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Sponsored by the Robert Wood Johnson Foundation, the Active for Life (AFL) initiative investigated how two physical activity programs for adults aged 50 and older, Active Choices (AC) and Active Living Every Day (ALED), worked in community settings. Created by researchers at Stanford University, Active Choices used lifestyle counseling and personalized telephone support to encourage older adults to be physically active. In AFL, this was a 6-month program delivered through one face-to-face meeting followed by up to eight one-on-one telephone counseling calls. Active Living Every Day, which was created by the Cooper Institute and Human Kinetics Inc., also provided lifestyle counseling to promote physical activity, but in a classroom and workbook format. During the first three years of the four-year AFL initiative, ALED was delivered as a 20-week program where participants attended weekly small group meetings, but in the last year it was shortened to 12 weekly meetings. Nine organizations received AFL grants to implement the programs during 2003-2006. Four grantees implemented the one-on-one AC model, while five implemented the group-based ALED model.

Data were collected from the AC and ALED sites for both a process and outcomes evaluation. The primary aims of the process evaluation were to (1) monitor the extent to which the grantees demonstrated fidelity to the AC and ALED models in their program implementation, (2) assess staff experiences implementing the programs, and (3) assess participants' impressions of the programs. A quasi-experimental, pre-post study design was used to assess outcomes. Primary aims of the outcomes evaluation were to evaluate the impact of AC and ALED on self-reported physical activity, and to evaluate the impact of the programs on self-reported stress, depressive symptoms, and satisfaction with body function and appearance. Secondary aims of the outcome evaluation were to (1) evaluate the impact of the programs on measures of functional fitness, (2) examine whether changes in self-reported physical activity and functional fitness were moderated by participant characteristics, including age, gender, race, baseline physical activity self-efficacy, and baseline physical activity social support, and (3) examine whether changes in self-reported physical activity were consistent with a mediation model for physical activity self-efficacy and physical activity social support.

The collection has 14 data files (datasets). Datasets 1-7 constitute the process evaluation data, and Datasets 8-14 the outcomes evaluation data:

Dataset 1 (AC Initial Face-to-Face Sessions Data) contains information about the initial face-to-face AC session: the format, date, and length of the session, whether the 8 steps required in the face-to-face session were completed, what was discussed between the health educator and the participant related to physical activity plans, interests, benefits, and barriers, and the health educator's progress notes. The file contains one record for each AC participant.

Dataset 2 (AC Completed Calls Data) comprises information about the completed AC calls, but does not cover the topics discussed on the calls. Recorded information about each call includes the date and length of the call, the health educator's progress notes, and whether the participant was assessed for injury, light activity, moderate activity, exercise goals, or exercise intentions. Each call is represented by a separate record in the data file and, typically, there are multiple records per participant.

Dataset 3 (AC Topics Discussed on Completed Calls ) contains information about the topics discussed on each completed AC call, e.g., exercise barriers/benefits, previous exercise experiences, goal setting, long term goals, injury prevention, rewards/reinforcement, social support, progress tracking, and relapse prevention. Each record in the file represents one topic and there are often multiple records per call for each participant.

Dataset 4 (AC Aggregate Call Data) aggregates the call data across calls for each AC participant. For example, for a given participant, this dataset shows the total number of calls completed, the number of calls where injury/health problems were assessed, etc. The file contains one record per participant.

Dataset 5 (ALED Sessions Data) contains information about each class session for every ALED group, including the session date, start time, and end time, learning activities covered in the session, participant evaluations of the session and the facilitator, facilitator progress notes, the number of participants who were in various stages of readiness for moderate exercise, and the number of participants who tracked physical activity and thoughts about physical activity. This file has one record for each session of every ALED group.

Dataset 6 (ALED Attendance and Tracking Data (Years 2-4)) consists of participant-level attendance and tracking data for every ALED session during the second to fourth years of the evaluation, including the participant's attendance at the session, whether the participant's stage of readiness was assessed, and whether the participant tracked thoughts about physical activity or actual physical activity. There is no participant-level ALED data for the first year. Each participant has a separate record for each session. Thus, the file contains 20 records per participant in the years 2-3, and 12 records per participant in year 4.

Dataset 7 (ALED Aggregate Attendance and Tracking Data (Years 2-4)) contains ALED attendance and tracking data for each participant in years 2-4, aggregated across the sessions. The data file has one record for each participant.

