Xiaolue Zhang
Graduate Trainee, Cornell University
8 active projects
Duplicate of WCM PHS Capstone Project of Suicide Risk
Scientific Questions Being Studied
What is the impact of genetic, lifestyle, social determinants on the suicide attempts and psychiatric conditions?
Suicide is a serious public health problem resulting from co-occurring risk factors. Previous research found suicidal ideation and suicide attempt rates vary by race/ethnicity, age, and other factors like region. However, a fuller understanding of genetic and non-genetic factors of suicide is yet unknown, partly due to the lack of comprehensive data - with clinical diagnoses and self-reported assessments. Another limitation has been the lack of representativeness from historically underrepresented groups in suicide prevention research. Therefore, it is critical to analyze the cause and consequences of suicide attempts and psychiatric conditions, and how they associate with genetic, lifestyle, and social determinants.
Project Purpose(s)
- Social / Behavioral
Scientific Approaches
The Controlled Tier All Of Us Data will be utilized in this research, datastes including genetic factors with non-genetic factors like lifestyle and social
determinants will be combined to investigate the cause of suicide and its consequences. We select related genomics data, lifestyle and social determinants to
analyze suicide attempts, as well as ICD-9/10-CM codes under the broader Observational Medical Outcomes Partnership (OMOP) Common Data Model categories of drug-related disorders, mental disorders, substance abuse, sleep disorders, and mental state findings.
This reseaech can be described as a retrospective one. We will perform exploratory data analysis, produce multivariate visualization models and summary statistics, formulate hypotheses, and then go through statistical methods. We will build mathematical models using variables that have obvious associations, such as linear regression models, logistic regression models, or other machine learning models.
Anticipated Findings
Participants proportion features will be visualized and observed. Association between genetic, lifestyle, social determinants, and suicide will be determined. Impacts on suicide attempts and psychiatric conditions will be explored. Model of suicide attempts concerning mental health conditions will be constructed.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled Tier
Duplicate of How to Work With Wearable Device Data (v6)
Scientific Questions Being Studied
We recommend that all researchers explore the notebooks in this workspace to learn the basics of how to work with Fitbit data, which is the first pilot of wearable device data currently available within the All of Us Registered Tier dataset. What should you expect? This notebook will give an overview characterization of the Fitbit data elements currently available in the current Curated Data Repository (CDR) and provide best practices and tips for how to retrieve them.
Project Purpose(s)
- Educational
- Methods Development
- Other Purpose (This is an All of Us Tutorial Workspace. It is meant to provide instruction for key Researcher Workbench components and All of Us data representation.)
Scientific Approaches
This Tutorial Workspace contains one Jupyter Notebook written in Python. The notebook contains information on how to extract and work with the current set of All of Us Fitbit data. What are the anticipated findings from the study? How would your findings contribute to the body of scientific knowledge in the field? By reading and running the notebook in this Tutorial Workspace, researchers will learn how to query information about steps, heart rate, and daily activity summary.
Anticipated Findings
By reading and running the notebook in this Tutorial Workspace, researchers will understand how to work with Fitbit CDR data from the workbench. They will learn how to query information about steps, heart rate, and daily activity summary.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierDuplicate of How to Work with All of Us Survey Data (v6)
Scientific Questions Being Studied
We recommend that all researchers explore the notebooks in this workspace to learn the basics of All of Us Program Data.
What should you expect?
By running the notebooks in this workspace, you should get familiar with how to query PPI questions/surveys, what the frequencies of answers for each question in each PPI module are.
Project Purpose(s)
- Educational
- Methods Development
- Other Purpose (This is an All of Us Tutorial Workspace created by the Researcher Workbench Support team. It is meant to provide instruction for key Researcher Workbench components and All of Us data representation.)
Scientific Approaches
By running the notebooks in this workspace, you should get familiar with how to query PPI questions/surveys, what the frequencies of answers for each question in each PPI module are.
Anticipated Findings
By reading and running the notebooks in this Tutorial Workspace, researchers will learn the following:
- how to query the survey data,
- how to summarize PPI modules, and questions.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierDuplicate of How to Work with All of Us Physical Measurements Data (v6)
Scientific Questions Being Studied
How to navigate around physical measurements?
Project Purpose(s)
- Educational
- Methods Development
Scientific Approaches
N/A
Anticipated Findings
N/A
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierDuplicate of How to Get Started with Controlled Tier Data (v6)
Scientific Questions Being Studied
1. Socio-Economic Metrics: How to retrieve participants' socio-economic data from the CDR.
2. Observation Date: How to query and plot an observation date using survey completion date as example.
3. Demographics: Examples of how to query and plot participant demographic data.
4. Death Cause: How to retrieve and plot deceased participants' death causes.
Project Purpose(s)
- Educational
- Methods Development
- Other Purpose (This is an All of Us Featured Workspace: - teaches the users how to set up this notebook, install and import software packages, and select the correct version of the CDR. - gives an overview of the data types available in the current Controlled Tier Curated Data Repository (CDR) that are not available in the Registered Tier - shows how to retrieve and summarize this data.)
