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The Michigan Metro Area Communities Study (MIMACS) is a panel survey of select Michigan communities residents aged 18 and older. Flint is one of the communities included in MIMACS. The initial survey in Flint was conducted in 2022 and the sample was drawn from an address-based probability sample of all occupied Flint households. The 3rd survey wave, collected between January 15 - March 18, 2024, researchers invited 823 previously enrolled panelists and 1,554 invitations to a randomly selected address-based refreshment sample of Flint households to participate in a self-administered online or interviewer-administered telephone survey. Survey topics included: Household Composition, Residence and Housing Status; Health, Social Determinants of Health, Long COVID, Mental Health; Disability; Perceptions of Neighborhood; Transportation Mode; Financial Precarity; Perception of Control; Voting; Employment; Demographics.

Tsogolo la Thanzi (TLT) is a longitudinal study in Balaka, Malwai designed to examine how young people navigate reproduction in an AIDS epidemic. Tsogolo la Thanzi means "Healthy Futures" in Chichewa, which is Malawi's most widely spoken language.

The 2019 Household Listing Data are the result of a new census of the original catchment area, 10 years after the initial study began. These data are supplemental to the main TLT series, providing insights into how the Balaka area developed over the past 10 years. It includes data from all persons living within 7 kilometers of the TLT research center.

Tsogolo La Thanzi (TLT) is a decade-long population-based cohort study of young women and men from Balaka, Malawi. Tsogolo La Thanzi means "Health Futures" in Chichewa, Malawi's most widely spoken language. TLT has followed young adults (ages 15-25 at enrollment, 15-35 inclusive) as they navigate relationships and childbearing within the context of a generalized AIDS epidemic. TLT enrolled more than 3000 individuals and collected 11 waves of data, covering a 10-year period (2009-2019) that spans massive changes in the HIV treatment context in Malawi as well as the ages of peak incidence and peak fertility for female respondents.

This particular study contains the data collected from an additional survey referred to as Tsogolo La Thanzi 3 (TLT-3), fielded in 2019, following the release of ten waves of data collected between 2009 and 2015. Unlike the past where the sample included male partners, this third round of data collection focused solely on women.

TLT-3 covered many of the same topics found in the original TLT multi-wave project such as: relationships, religion, HIV/AIDS, pregnancy, marriage, sexually transmitted diseases, and future expectations.

Additionally, modules specific to TLT-3 included: kinship, mental health, and trust in clinics. These data can be used cross-sectionally or can be merged with previous waves to facilitate analyses of a full ten years of social change in Balaka township and across the life course.

The standard care of hospital or emergency department patients experiencing an acute ischemic stroke includes intravenously administered tissue plasminogen activator (tPA). Mobile stroke units (MSUs) are ambulances equipped with staff and a computed tomographic scanner that can allow for tPA to be administered more quickly. This comparative effectiveness trial examined clinical outcomes in stroke patients who received either an earlier diagnosis and treatment using an MSU or standard triage and transport by Emergency Medical Services (EMS). The sample included multicenter cohorts with randomized deployment weeks and blinded assessment of both trial entry and clinical outcomes.

Fathers Empowered to Learn, Lead, and Achieve Success (FELLAS) is a Responsible Fatherhood program, funded by the Office of Family Assistance, and provided by the Partnership for Maternal and Child Health in Northern New Jersey. The program served community-based fathers aged 18 and older who reside in Essex County, New Jersey. To be eligible for the program, fathers must have had at least one child aged 24 or younger. Expectant fathers were eligible. The FELLAS program consisted of three key components:

• Responsible Parenting: Uses 24/7 Dad, an evidence-based, father-focused parenting curriculum designed to enhance parenting skills.
• Healthy Marriage/Relationship Skills: Incorporates Couple Communication I, an evidence-based curriculum that includes home visits to strengthen relationships and marriage dynamics.
• Economic Stability: Provides a comprehensive set of services, including employment assessments, basic technology training, and pre-employment soft skills development.

The core program consisted of 35 hours of intensive workshops, broken down as follows:

• 24 hours of 24/7 Dad group sessions
• 6 hours of economic stability group sessions
• 5 hours of Couple Communication I group sessions
• The program was taught over 15 weeks, two-three hours per week

For the five weeks prior to the start of each cohort, the Father Program Specialists (FPSs) recruited fathers by conducting street outreach throughout Essex County, outreach in-person at childcare centers and schools, outreach and marketing to local partners requesting referrals to the program. They also encouraged fathers who had previously completed the program to assist with word-of-mouth marketing. Recruitment was also facilitated, in part, by The Partnership's extensive experience in the community. Two cohorts were conducted each year. Each FPS facilitated the FELLAS programming for the fathers he recruited and also served as the case manager for these fathers.

The Seek, Test, Treat and Retain (STTR) Collaboration Project involved over twenty studies in the fields of HIV and drug abuse. These studies were independently developed, but were chosen for the collaboration because they focused on one or more steps of the HIV treatment cascade: Seek, Test, Treat and Retain. These studies were grouped into Criminal Justice-related studies and Vulnerable Population-related studies. The data collected by these studies included twelve common domains (e.g. demographic characteristics, mental health) in each of which a shared questionnaire or instrument was taken up by the studies and adapted to fit the study. This repository contains the collected data and documentation from the STTR collaboration.

This study in particular is part of the Urban Health Studies project, specifically assessing treatment outcomes of high-risk probationers and parolees with HIV in California from 2012 to 2013.

This project examined the implementation of student threat assessment in Florida public schools. Researchers investigated threat assessment training and implementation, which types of threat cases schools experienced, and how cases were resolved. This project used a mixed-method approach with four broad research questions: (1) What are stakeholder reactions to training and implementation of threat assessment in their school? (2) What are the characteristics of threat assessments conducted in Florida public schools? (3) What relationships exist among academic, disciplinary, and legal outcomes for students receiving a threat assessment? (4) Are there adverse disparities in student outcomes associated with race, ethnicity, or special education status?

The data produced by this study include three Case Data datasets (DS1-3), comprised of Florida Department of Education (FLDOE) case data on student threats from the 2020-21 and 2021-22 school years; two Training Survey Data datasets (DS4/5), containing results from surveys of participants who completed Comprehensive School Threat Assessment Guidelines (CSTAG) trainings; and Needs Assessment Survey Data (DS6) from a survey of district school safety leads assessing needs and concerns about their district's threat assessment process.

Drug use remains a major public health problem among youth in the United States. Effective implementation of evidence-based interventions for youth is critical for reducing the burden of drug use and its consequences. The Michigan Model for Health (MMH) is a universal prevention curriculum that has demonstrated efficacy in reducing adolescent substance use. Fidelity is essential to intervention effectiveness, yet youth rarely receive evidence-based interventions (EBIs) as intended; this is partly due to a poor fit between the intervention and the context. The disconnect between the EBI and context is especially pronounced among underserved and vulnerable populations, including among youth exposed to trauma. Trauma is a potent risk factor for substance use, abuse, and the development of substance use disorders. Consequently, there is a critical need to design and test effective, cost-efficient implementation strategies to optimize the fidelity of school-based drug use prevention to meet better the needs of youth exposed to trauma. The study designed and tested a multi-component implementation strategy to improve intervention-context fit and enhance fidelity and effectiveness.

This study was using a 2-group, mixed method, randomized trial design, this pilot study compared standard implementation (Replicating Effective Programs [REP]) versus enhanced REP to deliver MMH. REP is an implementation strategy bundle that promotes EBI fidelity through curriculum packaging, training, and as-needed technical assistance. Enhanced REP incorporates tailoring of the EBI package and training and deploys customized implementation support (i.e., implementation facilitation). The research focuses on youth at heightened risk of drug use and its consequences due to trauma exposure.

This study contains data from the Northwestern Juvenile Project (NJP) series, a prospective longitudinal study of the mental health needs and outcomes of youth in detention.

