Research Projects Directory

Research Projects Directory

1,637 active projects

This information was updated 5/28/2022

The Research Projects Directory includes information about all projects that currently exist in the Researcher Workbench to help provide transparency about how the Workbench is being used. Each project specifies whether Registered Tier or Controlled Tier data are used.

Note: Researcher Workbench users provide information about their research projects independently. Views expressed in the Research Projects Directory belong to the relevant users and do not necessarily represent those of the All of Us Research Program. Information in the Research Projects Directory is also cross-posted on AllofUs.nih.gov in compliance with the 21st Century Cures Act.

129 projects have 'COVID' in the scientific questions being studied description
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ARI Workspace V5

We now have 4 goals in our research. This workspace is for goals 1 through 3. We have created a new workspace for Goal #4. 1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the…

Scientific Questions Being Studied

We now have 4 goals in our research. This workspace is for goals 1 through 3. We have created a new workspace for Goal #4.

1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the US.

2. Determine comorbidity of autoimmune diseases, including statistics on comorbidity of other autoimmune diseases and non-autoimmune diseases for each autoimmune disease.

3. Determine the impact of COVID-19 on the autoimmune and autoinflammatory disease population. This work will be conducted in parallel with work we are doing at University of Southern California under an IRB there.

4. Explore the genomic component of autoimmune diseases, particularly among patients with more than one autoimmune disease, so that the underlying mechanisms of disease among these diseases can be better understood.

Project Purpose(s)

  • Disease Focused Research (Autoimmune diseases)
  • Ancestry

Scientific Approaches

We will create three data sets for analysis:

1. A list of diseases rated in the following ways:

a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism

b. Autoinflammatory versus autoimmune flag

c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause

2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics

Anticipated Findings

The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.

Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Collaborators:

  • Francis Ratsimbazafy - Other, All of Us Program Operational Use
  • Jeremy Harper - Senior Researcher, Autoimmune Registry
  • Jeffrey Green - Project Personnel, Autoimmune Registry
  • Emily Holladay - Project Personnel, Autoimmune Registry
  • Alexander Burrows - Research Assistant, Autoimmune Registry
  • Adnaan Jhetam - Project Personnel, Autoimmune Registry
  • Jagannadha Avasarala - Other, University of Kentucky

Srushti_LongCovid

Train Machine Learning models to identify potential long-COVID patients among (1) all COVID-19 patients, (2) patients hospitalized with COVID-19, and (3) patients who had COVID-19 but were not hospitalized.

Scientific Questions Being Studied

Train Machine Learning models to identify potential long-COVID patients among (1) all COVID-19 patients, (2) patients hospitalized with COVID-19, and (3) patients who had COVID-19 but were not hospitalized.

Project Purpose(s)

  • Disease Focused Research (Long COVID)

Scientific Approaches

To reflect that long-COVID may look different depending on the severity of the patient’s acute COVID-19, we built three different ML models using the three-site subset: (1) all patients, (2) patients who had been hospitalized with acute COVID-19, and (3) patients who were not hospitalized. The intent of each model is to identify the patients most likely to have long-COVID, using attendance at a long-COVID specialty clinic as a proxy for long-COVID diagnosis. To train and test each model, patients were randomly sampled to yield similar patient counts in both classes (long-COVID clinic patients and patients who did not attend the long-COVID clinic). For the all-patient model, data were also sampled to yield similar numbers of hospitalized and non-hospitalized patients.

Anticipated Findings

The combined demographics of the long-COVID clinic patients show significant differences from the COVID-19 patients at those sites who did not attend the long-COVID clinic (third and fourth columns of Table 1). Notably, non-hospitalized long-COVID clinic patients are disproportionately female.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

mental health during covid

According to a 2021 poll by the National Council for Mental Wellbeing, Nearly half of all Black, Hispanic, Asian, Native American and LGBTQ+ individuals say they have personally experienced increased mental health challenges between July 2020 and July 2021. Half…

Scientific Questions Being Studied

According to a 2021 poll by the National Council for Mental Wellbeing, Nearly half of all Black, Hispanic, Asian, Native American and LGBTQ+ individuals say they have personally experienced increased mental health challenges between July 2020 and July 2021. Half or more of adults surveyed said they have frequently experienced feeling tired or having less energy (63%); had difficulty sleeping (58%); felt nervous, anxious or on edge (51%); and had trouble relaxing (50%). We propose to use the All of Us data to study if the COVID-19 pandemic has disproportionately impacted the mental health of underrepresented population, and if so, shed lights on its impact.

Project Purpose(s)

  • Population Health
  • Social / Behavioral

Scientific Approaches

We propose to use multiple data modalities including EHR diagnosis codes and survey data, and appropriate statistical tools such as mixed effects model to analyse correlations.

Anticipated Findings

We hypothesise underrepresented groups may experience unique hardships and mental health struggle as a result of the COVID-19 pandemic. This study aims to investigate whether there are changes in minority mental health and well-being before and after the start of COVID-19.

