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National Academy of Medicine; The Learning Health System Series; Grossmann C, Chua PS, Ahmed M, et al., editors. Sharing Health Data: The Why, the Will, and the Way Forward. Washington (DC): National Academies Press (US); 2022.

Sharing Health Data: The Why, the Will, and the Way Forward.

• Hardcopy Version at National Academies Press

6 CASE STUDY: THE NATIONAL COVID COHORT COLLABORATIVE (N3C)

Interviewees: Melissa Haendel, PhD, Co-director; Chris Chute, DrPH, MD, MPH, Co-director; and Andrea Volz, Communications Manager

The National COVID Cohort Collaborative (N3C) was rapidly established in spring 2020 as an open science partnership between the 60 Clinical and Translational Science Awards (CTSA) Program hub sites, the National Center for Data to Health (CD2H), multiple distributed clinical data research networks, and other partner organizations ( Haendel et al., 2021 ; NCATS, 2021 ; CNDH, 2021 ). Born from the urgency to understand COVID-19, the N3C endeavors to improve the accessibility and efficiency of a large COVID-19 clinical data set while demonstrating a novel approach to sharing patient-level data and enabling individual researchers to use the data for approved projects. When COVID-19 emerged, CD2H leaders had been working on the harmonization of different common data models (see Box 2 ) already in use by the research community ( Weeks and Pardee, 2019 ). The pandemic galvanized the CTSA community, and the N3C leadership accelerated progress toward the launch of a cloud-based consortium for aggregating institution-level data in a research enclave. Leaders’ deep familiarity with collaboration challenges—including expedient human subjects review, aligned incentives for sharing, governance, and data privacy/ security requirements—enabled them to quickly gain cooperation from research collaborators, the cloud computing host, funding agency, and journal editors. The result is an active partnership and dynamic data enclave containing data for more than 3.2 million COVID-positive cases, and approximately 9.3 million patients as of November 2021. The N3C publications and data insights also continue to grow rapidly.

Common Data Models: Definition and Applied Example.

Case Study at-a-Glance: National COVID Cohort Collaborative.

The N3C is anchored by its data enclave, a secure, cloud-based platform housing individual-level clinical data from its contributing partners (all based in the U.S.). Partner organizations, such as the National Patient-Centered Clinical Research Network (PCORnet®) and TriNetX, provide access to structured data from electronic health records (EHRs) across the country that can be queried to answer questions related to COVID-19. The N3C developed a comprehensive list of demographic and clinical data elements to create a research registry of patients who have been tested for or diagnosed with COVID-19, augmented with data on treatment and outcomes. Data are mapped to the Observational Medical Outcomes Partnership (OMOP) Common Data Model ( Haendel et al., 2021 ). Researchers identify questions of mutual interest via meetings and during weekly presentation forums and can form dedicated workstreams based on collective expertise. The N3C website provides detailed information about various domain teams that have organized to address particular topics, including how to participate via Slack channels and other forums ( N3C, 2021a ). Potential collaborators have access to onboarding documents, descriptions of domain teams, and other resources. This team science approach leverages complementary capabilities and domain expertise in disciplines such as informatics, epidemiology, biostatistics, data science, and a range of clinical specialties (e.g., cardiology, pulmonology, nephrology, neurology), which is particularly important given the progress in understanding COVID-19 as an illness with varying short- and long-term effects on different organ systems. The enclave is notable for its dynamic nature; data partners contribute new patient records an average of twice per week. Updates on the refreshed data are made available on N3C’s website and the National Institutes of Health (NIH) website. Nonetheless, the enclave is dependent on the availability of “local” data and documentation in EHRs and/or claims data, which may be incomplete or inconsistent from one health system to the next.

• DESCRIPTION

Access to the N3C data enclave leverages best practices in collaborative data stewardship, privacy, and security, including institutional- and user-level permissions, two-factor authentication, compliance with all federal provisions for protecting data (e.g., Federal Information Security Management Act, HIPAA), and review of the nature and appropriateness of a given data request ( Haendel et al., 2021 ). This is balanced by measures that enhance efficiency, namely the creation of a single institutional review board (IRB) to review all requests to query the N3C research data. Details regarding the protocol approved by the Johns Hopkins University IRB are publicly available, as are the extensive data specifications and software tools for data visualization and constructing efficient queries. In addition to creating a limited dataset and de-identified dataset, a subgroup of N3C researchers have developed a unique synthetic dataset, comprised of data that are computationally derived from the limited dataset and resemble patient information statistically, but are not actual patient data.

The data use request process for the N3C data enclave (as of April 2021) is briefly outlined here ( N3C, 2021b ). The requirements support data security, consistency, and continual reinforcement of the trust fabric across N3C, and are consistent across the limited, de-identified, and synthetic datasets, except as noted below.

• An institution-level data use agreement (DUA) must be executed as a prerequisite.
• Users must have completed required training in NIH information security and protection of human participants.
• Users register for an account to access the enclave, verifying that they have a tool in place to complete two-factor authentication in order to access data.
• Users then complete a data use request form, specifying the nature and scope of the research question and justifying the level of detail needed in the data.
• Users supply documentation of IRB approval as part of the data use request process for limited and de-identified data (not applicable for the synthetic dataset).
• A Data Access Committee reviews and approves or declines each request. Approved requests are valid for one year, and training/support is provided as needed.

Tools to support cohort exploration, including data views and analyses of de-identified data, are offered to CTSA researchers as well as citizen scientists, upholding the N3C’s intent to maximize transparency and inclusivity, while preserving privacy and security.

Overall stewardship is provided by NIH’s National Center for Advancing Translational Sciences (NCATS), which funds the N3C ( Bennett et al., 2021 ). A Steering Committee approves activities and assures alignment of working groups, committees, and cores with the overall N3C goals. Much of the governance is focused on the data enclave, as described above. Primary governance documents include the Attribution and Publication Guidelines, the Community Guiding Principles, and the User Code of Conduct. This approach balances scientific autonomy with the creation of an open, respectful environment that encourages collaboration on this extraordinary health challenge. For instance, the Community Guiding Principles are partnership, inclusivity, transparency, reciprocity, accountability, and security.

While the N3C was an offshoot of the CTSA, a longstanding initiative that emphasizes collaboration, building the will for the N3C’s creation was not automatic. Recognizing the need to garner rapid cooperation in a team science environment, leaders of N3C sought to identify champions from the CTSA hubs, the funding agency, and other community affiliates who could serve as ambassadors for the importance of this work. In addition, the N3C leaders did not stipulate that data users had to also be data contributors. This was an important aspect of gaining buy-in, as was the early and explicit plan to recognize all contributors as manuscript authors. In many academic institutions, participation on a publication is a key type of “currency” that supports promotion and tenure and may be particularly significant for early career investigators. Thus, N3C balances the goals of a very large team science consortium and the needs and values of individual investigators in academia. The leadership recognized the recurring tension in academia regarding research productivity and aims to produce high impact papers that recognizes all of the contributors. To this end, a consortium authorship model was developed to address the objective of recognizing the vast number of contributors to any given N3C paper.

The CTSA program is a prominent and prestigious feature for many academic institutions. The ability to foster both intra- and inter-institutional collaboration has been a hallmark of the CTSAs for more than two decades and has helped launch careers in clinical and translational science for hundreds of scientists. Nonetheless, in the interviews that informed this case study, N3C leaders describe this as a “social engineering experiment,” in that it engenders a new level of openness and data sharing. The complexity of COVID-19 has helped collaborators recognize the importance of a diverse team with specialized expertise that could range from acute kidney injury to the Python programming language to pharmacokinetics. This team science approach is also intended to foster higher caliber research outputs, in that strong multidisciplinary teams and high-quality data can yield higher impact papers in leading journals. Participants in the N3C are encouraged to get involved via a prominent link on the N3C home page, either by joining existing collaborative groups listed on the N3C website, or self-organizing around topics of interest to create new “domain teams,” which could range from a specific clinical topic (COVID-19 outcomes among people with diabetes) to increasingly broad and cross-cutting issues (impact of the pandemic in rural communities, or genomics and COVID-19). This rapid growth presented early challenges, especially in resource management and communication.

A unique challenge early in the N3C’s formation was developing the DUA between the NIH and the contributing institutions. The research data reside on a platform funded by the NIH, and the N3C itself is not a formal legal entity—simply a funded project. As such, NCATS is the fiduciary agent, holding the data and operating in accord with pertinent federal rules. Consequently, the Data Access Committee is composed exclusively of federal officials; N3C community members cannot participate. Progress and successful execution of the DUA was facilitated by the urgent need for this research platform, and a strong partnership between the NIH and NCATS leadership and the principal investigators of the CD2H initiative (which incubated the N3C). A related challenge was establishing a single IRB for the N3C. Johns Hopkins assumed that responsibility, and the logistics of linking other IRBs and applications was greatly eased by the SmartIRB infrastructure (smartirb. org). This obviated the need for each data-contributing organization to write, submit, and review its own IRB application, instead ceding this regulatory requirement to a central IRB.