The purpose of this study was to examine the dose of incarceration and subsequent psychiatric and psychosocial functioning in 1,829 justice-involved youths in Chicago, Illinois 16 years after detention.

The study publication, "Incarceration and Subsequent Psychosocial Outcomes: A 16-Year Longitudinal Study of Youth After Detention", was published in April 2025 in the Journal of the American Academy of Child and Adolescent Psychiatry.

This NIJ-funded study used a data driven approach to understand rural police department responses to the opioid crisis. Researchers compiled County-Level Drug Data on overdose deaths to understand the spatio-temporal distribution of drug misuse and to identify counties with high levels of death that are doing better and worse than expected according to an inclusive statistical model. In combination with this data, researchers collected Police Agency Survey Data from police departments in four states to understand departments' access to intelligence resources. Based on this survey, six agencies with varying law enforcement structural relations with state-level agencies were selected to participate in the study intervention. Departments were partnered with mentors and encouraged to enhance their intelligence networks, design a simple initiative, equip themselves for it, and carry it out. Outcomes from the intervention were evaluated through survey data - available as Implementation Site Administrative and Survey Data - and through a series of qualitative interviews, which will be made available at a later date.

Child Trends was funded by the Office of Juvenile Justice and Delinquency Prevention (OJJDP) to conduct an implementation and impact evaluation of the Virginia Department of Juvenile Justice's (DJJ) Second Chance Act reentry reform efforts. Through a rigorous evaluation of DJJ's reentry efforts and the translation of study findings into recommendations for improving juvenile reentry efforts, this project aimed to enhance public safety and improve outcomes for young people reentering their communities. To achieve these goals, they completed three core objectives: 1) leverage DJJ's robust statewide administrative data system to conduct a quasi-experimental study to examine how the core components of DJJ's reentry reforms impact youth outcomes; 2) conduct an in-depth implementation evaluation to provide other states who are implementing federally funded reentry reforms with context for the study findings, as well as to identify challenges and solutions for implementing and sustaining the reforms; and 3) translate research findings for practitioners, policymakers, and researchers aiming to improve juvenile reentry.

The grant was transferred to the National Institute of Justice (NIJ) in October 2018.

In 2005, 592 African Americans from Milwaukee were added to the MIDUS sample to examine health issues in minority populations (for more details, see Midlife in the United States (MIDUS 2): Milwaukee African American Sample [ICPSR #22840]). Respondents were interviewed in their homes using a Computer Assisted Personal Interview (CAPI) survey protocol and asked to complete and return a Self-Administered Questionnaire (SAQ). Afterwards these individuals were eligible for participation in the same research protocol as the national MIDUS 2 sample, including cognitive, daily stress, biomarker, and neuroscience projects.

With support from the National Institute on Aging, a second wave of survey data collection on the Milwaukee sample was begun in 2016. The survey consisted of a 2.5 hour CAPI interview followed by a 45-page mailed SAQ. CAPI survey data was collected for 389 individuals, realizing a 78 percent response rate, adjusted for mortality and other eligibility criteria. Data collection for this follow-up wave largely repeated baseline assessments, with additional questions in selected areas (e.g., economic recession experiences, childhood experience with race, etc.). Following successful completion of the CAPI and SAQ protocols, individuals were eligible for participation in cognitive, daily stress, biomarker, and neuroscience projects.

Since 1976, MTF has enrolled ~2,450 individuals each year from its nationally representative annual sample of 12th graders into the MTF Longitudinal Panel study. A primary goal of MTF study is to examine potential consequences of substance use across the life course, including mortality. Therefore, the MTF Longitudinal Panel study now includes measures of mortality linked to the National Death Index (NDI).

The "MTF Longitudinal Panel Mortality Data and Weights, Cohorts 1976-2019 (Updated March 2026)" file includes MTF Longitudinal Panel members from the high school cohorts of 1976-2019 whose mortality status was confirmed through either (a) the MTF NDI match process or (b) the MTF panel tracking process (tracking through March 2026).

This updated file includes:

• The Panel Eligibility and Sampling Weight (PESW) variable to be used when mortality status is the outcome.
• Continued data management to update respondents and mortality status.

See the MTF Occasional Paper No.102 for details on the MTF mortality data and weights. Information about the MTF project can be accessed through the Monitoring the Future website. Annual reports are published by the research team, describing the data collection and trends over time.

The Healthy Marriage and Responsible Fatherhood (HMRF) grant programs have been funded by the Administration for Children and Families (ACF) and by the Office of Family Assistance (OFA) since 2006. The purpose of these programs is to promote the long-term well-being of children and families by strengthening the family unit and fostering healthy relationships and economic stability.

The Building Usage and Learning with Data in HMRF programs (BUILD HMRF) project supported the fourth cohort of HMRF grant recipients (2020-2025). OFA awarded 113 grants focused on marriage and relationship education and skills-building, responsible parenting, economic stability, and related activities depending on the type of grant awarded. Funded programs provided curriculum-based workshops and individual services to HM adult individuals and couples, HM youth individuals, and RF fathers and couples based on the type of grant awarded. RF fathers were either reentering or in the community.

In 2018 law enforcement agencies gained access to a federally created, nationwide, interoperable first responder broadband communications network, called the National Public Safety Broadband Network, also known as FirstNet. The RAND Corporation was funded to conduct research and provide guidance to law enforcement agencies on how to best transition to the broadband communication network. To this end, the RAND Corporation performed a literature review, interviewed subject-matter experts, and developed coverage maps for select areas. The interviews covered topics such as the current state of deployment, system governance, system reliability, vendors used, and plans for migration.

This data collection includes select quotes and interview notes from the interviews with subject-matter experts. The literature review and coverage maps for select areas are not included in this collection.

This study examined the impact of policy changes resulting in the removal of school police on student outcomes. The study took advantage of recent widespread school police policy changes in California and extant survey and administrative data, and used a quasi-experimental study to compare school districts that removed school police during 2019-20 or 2020-21 with a matched comparison group of districts that did not remove school police. The study examined the impact of such policies on middle and high school students' reported safety, behavior, and well-being as well as administrative disciplinary data (suspensions).

This study also examined whether school police policy changes had differential impacts depending on the level of schools' mental health supports (student-to-counselor ratio). Finally, researchers conducted interviews with a sample of administrators and partnering community-based providers to identify the reasons for, and impact of, removing or retaining school police as well as policies and practices implemented as alternatives. There are no impact studies, to the researchers' knowledge, that examined the impact of removing school police. This study's findings are critical to understanding how the presence of police in schools relate to student outcomes.

The Valuating Law Enforcement Data in the 21st Century study was conducted in four phases. Phase I included a literature scan and expert interviews. Phase II was an exploratory effort at understanding the dimensions and characteristics of valuation efforts focused on policing data. Phase III focused on developing a cost-benefit analysis (CBA) framework for body-worn cameras (BWCs). Finally, Phase IV turned the BWC CBA tool into a web-based calculator for law enforcement agencies to assess the likely impact of BWCs on their agency.

This collection includes qualitative notes from focus group discussions at site visits conducted in Phase II and Phase III of the study. Personnel from 13 law enforcement agencies across 10 U.S. states participated in the focus groups. Efforts were made to diversify among municipal police and sheriffs, the variety of agency sizes and populations served, and geography. In general, site visits were designed to include a variety of personnel, including from executive staff, information technology, patrol, investigations, and crime analysis.

The Juvenile Residential Facility Census (JRFC), which is conducted biennially, collects basic information on juvenile residential facility characteristics, including security, capacity and crowding, injuries and deaths in custody, and facility ownership and operation. The JRFC also includes questions about facility type (such as detention center, training school, ranch, or group home) and residential services provided by the facility (such as independent living, foster care, or other arrangements), and detailed questions about mental health, substance abuse, and educational services provided to young persons.