Demographic Categories of Interest

  • Race / Ethnicity
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Disability Status
  • Access to Care
  • Income Level

Data Set Used

Controlled Tier

Research Team

Owner:

  • Bo Wang - Research Fellow, Mass General Brigham

Collaborators:

  • zhaowen liu - Research Fellow, Mass General Brigham
  • Yi-han Sheu - Research Fellow, Mass General Brigham
  • Jun Qian - Other, All of Us Program Operational Use
  • Young A Lee - Research Fellow, Mass General Brigham

COVID-19 and Visual Impairment

How does the experience of the COVID-19 pandemic for individuals with visual impairment compare to individuals without visual impairment? Visual disorders are debilitating diseases that account for a majority of irreversible blindness in the United States. Visual impairment can be…

Scientific Questions Being Studied

How does the experience of the COVID-19 pandemic for individuals with visual impairment compare to individuals without visual impairment?
Visual disorders are debilitating diseases that account for a majority of irreversible blindness in the United States. Visual impairment can be a source of disability amongst affected individuals. The COVID-19 pandemic has brought several challenges to individuals with visual impairment, including difficulty accessing care and increased concerns about social interaction. As an example, rapid at-home testing is inaccessible to visually impaired individuals without a caretaker as they are unable to interpret the results. If individuals with visual impairment are suffering disproportionately throughout the pandemic, new tools and policies to increase access to care and mental health services may help mitigate this disparity. Better understanding the COVID-19 experience of people with visual impairment will allow us to address this issue.

Project Purpose(s)

  • Disease Focused Research (Visual Impairment and COVID-19 experience)

Scientific Approaches

Our study cohort will be individuals who have previously had an eye examination. Of these individuals, we will identify individuals who have a visual disorder by their ICD-9/ICD-10 codes or SNOMED diagnoses. We will then utilize the COVID-19 Participant Exposure survey to identify different “spheres” of the COVID-19 pandemic experience, including access to COVID-19 testing, social distancing experiences, and wellbeing. Univariate and multivariate regression models (controlling for age, sex, race, and other covariates) will be used to predict the relationship between the relationship between the visual impairment and the COVID-19 experience. Sub-analyses may be performed in certain demographics to see how the risk for a visual disorder may modulate in certain populations.

Anticipated Findings

Previous studies on this subject have been limited by their sample size (<300 individuals) and their limited sample population (>95% White, or not reporting race). The All of Us database is the largest and most racially diverse US database, where more than 50% of participants are from racial and ethnic minorities. Large-scale ophthalmology research often has a majority White study population; the opportunity to study the association between visual impairment and COVID-19 experience in individuals from historically underrepresented backgrounds will help us ascertain how this relationship might shift in certain populations. The large sample size may allow us to discover associations in populations where previous analyses were underpowered.

Demographic Categories of Interest

  • Disability Status

Data Set Used

Registered Tier

Research Team

Owner:

Collaborators:

  • Rishabh Singh - Graduate Trainee, Mass General Brigham

SODMH variations by region

Previous studies have reported substantial variations in the prevalence of psychiatric disorders and the distributions of social determinants of mental health outcomes. However, it remains unknown if we would observe similar patterns during the COVID-19 pandemic. We are interested in…

Scientific Questions Being Studied

Previous studies have reported substantial variations in the prevalence of psychiatric disorders and the distributions of social determinants of mental health outcomes. However, it remains unknown if we would observe similar patterns during the COVID-19 pandemic. We are interested in exploring social determinants of health that are known to vary substantially across the geographic regions in the United States and examining their relationship with mental health outcomes during the pandemic.

Project Purpose(s)

  • Disease Focused Research (psychiatric disorders)
  • Population Health
  • Social / Behavioral

Scientific Approaches

We plan to use demographic characteristics measured using the baseline survey, COVID-related measures from the COPE surveys, and electronic health records in terms of datasets. We will analyze these data using statistical methods ranging from mixed-effects regression models (when modeling repeated COPE survey measurements) to causal inference methods to estimate the potential causal effects of the social determinants on mental health outcomes during the pandemic.

Anticipated Findings

Taking into account the regional variations in the distribution of risk and protective factors of mental health outcomes would help us minimize confounding by geographic regions and thus allow us to produce potential causal evidence that could inform policies and interventions.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • zhaowen liu - Research Fellow, Mass General Brigham
  • Yingzhe Zhang - Graduate Trainee, Mass General Brigham
  • Chris Kennedy - Early Career Tenure-track Researcher, Mass General Brigham
  • Bo Wang - Research Fellow, Mass General Brigham

Mechanisms underlying LGBT disparities in subjective well-being during COVID-19

Individuals who identify as lesbian, gay, bisexual, or transgender (LGBT) are at higher risk for mental health and substance use than individuals who identify as heterosexual. Few studies have extended these findings by testing potential downstream effects of LGBT disparities…

Scientific Questions Being Studied

Individuals who identify as lesbian, gay, bisexual, or transgender (LGBT) are at higher risk for mental health and substance use than individuals who identify as heterosexual. Few studies have extended these findings by testing potential downstream effects of LGBT disparities on mental health and substance use to positive outcomes such as subjective well-being. Moreover, resilience and social support are critical protective factors, but their moderating roles are not well understood. The aims of this study are to: (1) examine LGBT disparities in mental health, substance use, and subjective well-being; (2) test COVID-related stress and LGBT-specific discrimination as potential mediators; and (3) understand the extent to which resilience and social support act as buffers against stress, discrimination, mental health, and substance use on subjective well-being. Secondary aims include the exploration of sex differences and sexual minority subgroup differences in the mediators and outcomes.

