sees change how people feel?

To investigate this, I designed and built a robot cat from scratch called BARC, the Bioinspired Automated Robotic Cat. BARC is part engineering platform and part research tool. It can switch between two controlled camera conditions: a clear, high-quality camera filter and a blurred, low-clarity filter that still allows for partial facial detection. These interchangeable physical filters let me directly compare how different levels of sensing clarity influence interaction.

BARC is also designed to feel expressive and lifelike. It uses camera-based facial detection for gaze behavior, animated OLED eyes, a speaker for cat-like sounds, and soft and rigid materials that mimic the look and feel of a household cat. Through surveys and observations of touch behavior, my ongoing study explores how these two camera conditions shape user engagement and perceived privacy.

To create BARC, I began with feline anatomical references, studying limb placement, joint spacing, and overall proportions, to inspire the CAD model for the chassis. I laser-cut the acrylic components and assembled them using screws and tab-and-slot joints for a sturdy, lightweight frame.

At the heart of the robot is a Raspberry Pi 4, which handles perception and behavioral control.

A camera provides the main sensory input for facial detection.

Two OLED displays animate expressive eyes that track the user once a face is detected, giving the illusion of attention and social presence.

A speaker and amplifier generate a range of cat sounds, from meows to purrs to alarmed yowls.

An accelerometer-gyroscope detects movement, such as being picked up or shaken, so BARC can respond appropriately.

Servos are controlled by a PCA9685 driver, animate the limbs, jaw, head, and tail.

All behaviors are programmed in Python and organized in a state machine with modes such as Idle, Seeking Attention, Interacting, and Startled. BARC transitions between these states based on sensory input and probability, helping interactions feel natural rather than scripted.

To examine how camera clarity influences engagement and privacy perceptions, BARC serves as a fully capable research platform. Seventy-two participants are currently part of a single-blind study with two groups:

Group 1: interacts with BARC using a clear camera filter

Group 2: interacts with BARC using a blurred, privacy-preserving filter

The physical filter is noticeable, so using filters in both groups keeps the robot visually consistent. That way, any differences we see are truly due to what the robot can or can’t perceive.

Participants interact with BARC, complete a survey measuring constructs such as Perceived Sociability and Perceived Enjoyment, and then are shown a live camera feed so they can see the actual resolution of the robot’s vision. Afterward, they complete a second survey measuring perceived privacy, perceived surveillance, disturbance, and attitudes about robots.

The hypotheses are:
1: No difference in sociability, enjoyment, or touch behavior.
2: The filtered-camera group will report higher perceived privacy.
3: The clear-camera group will report higher perceived surveillance.

This interdisciplinary project connects mechanical engineering, psychology, and human-robot interaction to better understand how people perceive robotic sensing. BARC’s expressiveness, biological inspiration, and controlled camera conditions make it a powerful research platform.

By comparing clear versus filtered camera views, this research explores whether privacy concerns come from what the robot actually sees, or what users believe it sees. Ultimately, the goal is to guide the design of future social robots that remain engaging and respectful of user’s privacy

Special thanks to Dr. Eileen Roesler (Psychology) and Dr. Daigo Shishika (Mechanical Engineering) for their invaluable mentorship. Thank you to Katya Schafer for assistance with data collection, and to Dr. Karen Lee and OSCAR for their support and funding, which made this project possible.

Thank you!

Cells, Individuals, and Community College of Public Health Honors College OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR

Rest and Results: The Relationship Between Sleep, Stress, and Grade Point Average (GPA) in Undergraduates

Author(s): Michael Kaleem

Mentor(s): Ali Weinstein, College of Public Health

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Abstract

Michael Kaleem
URSP Abstract

Title
Rest and Results: The Relationship Between Sleep, Stress, and Grade Point Average (GPA) in Undergraduates

Authors: MK and AW

Background
Sleep plays an important role in college students’ cognitive functioning and overall academic success, making it a crucial area of study. However, the specific relationship between parameters of sleep and academic performance has not been well studied. In addition, college students have also reported increasing levels of stress over the past few years, and stress can affect both sleep and academic success. Therefore, the current investigation examined the associations between duration of sleep, sleep quality, and stress with academic success.