In 2022, the JRFC was divided into seven sections:

1. General facility information
2. Mental health services
3. Educational services
4. Substance abuse services
5. Events in the 30 days prior to the census reference date
6. Deaths in the year prior to the census reference date
7. Space shared with other facilities

Congress requires the Office of Juvenile Justice and Delinquency Prevention (OJJDP) to report annually on the number of deaths of juveniles in custody; the JRFC gathers this information and offers a portrait of the nation's juvenile facilities. The census reference date was the fourth Wednesday in October (October 26, 2022).

This study is part of the Seek, Test, Treat and Retain (STTR) Collaboration Project involved over twenty studies in the fields of HIV and drug abuse. All studies were independently developed, but were chosen for the collaboration because they focused on one or more steps of the HIV treatment cascade: Seek, Test, Treat and Retain. As part of STTR Collaboration Project, the studies were grouped into Criminal Justice-related studies and Vulnerable Population-related studies. The data collected by these studies included twelve common domains (e.g., Demographic characteristics, Mental Health) in each of which a shared questionnaire or instrument was taken up by the studies and adapted to fit the study.

The data in this study focuses on adult respondents' health status and viral load involving HIV and HCV.

In an effort to make hearing aids more affordable and accessible to U.S. adults with hearing difficulty, the Food and Drug Administration (FDA) empowered these adults to self-fit over-the-counter (OTC) hearing aids. The effectiveness of two self-fit methods, Consumer Decides (CD) and Efficient Fitting (EF), was hypothesized to be non-inferior to the professional-fit method, (Audiology Based, AB). This was evaluated for both short-term (6 weeks post-fit) and long-term (6 months post-fit) outcomes.

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco.

45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent.

At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population (CNP) at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Units (PSUs) and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the CNP at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.

At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the CNP at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This "second replenishment sample" was combined for estimation and analysis purposes with the Wave 7 adult and youth respondents from the Wave 4 Cohort who were at least age 15 and in the CNP at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort.

Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts.

Dataset 0002 (DS0002) contains the data from the State Design Data. This file contains 7 variables and 82,139 cases. The state identifier in the State Design file reflects the participant's state of residence at the time of selection and recruitment for the PATH Study.

Dataset 1011 (DS1011) contains the data from the Wave 1 Adult Questionnaire. This data file contains 2,021 variables and 32,320 cases. Each of the cases represents a single, completed interview.

Dataset 1012 (DS1012) contains the data from the Wave 1 Youth and Parent Questionnaire. This file contains 1,431 variables and 13,651 cases.

Dataset 1411 (DS1411) contains the Wave 1 State Identifier data for Adults and has 5 variables and 32,320 cases. Dataset 1412 (DS1412) contains the Wave 1 State Identifier data for Youth (and Parents) and has 5 variables and 13,651 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state Federal Information Processing System (FIPS), state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 1, which is also their state of residence at the time of recruitment.

Dataset 1611 (DS1611) contains the Tobacco Universal Product Code (UPC) data from Wave 1. This data file contains 32 variables and 8,601 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 1. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used by these respondents at the time of Wave 1.

Dataset 1801 (DS1801) contains Location Characteristics for Wave 1 Adults. This data file contains 4 variables and 32,320 cases.

Dataset 1802 (DS1802) contains Location Characteristics for Wave 1 Youth. This data file contains 4 variables and 13,651 cases.

Dataset 1901 (DS1901) contains Study Research Derived Variables for Wave 1 Adults created by PATH Study analysts. This data file contains 104 variables and 32,320 cases.

Dataset 1902 (DS1902) contains Study Research Derived Variables for Wave 1 Youth created by PATH Study analysts. This data file contains 89 variables and 13,651 cases.

Dataset 2011 (DS2011) contains the data from the Wave 2 Adult Questionnaire. This data file contains 2,421 variables and 28,362 cases. Of these cases, 26,447 also completed a Wave 1 Adult Questionnaire. The other 1,915 cases are "aged-up adults" having previously completed a Wave 1 Youth Questionnaire.

Dataset 2012 (DS2012) contains the data from the Wave 2 Youth and Parent Questionnaire. This data file contains 1,596 variables and 12,172 cases. Of these cases, 10,081 also completed a Wave 1 Youth Questionnaire. The other 2,091 cases are "aged-up youth" having previously been sampled as "shadow youth."

Dataset 2411 (DS2411) contains the Wave 2 State Identifier data for Adults and has 5 variables and 28,362 cases. Dataset 2412 (DS2412) contains the Wave 2 State Identifier data for Youth and Parents and has 5 variables and 12,172 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state FIPS, state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 2.

Dataset 2611 (DS2611) contains the Tobacco Universal Product Code (UPC) data from Wave 2. This data file contains 32 variables and 7,295 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 2. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used by these respondents at the time of Wave 2.

Dataset 2801 (DS2801) contains Location Characteristics for Wave 2 Adults. This data file contains 4 variables and 28,362 cases.

Dataset 2802 (DS2802) contains Location Characteristics for Wave 2 Youth. This data file contains 4 variables and 12,172 cases.

Dataset 2901 (DS2901) contains Study Research Derived Variables for Wave 2 Adults created by PATH Study analysts. This data file contains 178 variables and 28,362 cases.

Dataset 2902 (DS2902) contains Study Research Derived Variables for Wave 2 Youth created by PATH Study analysts. This data file contains 123 variables and 12,172 cases.

Dataset 3011 (DS3011) contains the data from the Wave 3 Adult Questionnaire. This data file contains 2,359 variables and 28,148 cases. Of these cases, 26,241 are continuing adults having completed a prior Adult Questionnaire. The other 1,907 cases are "aged-up adults" having previously completed a Youth Questionnaire.

Dataset 3012 (DS3012) contains the data from the Wave 3 Youth and Parent Questionnaire. This data file contains 1,492 variables and 11,814 cases. Of these cases, 9,769 are continuing youth having completed a prior Youth Interview. The other 2,045 cases are "aged-up youth" having previously been sampled as "shadow youth."

Datasets 3111, 3211, 3112, and 3212 (DS3111, DS3211, DS3112, and DS3212) are data files comprising the weight variables for Wave 3. The weight variables for Wave 1 and Wave 2 are included in the main data files. However, starting with Wave 3, the weight variables have been separated into individual data files. The "all-waves" weight files contain weights for respondents who completed an interview for all waves in which they were old enough to do so or verified their information with the study for waves in which they were not old enough to be interviewed. The "single-wave" weight files contain weights for all respondents in Wave 3 regardless of their participation in previous waves.

Dataset 3503 (DS3503) contains data derived from responses to Wave 1-3 questionnaires indicating if participants had ever/never used various tobacco products as of the Wave 3 study period. This data file contains 25 variables for all 53,178 study participants as of Wave 3. This file is provided for reference only to simplify the definitions of tobacco use variables in the Adult and Youth data files for subsequent waves.

Dataset 3411 (DS3411) contains the Wave 3 State Identifier data for Adults and has 5 variables and 28,148 cases. Dataset 3412 (DS3412) contains the Wave 3 State Identifier data for Youth and Parents and has 5 variables and 11,814 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state FIPS, state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 3.

Dataset 3611 (DS3611) contains the Tobacco Universal Product Code (UPC) data from Wave 3. This data file contains 32 variables and 6,768 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 3. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used by these respondents at the time of Wave 3.

Dataset 3801 (DS3801) contains Location Characteristics for Wave 3 Adults. This data file contains 4 variables and 28,148 cases.

Dataset 3802 (DS3802) contains Location Characteristics for Wave 3 Youth. This data file contains 4 variables and 11,814 cases.

Dataset 3901 (DS3901) contains Study Research Derived Variables for Wave 3 Adults created by PATH Study analysts. This data file contains 107 variables and 28,148 cases.

Dataset 3902 (DS3902) contains Study Research Derived Variables for Wave 3 Youth created by PATH Study analysts. This data file contains 88 variables and 11,814 cases.

Dataset 4001 (DS4001) contains the data from the Wave 4 Adult Questionnaire. This data file contains 2,504 variables and 33,822 cases. Of these cases, 25,857 are continuing adults having completed a prior Adult Questionnaire, 1,900 are "aged-up adults" having previously completed a Youth Questionnaire, and 6,065 are "replenishment sample adults" (also known as "new cohort adults" in the annotated instrument).