Project Purpose(s)

  • Population Health
  • Social / Behavioral

Scientific Approaches

We plan to analyze data from the All of Us COPE Survey to examine whether individuals who identify as LGBT experience disparities in mental health, substance use, and subjective well-being, and test the hypothesized pathways within a structural equation modeling framework.

Anticipated Findings

(1) We hypothesize that individuals who identify as LGBT would be at higher risk for mental health and substance use behaviors, as well as lower subjective well-being than individuals who identify as heterosexual. (2) We anticipate that COVID-related stress and LGBT-specific discrimination would mediate the associations between LGBT status with mental health, substance use, and subjective well-being. (3) We expect that resilience and social support would moderate the hypothesized pathways. The findings from this study will add to the literature on LGBT health disparities as it uniquely focuses on stressors and discrimination experiences during the early phase of the COVID-19 pandemic. These findings will have the potential to inform prevention efforts on the population level during a public health crisis. Specific clinical implications include the development of targeted screening and interventions, as well as strategies to enhance resilience and social support in LGBT communities.

Demographic Categories of Interest

  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography

Data Set Used

Controlled Tier

Research Team

Owner:

  • Jeremy Luk - Other, National Institute on Alcohol Abuse and Alcoholism (NIH - NIAAA)

Stress, coping, and well-being during the COVID-19 pandemic

This project aims to (1) identify the types of coping strategies used in response to COVID-19-related distress, (2) how the types of distress, and cumulative COVID-related distress load affect the choice of coping strategy, (3) identify sociodemographic factors that affect…

Scientific Questions Being Studied

This project aims to (1) identify the types of coping strategies used in response to COVID-19-related distress, (2) how the types of distress, and cumulative COVID-related distress load affect the choice of coping strategy, (3) identify sociodemographic factors that affect the type and severity of distress experienced, and (4) evaluate the effectiveness of the coping strategies on well-being, mood, anxiety, alcohol and substance use. We will also evaluate the specific impact of the pandemic on alcohol and substance use behavior. Understanding the relationship between distress and outcomes in the context of COVID-19 pandemic can help identify the most effective response to cope with pandemic-related distress. Additionally, knowing how the pandemic has impacted individuals from different sociodemographic groups, and identifying the coping behaviors these groups employ, can help us understand and reduce health disparities in the population.

Project Purpose(s)

  • Social / Behavioral
  • Control Set

Scientific Approaches

Coping behavior will first be classified into either adaptive or maladaptive. Dimension reduction techniques may be employed to further categorize and summarize coping strategies. We will also evaluate the rates of alcohol and substance use as a response to COVID-related distress. Relationships between types of distress, demographic and socioeconomic factors, and effectiveness of coping strategies will be evaluated using a structural equation modeling approach. Items from the COVID-19 Related Impact section of the COPE survey will be used to assess COVID-19-related distress. Types of distress may be classified into categories (psychological, social, financial etc.) to reduce the number of variables to be analyzed. Well-being, anxiety, depression, and loneliness will be used as outcomes to determine effectiveness of the coping strategies. Separate analyses will be conducted to specifically examine alcohol- and drug-related coping strategies as they relate to the outcomes of interest.

Anticipated Findings

We expect sociodemographic factors to be associated with the types and severity of distress, with individuals from socially disadvantaged groups experiencing greater distress. We expect a positive relationship between severity of distress and engagement of coping strategies. Finally, we expect adaptive coping strategies to be associated with positive outcomes, while maladaptive coping strategies to be associated with negative outcomes. Finally, we expect endorsement of alcohol use as a coping behavior to be associated with higher problematic alcohol use, as indicated by AUDIT-C scores. Understanding how the COVID-19 pandemic differentially affects individuals of different sociodemographic backgrounds provide important information to reduce COVID-19-related health disparities. Results from the study can also help individuals choose the most effective method to cope with COVID-19-related distress.

Demographic Categories of Interest

  • Race / Ethnicity
  • Geography

Data Set Used

Controlled Tier

Research Team

Owner:

  • Tommy Gunawan - Research Fellow, National Institute on Alcohol Abuse and Alcoholism (NIH - NIAAA)

Fitbit heart rate signals for validation of infectious disease alerting system

We plan to use the All of Us study population to identify a similar cohort (to the outside studies defined in the next section) for pattern validation of heart rate signals to predict infection from Covid-19 and other infectious diseases.…

Scientific Questions Being Studied

We plan to use the All of Us study population to identify a similar cohort (to the outside studies defined in the next section) for pattern validation of heart rate signals to predict infection from Covid-19 and other infectious diseases. A primary goal is to validate our smartwatch-based Covid-19 alerting algorithms, as well as refine ways to exclude false alarms such as those driven by other lifestyle factors (travel, exercise...).