In the progenitor publication, Health Data Sharing to Support Better Health Outcomes: Building a Foundation of Stakeholder Trust, barriers cited by researchers and research oversight leaders centered on pace, process, and price of accessing data; data latency; and variability of IRB requirements. The urgency of the pandemic spurred partners to organize quickly and address issues related to rapid availability of high-quality, curated data as well as research oversight needs. In the time since the N3C leaders were interviewed, N3C has grown to 31 domain teams and contains data from more than 9.3 million patients, including more than 3.2 million COVID-19 cases. Nearly 200 institutions have signed a Data Transfer Agreement, signaling their willingness to contribute data to the enclave once it is harmonized to the Common Data Model. While the data enclave is the centerpiece, the N3C architects also describe it as “a collaborative research community committed to the rapid generation and dissemination of knowledge for the public good, and to the advancement of COVID-19 science.”

• FUTURE DIRECTIONS

Team science can offer an uneven value proposition, insofar as large, complex consortia can become unwieldy or bureaucratic and can present political or communication-related challenges. The N3C leaders noted that one of their goals was to show that building something of this magnitude can be done rapidly and without significant friction. Though it took a pandemic to attenuate many of the traditional “pain points” in research (variable interpretations of the same protocol by multiple IRBs, lag time to attain research-ready data), it has also shown that science can move much faster and have a more immediate impact on health care. It will be critical to hold the gains in this regard, preserving both efficiency and data quality in collaborative research without reverting to pre-pandemic “business as usual” practices that could slow overall progress. Results from N3C studies will inform how COVID-19 is treated in both the short- and long-term ( Bennett et al., 2021 ). The progress of the N3C to date demonstrates that both the philosophical and technical milestones of this initiative can serve as a blueprint for accelerating research, as well as implementation of findings in clinical practice.

• Cite this Page National Academy of Medicine; The Learning Health System Series; Grossmann C, Chua PS, Ahmed M, et al., editors. Sharing Health Data: The Why, the Will, and the Way Forward. Washington (DC): National Academies Press (US); 2022. 6, CASE STUDY: THE NATIONAL COVID COHORT COLLABORATIVE (N3C)
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Case studies & examples

Articles, use cases, and proof points describing projects undertaken by data managers and data practitioners across the federal government

Agencies Mobilize to Improve Emergency Response in Puerto Rico through Better Data

Federal agencies' response efforts to Hurricanes Irma and Maria in Puerto Rico was hampered by imperfect address data for the island. In the aftermath, emergency responders gathered together to enhance the utility of Puerto Rico address data and share best practices for using what information is currently available.

Federal Data Strategy

BUILDER: A Science-Based Approach to Infrastructure Management

The Department of Energy’s National Nuclear Security Administration (NNSA) adopted a data-driven, risk-informed strategy to better assess risks, prioritize investments, and cost effectively modernize its aging nuclear infrastructure. NNSA’s new strategy, and lessons learned during its implementation, will help inform other federal data practitioners’ efforts to maintain facility-level information while enabling accurate and timely enterprise-wide infrastructure analysis.

Department of Energy

data management , data analysis , process redesign , Federal Data Strategy

Business case for open data

Six reasons why making your agency's data open and accessible is a good business decision.

CDO Council Federal HR Dashboarding Report - 2021

The CDO Council worked with the US Department of Agriculture, the Department of the Treasury, the United States Agency for International Development, and the Department of Transportation to develop a Diversity Profile Dashboard and to explore the value of shared HR decision support across agencies. The pilot was a success, and identified potential impact of a standardized suite of HR dashboards, in addition to demonstrating the value of collaborative analytics between agencies.

Federal Chief Data Officer's Council

data practices , data sharing , data access

CDOC Data Inventory Report

The Chief Data Officers Council Data Inventory Working Group developed this paper to highlight the value proposition for data inventories and describe challenges agencies may face when implementing and managing comprehensive data inventories. It identifies opportunities agencies can take to overcome some of these challenges and includes a set of recommendations directed at Agencies, OMB, and the CDO Council (CDOC).

data practices , metadata , data inventory

DSWG Recommendations and Findings

The Chief Data Officer Council (CDOC) established a Data Sharing Working Group (DSWG) to help the council understand the varied data-sharing needs and challenges of all agencies across the Federal Government. The DSWG reviewed data-sharing across federal agencies and developed a set of recommendations for improving the methods to access and share data within and between agencies. This report presents the findings of the DSWG’s review and provides recommendations to the CDOC Executive Committee.

data practices , data agreements , data sharing , data access

Data Skills Training Program Implementation Toolkit

The Data Skills Training Program Implementation Toolkit is designed to provide both small and large agencies with information to develop their own data skills training programs. The information provided will serve as a roadmap to the design, implementation, and administration of federal data skills training programs as agencies address their Federal Data Strategy’s Agency Action 4 gap-closing strategy training component.

data sharing , Federal Data Strategy

Data Standdown: Interrupting process to fix information

Although not a true pause in operations, ONR’s data standdown made data quality and data consolidation the top priority for the entire organization. It aimed to establish an automated and repeatable solution to enable a more holistic view of ONR investments and activities, and to increase transparency and effectiveness throughout its mission support functions. In addition, it demonstrated that getting top-level buy-in from management to prioritize data can truly advance a more data-driven culture.

Office of Naval Research

data governance , data cleaning , process redesign , Federal Data Strategy

Data.gov Metadata Management Services Product-Preliminary Plan

Status summary and preliminary business plan for a potential metadata management product under development by the Data.gov Program Management Office

data management , Federal Data Strategy , metadata , open data

PDF (7 pages)

Department of Transportation Case Study: Enterprise Data Inventory

In response to the Open Government Directive, DOT developed a strategic action plan to inventory and release high-value information through the Data.gov portal. The Department sustained efforts in building its data inventory, responding to the President’s memorandum on regulatory compliance with a comprehensive plan that was recognized as a model for other agencies to follow.

Department of Transportation

data inventory , open data

Department of Transportation Model Data Inventory Approach

This document from the Department of Transportation provides a model plan for conducting data inventory efforts required under OMB Memorandum M-13-13.

data inventory

PDF (5 pages)

FEMA Case Study: Disaster Assistance Program Coordination

In 2008, the Disaster Assistance Improvement Program (DAIP), an E-Government initiative led by FEMA with support from 16 U.S. Government partners, launched DisasterAssistance.gov to simplify the process for disaster survivors to identify and apply for disaster assistance. DAIP utilized existing partner technologies and implemented a services oriented architecture (SOA) that integrated the content management system and rules engine supporting Department of Labor’s Benefits.gov applications with FEMA’s Individual Assistance Center application. The FEMA SOA serves as the backbone for data sharing interfaces with three of DAIP’s federal partners and transfers application data to reduce duplicate data entry by disaster survivors.

Federal Emergency Management Agency

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Federal CDO Data Skills Training Program Case Studies

This series was developed by the Chief Data Officer Council’s Data Skills & Workforce Development Working Group to provide support to agencies in implementing the Federal Data Strategy’s Agency Action 4 gap-closing strategy training component in FY21.

FederalRegister.gov API Case Study

This case study describes the tenets behind an API that provides access to all data found on FederalRegister.gov, including all Federal Register documents from 1994 to the present.

National Archives and Records Administration

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Fuels Knowledge Graph Project

The Fuels Knowledge Graph Project (FKGP), funded through the Federal Chief Data Officers (CDO) Council, explored the use of knowledge graphs to achieve more consistent and reliable fuel management performance measures. The team hypothesized that better performance measures and an interoperable semantic framework could enhance the ability to understand wildfires and, ultimately, improve outcomes. To develop a more systematic and robust characterization of program outcomes, the FKGP team compiled, reviewed, and analyzed multiple agency glossaries and data sources. The team examined the relationships between them, while documenting the data management necessary for a successful fuels management program.

metadata , data sharing , data access

Government Data Hubs

A list of Federal agency open data hubs, including USDA, HHS, NASA, and many others.

Helping Baltimore Volunteers Find Where to Help

Bloomberg Government analysts put together a prototype through the Census Bureau’s Opportunity Project to better assess where volunteers should direct litter-clearing efforts. Using Census Bureau and Forest Service information, the team brought a data-driven approach to their work. Their experience reveals how individuals with data expertise can identify a real-world problem that data can help solve, navigate across agencies to find and obtain the most useful data, and work within resource constraints to provide a tool to help address the problem.