Dataset 4002 (DS4002) contains the data from the Wave 4 Youth and Parent Questionnaire. This data file contains 1,600 variables and 14,798 cases. Of these cases, 9,365 are continuing youth having completed a prior Youth Interview, 1,694 cases are "aged-up youth" having previously been sampled as "shadow youth," and 3,739 are "replenishment sample youth" (also known as "new cohort youth" in the annotated instrument).

Datasets 4111, 4211, 4321, 4112, 4212, and 4322 (DS4111, DS4211, DS4321, DS4112, DS4212, and DS4322) are data files comprising the weight variables for Wave 4. In Wave 4, the weight variables have been separated into individual data files corresponding to the Wave 1 and Wave 4 Cohorts and different weight types. The "all-waves" weight files contain weights for those Wave 1 Cohort respondents who completed an interview for all waves in which they were old enough or verified their information for waves in which they were not old enough to be interviewed. The "single-wave" weight files contain weights for Wave 1 Cohort respondents at Wave 4 who completed an interview at Wave 1, regardless of their participation in previous waves. The "cross-sectional" weight files contain weights for all respondents in the Wave 4 Cohort.

Dataset 4401 (DS4401) contains the Wave 4 State Identifier data for Adults and has 5 variables and 33,822 cases. Dataset 4402 (DS4402) contains the Wave 4 State Identifier data for Youth and Parents and has 5 variables and 14,798 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state FIPS, state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 4. For adults and youth from the replenishment sample, the values also represent state of residence at the time of recruitment.

Dataset 4503 (DS4503) contains data derived from responses to Wave 1-4 questionnaires, indicating if participants had ever/never used various tobacco products as of the Wave 4 data collection period. This data file contains 27 variables for all 67,276 study participants as of the Wave 4 data collection. This file is provided for reference only to simplify the definitions of tobacco use variables in the Adult and Youth data files for subsequent waves.

Dataset 4601 (DS4601) contains the Tobacco Universal Product Code (UPC) data from Wave 4. This data file contains 32 variables and 7,684 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 4. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used by these respondents at the time of Wave 4.

Dataset 4801 (DS4801) contains Location Characteristics for Wave 4 Adults. This data file contains 4 variables and 33,822 cases.

Dataset 4802 (DS4802) contains Location Characteristics for Wave 4 Youth. This data file contains 4 variables and 14,798 cases.

Dataset 5001 (DS5001) contains the data from the Wave 5 Adult Questionnaire. This data file contains 2,606 variables and 34,309 cases. Of these cases, 29,876 are continuing adults having completed a prior Adult Questionnaire and 4,433 are "aged-up adults" having previously completed a Youth Questionnaire.

Dataset 5002 (DS5002) contains the data from the Wave 5 Youth and Parent Questionnaire. This data file contains 1,776 variables and 12,098 cases. Of these cases, 10,446 are continuing youth having completed a prior Youth Interview and 1,652 cases are "aged-up youth" having previously been sampled as "shadow youth."

Datasets 5111, 5112, 5211, 5212, 5221, 5222, 5711, 5712, 5721, and 5722 (DS5111, DS5112, DS5211, DS5212, DS5221, DS5222, DS5711, DS5712, DS5721, and DS5722) are data files comprising the weight variables for Wave 5. In Wave 5, the weight variables are in individual data files corresponding to the Wave 1 and Wave 4 Cohorts and different weight types. The "all-waves" weight files contain weights for those Wave 1 Cohort participants who completed a Wave 5 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 1, 2, 3, and 4.

There are two separate sets of files with "single wave" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "single-wave" weight files for the Wave 1 Cohort contain weights for participants who completed an interview in Wave 1 and in Wave 5, regardless of their participation in the intervening waves. The "single-wave" weight files for the Wave 4 Cohort contain weights for all Wave 5 interview respondents in the Wave 4 Cohort.

There are also two separate sets of files with "special collection all-waves" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "special collection all-waves" weight files for the Wave 1 Cohort contain weights for participants who completed a Wave 5 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 1, 2, 3, 4, and the special collection in Wave 4.5. The "special collection all-waves" weight files for the Wave 4 Cohort contain weights for participants who completed a Wave 5 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Wave 4 and the special collection in Wave 4.5.

Dataset 5401 (DS5401) contains the Wave 5 State Identifier data for Adults and has 5 variables and 34,309 cases. Dataset 5402 (DS5402) contains the Wave 5 State Identifier data for Youth and Parents and has 5 variables and 12,098 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state FIPS, state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 5.

Dataset 5503 (DS5503) contains data derived from responses to Wave 1-5 (including Wave 4.5) questionnaires indicating if participants had ever/never used various tobacco products as of the Wave 5 data collection period. This data file contains 26 variables for all 67,276 study participants as of the Wave 5 data collection. This file is provided for reference only to simplify the definitions of tobacco use variables in the Adult and Youth data files for subsequent waves.

Dataset 5601 (DS5601) contains the Tobacco Universal Product Code (UPC) data from Wave 5. This data file contains 33 variables and 6,678 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 5. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used by these respondents at the time of Wave 5.

Dataset 5801 (DS5801) contains Location Characteristics for Wave 5 Adults. This data file contains 4 variables and 34,309 cases.

Dataset 5802 (DS5802) contains Location Characteristics for Wave 5 Youth. This data file contains 4 variables and 12,098 cases.

Dataset 6001 (DS6001) contains the data from the Wave 6 Adult Questionnaire. This data file contains 2,935 variables and 30,516 cases

Of these cases, 28,852 are continuing adults having completed a prior Adult Questionnaire and 1,664 are "aged-up adults" having previously completed a Youth Questionnaire.

Dataset 6002 (DS6002) contains the data from the Wave 6 Youth and Parent Questionnaire. This data file contains 2,080 variables and 5,652 cases. Of these cases, 5,622 are continuing youth having completed a prior Youth Interview and 60 cases are "aged-up youth" having previously been sampled as "shadow youth."

Datasets 6111, 6112, 6121, 6122, 6211, 6212, 6221, 6222, 6711, 6712, 6721, and 6722 (DS6111, DS6112, DS6121, DS6122, DS6211, DS6212, DS62221, DS6222, DS6711, DS6712, DS6721, and DS6722) are data files comprising the weight variables for Wave 6. In Wave 6, the weight variables are in individual data files corresponding to the Wave 1 and Wave 4 Cohorts and different weight types. There are two separate sets of files with "all-waves" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "all-waves" weight files for the Wave 1 Cohort contain weights for participants who completed a Wave 6 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 1, 2, 3, 4, and 5. The "all-waves" weight files for the Wave 4 Cohort contain weights for participants who completed a Wave 6 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 4 and 5.

There are two separate sets of files with "single-wave" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "single-wave" weight files for the Wave 1 Cohort contain weights for participants who completed an interview in Wave 1 and in Wave 6, regardless of their participation in the intervening waves. The "single-wave" weight files for the Wave 4 Cohort contain weights for participants who completed an interview in Wave 4 and in Wave 6, regardless of their participation in the intervening waves.

There are also two separate sets of files with "special collection all-waves" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "special collection all-waves" weight files for the Wave 1 Cohort contain weights for participants who completed a Wave 6 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 1, 2, 3, 4, 5, and the special collections in Wave 4.5, and Wave 5.5 or PATH-ATS. The "special collection all-waves" weight files for the Wave 4 Cohort contain weights for participants who completed a Wave 6 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 4 and 5, and the special collections in Wave 4.5, and Wave 5.5 or PATH-ATS.

Dataset 6401 (DS6401) contains the Wave 6 State Identifier data for Adults and has 5 variables and 30,516 cases. Dataset 6402 (DS6402) contains the Wave 6 State Identifier data for Youth and Parents and has 5 variables and 5,652 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state FIPS, state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 6.