Project Purpose(s)

  • Methods Development
  • Control Set

Scientific Approaches

In our (Stanford) collaboration with Fitbit and the PAC-12 sports conference, 925 student athletes at PAC-12 universities have been wearing Fitbit watches for 1-2 years to aid in the prediction of COVID-19 and other infectious diseases. We also have wearable data from our phase I (N=6,187) and phase II (N=5,285) studies where we developed algorithms attempting to predict Covid-19 and other infectious diseases, but also predicted elevated physiological signals from other lifestyle factors. Comparing algorithms across studies will help us to identify factors that lead to "false" alarms, such as exercise, other health conditions, or travel.

Anticipated Findings

We hope to better refine our ability to predict infectious disease, and to distinguish other factors that create elevated or outlying signals in wearable data. This would complement our previous publications in Nature Medicine and Nature Biomedical Engineering by improving the alerts we are sending to study participants about elevated physiological signals.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

COVID_on_Cancer_Survivors

We try to explore the effects of COVID on cancer survivors, establish the relationship using All of Us data.

Scientific Questions Being Studied

We try to explore the effects of COVID on cancer survivors, establish the relationship using All of Us data.

Project Purpose(s)

  • Methods Development

Scientific Approaches

We plan to use the COVID survey data, demographic data and other related data to study the relationship. Generalized linear model and methods will be used.

Anticipated Findings

The outcome may help us to understand what factors contribute to the life of cancer survivor when COVID was there.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Jie Chen - Late Career Tenured Researcher, Augusta University

Collaborators:

  • Jun Qian - Other, All of Us Program Operational Use

Disparities in Cervical Cancer Screening Among Hispanic Women

We propose using the All of Us Research Database to answer two primary scientific questions: 1. What was the impact of the COVID-19 pandemic on the cervical cancer screening behaviors of Hispanic women, compared to non-Hispanic White women, in the…

Scientific Questions Being Studied

We propose using the All of Us Research Database to answer two primary scientific questions:
1. What was the impact of the COVID-19 pandemic on the cervical cancer screening behaviors of Hispanic women, compared to non-Hispanic White women, in the United States?
a. Is this impact different between subgroups? We will specifically examine geographic regions of the country, immigration status, socioeconomic variables such as home community area deprivation index, and the impact of COVID-19 on both mental and physical health.
2. Have Hispanic women re-emerged into preventative screenings as the COVID-19 pandemic has continued?
a. Comparing screening rates for 2019, 2020 and 2021, we plan to examine if there is a responsive surge in catch-up screenings among Hispanic women, compared to non-Hispanic White women.

Project Purpose(s)

  • Population Health

Scientific Approaches

Our study will include Hispanic and non-Hispanic White women ages 18+ who are eligible for cervical cancer screening during 2019, 2020, and 2021. Cervical cancer screening will be identified based on the procedure of cervical cancer screening. The existence of COVID-19 will be classified firstly based on the onset of the COVID-19 in the U.S. Specific COVID-19 impact will be defined based on COPE survey questions. Descriptive analyses will be conducted to assess the screening rate over the study period and across US regions. The Cochrane-Armitage test will be performed to detect a linear trend of the screening rate. Multivariable logistic regression will be conducted to assess the association of COVID-19 impact and the likelihood of screening between Hispanic and non-Hispanic White women, adjusting for sociodemographic and socioeconomic factors. Maps showing the screening rates during 2019-2021 across US regions will be created using visualization software, if possible.

Anticipated Findings

Studies have shown that the COVID-19 pandemic has led to a significant decrease in cervical cancer screenings across the country. However, few studies have examined the impact of COVID-19 on the Hispanic population, which even without the pandemic, bears a disproportionate cervical cancer disease burden. It is anticipated that cervical cancer incidence will sharply increase in the future without a responsive surge in screening as catch-up. Furthermore, the direct impact of COVID-19 has likely exacerbated the existing disparities in the cervical cancer burden due to compounding socioeconomic factors which were affected by the pandemic, such as insurance status, employment, and income. Our project is unique in that it addresses a vulnerable population that was made more vulnerable during the COVID-19 pandemic. It is also distinctive in that we aim to use these results to inform our own outreach efforts to expand cervical cancer screening among Hispanic women in our community.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

  • Linh Nguyen - Project Personnel, University of Texas Health Science Center, Houston

Loneliness and substance use

The coronavirus disease 2019 (COVID-19) pandemic contributed to an increase in anxiety, depression, loneliness and isolation in 2020 in the US. Studies suggest that the increase in alcohol and cannabis use during COVID-19 may be due to pandemic related loneliness…

Scientific Questions Being Studied

The coronavirus disease 2019 (COVID-19) pandemic contributed to an increase in anxiety, depression, loneliness and isolation in 2020 in the US. Studies suggest that the increase in alcohol and cannabis use during COVID-19 may be due to pandemic related loneliness or isolation, as loneliness has been shown to predict increased frequency of alcohol or cannabis use among people with problematic substance use. Women have experienced greater increases in alcohol use and have also been more likely to report lack of social support during the pandemic, suggesting gender may be a modifier of the effect of the pandemic on substance use. However, many studies investigating COVID-19 related substance use have relied on small clinical samples or convenience samples, which may limit generalizability of study findings. This study aims to determine whether past-month loneliness increases substance use during the COVID-19 pandemic among US adults.