Methods
Data were collected by surveys completed by undergraduate students at a large, public university. Sleep duration and sleep quality were assessed by the Pittsburgh Sleep Quality Index (PSQI), and stress was measured with the Perceived Stress Scale. Academic success was operationalized as a self-reported GPA. Pearson correlations determined association between the variables of interest with p<0.05 set as the level of statistical significance. Results
There were 196 undergraduate students that participated (70.1% female, 36% white/non-Hispanic, 27.6% Asian/Pacific Islander, age: 18.1±0.5). Both sleep duration and sleep quality were statistically significantly related to GPA (r=0.17, p=0.02, r=-0.13; p=0.001, respectively). Therefore, as the number of hours of sleep increased and as sleep quality increased (lower number on PSQI is indicative of better sleep), GPA increased. Elevated stress levels were related to both sleep duration (r=-0.14; p=0.01) and sleep quality (r=0.40; p<0.001) but not significantly correlated to GPA (r=-0.01; p=0.92). Conclusion
This study found that sleep duration and sleep quality were positively associated with academic success. Although stress was not directly related to academic success, it was associated with both sleep duration and quality, suggesting that stress may influence academic success indirectly through its effects on sleep. Future research should explore how demographic, socioeconomic, and environmental factors influence sleep patterns and academic success to better inform strategies that support student success.

Audio Transcript

How many hours of sleep did you get last night? And do you think it affects your GPA? Sleep is something most college students sacrifice, yet it’s essential for memory, learning, and mental functioning. My name is Michael Kaleem, and our research explored the relationship between sleep, stress, and academic performance in undergraduates. We wanted to know: Could better sleep actually lead to better grades—and how does stress fit into the picture?

Sleep is more than just rest. During sleep, the brain strengthens memories, organizes information, and supports attention and problem-solving. So, in theory, students who sleep longer and sleep better should perform better academically. But college life is complex—so real data is needed to understand what’s actually happening.

Stress is one of the biggest disruptors of sleep. High stress can shorten sleep duration, worsen sleep quality, and impact mood and focus. Because stress influences both sleep and academic functioning, we wanted to understand whether stress plays a direct role in GPA—or whether its effects occur indirectly through sleep.
We surveyed 196 undergraduate students at a large public university. Sleep duration and sleep quality were measured using the Pittsburgh Sleep Quality Index, stress was assessed using the Perceived Stress Scale, and students self-reported their GPA. We used Pearson correlations to examine how these variables were related, with significance set at p < 0.05.
We found that both sleep duration and sleep quality were significantly related to GPA. Students who slept more hours tended to have higher GPAs. And students with better sleep quality—which means fewer sleep problems—also had higher GPAs. So in this sample, sleep really did matter for academic success.
Stress told a different story. Stress levels were not directly related to GPA. However, stress was strongly connected to both sleep duration and sleep quality. Students with higher stress slept fewer hours and had worse sleep quality. This suggests that stress may influence academic performance indirectly—by affecting the amount and quality of sleep students get.
Our findings show that sleep duration and sleep quality are important predictors of academic success. Even though stress didn’t directly affect GPA, it played a major role in disrupting sleep. This highlights a powerful message: helping students improve sleep habits and manage stress can support academic performance, cognitive functioning, and overall well-being.
Future research should explore how demographic, socioeconomic, and environmental factors influence sleep and academic outcomes. Understanding these differences can help universities design more effective programs to support healthier sleep, reduce stress, and improve student success across diverse populations.