Dataset 6503 (DS6503) contains data derived from responses to questionnaires in Waves 1-6 (including the special collections in Wave 4.5, Wave 5.5, and PATH-ATS) indicating if participants had ever/never used various tobacco products as of the Wave 6 data collection period. This data file contains 24 variables for all 67,276 study participants as of the Wave 6 data collection. This file is provided for reference only to simplify the definitions of tobacco use variables in the Adult and Youth data files for subsequent waves.

Dataset 6601 (DS6601) contains the Tobacco Universal Product Code (UPC) data from Wave 6. This data file contains 53 variables and 5,408 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 6. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used by these respondents at the time of Wave 6.

Dataset 6801 (DS6801) contains Location Characteristics for Wave 6 Adults. This data file contains 4 variables and 30,516 cases.

Dataset 6802 (DS6802) contains Location Characteristics for Wave 6 Youth. This data file contains 4 variables and 5,652 cases.

Dataset 7001 (DS7001) contains the data from the Wave 7 Adult Questionnaire. This data file contains 3,221 variables and 30,801 cases. Of these cases, 27,258 are continuing adults having completed a prior Adult Questionnaire, 1,740 are "aged-up adults" having previously completed a Youth Questionnaire, and 1,803 are "replenishment sample adults" (also known as "new cohort adults" in the annotated instrument).

Dataset 7002 (DS7002) contains the data from the Wave 7 Youth and Parent Questionnaire. This data file contains 2,171 variables and 10,834 cases. Of these cases, 3,512 are continuing youth having completed a prior Youth Interview, 1 case is an "aged-up youth" having previously been sampled as "shadow youth," and 7,321 are "replenishment sample youth" (also known as "new cohort youth" in the annotated instrument).

Datasets 7111, 7112, 7121, 7122, 7211, 7212, 7221, 7222, 7331, 7332, 7711, 7712, 7721, and 7722 (DS DS7111, DS7112, DS7121, DS7122, DS7211, DS7212, DS7221, DS7222, DS7331, DS7332, DS7711, DS7712, DS7721, and DS7722) are data files comprising the weight variables for Wave 7. In Wave 7, the weight variables are in individual data files corresponding to the Wave 1, Wave 4, and Wave 7 Cohorts and different weight types.

There are two separate sets of files with "all-waves" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "all-waves" weight files for the Wave 1 Cohort contain weights for participants who completed a Wave 7 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 1, 2, 3, 4, 5, and 6. The "all-waves" weight files for the Wave 4 Cohort contain weights for participants who completed a Wave 7 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 4, 5, and 6.

There are two separate sets of files with "single-wave" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "single-wave" weight files for the Wave 1 Cohort contain weights for participants who completed an interview in Wave 1 and in Wave 7, regardless of their participation in the intervening waves. The "single-wave" weight files for the Wave 4 Cohort contain weights for participants who completed an interview in Wave 4 and in Wave 7, regardless of their participation in the intervening waves.

There are also two separate sets of files with "special collection all-waves" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "special collection all-waves" weight files for the Wave 1 Cohort contain weights for participants who completed a Wave 7 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 1, 2, 3, 4, 5, 6, and the special collections in Wave 4.5, and Wave 5.5 or PATH-ATS. The "special collection all-waves" weight files for the Wave 4 Cohort contain weights for participants who completed a Wave 7 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 4, 5, 6, and the special collections in Wave 4.5, and Wave 5.5 or PATH-ATS.

The "cross-sectional" weight files contain weights for all respondents in the Wave 7 Cohort.

Dataset 7401 (DS7401) contains the Wave 7 State Identifier data for Adults and has 5 variables and 30,801 cases. Dataset 7402 (DS7402) contains the Wave 7 State Identifier data for Youth and Parents and has 5 variables and 10,834 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state FIPS, state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 7.

Dataset 7503 (DS7503) contains data derived from responses to questionnaires in Waves 1-7 (including the special collections in Wave 4.5, Wave 5.5, and PATH-ATS) indicating if participants had ever/never used various tobacco products as of the Wave 7 data collection period. This data file contains 26 variables for all 82,139 study participants as of the Wave 7 data collection. This file is provided for reference only to simplify the definitions of tobacco use variables in the Adult and Youth data files for subsequent waves.

Dataset 7601 (DS7601) contains the Tobacco Universal Product Code (UPC) data from Wave 7. This data file contains 53 variables and 4,533 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 7. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used by these respondents at the time of Wave 7.

Dataset 7801 (DS7801) contains Location Characteristics for Wave 7 Adults. This data file contains 4 variables and 30,801 cases.

Dataset 7802 (DS7802) contains Location Characteristics for Wave 7 Youth. This data file contains 4 variables and 10,834 cases.

Dataset 8001 (DS8001) contains the data from the Wave 8 Adult Questionnaire. This data file contains 3,467 variables and 31,477 cases. Of these cases, 30,021 are continuing adults having completed a prior Adult Questionnaire and 1,456 are "aged-up adults" having previously completed a Youth Questionnaire.

Dataset 8002 (DS8002) contains the data from the Wave 8 Youth and Parent Questionnaire. This data file contains 2,393 variables and 8,002 cases. Of these cases, 7,046 are continuing youth having completed a prior Youth Interview and 956 are "aged-up youth" having previously been sampled as "shadow youth."

Datasets 8111, 8121, 8122, 8211, 8221, 8231, 8232, 8711, 8721, 8722, 8731, and 8732 (DS8111, DS8121, DS8122, DS8211, DS8221, DS8231, DS8232, DS8711, 8DS721, DS8722, DS8731, and DS8732) are data files comprising the weight variables for Wave 8. In Wave 8, the weight variables are in individual data files corresponding to the Wave 1, Wave 4, and Wave 7 Cohorts and different weight types.

There are two separate sets of files with "all-waves" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "all-waves" weight files for the Wave 1 Cohort contain weights for participants who completed a Wave 8 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 1, 2, 3, 4, 5, 6, and 7. Note that only adults have "all-waves" weights for the Wave 1 Cohort; youth from the Wave 1 Cohort aged-up to adults by the time of Wave 8. The "all-waves" weight files for the Wave 4 Cohort contain weights for participants who completed a Wave 8 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 4, 5, 6, and 7.

There are three separate sets of files with "single-wave" weights: one for the Wave 1 Cohort, one for the Wave 4 Cohort, and one for the Wave 7 Cohort. The "single-wave" weight files for the Wave 1 Cohort contain weights for participants who completed an interview in Wave 1 and in Wave 8, regardless of their participation in the intervening waves. The "single-wave" weight files for the Wave 4 Cohort contain weights for participants who completed an interview in Wave 4 and in Wave 8, regardless of their participation in the intervening waves. Note that only adults have "single-wave" weights for the Wave 1 and Wave 4 Cohorts; youth from the Wave 1 Cohort aged-up to adults by the time of Wave 8 and youth from the Wave 4 Cohort were selected as shadow youth so they do not have any interview data from Wave 4. The "single wave" weights files for the Wave 7 Cohort contain weights for participants who completed an interview in Wave 7 and in Wave 8.

There are also three separate sets of files with "special collection all-waves" weights: one for the Wave 1 Cohort, one for the Wave 4 Cohort, and one for the Wave 7 Cohort. The "special collection all-waves" weight files for the Wave 1 Cohort contain weights for participants who completed a Wave 8 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 1, 2, 3, 4, 5, 6, 7 and the special collections in Wave 4.5, Wave 5.5, and Wave 7.5. Note that only adults have "special collection all-waves" weights for the Wave 1 Cohort; youth from the Wave 1 Cohort aged-up to adults by the time of Wave 8. The "special collection all-waves" weight files for the Wave 4 Cohort contain weights for participants who completed a Wave 8 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Waves 4, 5, 6, 7, and the special collections in Wave 4.5, Wave 5.5, and Wave 7.5. The "special collection all-waves" weight files for the Wave 7 Cohort contain weights for participants who completed a Wave 8 interview and completed interviews (if old enough to do so) or verified their information (if not old enough to be interviewed) in Wave 7 and the special collection in Wave 7.5.