Project Purpose(s)

  • Disease Focused Research (psychiatric disorders, substance use)
  • Population Health

Scientific Approaches

This study will use the COPE surveys, mostly focused on the surveys from May, June, and July 2020. We will use GEE models to account for repeated observations.

Anticipated Findings

We anticipate that people who experience higher levels of loneliness, and who are chronically lonely, will use more substances during COVID-19 and be more likely to endorse using substances to cope with the COVID-19 pandemic. We expect women to be more lonely but use less substances.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

The affect of mental health during COVID-19 among Hispanics

The study will focus on how mental health among Hispanics in the United States has been affected during the COVID-19 pandemic. This study will be important to science and public health because it will be addressing certain issues among an…

Scientific Questions Being Studied

The study will focus on how mental health among Hispanics in the United States has been affected during the COVID-19 pandemic. This study will be important to science and public health because it will be addressing certain issues among an underrepresented population and will provide more data in this area in order to help create strategies for change.

Project Purpose(s)

  • Population Health
  • Educational

Scientific Approaches

Scientific approaches will include building cohorts among different mental health symptoms and disorders. Data analysis will be conducted using R in order to obtain correlations and descriptive statistics.

Anticipated Findings

We anticipate to see an increase in mental health symptoms and mental disorders during the COVID-19 pandemic. Findings will contribute to the body of knowledge in the field because it will help non-profit health organizations address correlational issues among the mental health of Hispanics. This will also help because we are helping an underrepresented population in the United States.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

  • William Molina - Undergraduate Student, University of California, Los Angeles

COVID_SUD_MH

Our scientific question is about the health disparity in the impact of COVID pandemics on substance use disorder (SUD) and mental health. COVID pandemic has been bringing financial, social, and psychological burdens, which are known risk factors for SUD and…

Scientific Questions Being Studied

Our scientific question is about the health disparity in the impact of COVID pandemics on substance use disorder (SUD) and mental health. COVID pandemic has been bringing financial, social, and psychological burdens, which are known risk factors for SUD and mental problems. Populations from minority groups, being socioeconomically disadvantaged, of younger ages, or with limited access to corresponding health care are at particularly higher risk of developing SUD or mental problems. The adolescent and young adults are also at higher risk. The understanding of how social determinants of health (SDoHs) are associated with the risk of new SUD and mental health problems will help better support the high-risk populations during and after the COVID pandemic.

Project Purpose(s)

  • Disease Focused Research (Substance use disorder and mental health )
  • Population Health
  • Social / Behavioral
  • Educational
  • Methods Development

Scientific Approaches

We plan to use the survey data, including the COVID-19 Participant Experience (COPE), the Basics, the Personal Medical History, the Family Heath History as well as the Conditions in EHR Domain data set to identify newly developed SUD and mental health issues occurred during the COVID-19 pandemics as well as SDoHs and other major risk factors. Logistic regression models will be used to identify the major risk factors. We will also explore whether graph artificial intelligence models can be used to disentangle the effects of SDoHs from other risk factors.

Anticipated Findings

We expect to quantitatively identify major risk factors, especially SDoHs, for SUD and for mental health issues. Such knowledge can help better understanding the impact of COVID to public health. A prediction model will also be developed to identify high-risk populations.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Geography
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Registered Tier

Research Team

Owner:

  • Jing Su - Early Career Tenure-track Researcher, Indiana University

Collaborators:

  • Nathan Peters - Undergraduate Student, Indiana University
  • Megan Whitmore - Undergraduate Student, Indiana University
  • Carter Parrish - Undergraduate Student, Indiana University

AoU Shifts in Healthcare Seeking Behavior

This is a continuation of the initial exploration on a previous registered tier dataset. This will examine AoU participants who demonstrated a shift in their healthcare seeking behavior. We will seek to characterize this population, understand the role of self…

Scientific Questions Being Studied

This is a continuation of the initial exploration on a previous registered tier dataset. This will examine AoU participants who demonstrated a shift in their healthcare seeking behavior. We will seek to characterize this population, understand the role of self reported COVID-19 (if any), and examine this population for other insights.

Project Purpose(s)

  • Population Health

Scientific Approaches

The dataset will be the Control Tier v5, and participants who submitted survey responses.
This will use t-tests, chi-square, and potentially multivariable logistic regression.