Census Bureau

geospatial , data sharing , Federal Data Strategy

How USDA Linked Federal and Commercial Data to Shed Light on the Nutritional Value of Retail Food Sales

Purchase-to-Plate Crosswalk (PPC) links the more than 359,000 food products in a comercial company database to several thousand foods in a series of USDA nutrition databases. By linking existing data resources, USDA was able to enrich and expand the analysis capabilities of both datasets. Since there were no common identifiers between the two data structures, the team used probabilistic and semantic methods to reduce the manual effort required to link the data.

Department of Agriculture

data sharing , process redesign , Federal Data Strategy

How to Blend Your Data: BEA and BLS Harness Big Data to Gain New Insights about Foreign Direct Investment in the U.S.

A recent collaboration between the Bureau of Economic Analysis (BEA) and the Bureau of Labor Statistics (BLS) helps shed light on the segment of the American workforce employed by foreign multinational companies. This case study shows the opportunities of cross-agency data collaboration, as well as some of the challenges of using big data and administrative data in the federal government.

Bureau of Economic Analysis / Bureau of Labor Statistics

data sharing , workforce development , process redesign , Federal Data Strategy

Implementing Federal-Wide Comment Analysis Tools

The CDO Council Comment Analysis pilot has shown that recent advances in Natural Language Processing (NLP) can effectively aid the regulatory comment analysis process. The proof-ofconcept is a standardized toolset intended to support agencies and staff in reviewing and responding to the millions of public comments received each year across government.

Improving Data Access and Data Management: Artificial Intelligence-Generated Metadata Tags at NASA

NASA’s data scientists and research content managers recently built an automated tagging system using machine learning and natural language processing. This system serves as an example of how other agencies can use their own unstructured data to improve information accessibility and promote data reuse.

National Aeronautics and Space Administration

metadata , data management , data sharing , process redesign , Federal Data Strategy

Investing in Learning with the Data Stewardship Tactical Working Group at DHS

The Department of Homeland Security (DHS) experience forming the Data Stewardship Tactical Working Group (DSTWG) provides meaningful insights for those who want to address data-related challenges collaboratively and successfully in their own agencies.

Department of Homeland Security

data governance , data management , Federal Data Strategy

Leveraging AI for Business Process Automation at NIH

The National Institute of General Medical Sciences (NIGMS), one of the twenty-seven institutes and centers at the NIH, recently deployed Natural Language Processing (NLP) and Machine Learning (ML) to automate the process by which it receives and internally refers grant applications. This new approach ensures efficient and consistent grant application referral, and liberates Program Managers from the labor-intensive and monotonous referral process.

National Institutes of Health

standards , data cleaning , process redesign , AI

FDS Proof Point

National Broadband Map: A Case Study on Open Innovation for National Policy

The National Broadband Map is a tool that provide consumers nationwide reliable information on broadband internet connections. This case study describes how crowd-sourcing, open source software, and public engagement informs the development of a tool that promotes government transparency.

Federal Communications Commission

National Renewable Energy Laboratory API Case Study

This case study describes the launch of the National Renewable Energy Laboratory (NREL) Developer Network in October 2011. The main goal was to build an overarching platform to make it easier for the public to use NREL APIs and for NREL to produce APIs.

National Renewable Energy Laboratory

Open Energy Data at DOE

This case study details the development of the renewable energy applications built on the Open Energy Information (OpenEI) platform, sponsored by the Department of Energy (DOE) and implemented by the National Renewable Energy Laboratory (NREL).

open data , data sharing , Federal Data Strategy

Pairing Government Data with Private-Sector Ingenuity to Take on Unwanted Calls

The Federal Trade Commission (FTC) releases data from millions of consumer complaints about unwanted calls to help fuel a myriad of private-sector solutions to tackle the problem. The FTC’s work serves as an example of how agencies can work with the private sector to encourage the innovative use of government data toward solutions that benefit the public.

Federal Trade Commission

data cleaning , Federal Data Strategy , open data , data sharing

Profile in Data Sharing - National Electronic Interstate Compact Enterprise

The Federal CDO Council’s Data Sharing Working Group highlights successful data sharing activities to recognize mature data sharing practices as well as to incentivize and inspire others to take part in similar collaborations. This Profile in Data Sharing focuses on how the federal government and states support children who are being placed for adoption or foster care across state lines. It greatly reduces the work and time required for states to exchange paperwork and information needed to process the placements. Additionally, NEICE allows child welfare workers to communicate and provide timely updates to courts, relevant private service providers, and families.

Profile in Data Sharing - National Health Service Corps Loan Repayment Programs

The Federal CDO Council’s Data Sharing Working Group highlights successful data sharing activities to recognize mature data sharing practices as well as to incentivize and inspire others to take part in similar collaborations. This Profile in Data Sharing focuses on how the Health Resources and Services Administration collaborates with the Department of Education to make it easier to apply to serve medically underserved communities - reducing applicant burden and improving processing efficiency.

Profile in Data Sharing - Roadside Inspection Data

The Federal CDO Council’s Data Sharing Working Group highlights successful data sharing activities to recognize mature data sharing practices as well as to incentivize and inspire others to take part in similar collaborations. This Profile in Data Sharing focuses on how the Department of Transportation collaborates with the Customs and Border Patrol and state partners to prescreen commercial motor vehicles entering the US and to focus inspections on unsafe carriers and drivers.

Profiles in Data Sharing - U.S. Citizenship and Immigration Service

The Federal CDO Council’s Data Sharing Working Group highlights successful data sharing activities to recognize mature data sharing practices as well as to incentivize and inspire others to take part in similar collaborations. This Profile in Data Sharing focuses on how the U.S. Citizenship and Immigration Service (USCIS) collaborated with the Centers for Disease Control to notify state, local, tribal, and territorial public health authorities so they can connect with individuals in their communities about their potential exposure.

SBA’s Approach to Identifying Data, Using a Learning Agenda, and Leveraging Partnerships to Build its Evidence Base

Through its Enterprise Learning Agenda, Small Business Administration’s (SBA) staff identify essential research questions, a plan to answer them, and how data held outside the agency can help provide further insights. Other agencies can learn from the innovative ways SBA identifies data to answer agency strategic questions and adopt those aspects that work for their own needs.

Small Business Administration

process redesign , Federal Data Strategy

Supercharging Data through Validation as a Service

USDA's Food and Nutrition Service restructured its approach to data validation at the state level using an open-source, API-based validation service managed at the federal level.

data cleaning , data validation , API , data sharing , process redesign , Federal Data Strategy

The Census Bureau Uses Its Own Data to Increase Response Rates, Helps Communities and Other Stakeholders Do the Same

The Census Bureau team produced a new interactive mapping tool in early 2018 called the Response Outreach Area Mapper (ROAM), an application that resulted in wider use of authoritative Census Bureau data, not only to improve the Census Bureau’s own operational efficiency, but also for use by tribal, state, and local governments, national and local partners, and other community groups. Other agency data practitioners can learn from the Census Bureau team’s experience communicating technical needs to non-technical executives, building analysis tools with widely-used software, and integrating efforts with stakeholders and users.

open data , data sharing , data management , data analysis , Federal Data Strategy

The Mapping Medicare Disparities Tool

The Centers for Medicare & Medicaid Services’ Office of Minority Health (CMS OMH) Mapping Medicare Disparities Tool harnessed the power of millions of data records while protecting the privacy of individuals, creating an easy-to-use tool to better understand health disparities.

Centers for Medicare & Medicaid Services

geospatial , Federal Data Strategy , open data

The Veterans Legacy Memorial

The Veterans Legacy Memorial (VLM) is a digital platform to help families, survivors, and fellow veterans to take a leading role in honoring their beloved veteran. Built on millions of existing National Cemetery Administration (NCA) records in a 25-year-old database, VLM is a powerful example of an agency harnessing the potential of a legacy system to provide a modernized service that better serves the public.

Veterans Administration

data sharing , data visualization , Federal Data Strategy

Transitioning to a Data Driven Culture at CMS

This case study describes how CMS announced the creation of the Office of Information Products and Data Analytics (OIPDA) to take the lead in making data use and dissemination a core function of the agency.

data management , data sharing , data analysis , data analytics

PDF (10 pages)

U.S. Department of Labor Case Study: Software Development Kits

The U.S. Department of Labor sought to go beyond merely making data available to developers and take ease of use of the data to the next level by giving developers tools that would make using DOL’s data easier. DOL created software development kits (SDKs), which are downloadable code packages that developers can drop into their apps, making access to DOL’s data easy for even the most novice developer. These SDKs have even been published as open source projects with the aim of speeding up their conversion to SDKs that will eventually support all federal APIs.

Department of Labor

open data , API

U.S. Geological Survey and U.S. Census Bureau collaborate on national roads and boundaries data

It is a well-kept secret that the U.S. Geological Survey and the U.S. Census Bureau were the original two federal agencies to build the first national digital database of roads and boundaries in the United States. The agencies joined forces to develop homegrown computer software and state of the art technologies to convert existing USGS topographic maps of the nation to the points, lines, and polygons that fueled early GIS. Today, the USGS and Census Bureau have a longstanding goal to leverage and use roads and authoritative boundary datasets.