Dataset 8401 (DS8401) contains the Wave 8 State Identifier data for Adults and has 5 variables and 31,477 cases. Dataset 8402 (DS8402) contains the Wave 8 State Identifier data for Youth and Parents and has 5 variables and 8,002 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state FIPS, state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 8.

Dataset 8801 (DS8801) contains Location Characteristics for Wave 8 Adults. This data file contains 4 variables and 31,477 cases.

Dataset 8802 (DS8802) contains Location Characteristics for Wave 8 Youth. This data file contains 4 variables and 8,002 cases.

Each case in an Adult data file represents a single, completed interview. Each case in a Youth data file represents one youth and his or her parent's responses about that youth. Parents who provided permission for their child to participate in a Youth Interview were asked to complete a brief interview about their child. In all waves of data collection, less than 0.5 percent of the parents did not complete an interview. Most questions are asked about the child.

When multiple youth from the same household were selected to be in the study, the parent(s) completed separate interviews about each youth. If one parent completed two or more interviews, that parent only answered questions about himself/herself once. Those questions were then skipped in the subsequent interview(s) for the other child(ren) and the responses duplicated in that child(ren)'s data file(s).

HeyJay! is a restricted-access study consisting of speech audio files and associated metadata, including file-level annotations and participant-level information. HeyJay! is a new corpus of atypical speech from participants with neurodegenerative disorders, including Parkinson's Disease, Ataxias, or Amyotrophic Lateral Sclerosis.

The current corpus version contains more than 8,500 utterance recordings encompassing supervised transcriptions and intent annotations. Additionally, it includes speech quality ratings for each participant, performed by three expert speech and language pathologists. This corpus, the first one with intent annotation of atypical speech that is publicly available, is intended to create more fair speech technologies for atypical speakers by adapting and improving the state of the art and to enable further research in the field.

The Population Assessment of Tobacco and Health (PATH) Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study was launched in 2011 to inform the FDA's tobacco regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). For Wave 1 (baseline), the PATH Study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco, yielding interviews with 45,971 adult and youth respondents.

45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent.

At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled PSUs and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.

At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This second replenishment sample was combined for estimation and analysis purposes with Wave 7 adult and youth respondents from the Wave 4 Cohort who were at least age 15 and in the civilian, noninstitutionalized population at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort

Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts.

Biospecimen Collection

Each adult respondent, who completed the interview at Wave 1, was asked to provide at least two biospecimens. Providing biospecimens was voluntary and was not a condition of participation. Respondents were asked to report their use of all nicotine-containing products during the 3-day period prior to the time of any biospecimen collection (Nicotine Exposure Questions (NEQs)) to facilitate interpretation of biomarker results.

Of the 32,320 respondents who completed the Adult Interview at Wave 1, 21,801 (67.4 percent) provided a urine specimen and 14,520 (44.9 percent) provided a blood specimen. For the purposes of subsampling adults into the Wave 1 Biomarker Core, adult participants were grouped by tobacco product use at Wave 1 into nine mutually exclusive groups.

A sample of 11,522 adults who provided sufficient urine for the planned analyses were selected from the first six tobacco product use groups (see section 3.1 of the Biomarker Restricted-Use Files User Guide) representing people who never used tobacco, currently use tobacco, and formerly used tobacco (within the last 12 months). This group constitutes the original Wave 1 Biomarker Core. Of the 11,522 adults, 7,159 also provided a blood specimen. All urine and blood specimens provided by the Wave 1 Biomarker Core were sent for laboratory analysis.

Subsequent to this selection, an additional stratified probability sample of adults who completed the Wave 1 Adult Interview and provided a sufficient amount of urine for the planned analyses at Wave 1 (independent of whether they provided a blood specimen) was selected from the remaining three product use groups (see section 3.1 of the Biomarker Restricted-Use Files User Guide). Wave 1 blood and urine specimens from this expansion sample were also sent for laboratory analysis. The original and expansion samples together form the expanded Wave 1 Biomarker Core. The expansion sample did not provide urine specimens for laboratory analysis again until Wave 7.

Each youth who completed the Wave 4 interview was asked to provide a urine specimen. Each Wave 4 shadow youth (ages 10 and 11 at Wave 4) who completed the Wave 5 youth interview was also asked to provide a urine specimen. Providing this urine biospecimen was voluntary and was not a condition of participation.

Of the 14,798 respondents who completed the Youth Interview at Wave 4, 13,097 (88.5 percent) provided a urine specimen. A sample of 3,509 Wave 4 Cohort youth ages 12 to 17 who completed the Wave 4 Youth Interview and provided a sufficient amount of urine for the planned laboratory analyses was selected from a diverse mix of five tobacco product use and non-use groups. In addition, a sample of 528 Wave 4 shadow youth who completed a Wave 5 interview and provided a sufficient amount of urine for the planned laboratory analyses at Wave 5 was also selected. These 4,037 sampled youth and shadow youth constitute the Wave 4 Biomarker Core. All urine specimens provided by the Wave 4 Biomarker Core were sent for laboratory analysis.

As members of the Wave 1 and Wave 4 Biomarker Cores age over time, a new Wave 7 Biomarker Core was designed to provide nationally representative estimates for the U.S. civilian noninstitutionalized adult (ages 18 and older) population (CNP) at the time of Wave 7 (2022-2023). To that end, Aat the conclusion of Wave 7, a new biomarker core was selected from Wave 7 Cohort adults who completed an interview and provided a urine specimen at Wave 7. The Wave 7 Biomarker Core sample selection was a two-stage process. Prior to the start of data collection, a subsample of continuing participants expected to be adults at the time of their Wave 7 interview, including some participants who were part of the Wave 1 or Wave 4 Biomarker Cores, was selected and flagged for urine collection; additionally, a subsample of replenishment sample address was selected and flagged so that any Wave 7 Adult Interview respondents living at the selected addresses would be asked to provide a urine specimen. Of the 10,698 Adult Interview respondents from these subsamples, 9,187 (85.9 percent) provided a urine specimen. A sample of 7,750 Wave 7 Cohort adults who completed the Wave 7 Adult Interview and provided a sufficient amount of urine for the planned laboratory analyses was selected from six mutually exclusive and exhaustive tobacco use groups (see section 3.3 of the Biomarker Restricted-Use Files User Guide). All urine specimens provided by the Wave 7 Biomarker Core were sent for laboratory analysis.

Biomarker Restricted Use Files

Wave 1 Restricted-Use Biomarker Data Files (Biomarker RUF) consists of three different types of files for the Wave 1 Biomarker Core:

• 2 Collection and NEQ files for Urine (DS1001) and Blood (DS1101)
• 2 Biomarker Weight files including variables for use in variance estimation for Urine (DS1021) and Blood (DS1121). Both files are updated to include records for the expanded Wave 1 Biomarker Core.
• 8 Urine Panels (DS1031 to DS1038), 4 Serum Panels (DS1131 to DS1134) and 1 Plasma Panel (DS1231) containing biomarker assay results. 6 Urine Panels (DS1032, DS1033, DS1035, DS1036, DS1037, and DS1038) and 2 Serum Panels (DS1131 and DS1132) are updated to include records for the expanded Wave 1 Biomarker Core.

All files updated to include records for the expanded Wave 1 Biomarker Core contain an indicator R01_A_W1BC_TYPE (1 = Original, 2 = Expansion) to identify respondents in the Wave 1 Biomarker Core original and expansion subsamples.

For Wave 2, urine biospecimens were requested from the original Wave 1 Biomarker Core. Respondents were also asked to complete the NEQs prior to biospecimen collection.

The Wave 2 Biomarker RUF consists of three different types of files:

• 1 Collection and NEQ file for Urine (DS2001)
• 2 Biomarker Weight files including variables for use in variance estimation for Urine (DS2021) and F2PG2a (DS2022)
• 8 Urine Panels (DS2031 to DS2038) containing biomarker assay results.