Anticipated Findings

It is unclear what the findings of the study will be, our hope is to provide insights in the role of self reported COVID19 in healthcare seeking behavior shifts. Characterizing healthcare seeking behavior, or lack thereof, and what can shift this is a valuable contribution to the field.

Demographic Categories of Interest

  • Others

Data Set Used

Controlled Tier

Research Team

Owner:

Hcare Seeking Behavior

This research is designed to explore healthcare seeking behavior among participants. More specifically we are looking at if self reported COVID led to a shift in healthcare seeking behavior. This is relevant to public health, particularly in understanding the AoU…

Scientific Questions Being Studied

This research is designed to explore healthcare seeking behavior among participants. More specifically we are looking at if self reported COVID led to a shift in healthcare seeking behavior. This is relevant to public health, particularly in understanding the AoU population.

Project Purpose(s)

  • Population Health

Scientific Approaches

This will use standard statistical methods. Characterization of populations, chi-square, and anova. This will use a python jupyter notebook.

Anticipated Findings

This is not currently determined, however the goal of this research is to better understand participants, particularly those who are normally not healthcare seeking but may have changed behavior due to a covid diagnosis.

Demographic Categories of Interest

  • Others

Data Set Used

Registered Tier

Research Team

Owner:

Cancer Care and COVID-19 Dataset v5

The goal of this study is to examine if COVID-19 changed the care of cancer patients. In particular, we are interested in examining if cancer patients during, before and after COVID-19 period have the same frequency of medical appointments. The…

Scientific Questions Being Studied

The goal of this study is to examine if COVID-19 changed the care of cancer patients. In particular, we are interested in examining if cancer patients during, before and after COVID-19 period have the same frequency of medical appointments.

The study will use the data to examine if medical care of cancer patients and non-cancer patients during the above period changed and if these changes are different by age, sex, race, and ethnicity.

Project Purpose(s)

  • Disease Focused Research (Cancer)
  • Social / Behavioral

Scientific Approaches

The datasets will come from: The Basics, Medical History, and Overall Health Surveys. Analysis will use logistic regression modeling.

Anticipated Findings

It is anticipated that there will be differences in the follow-up of medical care in cancer and non-cancer patients during the time periods that include pre-COVID-19, during COVID-19, and after COVID-19.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Steven Hiek - Project Personnel, University of California, Irvine
  • Argyrios Ziogas - Late Career Tenured Researcher, University of California, Irvine

Collaborators:

  • Kathryn Campbell - Project Personnel, University of California, Irvine

Stress and Physical Activity in SC

Is the impact of stress on physical activity consistent across urban/rural residence in South Carolina? Does the stress-physical relationship differ by race/ethnicity within urban/rural designations? The relationship between stress and physical activity is reciprocal. Yet, there remains a need to…

Scientific Questions Being Studied

Is the impact of stress on physical activity consistent across urban/rural residence in South Carolina?
Does the stress-physical relationship differ by race/ethnicity within urban/rural designations?

The relationship between stress and physical activity is reciprocal. Yet, there remains a need to understand the impact of stress on physical activity. The COVID-19 pandemic has become a new stressor that may impact physical activity. To promote health and equity, it is important to examine COVID-19 as a stressor alongside discrimination and chronic stressors to understand their impact on physical activity. This study is important to public health and contributes to scientific knowledge by conceptualizing stress in three ways and intersectional approach (e.g., race/ethnicity and geography) to health equity research. To inform policy, programs, and interventions, this study focuses on South Carolina.

Project Purpose(s)

  • Population Health
  • Social / Behavioral

Scientific Approaches

For this proposed study, data will come from the All of Us Research Hub. Specifically, participant data will come from electronic health records and the key survey sections—Basics, Overall Health, Personal Medical History, Health Care Access & Utilization, and COVID-19 Participant Experience. Inclusion criteria for the study sample includes South Carolina residency, adult participants aged 18 years or older, and no missing data for the outcomes (i.e., physical activity measures) and key predictors (i.e., race/ethnicity and stress measures). Sample characteristics will be stratified by urban/rural residence to examine mean and proportional differences. Multivariate logistic regression models will examine associations among race/ethnicity, urban/rural residence, stress measures, and physical activity, after adjusting for covariates described in the proposed methods section. Regression output will be shown as odds ratios. P values < 0.05 and 95% intervals will determine significance.

Anticipated Findings

We anticipate finding urban-rural differences in the impact of stress on physical activity. Further, we anticipate finding unique race/ethnicity differences in the relationship between stressors and physical activity within urban and rural designations. Findings may contribute to growing scientific knowledge on addressing the obesity epidemic by considering the extent that acute, chronic, and discriminatory stressors impacted participants from South Carolina based on place and race/ethnicity.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

COVID, Discrimination, and Resilience

Researcher have shown that there was an increase in discrimination some points of the COVID-19 pandemic. Many researchers have suggested a myriad of reasons why this may be. However, it remains unclear what the correlates and distribution of discrimination experiences…

Scientific Questions Being Studied

Researcher have shown that there was an increase in discrimination some points of the COVID-19 pandemic. Many researchers have suggested a myriad of reasons why this may be. However, it remains unclear what the correlates and distribution of discrimination experiences were for different groups of people. In addition, it is unknown how these experiences increased or decreased during high points in the pandemic. Lastly, it is unclear how social isolation and the disruption in human connection (e.g. with family, friends, etc.) may have been associated with the mental health effects of discrimination during the pandemic. This is of considerable public health significance because we must not only address the mental health needs of those in need, but understand the specific correlates of mental health, such as discrimination, to prevent such an uptick in mental health distress due to discrimination during the next pandemic.