Making and Creating Undergraduate Research Scholars Program (URSP) - OSCAR

Design and characterization of a de-novo adenine binding protein

Author(s): Amber Middleton

Mentor(s): Lee Solomon, Biochemistry

Abstract

This study explores the de novo design and characterization of a protein engineered to selectively bind adenine; a molecule critical to ATP function, nucleotide recognition, and a wide range of cellular processes [2]. Our objective is to determine whether targeted structural mutations can enhance adenine binding affinity beyond the levels achieved by the original computational model. The designed protein will be expressed via recombinant DNA techniques and purified using Ni-NTA affinity chromatography. Structural and functional characterization will be carried out using a variety of analytical techniques. Those include SDS-PAGE, circular dichroism (CD), fluorescence spectroscopy, surface plasmon resonance (SPR), and isothermal titration calorimetry (ITC). These methods will evaluate protein purity, secondary structure, and protein-ligand binding behavior. Through this approach we aim to identify key structural determinants that improve adenine specificity, offering new insights into rational protein design and the molecular basis of protein-ligand recognition.

Audio Transcript

My name is Amber Middleton and my project is called the design and characterization of a Doo adding binding protein. Our research question is can specific structure mutations and Danovo designed protein enhanced binding affinity and specificity for adding compared to the original computational design so why adding all nucleotide bases are rigid and aromatic, but addinine has a hydrogen bon or donor arrangement that is unique and specific um for selective and specific binding to proteins so it’s better suited for binding when interacted with ATP. The mutations that we made are from Alline to Isosine Alline to veailinging to 3ine and glycine to searin all these mutations were done by a regent PhD student Robert Spain for our methods, we had to express the protein purify it check the purity check the secondary structure and do a series of binding assets. The first thing is the expression of the proteins and recombinent DNA techniques, TB Media, LB Media, and inoculation overnight then we move on to NINTA chomatography to purify your protein where you’ll put your protein down into the column. It’ll run through. You’ll rise it with binding buffer samples and then you’ll rinse it with mixtures of binding buffer and ausion buffer samples and then you’ll collect each of those for analysis separately you then check the purity via SDS page so you’ll take those samples that you collected from the column, put them in run them at 180 V and they will separate by mass ideally, the thicker or darker the bands they hire their protein concentration. You’ll take the thickest ones, darkest ones, and do dialysis to remove all small salts and then we’ll move on a circulularichroism to check the secondary structure for for alpha helix proteins. You’ll see two negative peaks one at 208 n and one at 222 n which we do see in both of the pictures to the right the top being the wild type and the bottom being the mutant we then moved on to our first binding assay, which is surface plasma residence. We were only able to do a negative control with the wild type in adding proving that adding does not bind to the wild type. We then moved to our second binding assay fluorescence, and isodropy. This measures molecular interacts by detecting changes in fluorescent molecules, rotations so the faster the tumbling, the less binding that’s happening and the slower the tumbling, the more binding that is happening. This is some of our results from the first few anisropy experiments as you can see in yellow these are a little bit weird values. They imply that they’ protein technal gives more of a signal than protein addinine does, which essentially means that addingine quitching the protein signal or other things such as G-factor issues are going wrong our values are specific are expected to be between zero and 0.4 for anisatropy, but that’s not what we see in the highlighted so because of this, we wanted to move on to isothermal titration calorimetry, which measures heat released or absorbed, and these are the results that followed that on the left we have a IC thermogram of Valerab into the wild type AT&D, which is our positive controls and we were able to see that there is decreasing exothermic peaks, which proves that there was um functional liggin interaction and binding with the wild type protein, but on the right we have a ITC thermogram of adding with AT&D mutant, which looks nothing like the one on the left showing that there were only small producible changes in heat changes and there was no binding happening so our conclusions and future directions again we were able to purify and express our proteins and get up for alpha helix bundle, but upon doing finding assays, we were able to determine that addine and our mutant do not bond to each other so we have to go back to insilical design to re-engineer the binding pocket for addinine recognition using structural modeling and computational design followed by the validation CDEFSPRNITC and we aim to create a new mutant capable of selectively binding addine and this will help our understanding of targeted mutations to shape Lan specificity and enobble protein scaffolds