Scientific Approaches
We recommend that all researchers explore the notebooks in this workspace to learn the basics of All of Us Program Data. The tutorial Workspace contains two Jupyter Notebooks (one written in Python, the other in R). It contains helper functions for repeatedly, code readability and efficiency and repeatedly.
Anticipated Findings
By reading and running the notebooks in this Tutorial Workspace, you will understand the following: All of Us data are made available in two Curated Data Repository: the Registered Tier and Controlled Tier. The latter was subject to more relaxed privacy rules relative to the Registered Tier. As a result, you can expect to find more concept ids in certain data types such as EHR and Survey.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierDuplicate of Data Wrangling in All of Us Program (v6)
Scientific Questions Being Studied
For Educational purpose to show best practices when using jupyter notebooks for data access, storage, data manipulations - transformations, conversions, cleaning, optimization and other research support related issues that is useful for multiple AoU researchers.
Project Purpose(s)
- Educational
- Other Purpose (For use with Office hours. notebooks for adding code snippets useful for researchers. This is a placeholder for creating notebooks for best practices among other things)
Scientific Approaches
For Educational purpose to show best practices when using jupyter notebooks for data access, storage, data manipulations - transformations, conversions, cleaning, optimization and other research support related issues that is useful for multiple AoU researchers.
Anticipated Findings
For Educational purpose to show best practices when using jupyter notebooks for data access, storage, data manipulations - transformations, conversions, cleaning, optimization and other research support related issues that is useful for multiple AoU researchers.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierWCM PHS Capstone Project of Suicide Risk
Scientific Questions Being Studied
What is the impact of genetic, lifestyle, social determinants on the suicide attempts and psychiatric conditions?
Suicide is a serious public health problem resulting from co-occurring risk factors. Previous research found suicidal ideation and suicide attempt rates vary by race/ethnicity, age, and other factors like region. However, a fuller understanding of genetic and non-genetic factors of suicide is yet unknown, partly due to the lack of comprehensive data - with clinical diagnoses and self-reported assessments. Another limitation has been the lack of representativeness from historically underrepresented groups in suicide prevention research. Therefore, it is critical to analyze the cause and consequences of suicide attempts and psychiatric conditions, and how they associate with genetic, lifestyle, and social determinants.
Project Purpose(s)
- Social / Behavioral
Scientific Approaches
The Controlled Tier All Of Us Data will be utilized in this research, datastes including genetic factors with non-genetic factors like lifestyle and social
determinants will be combined to investigate the cause of suicide and its consequences. We select related genomics data, lifestyle and social determinants to
analyze suicide attempts, as well as ICD-9/10-CM codes under the broader Observational Medical Outcomes Partnership (OMOP) Common Data Model categories of drug-related disorders, mental disorders, substance abuse, sleep disorders, and mental state findings.
This reseaech can be described as a retrospective one. We will perform exploratory data analysis, produce multivariate visualization models and summary statistics, formulate hypotheses, and then go through statistical methods. We will build mathematical models using variables that have obvious associations, such as linear regression models, logistic regression models, or other machine learning models.
Anticipated Findings
Participants proportion features will be visualized and observed. Association between genetic, lifestyle, social determinants, and suicide will be determined. Impacts on suicide attempts and psychiatric conditions will be explored. Model of suicide attempts concerning mental health conditions will be constructed.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Xiaolue Zhang - Graduate Trainee, Cornell University
- Shiveen Kumar - Undergraduate Student, Cornell University
- Chenchen Yu - Graduate Trainee, Cornell University
Duplicate of Skills Assessment Training Notebooks For Users
Scientific Questions Being Studied
This workspace contains multiple notebooks that assess users' understanding of the workbench and OMOP. These notebooks are meant to help users check their knowledge not only on Python, R, and SQL, but also on the general data structure and data model used by the All of Us program.
Project Purpose(s)
- Educational
Scientific Approaches
There are no scientific approach used in this workspace because it is meant for educational purposes only. We will cover all aspects of OMOP, and hence will use most datasets available in the workbench.
Anticipated Findings
We do not anticipate to have any findings. Instead, we are educating people on the use of the workbench and the common data model OMOP used by the program.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered TierRequest a Review of this Research Project
You can request that the All of Us Resource Access Board (RAB) review a research purpose description if you have concerns that this research project may stigmatize All of Us participants or violate the Data User Code of Conduct in some other way. To request a review, you must fill in a form, which you can access by selecting ‘request a review’ below.