Project Purpose(s)

  • Social / Behavioral

Scientific Approaches

I plan on using the COPE data source from May 2020-February 2021 to examine changes in experiences of discrimination, social isolation, human connection, and mental health. I will utilize hierarchical linear models to asses random and fixed effects, as well as potential mediators and moderators. The COPE has questions related to discrimination experiences in each wave, family connections, social isolation, and mental health. I will also utilize the main survey to access basic sociodemographic information (e.g. race/ethnicity, age, socio economic status, etc.) to utilize as covariates in my analyses.

Anticipated Findings

Based on the extant research literature, I believe that we will find that there is a general uptick in perceived discrimination during COVID. In addition, we hypothesize that as discrimination experiences increase, so does poor mental health. We also hypothesize that social isolation will mediate the longitudinal relationship between perceived discrimination and perceive social isolation and perceived mental health. Lastly, we hypothesize a mediated-moderated model whereby those with perceived positive human connections who experience greater discrimination will report less social isolation and thus less poor mental health compared to those with perceived negative human connections who experience greater discrimination.

Demographic Categories of Interest

  • Race / Ethnicity
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Education Level
  • Income Level

Data Set Used

Controlled Tier

Research Team

Owner:

  • Stephanie Cook - Early Career Tenure-track Researcher, New York University

Collaborators:

  • Catherine Xin - Graduate Trainee, New York University
  • zhilin Wang - Project Personnel, New York University
  • Chenziheng Weng - Graduate Trainee, New York University

Covid-19 and Mental Health

I manage a lab of undergraduate psychology students who are interested in conducting research on covid-19 and mental health outcomes. We have not yet selected all of the relevant variables we will explore.

Scientific Questions Being Studied

I manage a lab of undergraduate psychology students who are interested in conducting research on covid-19 and mental health outcomes. We have not yet selected all of the relevant variables we will explore.

Project Purpose(s)

  • Social / Behavioral
  • Educational

Scientific Approaches

We will most likely use basic inferential statistics like t-tests, ANOVA, and multiple regression. We do not yet have a specified set of research questions, so this will be adjusted once those have been discussed in the lab.

Anticipated Findings

Again, we do not know yet as we have not been able to look at what variables are available yet. We expect covid-19 measures to be related to feelings of isolation, but we aren't sure yet if isolation is a available variable. This will be edited and adjusted once we know what variables are available to us.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Kathleen Jocoy - Early Career Tenure-track Researcher, Frostburg State University

COVID-19 Derm

We aim to study dermatologic conditions in the face of the COVID-19 pandemic. We are interested in the way socioeconomic disparities exacerbated by the pandemic may have effected the prevalence of COVID-19. Our secondary goal is to evaluate other socioeconomic…

Scientific Questions Being Studied

We aim to study dermatologic conditions in the face of the COVID-19 pandemic. We are interested in the way socioeconomic disparities exacerbated by the pandemic may have effected the prevalence of COVID-19. Our secondary goal is to evaluate other socioeconomic factors and environmental factors on dermatologic conditions.

Project Purpose(s)

  • Disease Focused Research (dermatologic)
  • Social / Behavioral

Scientific Approaches

We plan to utilize the COVID-19 survey responses, basic lifestyle survey responses, wearable data, and the disease condition information from the electronic health record datasets. We will utilize the Jupyter environment to analyze the data.

Anticipated Findings

We anticipate that the burden of dermatologic conditions may have increased due to factors associated with the COVID-19 pandemic. We hope to increase the knowledge of socioeconomic and environmental factors that may affect dermatologic conditions, especially immunologic dermatologic conditions.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

ARI Genomics Workspace

We now have 4 goals in our research - this workspace has been created specifically for Goal #4. 1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the US. 2. Determine comorbidity of autoimmune diseases,…

Scientific Questions Being Studied

We now have 4 goals in our research - this workspace has been created specifically for Goal #4.

1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the US.

2. Determine comorbidity of autoimmune diseases, including statistics on comorbidity of other autoimmune diseases and non-autoimmune diseases for each autoimmune disease.

3. Determine the impact of COVID-19 on the autoimmune and autoinflammatory disease population. This work will be conducted in parallel with work we are doing at University of Southern California under an IRB there.

4. Explore the genomic component of autoimmune diseases, particularly among patients with more than one autoimmune disease, so that the underlying mechanisms of disease among these diseases can be better understood.