U.S. Geological Survey and U.S. Census Bureau

data management , data sharing , data standards , data validation , data visualization , Federal Data Strategy , geospatial , open data , quality

USA.gov Uses Human-Centered Design to Roll Out AI Chatbot

To improve customer service and give better answers to users of the USA.gov website, the Technology Transformation and Services team at General Services Administration (GSA) created a chatbot using artificial intelligence (AI) and automation.

General Services Administration

AI , Federal Data Strategy

resources.data.gov

An official website of the Office of Management and Budget, the General Services Administration, and the Office of Government Information Services.

This section contains explanations of common terms referenced on resources.data.gov.

Research Writing and Analysis

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Writing a Case Study

What is a case study?

A Case study is: 

• An in-depth research design that primarily uses a qualitative methodology but sometimes​​ includes quantitative methodology.
• Used to examine an identifiable problem confirmed through research.
• Used to investigate an individual, group of people, organization, or event.
• Used to mostly answer "how" and "why" questions.

What are the different types of case studies?

Note: These are the primary case studies. As you continue to research and learn

about case studies you will begin to find a robust list of different types. 

Who are your case study participants?

What is triangulation ? 

Validity and credibility are an essential part of the case study. Therefore, the researcher should include triangulation to ensure trustworthiness while accurately reflecting what the researcher seeks to investigate.

How to write a Case Study?

When developing a case study, there are different ways you could present the information, but remember to include the five parts for your case study.

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... or start browsing by, country crime type cross-cutting issues, afghanistan, antigua and barbuda 2, argentina 106, australia 235, azerbaijan 17, bangladesh 2, bolivia (plurinational state of) 7, bosnia and herzegovina 36, brunei darussalam 2, bulgaria 11, burkina faso, cambodia 12, central african republic, colombia 53, cook islands*, costa rica 9, côte d'ivoire, democratic people's republic of korea, democratic republic of the congo, dominican republic 11, east africa, el salvador 37, equatorial guinea, european union 11, guatemala 8, guinea-bissau, honduras 21, indian ocean, indonesia 31, international and regional bodies 27, iran (islamic republic of) 1, kazakhstan 5, kyrgyzstan 1, lao people's democratic republic, liechtenstein, lithuania 6, luxembourg 4, marshall islands 1, mauritius 4, micronesia (federated states of) 3, montenegro 20, mozambique 3, netherlands (kingdom of the) 16, new zealand 18, nicaragua 6, north macedonia 41, papua new guinea 3, philippines 96, portugal 11, republic of korea 5, republic of moldova 66, russian federation 13, saint kitts and nevis, saint lucia, saint vincent and the grenadines, sao tome and principe, saudi arabia 1, seychelles 11, sierra leone 1, singapore 21, slovakia 49, solomon islands 2, south africa 41, south america, south sudan, sri lanka 1, state of palestine*, switzerland 31, syrian arab republic, tajikistan 5, thailand 15, timor - leste, trinidad and tobago, turkmenistan, united arab emirates 2, united kingdom of great britain and northern ireland 155, united republic of tanzania 2, united states of america 473, uzbekistan 4, venezuela (bolivarian republic of) 2, west africa, * please see  disclaimer, counterfeiting, drug offences, money laundering, obstruction of justice, participation in an organized criminal group, piracy and maritime crime, smuggling of migrants, trafficking in firearms, trafficking in cultural property, crimes that affect the environment, falsified medical products, trafficking in persons,    offending.

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   Investigation Procedure

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   Victims

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   Electronic Evidence

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   Human rights

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   Coordination

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National Case Study Competition  

20th january -  27th january '24  , national celebration of academic and intellectual accomplishment, as guided by nep 2020..

Asia's First High-School Student Case Competition

"The power of education extends beyond the development of skills we need for economic success. It can contribute to nation-building and reconciliation."

-Nelson Mandela

National Case Study Competition

The National Case Study competition presented by ICG, Powered by Tads Education is one of the most upcoming case study competitions. We aim to bring together students of all courses throughout India and Nepal and offer them fantastic opportunities: to meet like minded students, leading schools and renowned guests. For the First edition of the competition , all participants will have the opportunity to network with the top schools of India and Nepal . The competition is a unique opportunity connecting smartest academics from around the country. A case study is an in-depth investigation and evaluation of a particular topic, circumstance, or person within a predetermined amount of time. It entails conducting in-depth study and analysis on a certain case or situation in order to comprehend its intricacies, difficulties, solutions, and results. Teams or individuals analyze a real or imaginary business scenario or challenge within a particular sector or field as part of a national case study competition. The participants have to give a panel of judges their analysis, suggestions, and solutions in a condensed amount of time.

IIT Kanpur Consulting Group

Established in 2018, IIT Kanpur Consulting Group is driven by the vision of using data science and case solving skills to help organizations leverage better insights from their data and thereby create a strong social impact. The group aims at leveraging the power of data science and Machine Learning to address societal issues. It also helps to explore the world of consulting with an aim to create a positive social impact.

100+ Schools

800+ students.

Our competition offers valuable rewards and recognition to the winners, including prestigious scholarships, cash prizes, and certificates endorsed by IIT Kanpur Consulting Group. These prizes aim to foster learning, academic growth, and professional development among our participants.

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• About Adverse Childhood Experiences
• Risk and Protective Factors
• Program: Essentials for Childhood: Preventing Adverse Childhood Experiences through Data to Action
• Adverse childhood experiences can have long-term impacts on health, opportunity and well-being.
• Adverse childhood experiences are common and some groups experience them more than others.

What are adverse childhood experiences?

Adverse childhood experiences, or ACEs, are potentially traumatic events that occur in childhood (0-17 years). Examples include: 1

• Experiencing violence, abuse, or neglect.
• Witnessing violence in the home or community.
• Having a family member attempt or die by suicide.

Also included are aspects of the child’s environment that can undermine their sense of safety, stability, and bonding. Examples can include growing up in a household with: 1

• Substance use problems.
• Mental health problems.
• Instability due to parental separation.
• Instability due to household members being in jail or prison.

The examples above are not a complete list of adverse experiences. Many other traumatic experiences could impact health and well-being. This can include not having enough food to eat, experiencing homelessness or unstable housing, or experiencing discrimination. 2 3 4 5 6

Quick facts and stats

ACEs are common. About 64% of adults in the United States reported they had experienced at least one type of ACE before age 18. Nearly one in six (17.3%) adults reported they had experienced four or more types of ACEs. 7

Preventing ACEs could potentially reduce many health conditions. Estimates show up to 1.9 million heart disease cases and 21 million depression cases potentially could have been avoided by preventing ACEs. 1

Some people are at greater risk of experiencing one or more ACEs than others. While all children are at risk of ACEs, numerous studies show inequities in such experiences. These inequalities are linked to the historical, social, and economic environments in which some families live. 5 6 ACEs were highest among females, non-Hispanic American Indian or Alaska Native adults, and adults who are unemployed or unable to work. 7

ACEs are costly. ACEs-related health consequences cost an estimated economic burden of $748 billion annually in Bermuda, Canada, and the United States. 8

ACEs can have lasting effects on health and well-being in childhood and life opportunities well into adulthood. 9 Life opportunities include things like education and job potential. These experiences can increase the risks of injury, sexually transmitted infections, and involvement in sex trafficking. They can also increase risks for maternal and child health problems including teen pregnancy, pregnancy complications, and fetal death. Also included are a range of chronic diseases and leading causes of death, such as cancer, diabetes, heart disease, and suicide. 1 10 11 12 13 14 15 16 17

ACEs and associated social determinants of health, such as living in under-resourced or racially segregated neighborhoods, can cause toxic stress. Toxic stress, or extended or prolonged stress, from ACEs can negatively affect children’s brain development, immune systems, and stress-response systems. These changes can affect children’s attention, decision-making, and learning. 18

Children growing up with toxic stress may have difficulty forming healthy and stable relationships. They may also have unstable work histories as adults and struggle with finances, jobs, and depression throughout life. 18 These effects can also be passed on to their own children. 19 20 21 Some children may face further exposure to toxic stress from historical and ongoing traumas. These historical and ongoing traumas refer to experiences of racial discrimination or the impacts of poverty resulting from limited educational and economic opportunities. 1 6

Adverse childhood experiences can be prevented. Certain factors may increase or decrease the risk of experiencing adverse childhood experiences.

Preventing adverse childhood experiences requires understanding and addressing the factors that put people at risk for or protect them from violence.

Creating safe, stable, nurturing relationships and environments for all children can prevent ACEs and help all children reach their full potential. We all have a role to play.