Dataset 8 (Demographics) comprises program information (e.g., program status, start date, end date, site, etc.), demographic information (e.g., age, gender, race, Hispanic origin, employment status, income, and the participant's state and ZIP code of residence), and responses to the Physical Activity Readiness Questionnaire (PAR-Q), a screening tool that was used to assess possible risks of exercising based on answers to specific health history questions. The file contains one record for each AFL participant, except for those with a status of "nonstarter" or "repeater."

Datasets 9 (Pretest Survey Data) and 10 (Posttest Survey Data) contain data from the Pretest and Posttest Surveys. The Pretest Survey was administered at the beginning of the AC and ALED programs, while the Posttest Survey was administered at their end. Topics covered by the surveys include social and recreational activities, activities undertaken for exercise, perceived stress, depressive symptoms, satisfaction with body appearance and function, social support for physical activity, self-efficacy for physical activity, neighborhood environment, health conditions, health-related quality of life, caregiving, and self-reported height and weight. Both surveys included items from the Community Health Activities Model Program for Seniors Physical Activity Questionnaire (CHAMPS), the Center for Epidemiological Studies Depression Questionnaire (CES-D), the Behavioral Risk Factor Surveillance System Questionnaires (BRFSS), and the International Physical Activity Prevalence Study Environmental Module. These data files each have one record for each participant who submitted a questionnaire.

Dataset 11 (ALED Week 12 Survey Data (Year 4)) contains responses to the ALED Week 12 Posttest Survey, which was used to evaluate the 12-week adaptation of ALED in Year 4. (In Year 4, ALED participants completed both a 12- and 20-week posttest survey). There is one record for each participant who returned this survey.

Dataset 12 (Six-Month Posttest Follow-Up Survey Data (Years 3-4)) comprises data from a special 6-month follow-up survey which was administered in years 3-4 in six of the ALED sites and one of the AC sites. Participants were questioned about their current physical activities, weight, health-related quality of life, satisfaction with bodily function, and other topics. As with Datasets 9-11, the data file contains one record for each participant who returned a questionnaire.

Dataset 13 (Functional Fitness Tests Data) contains the results of pretest and posttest functional fitness tests which were administered by one ALED grantee. Four tests were adminstered: (1) the 30-Foot Walk Test, (2) the 30-Second Chair Stand, (3) 8-Foot Up and Go, and (4) the Chair Sit and Reach Test. This participant-level data file also includes pretest height measurements plus pretest and posttest weight measurements.

Dataset 14 (Participants' Impressions of the Programs (Years 1, 3, and 4)) contains data collected by the last sections of the Posttest Survey, ALED Week 12 survey, and 6-Month Follow-up Survey. The topics it covers include the participants' impressions of the programs, participation in physical activities, and changes (compared to before they started the AFL program) in motivation to be physically active, actual level of physical activity, medical and health conditions, overall pain, flexibility/limberness, level of stress, happiness, and enjoyment of life. The file has a separate record for each survey completed by the participants. Thus, there are 1-3 records per participant.

The data producers have recompiled the ACTIVE data into a new study which is available as of December 2023, ICPSR 38821; data users should plan to use study 38821 instead.

ACTIVE (Advanced Cognitive Training for Independent and Vital Elderly), 1999-2001 [United States] was a multisite randomized controlled trial conducted at six field sites with New England Research Institutes (NERI) as the coordinating center. The field sites included the University of Alabama at Birmingham, Hebrew Rehabilitation Center for the Aged in Boston, Indiana University, Johns Hopkins University in Baltimore, Pennsylvania State University, and the University of Florida/Wayne State University (Detroit). The primary aim of the trial was to test the effects of three distinct cognitive interventions -- previously found to be successful in improving elders' performance on basic measures of cognition under laboratory or small-scale field conditions -- on measures of cognitively demanding daily activities. Trainings consisted of an initial series of ten group sessions followed by four-session booster trainings at one and three years. The three cognitive interventions focused on memory, executive reasoning, and speed of processing. The design included a no-contact control group. Participants were assessed at baseline, immediately after training, and annually thereafter. A total of 2,832 older adults were enrolled in the trial, and 2,802 were included in the analytical sample. Twenty-six percent of the participants were African American.

The Helping Young Smokers Quit (HYSQ) initiative was a multi-phase project that addressed the critical need to disseminate effective, developmentally appropriate cessation programs for young smokers. Phase I identified and described tobacco treatment programs available for youth in the United States, Phase II evaluated smoking secession programs tailored for youth to help understand what works, and Phase III identified factors associated with program sustainability. Phase II collected data from five sources: (1) program participants, (2) program providers, (3) program curricula, (4) organizational leaders, and (5) community leaders and community ordinances.