For Wave 3, urine biospecimens were requested from the original Wave 1 Biomarker Core. Respondents were also asked to complete the NEQs prior to biospecimen collection.

The Wave 3 Biomarker RUF consists of three different types of files:

• 1 Collection and NEQ file for Urine (DS3001)
• 4 Biomarker Weight files including variables for use in variance estimation for Urine (DS3021 and DS3022) and F2PG2a (DS3023 and DS3024).
• 7 Urine Panels (DS3032 to DS3038) containing biomarker assay results.

For Wave 4, urine biospecimens were requested from the original Wave 1 Biomarker Core and all youth who completed the Wave 4 interview. Respondents were also asked to complete the NEQs prior to biospecimen collection.

The Wave 4 Biomarker RUF consists of the following files for each Biomarker Core:

Wave 1 Biomarker Core:

• 1 Collection and NEQ file for Urine (DS4001)
• 4 Biomarker Weight files including variables for use in variance estimation for Urine (DS4021 and DS4022) and F2PG2a (DS4023 and DS4024).
• 7 Urine Panels (DS4032, DS4033, DS4034, DS4035, DS4036, DS4037 and DS4038) containing biomarker assay results.

Wave 4 Biomarker Core:

• 1 Collection and NEQ file for Youth Urine (DS4011)
• 1 Biomarker Weight files including variables for use in variance estimation for Urine (DS4043)
• 7 Urine Panels (DS4051, DS4053, DS4054, DS4055, DS4056, DS4057 and DS4058) containing biomarker assay results.

For Wave 5, urine biospecimens were requested from the original Wave 1 Biomarker Core and the Wave 4 Biomarker Core. Respondents were also asked to complete the NEQs prior to biospecimen collection.

The Wave 5 Biomarker RUF consists of the following files for each Biomarker Core:

Wave 1 Biomarker Core:

• 1 Collection and NEQ file for Urine (DS5001)
• 4 Biomarker Weight files including variables for use in variance estimation for Urine (DS5021 and DS5022) and F2PG2a (DS5023 and DS5024)
• 6 Urine Panels (DS5032, DS5033, DS5035, DS5036, DS5037, and DS5038) containing biomarker assay results.

Wave 4 Biomarker Core:

• 1 Collection and NEQ file for Youth Urine (DS5011)
• 1 Collection and NEQ file for Adult Urine (DS5001)
• 1 Biomarker Weight file including variables for use in variance estimation for Urine (DS5042)
• 7 Urine Panels (DS5051, DS5053, DS5054, DS5055, DS5056, DS5057, and DS5058) containing biomarker assay results.

Note that the initial release of 3 Urine Panels and Biomarker weights for the Wave 4 Biomarker Core only included records for those among the 3,509 members who responded in Wave 5 and provided urine specimens in sufficient quantities for laboratory analyses. As of version 20, the Wave 5 biomarker data files and weights include data for all Wave 4 Biomarker Core members who provided urine specimens at Wave 5 in sufficient quantities for laboratory analyses, including the Wave 4 shadow youth who completed their first interviews at Wave 5. This means that records were added to previously released urine panel data files (DS5051, DS5053, and DS5056) and biomarker weights (DS5042) to include data for the Wave 4 shadow youth (N=528) who completed their first interviews at Wave 5. All panels released in version 20 and beyond will include records for the complete Wave 4 Biomarker Core.

Also note that the Collection and NEQ file for Adult Urine (DS5001) includes data for both the Wave 1 Biomarker Core and Wave 4 Biomarker Core.

For Wave 7, urine biospecimens were requested from the Wave 1 Biomarker Core, the Wave 4 Biomarker Core, and those in the subsample eligible for the Wave 7 biomarker Core. Respondents were also asked to complete the NEQs prior to biospecimen collection.

The Wave 7 Biomarker RUF consists of the following files for each Biomarker Core:

Wave 1 Biomarker Core:

• 1 Collection and NEQ file for Urine (DS7001)
• 4 Biomarker Weight files including variables for use in variance estimation for Urine (DS7021 and DS7022) and F2PG2a (DS7023 and DS7024)
• 6 Urine Panels (DS7032, DS7033, DS7035, DS7036, DS7037, and DS7038) containing biomarker assay results.

Wave 4 Biomarker Core:

• 1 Collection and NEQ file for Youth Urine (DS7011)
• 1 Collection and NEQ file for Adult Urine (DS7001)
• 2 Biomarker Weight files including variables for use in variance estimation for Urine (DS7041 and DS7042)
• 6 Urine Panels (DS7051, DS7053, DS7055, DS7056, DS7057, and DS7058) containing biomarker assay results.

Wave 7 Biomarker Core:

• 1 Collection and NEQ file for Urine (DS7001)
• 1 Biomarker Weight file including variables for use in variance estimation for Urine (DS7061)
• 6 Urine Panels (DS7072, DS7073, DS7075, DS7076, DS7077, and DS7078) containing biomarker assay results.

The Collection and NEQ file for Adult Urine (DS7001) includes data for the Wave 1 Biomarker Core, Wave 4 Biomarker Core, and Wave 7 Biomarker Core.

Please refer to the Biomarker Restricted-Use Files User Guide for additional information about the Biomarker Cores.

References to the collection of biospecimens will be specified by the collected specimen, i.e., urine and (whole) blood. However, references to biomarker analyses and analytes will be specified by the type of matrix (serum, plasma, or urine) used for the analysis.

The Toledo Adolescent Relationships Study (TARS) explores the relationship qualities and the subjective meanings that motivate adolescent behavior. More specifically, this study seeks to examine the nature and meaning of adolescent relationship experiences (e.g. with family, peers, and dating partners) in an effort to discover how experiences associated with age, gender, race, and ethnicity influence the meaning of dating relationships. The study further investigates the relative impact of dating partners and peers on sexual behavior and contraceptive practices, as well as involvement in other problem behaviors that can contribute independently to sexual risk-taking. The longitudinal design of the Toledo Adolescent Relationships Study (TARS) includes a schedule of follow-up interviews occurring one, three, five, ten, and about eighteen years after the initial interview. Additional waves have since been conducted.

Wave 2 of TARS includes data from follow-up surveys of adolescent respondents conducted approximately one year after the initial TARS survey. These data are accompanied by a series of weights for use in secondary analysis.

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). For Wave 1 (baseline), the study sampled over 150,000 mailing addresses across the United States to create a national sample of people who do and do not use tobacco.

45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete the Youth Interview after parental consent.

At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population (CNP) at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Units (PSUs) and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the CNP at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.

At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the CNP at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This second replenishment sample was combined for estimation and analysis purposes with Wave 7 adult and youth respondents from the Wave 4 Cohort who were at least age 15 and in the CNP at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort.

Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts.

Dataset 0001 (DS0001) contains the data from the Public-Use File Master Linkage File (PUF-MLF). This file contains 103 variables and 82,139 cases. The file provides a master list of every person's unique identification number and what type of respondent they were in each wave for data that are available in the Public-Use Files and Special Collection Public-Use Files.

Dataset 0002 (DS0002) contains the data from the Restricted-Use File Master Linkage File (RUF-MLF). This file contains 217 variables and 82,139 cases. The file provides a master list of every person's unique identification number and what type of respondent they were in each wave for data that are available in the Restricted-Use Files, Special Collection Restricted-Use Files, and Biomarker Restricted-Use Files.

This study is part of the Seek, Test, Treat and Retain (STTR) Collaboration Project that involved over twenty studies in the fields of HIV and drug abuse. All studies were independently developed, but were chosen for the collaboration because they focused on one or more steps of the HIV treatment cascade: Seek, Test, Treat and Retain. As part of STTR Collaboration Project, the studies were grouped into Criminal Justice-related studies and Vulnerable Population-related studies. The data collected by these studies included twelve common domains (e.g., Demographic characteristics, Mental Health) in each of which a shared questionnaire or instrument was taken up by the studies and adapted to fit the study.