Making and Creating OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR

Plasmonic Metal-Infused Laser-Induced Graphene for Enhanced Photodetection

Author(s): Graham Harper

Mentor(s): Pilgyu Kang, GMU Mechanical Engineering

Abstract

Laser-Induced Graphene (LIG) is a promising platform for next-generation flexible photodetectors due to its high conductivity, scalability, and low-cost fabrication. However, its optical-to-electrical conversion efficiency remains limited by weak light–matter interaction. In this work, we enhance LIG photodetection performance through the in-situ infusion of plasmonic palladium nanoparticles into the polymer precursor prior to laser carbonization. During laser processing, the nanoparticles become embedded within the porous graphene microstructure, enabling localized electromagnetic field enhancement via surface plasmon resonance. Electrical characterization under UV illumination demonstrates improved resistance modulation and consistent ON/OFF cycling behavior in Pd-infused LIG compared to bare LIG samples. These initial results confirm plasmon-assisted photocarrier generation and highlight an effective, single-step approach to improving responsivity in flexible photodetectors. Future efforts will investigate wavelength-dependent response and additional plasmonic materials such as silver and gold nanoparticles.

Audio Transcript

Hello, my name is Graham Harper from the Mechanical Engineering Department at George Mason University. Today, I’ll be presenting my research about Plasmonic Metal-Infused Laser-Induced Graphene for Enhanced Photodetection.

Photodetectors are critical components in environmental and optical sensing systems. However, many conventional photodetectors are expensive to fabricate and lack flexibility.
Laser-Induced Graphene offers a more scalable and low-cost alternative due to its conductive porous structure and ability to be processed on flexible substrates.
The challenge is improving how efficiently it converts light into a measurable electrical signal.

One promising way to improve photodetection is by taking advantage of surface plasmon resonance.
Metal nanoparticles, such as palladium, can enhance local electromagnetic fields when illuminated, generating more charge carriers in the device.
By infusing metal nanoparticles directly into the polymer before laser conversion, the plasmonic functionality becomes embedded within the graphene structure.
Our hypothesis is that metal infused laser-induced graphene will perform better under illumination than bare laser-induced graphene.

Our objective is to fabricate laser induced graphene using a UV or CO₂ laser, characterize its structure and electrical properties, and measure photodetection performance under illumination.
The main goal is to determine whether palladium-embedded laser induced graphene produces enhanced optical-electrical response.

To create Palladium infused laser-induced graphene, a palladium-doped polymer solution is spin-coated for thickness uniformity. A laser induces carbonization to form conductive graphene that has palladium nanoparticles dispersed throughout.
Electrical contacts are added using silver paste and copper wires.
Samples are tested under a 62 mA UV laser while recording resistance changes as the light switches on and off.

Our results show a clear increase in resistance change under illumination for the Pd-infused samples.
The cycling data demonstrates consistent ON/OFF behavior with strong repeatability, confirming plasmon-assisted photocarrier generation and successful light response.

We successfully created plasmonically enhanced laser-induced graphene, palladium-infused laser-induced graphene showed stronger optical-electrical response, and the fabrication method remains low-cost and scalable.
This demonstrates that plasmonic nanoparticles provide an effective pathway to improve flexible photodetectors.

Future goals include testing silver and gold nanoparticles with stronger plasmonic response, expanding testing to more wavelengths beyond UV, conducting durability and reliability testing, and performing additional structural analysis (Raman, SEM).

Thanks to the Undergraduate Research Scholars Program, Dr. Pilgyu Kang, and the Nanomaterials Lab at GMU for their support.