• Merrick MT, Ford DC, Ports KA, et al. Vital Signs: Estimated Proportion of Adult Health Problems Attributable to Adverse Childhood Experiences and Implications for Prevention — 25 States, 2015–2017. MMWR Morb Mortal Wkly Rep 2019;68:999-1005. DOI: http://dx.doi.org/10.15585/mmwr.mm6844e1 .
• Cain KS, Meyer SC, Cummer E, Patel KK, Casacchia NJ, Montez K, Palakshappa D, Brown CL. Association of Food Insecurity with Mental Health Outcomes in Parents and Children. Science Direct. 2022; 22:7; 1105-1114. DOI: https://doi.org/10.1016/j.acap.2022.04.010 .
• Smith-Grant J, Kilmer G, Brener N, Robin L, Underwood M. Risk Behaviors and Experiences Among Youth Experiencing Homelessness—Youth Risk Behavior Survey, 23 U.S. States and 11 Local School Districts. Journal of Community Health. 2022; 47: 324-333.
• Experiencing discrimination: Early Childhood Adversity, Toxic Stress, and the Impacts of Racism on the Foundations of Health | Annual Review of Public Health https://doi.org/10.1146/annurev-publhealth-090419-101940 .
• Sedlak A, Mettenburg J, Basena M, et al. Fourth national incidence study of child abuse and neglect (NIS-4): Report to Congress. Executive Summary. Washington, DC: U.S. Department of Health an Human Services, Administration for Children and Families.; 2010.
• Font S, Maguire-Jack K. Pathways from childhood abuse and other adversities to adult health risks: The role of adult socioeconomic conditions. Child Abuse Negl. 2016;51:390-399.
• Swedo EA, Aslam MV, Dahlberg LL, et al. Prevalence of Adverse Childhood Experiences Among U.S. Adults — Behavioral Risk Factor Surveillance System, 2011–2020. MMWR Morb Mortal Wkly Rep 2023;72:707–715. DOI: http://dx.doi.org/10.15585/mmwr.mm7226a2 .
• Bellis, MA, et al. Life Course Health Consequences and Associated Annual Costs of Adverse Childhood Experiences Across Europe and North America: A Systematic Review and Meta-Analysis. Lancet Public Health 2019.
• Adverse Childhood Experiences During the COVID-19 Pandemic and Associations with Poor Mental Health and Suicidal Behaviors Among High School Students — Adolescent Behaviors and Experiences Survey, United States, January–June 2021 | MMWR
• Hillis SD, Anda RF, Dube SR, Felitti VJ, Marchbanks PA, Marks JS. The association between adverse childhood experiences and adolescent pregnancy, long-term psychosocial consequences, and fetal death. Pediatrics. 2004 Feb;113(2):320-7.
• Miller ES, Fleming O, Ekpe EE, Grobman WA, Heard-Garris N. Association Between Adverse Childhood Experiences and Adverse Pregnancy Outcomes. Obstetrics & Gynecology . 2021;138(5):770-776. https://doi.org/10.1097/AOG.0000000000004570 .
• Sulaiman S, Premji SS, Tavangar F, et al. Total Adverse Childhood Experiences and Preterm Birth: A Systematic Review. Matern Child Health J . 2021;25(10):1581-1594. https://doi.org/10.1007/s10995-021-03176-6 .
• Ciciolla L, Shreffler KM, Tiemeyer S. Maternal Childhood Adversity as a Risk for Perinatal Complications and NICU Hospitalization. Journal of Pediatric Psychology . 2021;46(7):801-813. https://doi.org/10.1093/jpepsy/jsab027 .
• Mersky JP, Lee CP. Adverse childhood experiences and poor birth outcomes in a diverse, low-income sample. BMC pregnancy and childbirth. 2019;19(1). https://doi.org/10.1186/s12884-019-2560-8 .
• Reid JA, Baglivio MT, Piquero AR, Greenwald MA, Epps N. No youth left behind to human trafficking: Exploring profiles of risk. American journal of orthopsychiatry. 2019;89(6):704.
• Diamond-Welch B, Kosloski AE. Adverse childhood experiences and propensity to participate in the commercialized sex market. Child Abuse & Neglect. 2020 Jun 1;104:104468.
• Shonkoff, J. P., Garner, A. S., Committee on Psychosocial Aspects of Child and Family Health, Committee on Early Childhood, Adoption, and Dependent Care, & Section on Developmental and Behavioral Pediatrics (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), e232–e246. https://doi.org/10.1542/peds.2011-2663
• Narayan AJ, Kalstabakken AW, Labella MH, Nerenberg LS, Monn AR, Masten AS. Intergenerational continuity of adverse childhood experiences in homeless families: unpacking exposure to maltreatment versus family dysfunction. Am J Orthopsych. 2017;87(1):3. https://doi.org/10.1037/ort0000133 .
• Schofield TJ, Donnellan MB, Merrick MT, Ports KA, Klevens J, Leeb R. Intergenerational continuity in adverse childhood experiences and rural community environments. Am J Public Health. 2018;108(9):1148-1152. https://doi.org/10.2105/AJPH.2018.304598 .
• Schofield TJ, Lee RD, Merrick MT. Safe, stable, nurturing relationships as a moderator of intergenerational continuity of child maltreatment: a meta-analysis. J Adolesc Health. 2013;53(4 Suppl):S32-38. https://doi.org/10.1016/j.jadohealth.2013.05.004 .

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Study Protocol

Protocol for a nationwide case-control study of firearm violence prevention tactics and policies in K-12 schools

Contributed equally to this work with: Navjot Buttar, Sonali Rajan, Charles C. Branas

Roles Data curation, Methodology, Project administration, Writing – original draft

* E-mail: [email protected]

Affiliation Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States of America

Roles Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Validation, Writing – original draft

Affiliations Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States of America, Department of Health Studies & Applied Educational Psychology, Teachers College, Columbia University, New York, NY, United States of America

Roles Conceptualization, Validation, Writing – review & editing

¶ ‡ These authors also contributed equally to this work.

Affiliation Department of Mathematics, Science and Technology, Teachers College, Columbia University, New York, NY, United States of America

Roles Methodology, Writing – review & editing

Affiliations Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States of America, Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States of America

Roles Conceptualization, Writing – review & editing

Affiliation Department of Health Behavior and Health Education, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America

Affiliation Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States of America

Affiliation Children’s National Hospital, Washington, DC, United States of America

Affiliations Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America, Institute for Firearm Injury Prevention, University of Michigan, Ann Arbor, MI, United States of America

• Navjot Buttar, 
• Sonali Rajan, 
• Louis Klarevas, 
• Seth J. Prins, 
• Justin Heinze, 
• Ken Cheung, 
• Kara E. Rudolph, 
• Monika Goyal, 
• April Zeoli, 
• Charles C. Branas

• Published: May 20, 2024
• https://doi.org/10.1371/journal.pone.0302622
• Reader Comments

Most U.S. K-12 schools have adopted safety tactics and policies like arming teachers and installing metal detectors, to address intentional school gun violence. However, there is minimal research on their effectiveness. Furthermore, sociodemographic factors may influence their implementation. Controlled studies are necessary to investigate their impact on gun violence and related disciplinary outcomes.

The paper outlines the protocol for a case-control study examining gun violence prevention policies in U.S. K-12 schools. The study aims to investigate if there is an association between the total number and type of specific safety tactics and policies and the occurrence of intentional shootings in K-12 public schools, student disciplinary outcomes, and if urbanicity, economic, and racial factors modify these associations.

We will create a nationally representative dataset for this study and ascertain a full census of case schools (schools that experienced intentional gunfire on the campus during school hours since 2015) through national school shooting databases. Matched control schools will be randomly selected from U.S. Department of Education’s national database of all public schools. We will analyze 27 school safety strategies organized into seven key exposure groupings.

Supported by the National Institutes for Child Health and Development (R01HD108027-01) and having received Institutional Review Board approval, our study is currently in the data collection phase. Our analytical plan will determine the association between the number and type of school safety tactics and policies with the occurrence of intentional shootings and suspensions and expulsions in a national sample of approximately 650 K-12 public schools. Additional analyses will investigate the effect modification of specific covariates.

As the first national, controlled study, its results will provide novel and needed data on the effectiveness of school safety tactics and policies in preventing intentional shootings at K-12 public schools.

Citation: Buttar N, Rajan S, Klarevas L, Prins SJ, Heinze J, Cheung K, et al. (2024) Protocol for a nationwide case-control study of firearm violence prevention tactics and policies in K-12 schools. PLoS ONE 19(5): e0302622. https://doi.org/10.1371/journal.pone.0302622

Editor: Johanna Pruller, PLOS: Public Library of Science, UNITED KINGDOM

Received: March 31, 2024; Accepted: April 5, 2024; Published: May 20, 2024

Copyright: © 2024 Buttar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: No datasets were generated or analysed during the current study. All relevant data from this study will be made available upon study completion.