This feasibility study tested the logistics and acceptance of the intervention and its evaluation tools against "usual care" conditions in preparation for a future randomized controlled trial. Specific aims included:

1. Demonstrating that recruitment and delivery of the intervention are feasible.
2. Demonstrating that enrolled releasees will link to HIV care by 3 months post release. A successful linkage to HIV medical care was defined as a confirmed visit to a clinic post release, validated by a recorded HIV viral load and CD4 count in the clinic's medical records.
3. Documenting retention in care, defined as a minimum of 2 HIV clinical visits occurring within 12 months post release, with at least 2 clinical visits spaced a minimum of 3 months apart. Related retention outcome measures included proportion with viral load suppression and, as needed, attendance at substance abuse rehabilitation, and mental health treatment.

Data was collected at baseline, and at 3 and 12 months post-release. The 1st and 2nd sessions occurred in jail and 4 post-release sessions in the community.

Under the Second Chance Act (SCA) of 2008, the U.S. Department of Justice (DOJ) Bureau of Justice Assistance (BJA) awarded hundreds of grants under various categories of competition to state, local, and tribal governments to develop or enhance re-entry programs. In 2018, the First Step Act was signed into law, helping to continue the financial support of the SCA program, among other reentry-focused services. While SCA programs have been operating for about 15 years, the research conducted on these programs and their services has been relatively short-term, examining outcomes on participants no more than a few years past the point of program enrollment. There had not yet been an examination of the long-term impacts of SCA services.

In 2021, DOJ's National Institute of Justice (NIJ) awarded a cooperative agreement to NORC at the University of Chicago (NORC) and its partner, Social Policy Research Associates (SPR), to evaluate the long-term impacts of seven SCA Adult Demonstration Program grantees, which were first awarded SCA funding in FY 2009. NORC and SPR, along with an additional partner, MDRC, previously evaluated these grantees by conducting an implementation study and a randomized controlled trial (RCT) impact study, with random assignment beginning in December 2011 (or approximately two years after the grantees began operating their SCA programs) and ending in March 2013. The results of this earlier evaluation were included in an implementation study report, an 18-month impact study report, based on a follow-up survey and administrative data, and a 30-month impact study report based on administrative data.

The goal of the current longitudinal research was to estimate the impacts of the SCA program on the outcomes of the original impact study participants, over the approximately ten to twelve years following the point when these participants were first randomly assigned. More specifically the current research has sought to assess:

1. whether SCA participants demonstrated better long-term outcomes related to recidivism (arrest, conviction, and incarceration) than did control group members;
2. whether SCA participants demonstrated better long-term employment and earnings outcomes than control group members
3. whether SCA participants demonstrated better long-term outcomes on other indicators of well-being (e.g., housing, family formation, benefits, substance abuse, etc.) than control group members.

To answer these questions the study team gathered both participant survey and administrative data.

• Survey data: Using a multi-phase process, the study team began administering a survey to study participants in late November 2021 and closed the survey on December 19, 2023. At that point, all pending respondents had been contacted by study team staff multiple times. The study team was able to complete 378 interviews during the entire survey data collection period.
• Criminal justice administrative data:The study team obtained arrest, conviction, and state prison and jail incarceration data from state and local public agencies (for the counties to which participants were released or served) in the six states and seven counties in which the seven grantees operated. The study team was able to collect these data from all agencies except two (arrest data in South Dakota and jail data from Oklahoma City). These data included all periods between random assignment and nearly ten years after random assignment for all participants.
• Employment and earnings administrative data: The study team was able to access data from the Department Health and Human Services' National Directory of New Hires database which allowed for the analysis of employment and earnings data for study participants over a two-year period from July 2022 to June 2024.

Survey and administrative data were used to answer the first two research questions with survey data being the only source for the third research question.

Nearly half of the law enforcement officers killed in the line of duty in the United States were due to automobile crashes. Driver distraction has been identified as a common causal factor leading to the crash, with the primary source of distractions being the mobile computer. While there is plenty of literature on officer safety, what is lacking is an understanding of the needs of the officers to interact with the control or communication equipment while driving and how that interaction impacts distraction and, consequently, officer safety. To examine these issues, the research team conducted focus group discussions with law enforcement officers from local, county, and state agencies in four states. The two primary topics of discussion were:

1. Officer requirements to operate different pieces of equipment while driving, and
2. Different software and systems being used in patrol cars.

Recently there has been an influx of changes in gun legislation in the United States. There is now a growing trend in states adopting "constitutional carry" laws, which allow citizens of legal age who have not been legislatively denied the right, to legally and publicly possess and carry a concealed firearm without a permit. As of April 2019, fifteen states have passed constitutional carry (i.e., permit-less) firearm legislation. Two additional states, Kentucky and Oklahoma, will become the 16th and 17th states to allow constitutional carry before the end of 2019, and additional states (e.g., Alabama) are currently considering adopting constitutional carry in the future. Though arguments for (e.g., deterrent effects) and against (e.g., increased exposure to firearms in public) the relaxation of concealed carry laws often cite the potential impact of such laws on public safety, a review of available research provides limited insight on the effects of constitutional carry legislation on crime, violence, and other outcomes. There is also little known about the impact of constitutional carry on changes in police-citizen encounters, officer safety, and changes in police training.

The proposed study seeks to fill this void in empirical knowledge through a multi-phase analytical approach using data gathered from three cities within two states that recently passed constitutional carry laws. Specifically, this study seeks to examine the impact of constitutional carry legislation on 1) firearm and offense counts in Lexington (KY), Oklahoma City (OK), and Tulsa (OK); 2) arrest reports related to firearm arrests; and (3) officer perceptions of safety, training, and police-citizen encounters. Each data source aligns with a specific analytic approach, including interrupted time series analysis and frequency/bivariate analyses

This study will contribute to the body of research using a strong multi-methodological approach, address a gap in rigorous empirical scholarship regarding the impact of gun legislation and crime and public/police safety.

The 2024 National Survey of Early Care and Education (2024 NSECE) is a set of four integrated surveys which include 1) households with children under age 13, 2) home-based early care and education (ECE) providers serving children under age 13, 3) center-based ECE providers serving children age 5 years and under (not yet in kindergarten), and 4) the center-based ECE workforce. Together, these surveys characterize the supply of and demand for ECE in the United States and permit a clearer understanding of how well families' needs and preferences coordinate with providers' offerings and constraints and the local ECE workforce. The NSECE surveys make particular effort to measure the experiences of low-income families, as these families are the focus of a significant component of ECE and school-age public policy.

The NSECE was first conducted in 2012. Before that effort, there had been a 20-year long absence of nationally representative data on the use and availability of ECE in the United States. The NSECE was conducted again in 2019 to update the information from 2012 and shed light on how the ECE and school-age care landscape changed from 2012 to 2019. To facilitate over-time comparisons, the 2024 NSECE largely replicates the design of the 2019 and 2012 NSECE, although all are cross-sectional surveys with no intentional overlap in sampled households, providers, or workers.

The 2024 NSECE was funded by the the Administration for Children and Families (ACF), United States Department of Health and Human Services (HHS). The project team was led by NORC at the University of Chicago, with partners including Child Trends and a Content Advisory Team of collaborating experts. Chapin Hall at the University of Chicago worked closely with NORC on the building of the provider sampling frame in 2023.

Level 2 restricted-use files are available via NORC. For more information, please see the instructions for NSECE Levels 2 Restricted-Use Data.

For additional information about this study, please see:

• NSECE project page on the OPRE website
• NSECE study page on NORC's website
• NSECE Data Users Page on NORC's website

For quick links to the User's Guides, please visit CFData's Data Training Resources from the NSECE page. In addition, users can select "Documentation Only" from the Download tab on this study homepage to download all NSECE documentation in one zip file. Researchers interested in applying for the Restricted-Use Data Files are encouraged to read the User's Guides before completing their application.