Cells, Individuals, and Community College of Engineering and Computing OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR

Pain, Medication Use and Biomarker Associations in Individuals with Polycystic Ovary Syndrome (PCOS) : Insights from the All of Us Research Program

Author(s): Jannatul Nayeem

Mentor(s): Jenny Phan, CASSBI

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Abstract

Background:
Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder often accompanied by chronic pain, yet the biological and social determinants of this pain remain underexplored. Understanding how stress-related biomarkers and healthcare access interact in shaping pain experiences may reveal mechanisms underlying health disparities in PCOS populations.

Objective:
This study examined associations between inflammatory and neuroendocrine biomarkers (C-reactive protein (CRP), cortisol, and body mass index (BMI)) and pain burden among individuals with PCOS, while exploring the moderating role of healthcare access and insurance coverage.

Methods:
Using data from the All of Us Research Program, 2,160 adults with PCOS (identified by ICD-9/10 codes) were analyzed. Pain burden was measured through pain-related diagnoses and pain medication dosage. Biomarker distributions were winsorized, log-transformed, and analyzed via multivariate regression models adjusting for age, race, socioeconomic status, and healthcare variables.

Results:
Pain burden alone was not significantly associated with higher CRP, cortisol, or BMI levels. However, healthcare access moderated these relationships: participants with greater barriers to care exhibited elevated inflammation and BMI with increasing pain, whereas those with adequate access showed flatter or reduced biomarker trends.

Conclusions:
Findings suggest that chronic pain and stress responses in PCOS may be shaped more by social and contextual factors than biological burden alone. Enhancing healthcare accessibility and equity could mitigate stress-related physiological outcomes and improve pain management for individuals with PCOS.

Audio Transcript

0:01 Hello, my name is Jannatul Nayeem. I am a student researcher with the B&LAB, um, at George Mason. I’m working directly with, um, Dr.
0:13 Jenny, um, in her our static load study. Which is the body’s biological stress response, and how it relates to menstrual disorders and chronic pain.
0:23 Um, from that study, I wanted to dive deeper into PCOS, and look at pain medication use and biomarker. Or associations and individuals with that disorder.
0:36 Umm, for methodology, I started off by using, umm, the all of us data set, uhh, database. Umm, it has a ton of data on- individuals, uhh, with all sorts of diseases and, umm, information from their doctor visits, umm, patient records, and also, umm, some survey questions that, the program itself asks
1:06 those participants, umm, and so through that, through that database, I was able to find what 2160 individuals with PCOS, and dive deeper into, uhh, their- biomarkers, uh, specifically for this, I’m using, umm, 3 biomarkers as predictors for inflammation and stress.
1:30 I’m using BMI, C-reactive protein, and cortisol. And then, umm, for- for their outcome variable, I use pain diagnosis along with their medication usage, umm, for medication usage, umm, I accounted for, umm, how many medications they’re taking.
1:52 And, and also what the dosage was for that medication, umm, and then some co-variates, such moderators that, sorry, some co-variates that I used was age, race, uhh, and SES index, and then for moderators, umm, I looked at healthcare access, uh, specifically insurance insurance status and access to care
2:19 . there. And so, I’m going to zoom into the results that I had, umm, hopefully in the video it resumes in two.
2:33 umm, but for my results, I found that, umm, pain alone didn’t start- we predict inflammation or stress, but limited access to care did.
2:45 Individuals with more barriers, such as lack of insurance, showed higher inflammation and BMI with pain, suggesting that health equity plays a critical role in PCOS pain.
2:56 Um, while my insurance data was limited, uh, because, uh, that not many people answered those questions, um, there’s still show some support that the idea- that stress biology and pain in PCOS are influenced by social environment and not just physiology.
3:22 Um, right now, I am continuing this study, um, to- or they’re deep in my understanding and advocate for equitable pain care in PCOS populations.
3:36 Umm, and so one thing I want to focus on more is, uh, imp- moving, um, how we, uh, state these questions, because I do feel like how the, uh, question is stated about access to care and insurance status is pretty sensitive.
3:58 So how can we go about it to, change the way, um, someone feels about answering those type of questions. Um, and so yeah, that was my study.
4:09 Thank you for listening.