Funding: "This work was funded by the National Institutes of Health (R01HD108027-01), funding awarded to CCB and SR.(reporter.nih.gov/search/RKpJsub6YEqsuJ0OSpG8JQ/project-details/10841282; https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nih.gov%2Finstitutes-nih&data=05%7C02%7Cnb2889%40cumc.columbia.edu%7C66fa099c0c4a4a13576508dc69f3a5f1%7Cb0002a9b0017404d97dc3d3bab09be81%7C0%7C0%7C638501742392070071%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=9GOY7zINcGmNoBIc%2BQxssQj0oQY7LfO00LJWnAa3rs8%3D&reserved=0 ) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Gun violence is currently the leading cause of death among children and teens in the US [ 1 , 2 ]. Gun violence in K-12 public schools around the US persists as a public health crisis. Over 357,000 students have been exposed to gun violence in K–12 schools since the Columbine High School shooting in Colorado in 1999. These numbers do not fully capture the impact of school shootings on children, teachers, and other school staff who may not have been directly injured by firearms but may have experienced indirect forms of gun violence such as witnessing a shooting. The nature of this kind of violence significantly impacts the well-being of entire school communities, with enormous consequences for children’s health, learning, and development [ 3 , 4 ].

In response to the persistence of this kind of violence, K-12 schools across the US are widely implementing numerous safety tactics and policies as a way to secure their buildings and prepare their communities for the possibility of gunfire on school grounds. However, the effectiveness of these security tactics and policies at deterring school shootings remains largely untested. Implementation of security measures, such as metal detectors, armed school staff, and zero-tolerance policies has significantly changed the daily school experience since Columbine [ 5 ]. In 1999, less than 20% of schools had security cameras; now more than 80% do [ 6 ]. Similarly, as of 2019, 96% of K-12 schools now conduct lockdown drills, compared with far fewer who implemented such procedures prior to the Sandy Hook school shooting in 2012 [ 7 ]. This is significant, as there are currently over 90,000 public K-12 schools across the nation, serving an estimated 51 million children. Unfortunately, there is limited and conflicting evidence surrounding these tactics and policies. Some studies show that more security measures in schools, such as metal detectors and armed guards, can result in students feeling less safe [ 8 – 10 ]. However, other work suggests that students feel safer with these policies [ 11 ]. Further, there is evidence that security measures have little effect [ 12 ]. Overall, studies evaluating school security policies have been inconclusive and inadequately designed with no comparator or control schools or student populations [ 13 , 14 ].

Thousands of instances of gunfire have occurred in US K–12 schools over the twenty years since the Columbine High School shooting [ 15 ]. However, following the Columbine shooting in 1999, the yearly incidence of school shootings remained relatively constant until a noticeable uptick beginning in 2015 [ 16 ]. Despite this recent increase, little comparative research has examined what specific safety tactics and policies work to prevent intentional shootings on K-12 school grounds [ 17 ]. Definitions of what counts as a “school shooting” currently range from an accidental discharge of a gun at school to injury or death of a student by a firearm. Although the prevention of accidental shootings or suicides are extremely important, our focus in this proposed study is on efforts aimed at the prevention of intentional shootings of other individuals in K-12 public schools, particularly since many existing school safety strategies have been designed specifically to prevent intentional, interpersonal gun violence.

K-12 school security

In response to the anticipation of school gun violence, millions of K-12 students now walk through airport-style security every day in the US [ 17 ]. The effectiveness of such measures is understudied, but some research suggests that visible security measures, such as metal detectors, cameras, and police officers, do not improve school safety or academic achievement and may increase student anxiety and stress [ 18 ]. For instance, metal detectors cannot distinguish between different objects made of metal and often require searches by security personnel questioning their effectiveness, while possibly heightening student anxiety [ 19 , 20 ]. Security measures may also exacerbate disparities in school discipline outcomes. Available research on active shooters in schools has been conducted via small sample case-series studies. While limited, this research suggests that commonalities exist across individuals who commit school shootings, such as having experiences with bullying, access to weapons, and poor social skills [ 21 , 22 ]. Research has also illustrated that school shooters are typically teenage, middle-class, White males, that live in suburbs and rural neighborhoods [ 23 ] and with parents that own firearms [ 24 ].

Despite these known demographics, “hardening” of schools through addition of armed guards, metal detectors, and zero-tolerance policies is more likely to occur in schools that are primarily serving minoritized students and in urban areas of lower socioeconomic status, even after accounting for violent crime rates [ 3 , 4 , 6 ]. Thus, schools appear to differentially employ security interventions and disciplinary action based on sociodemographic factors unrelated to school safety [ 25 – 27 ]. Critics have argued that this criminalizes students for minor misbehaviors, possibly provoking pathways into the criminal justice system, a phenomenon often described as the school-to-prison pipeline [ 28 – 30 ]. Some patterns of school security usage are associated with increased exposure to crime and violence at school [ 31 , 32 ] and misusage of security may have detrimental effects on academic outcomes [ 33 ]. Little research has been completed using readily available data on suspensions and expulsions, as indicators of student criminalization, across disparate school types. In this way, school securitization is part of a broader, poorly understood policy trend to manage, rather than repair, consequences of disinvestment, economic austerity, and unprecedented social inequality. Research on the effectiveness and unintended negative consequences of school safety interventions in a wide variety of communities is critical.

Prior methodological limitations

Prior studies of school safety tactics and school shootings have been case-series designs, i.e., only involving schools that have experienced shootings. This is a critical methodological shortcoming because there is no way to determine if the safety tactics and policies in question are protective with no comparison group of schools that have not experienced shootings (but that could have) and may have had many of the same safety tactics and policies in place at similar points in time. The present study is therefore employing a population-based, incidence density sampled case-control study of shootings in K–12 schools that includes a national group of schools that have experienced shootings and national comparator group of control schools that have not experienced a shooting.

Using this case-control study design, the study protocol has the following three specific aims and hypotheses,

• ○ Primary Aim 1 hypothesis—The total number of cumulative safety tactics and policies will be significantly associated with intentional school shootings.
• ○ Secondary Aim 1 hypothesis—When organized into three domains (physical target hardening, emergency response and technologies, and school security), the total number of safety tactics and policies within each domain will be significantly associated with intentional school shootings.
• ○ Primary Aim 2 hypothesis—The total number of cumulative safety tactics and policies will be significantly associated with student discipline outcomes.
• ○ Secondary Aim 2 hypothesis—When organized into three domains (physical target hardening, emergency response and technologies, and school security), the total number of safety tactics and policies within each domain will be significantly associated with student discipline outcomes.
• ○ Aim 3 Hypothesis: Significant urban/non-urban, economic, and racial disparities will modify the relationships between the implementation of safety tactics and policies, suspensions and expulsions, and intentional shootings in K-12 public schools.

Methodology

Sampling frame.

National data from a random sample of K-12 public schools around the US are being collected for this case-control study. Case schools are being ascertained through a comprehensive review of multiple national school shooting databases, including the K-12 School Shooting database, the Everytown for Gun Safety database on gunfire on school grounds, and the Washington Post database on school shootings, to identify all schools that have experienced an intentional gunfire against others on the campus during school hours. Control schools will be ascertained via random selection from the US department of Education’s national database on all K-12 schools and matched to case schools in 1:1 ratio. The full set of inclusion and exclusion criteria developed by the study team are included [ S1 File ].

Case school ascertainment.

We are primarily identifying all school shooting cases via the K-12 School Shooting database (SSDB), as these data detail “all incidents in which a gun is fired, or a bullet hits school property for any reason, regardless of the number of victims, time, day of the week” [ 34 ]. Two members of the research team have independently coded this list of incidents to identify the cases that meet the proposed study’s criteria for “intentional school shooting.” And a third member of the study team has reviewed any potential discrepancies in coding efforts. By the study’s completion, the list of cases will be a full, national census of schools that have experienced an intentional shooting on school property, during school hours (including one hour prior to official school activities starting and one hour after all official school activities end) beginning January 1, 2015. The study will exclude accidental discharges and attempted suicides where no other person was targeted or shot. It will also exclude any incidents taking place on a school bus or on school property that is non-contiguous with the school’s primary campus. This list of intentional school shootings meeting the study criteria will be cross-referenced via secondary inspection and inclusion of case data from a series of additional databases that also record and publicly report school shooting incidents, including the Washington Post school shooting incident database and the Everytown for Gun Safety list of gunfire on school ground. These databases are being linked and harmonized to detail all school shooting incidents by the definition above, from January 1, 2015 –December 31, 2023.

Control school ascertainment.

Control schools are a randomly selected national sample of schools that have not experienced a shooting, by the definition described above and within the same time frame (1/1/2015–12/31/2023). Control schools are being obtained via random selection from a national database of public K-12 schools via the U.S. Department of Education’s National Center for Education Statistics (NCES). For each case school, one control school is being chosen as part of a stratified random sample and matched to each case school based on their geographic state, urban/non-urban status, and elementary/middle/high school status. State and urban/non-urban status will be determined using each school’s address and standard definitions of urbanicity taken from the NCES locale codes.