Project Purpose(s)

  • Disease Focused Research (Autoimmune diseases)
  • Ancestry

Scientific Approaches

We will create three data sets for analysis:

1. A list of diseases rated in the following ways:

a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism

b. Autoinflammatory versus autoimmune flag

c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause

2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics
4. We will develop statistics analyzing the association of variants known to affect autoimmune diseases for specific diseases to see if those variants corelate with other autoimmune diseases.

Anticipated Findings

There are recognized associations between specific gene variants and some autoimmune diseases. We are going to explore whether those associations can be found in other autoimmune and autoinflammatory diseases. We hope this work can uncover the common mechanisms that underlie autoimmune conditions that appear to be unconnected but which are comorbid.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

COVID

I am building a dataset to try and understand what data are available in allofus. This will be primarily to understand inequity in COVID infection rates and treatments

Scientific Questions Being Studied

I am building a dataset to try and understand what data are available in allofus. This will be primarily to understand inequity in COVID infection rates and treatments

Project Purpose(s)

  • Educational

Scientific Approaches

This will mostly be generating a set of features based on what data is available in allofus around social determinants and performing a logistic regression for multiple clinical outcomes or treatment administrations

Anticipated Findings

This study will help elucidate any inequity in how minority populations may be getting inequitably infected or treated by covid

Demographic Categories of Interest

  • Race / Ethnicity
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Registered Tier

Research Team

Owner:

  • Michael Wang - Early Career Tenure-track Researcher, University of California, San Francisco

Primary Care Usage and Barriers During the Time of the COVID-19 Pandemic

The proposed research project aims to first assess whether access to primary care physicians is different among racial and ethnic groups. Then, we will access how COVID-19 may have impacted individuals' health habits. The significance of this project is to…

Scientific Questions Being Studied

The proposed research project aims to first assess whether access to primary care physicians is different among racial and ethnic groups. Then, we will access how COVID-19 may have impacted individuals' health habits. The significance of this project is to help medical providers gain a better understanding of the impact of COVID-19 on their patients.

Project Purpose(s)

  • Population Health

Scientific Approaches

Using the COPE survey in addition to the Healthcare Access and Utilization survey, I will assess how the COVD-19 pandemic has influenced access to healthcare and whether significant differences in access to healthcare and health behaviors exist among racial and ethnic groups.

Comparisons between cases and controls will be performed using Pearson's χ2 test. Odds ratios and 95% confidence intervals will also be computed during analysis.

Anticipated Findings

Our findings will demonstrate how access to basic medical services may have changed in the recent year due to COVID-19 and how medical providers can be cognizant of any disproportionate impact COVID-19 has had on racial and ethnic groups when working with their patients.

Demographic Categories of Interest

  • Race / Ethnicity
  • Access to Care

Data Set Used

Registered Tier

Research Team

Owner:

Mental Health & Neighborhood Risk

The aims of this study are (a) to explore the associations between income loss, food insecurity and parents’ mental health (b) to explore the associations between social and structural neighborhood factors and parents’ mental health across racial/ethnic groups, and (c)…

Scientific Questions Being Studied

The aims of this study are (a) to explore the associations between income loss, food insecurity and parents’ mental health (b) to explore the associations between social and structural neighborhood factors and parents’ mental health across racial/ethnic groups, and (c) to explore whether the associations between food insecurity, income loss and parents’ mental health trajectories were mediated or moderated by SES and neighborhood risk across racial/ethnic groups during the COVID-19 pandemic.

Project Purpose(s)

  • Social / Behavioral

Scientific Approaches

A series of Bayesian latent growth modeling will be used to assess between person differences and within-person changes on parents' anxiety, stress, and depression levels over time. Using a step-wise approach, a series of models will be tested iteratively by increasing model complexity: random intercept, random slope, non-linear slope, and growth mixture models to determine the best fitting trajectory. Next, the impact of age, SES, and history of mental illness will be tested using conditional growth curve modeling, and growth trajectories will be compared across racial/ethnic groups by using multigroup latent growth curve models.

Anticipated Findings

Experiencing income loss or food insecurity during the COVID-19 could negatively affect the quality of parent-child interactions due to parents' increased distress. However, identifying the role of SES and neighborhood risk on the association between family financial difficulties and parents’ mental health trajectories can assist policymakers to help identify the low-resource communities where programs and services can then focus efforts to provide services to in-need families.

Demographic Categories of Interest

  • Race / Ethnicity
  • Geography
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Controlled Tier

Research Team

Owner:

Alcoholism

With the COVID pandemic it is believed that there would be an increase in alcoholism as well as alcohol withdrawal. Will do a comparison pre covid , at the beginning of covid and one year into covid.

Scientific Questions Being Studied

With the COVID pandemic it is believed that there would be an increase in alcoholism as well as alcohol withdrawal. Will do a comparison pre covid , at the beginning of covid and one year into covid.

Project Purpose(s)

  • Educational

Scientific Approaches

data mining looking at ICD codes and hospital admissions

Anticipated Findings

expect that there was a significant increase in alcoholism and withdrawal

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

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