Data collection

Driven by preliminary study planning and statistical power calculations, the study protocol intends to collect data on an estimated 658 K–12 public schools (329 cases and 329 controls) across the US.

Independent variable—school safety strategies.

Data on school safety tactics and policies will be predominantly based on those listed in the School Survey on Crime and Safety (SSOCS); a national survey that is administered via the US Department of Education’s NCES to a representative sample of public schools every two years to assess a range of school safety and security interventions, among other indicators of school violence and school violence prevention. Drawing on this survey and also on the existing literature, our study team has identified a comprehensive set of 27 different school safety tactics and policies, which have been further grouped into seven categories ( S2 File ). Each school’s safety plan, their student handbook, their code of conduct, their school improvement plan, and/or the school’s facilities information, satellite and Google Street View images, and additional publicly available secondary data sources will be used to identify the specific security tactics and policies in place at both case and control schools during the school year before each pair-matched case school’s shooting event.

It should be noted that public school safety plans are comprehensive documents developed by school leaders that detail preparation and response protocols for a range of possible school situations and emergencies included in the proposed study. Data on school safety strategies are being obtained from each school’s publicly available written school safety plan or handbook online at local school district websites. In the case that a given school’s safety plan is not available online, the research team is emailing the superintendents of the school district directly to inquire if they are able to provide a copy of that specific school’s safety plan for the purposes of this study and in line with the study’s IRB protocol.

Furthermore, in completing the specific aims that address the impact of school safety tactics and policies at different points in time, we are obtaining school safety plans with valid timestamps of the years they went into effect, including the year of a case school shooting. To obtain complete safety information for each school in the study, researchers are triangulating the data obtained via the school safety plans with other reliable and date-stamped sources of data. Using the Google Street View “time machine” feature to obtain images of schools in the index year of each shooting, street-level and satellite imagery data are also being audited to confirm whether external structures of schools have illuminated school entry doors, external barriers, bollards or buffer zones, and/or external security cameras.

Publicly available school suspensions and expulsions data.

Using Local Education Agency codes for each case and control school obtained from the NCES, annual data on suspensions and expulsions, percentage of discipline outcomes tied directly to zero-tolerance policies, and the frequency of interactions between schools and local law enforcement will be directly downloaded from the Civil Rights Data Collection Website where data is available for all K-12 schools [ 35 ]. These data for each case and control school will be linked and used to comprise a “school discipline” summative score that includes the following indicators (accounting for school population size): number of in-school suspensions, out-of-school suspensions, and student expulsions. Other data (e.g., the number of students referred to law enforcement and number of school-related arrests) will also be collected from the Civil Rights Data Collection Website. Suspensions and expulsions are being considered as intervening outcomes stemming from both the implementation of school safety tactics and policies and the occurrence of shootings as a way to understand the role of student criminalization.

Other publicly available data on schools and their neighborhoods.

Other publicly available data specific to the study schools, their neighborhoods (measured as census tracts and block groups), and their states are also being collected specific to each year of the study period and linked to each school and their school safety and discipline outcome data. These independent covariates are being collected via multiple data sources at the NCES and via US Census data. They include key variables at the school level: political orientation (as measured by voting patterns data obtained from US Census Bureau’s county-level Voting and Registration estimates), policies mandated by state government and insurance regulators (e.g., schools designated as gun-free zones), urban/non-urban (determined using NCES locale codes), economic (determined using percentage of students in each school eligible for free and reduced price lunches as well as residents below the poverty threshold in the surrounding neighborhood), and race/ethnicity (measured as differences in each school as well as among residents in the surrounding neighborhood). Additional covariates specific to the proposed study’s schools and their surrounding neighborhoods will include school staffing characteristics, school budget, student academic performance, and the school’s physical plant (e.g., outdoor play areas, number of floors).

Protection of human subjects

The large majority of data collected in this study do not involve human subjects. Indeed, much of the data collected in this study are publicly available. In the case that a school’s safety plan for a specific academic year of interest is not available online, the study directors are emailing the district’s superintendent of the school directly to inquire if they would be willing to provide a copy of the safety plan for the purpose of this research study. As a result, the superintendent of every participating school district in this proposed work is eligible for participation, but no identifying or private information about the superintendents themselves will be recorded.

Approval for this study was obtained from the Columbia University Human Research Protection Office and Institutional Review Board in November 2021 (IRB protocol number: AAAT9087). The study was deemed exempt from the requirement of obtaining written or oral consent.

Data organization and management

Study design..

The case-control study design is a natural choice in accomplishing the aims proposed here given the relatively rare outcome of school shootings and the need to quantitatively test school safety tactics and policies by including a national comparator group of control schools that have not experienced shootings. In addition, other study designs, such as randomized controlled trials or cohort studies, would be unethical to conduct or would take infeasibly long periods of time to complete, thus underscoring the benefits of utilizing the case-control study design as described here.

Per the study’s Specific Aims, this study is examining associations between safety tactics/policies and various outcomes ( Fig 1 ). As described in Specific Aim 1, our research team is testing relationships between the total number and specific presence of 27 school safety tactics and policies using a case-control design to calculate the odds of intentional school shootings. In Specific Aim 2, we are testing the relationships between the total number and specific presence of 27 types of school safety tactics and policies and the occurrence of school suspensions and expulsions. Aims 1 and 2 are possible due to the temporal specificity of the data, as implementation of safety tactics/policies and occurrence of school shootings and suspensions/expulsions are date stamped.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0302622.g001

In addition, our research team is exploring whether implementation of school safety tactics and policies prompts the occurrence of school suspensions and expulsions, which may then potentially lead to the occurrence of later school shootings. Some school shooters had been previously expelled or had a history of being suspended. Certain security tactics/policies may increase suspensions/expulsions, which can then affect school shootings. Aim 3 further delineates these potential relationships in terms of urban/non-urban, economic, and racial subgroups. This final aim is key to understanding how various relationships among safety strategies, suspensions/expulsions, and shootings play out for different populations and where school districts and policymakers may best and most effectively focus their safety efforts.

Data analysis plan and study registration.

An estimated 658 K-12 public schools will be included in our study sample. The presence or absence (binary 0–1 variables) of each of the 27 safety tactics and policies in case and control schools before each case school’s shooting will be statistically tested as independent variables of interest. The number of safety tactics and policies that each school has in place (from 0–27) will be statistically tested as independent count variables. And the number of suspensions and expulsions that have occurred will also be statistically tested as a proportion of the number of students in each school. Specific safety tactics and policies found to have small numbers will also be combined into groupings of safety tactics and policies as per prior aggregated categories: external target hardening, internal target hardening, student/staff monitoring, emergency procedures/drills, emergency notification technologies, medical support, and school security staff.

Analyses will begin with descriptive statistics to characterize cases and controls relative to independent variables. Categorical and continuous variables will be explored using frequency distributions, means, medians, standard deviations, skewness coefficients, and ranges. Bivariable analyses of predictor variables for each outcome will consist of t -tests, Chi-squared tests, and nonparametric comparison tests. Collinear independent variables will be identified using Spearman coefficients, tolerance statistics, and condition indices. As this population-based case-control study will be matched on state, urban/non-urban, and elementary/middle/high school status, conditional logistic regression model specifications will be used. The first two aims will adjust for confounders that will be methodologically and theoretically justified. The third aim will include interaction analyses with select effect modifiers: urban/nonurban, economic, and racial disparities. Despite having matched on these variables, effect modification analyses with these variables are possible and commonly conducted in case-control studies. Disparities analyses will include adjustments for sparse data. Researchers will reasonably limit the final group of predictor variables to promote statistical efficiency and provide the best unbiased estimators.

Multiple testing in regression models will be handled by pre-specified variable selection procedures (Benjamini-Hochberg) to control false positive findings in terms of type I error rate and false discovery rate. Several regression models will be tested and compared using Wald statistics, and multiple testing adjustments and false discovery rates accounting for correlated conditions and dependency will also be used to provide appropriate estimates of statistical significance and statistical inference. Our research team has pair-matched to increase efficiency in a situation where the distributions of the matching covariates are drastically different in case and control populations. We will use a double robust, efficient, weighted targeted maximum likelihood procedure for the estimation of causal parameters in matched case-control study designs. Where missing data do exist and are missing at random, researchers will use multiple imputation.

Lastly, in line with best practices regarding data storage and in order to assure research quality and integrity, we will implement processes to maximize the rigor, reproducibility, and generalizability of our proposed study. Openness and transparency are being facilitated by pre-registering our planned methods, analyses, and covariates, and sharing of computer code, datasets, and research results. To reduce the likelihood of any possible publication or confirmation biases that might be skewed towards positive results, primary analyses and hypotheses involving tests of the school tactics and policies specified in our specific aims have been publicly pre-registered via clinicaltrials.gov. We will also take every care to ensure that relevant alternative arguments are considered when presenting our results. This will offer school districts and policymakers at the state and federal levels a sound evidence base for the development of fair, objective, and evidence-based policies.

Persistent school gun violence has led to schools adopting a number of school safety tactics and policies. Most of these school safety strategies are designed based on common knowledge rather than scientific evidence of their effectiveness. Despite their widespread implementation in public schools, the association between number and type of safety strategy with the occurrence of school shootings has not been sufficiently established through controlled scientific study. It is also unclear how these safety strategies are associated with school discipline outcomes such as suspensions and expulsions rates. Furthermore, it is not known how urban/non-urban, economic, and racial disparities modify the relationship between school safety tactics and policies, school suspensions and expulsions, and the occurrence of intentional gun violence at schools.

Implementation of school safety strategies also takes up resources in terms of finances and time from the school and therefore research on their effectiveness is required. At present there is no research that has documented the usefulness of the number and type of school safety strategies in preventing school gun violence. There is also a lack of evidence on how these strategies inform school discipline processes, and research is needed to establish if any association is present.

The anticipated results of this work will fill a significant gap in our understanding of the effectiveness and functionality of various school safety tactics and policies in preventing school shootings, as well as their impact on student discipline. Ultimately, this study is intended to provide schools with data-driven evidence with which to choose, implement, and monitor safety tactics and strategies within a national sample of diverse school contexts and student populations, ultimately contributing to safer and more equitable learning conditions.

Supporting information

S1 file. inclusion and exclusion criteria for case and control schools..

https://doi.org/10.1371/journal.pone.0302622.s001

S2 File. School safety strategies and tactics.

https://doi.org/10.1371/journal.pone.0302622.s002

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Daily marijuana use outpaces daily drinking in…

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Denying eatonville, task force votes 5-4 to put florida black history museum in st. augustine, news national news, daily marijuana use outpaces daily drinking in the us, a new study says.

For the first time, the number of Americans who use marijuana just about every day has surpassed the number who drink that often, a shift some 40 years in the making as recreational pot use became more mainstream and legal in nearly half of U.S. states.

In 2022, an estimated 17.7 million people reported using marijuana daily or near-daily compared to 14.7 million daily or near-daily drinkers, according an analysis of national survey data . In 1992, when daily pot use hit a low point, less than 1 million people said they used marijuana nearly every day.

Alcohol is still more widely used, but 2022 was the first time this intensive level of marijuana use overtook daily and near-daily drinking, said the study’s author, Jonathan Caulkins, a cannabis policy researcher at Carnegie Mellon University.

“A good 40% of current cannabis users are using it daily or near daily, a pattern that is more associated with tobacco use than typical alcohol use,” Caulkins said.

The research, based on data from the National Survey on Drug Use and Health, was published Wednesday in the journal Addiction. The survey is a highly regarded source of self-reported estimates of tobacco, alcohol and drug use in the United States.

From 1992 to 2022, the per capita rate of reporting daily or near-daily marijuana use increased 15-fold. Caulkins acknowledged in the study that people may be more willing to report marijuana use as public acceptance grows, which could boost the increase.

Most states now allow medical or recreational marijuana, though it remains illegal at the federal level. In November, Florida voters will decide on a constitutional amendment allowing recreational cannabis, and the federal government is moving to reclassify marijuana as a less dangerous drug.

Research shows that high-frequency users are more likely to become addicted to marijuana, said Dr. David A. Gorelick, a psychiatry professor at the University of Maryland School of Medicine, who was not involved in the study.

The number of daily users suggests that more people are at risk for developing problematic cannabis use or addiction, Gorelick said.

“High frequency use also increases the risk of developing cannabis-associated psychosis,” a severe condition where a person loses touch with reality, he said.

The Associated Press Health and Science Department receives support from the Howard Hughes Medical Institute’s Science and Educational Media Group. The AP is solely responsible for all content.

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Breaking Bad: Real Science or Hollywood Science?

By Catherine S. Haslag

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This two-part case study with a laboratory component uses a pop-cultural reference to engage students and takes the study of electrochemistry from the lecture hall into the lab. Part I of the case describes a scene from the popular television series Breaking Bad in which a series of homemade electrochemical cells are used to jump-start a large recreational vehicle (RV).  Part II of the case consists of a laboratory activity in which students recreate the electrochemical cells depicted in the television show, determine how much current is produced by the cell, and then determine if the electrochemical cells would actually jump-start an RV or if the science is exaggerated for the sake of the story line.  Students learn how an electrochemical cell works and how to use critical thinking skills to separate solid scientific facts from “Hollywood science.”  The case requires a basic understanding of electrochemistry and is suitable for majors and non-majors courses in chemistry and general sciences.

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• Define the following terms: voltage, current, anode, cathode, salt bridge, electrolyte, galvanized, parallel circuit, series circuit, and electrochemical cells .
• Form and test a hypothesis.
• Explain how an electrochemical cell works.
• Describe how a battery functions in an automobile.
• Evaluate a scene portrayed on television and utilize critical thinking to determine if what is demonstrated is reality or Hollywood fiction.
• Draw conclusions based on experimental data and articulate these conclusions to others.

Electrochemical cells; oxidation-reduction; electrochemistry; circuits; redox reactions; voltage; battery; current; data interpretation; Breaking Bad; Hollywood

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Undergraduate lower division

TOPICAL AREAS

Science and the media

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Case teaching notes are protected and access to them is limited to paid subscribed instructors. To become a paid subscriber, purchase a subscription here .

Teaching notes are intended to help teachers select and adopt a case. They typically include a summary of the case, teaching objectives, information about the intended audience, details about how the case may be taught, and a list of references and resources.

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Answer Keys are protected and access to them is limited to paid subscribed instructors. To become a paid subscriber, purchase a subscription here .

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Materials & Media

Supplemental materials.

• Alternators and Batteries – How They Work This video explains how a lead acid car battery works and the function of the alternator in a car. Running time: 7:17 min. Produced by Donut Media, 2018.

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Daily Marijuana Use Outpaces Daily Drinking in the US, a New Study Says

Millions of people in the U.S. report using marijuana daily or nearly every day, and those people now outnumber those who say they are daily or nearly-daily drinkers of alcohol

FILE - Marijuana plants are displayed at a shop in San Francisco, Monday, March 20, 2023. Daily and near-daily marijuana use is now more common than similar levels of high-frequency drinking in the U.S., according to an analysis of survey data over four decades, according to research published Wednesday, May 22, 2024, in the journal Addiction. (AP Photo/Jeff Chiu, File)ff

For the first time, the number of Americans who use marijuana just about every day has surpassed the number who drink that often, a shift some 40 years in the making as recreational pot use became more mainstream and legal in nearly half of U.S. states.

In 2022, an estimated 17.7 million people reported using marijuana daily or near-daily compared to 14.7 million daily or near-daily drinkers, according an analysis of national survey data . In 1992, when daily pot use hit a low point, less than 1 million people said they used marijuana nearly every day.

Alcohol is still more widely used, but 2022 was the first time this intensive level of marijuana use overtook daily and near-daily drinking, said the study’s author, Jonathan Caulkins, a cannabis policy researcher at Carnegie Mellon University.

“A good 40% of current cannabis users are using it daily or near daily, a pattern that is more associated with tobacco use than typical alcohol use,” Caulkins said.

The research, based on data from the National Survey on Drug Use and Health, was published Wednesday in the journal Addiction. The survey is a highly regarded source of self-reported estimates of tobacco, alcohol and drug use in the United States.

From 1992 to 2022, the per capita rate of reporting daily or near-daily marijuana use increased 15-fold. Caulkins acknowledged in the study that people may be more willing to report marijuana use as public acceptance grows, which could boost the increase.

Most states now allow medical or recreational marijuana, though it remains illegal at the federal level. In November, Florida voters will decide on a constitutional amendment allowing recreational cannabis, and the federal government is moving to reclassify marijuana as a less dangerous drug.

Research shows that high-frequency users are more likely to become addicted to marijuana, said Dr. David A. Gorelick, a psychiatry professor at the University of Maryland School of Medicine, who was not involved in the study.

The number of daily users suggests that more people are at risk for developing problematic cannabis use or addiction, Gorelick said.

“High frequency use also increases the risk of developing cannabis-associated psychosis,” a severe condition where a person loses touch with reality, he said.

The Associated Press Health and Science Department receives support from the Howard Hughes Medical Institute’s Science and Educational Media Group. The AP is solely responsible for all content.

Copyright 2024 The  Associated Press . All rights reserved. This material may not be published, broadcast, rewritten or redistributed.

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