Program participants were interviewed at baseline, end-of program, 6-month follow-up, and 12-month follow-up. Topics covered by the interviews include age, gender, race, Hispanic origin, language spoken at home, employment, income, religiosity, school enrollment, education level, school grades, height, weight, extracurricular activities, recreation, sports, exercise, aspirations after high school, psychological well-being, alcohol consumption, cigarette use and use of other tobacco products, attitudes about smoking, plans to stop/continue smoking, attempts to quit smoking, reasons for participating in the program, topics/issues covered by the program, opinions about the program, and smoking experience since the beginning of the program. In addition, for each follow-up survey, the participants provided a breath sample for carbon monoxide analysis to validate self-reported quit status.

After the last session of each program delivery, the program providers, such as program leaders and cessation counselors, were interviewed about the content and delivery of the program and the reactions of the participants and themselves to the program as delivered. The program providers also kept attendance records.

Curriculum content was abstracted from program manuals and other materials used in each program.

Organizational leaders of the organizations that offered the programs were surveyed about various aspects of each organization, including the organization's smoking cessation program and the organization's mission, general operations, and smoking-related policies and practices.

Community-level information was collected in two ways: (1) interviews of community leaders representing local health departments, school boards, and juvenile justice offices, and (2) archival research of public ordinances relevant to tobacco and control policies.

Nine data files/datasets constitute the data. Datasets 1-4 contain the participant questionnaire data, carbon monoxide measurement data, and program attendance data. Dataset 5 comprises information about each program and its curriculum, some information about the community in which the program was located, and summary data about enforcement of tobacco-related ordinances. Dataset 6 contains information about about the program providers and each program delivery, including recruitment, logistics, content, and the reactions of providers and participants. Dataset 7 covers administrative aspects of the smoking cessation programs and each offering organization's mission, general operations, and smoking-related policies and norms. Dataset 8 contains information about local and state-level tobacco-related ordinances for every state and local jurisdiction where each program was located, and Dataset 9 condenses the information in Dataset 8 into one summary record for each community. The unit of observation for Datasets 1-4 is the participant, for Datasets 5 and 7 the smoking cessation program/offering organization, for Dataset 6 the program delivery/program cohort, for Dataset 8 the ordinance, and for Dataset 9 the community.

The Moving to Opportunity (MTO) program was a randomized housing experiment administered by the United States Department of Housing and Urban Development (HUD) that gave low-income families living in high-poverty areas the chance to move to lower-poverty areas. This Restricted Access Dataset (RAD) includes data from the 3,273 adults interviewed as part of the MTO long-term evaluation and is comprised of variables analyzed for the article "Neighborhood Effects on the Long-Term Well-Being of Low-Income Adults" that was published in the journal Science on September 21, 2012. The article focused on subjective well-being, physical and mental health, social networks, neighborhoods, housing, and economic self-sufficiency. Families were tracked from the baseline survey (1994-1998) through the long-term evaluation survey fielding period (2008-2010) with the purpose of determining the effects of "neighborhood" on participating families from five United States cities. Households were randomly assigned to one of three groups:

1. The low-poverty voucher (LPV) group (also called the experimental group) received Section 8 rental assistance certificates or vouchers that they could use only in census tracts with 1990 poverty rates below 10 percent. The families received mobility counseling and help in leasing a new unit. One year after relocating, families could use their voucher to move again if they wished, without any special constraints on location.
2. The traditional voucher (TRV) group (also called the Section 8 group) received regular Section 8 certificates or vouchers that they could use anywhere; these families received no special mobility counseling.
3. The control group received no certificates or vouchers through MTO, but continued to be eligible for project-based housing assistance and other social programs and services to which they would otherwise be entitled.

The dataset contains all outcomes and mediators analyzed for the Science article, as well as a variety of demographic and other baseline measures that were controlled for in the analysis. Demographic information includes age, gender, race/ethnicity, employment status, and education level.

Nearly 9 million Americans live in extreme-poverty neighborhoods, places that also tend to be racially segregated and dangerous. Yet, the effects on the well-being of residents of moving out of such communities into less distressed areas remain uncertain. Moving to Opportunity (MTO) is a randomized housing experiment administered by the United States Department of Housing and Urban Development that gave low-income families living in high-poverty areas in five cities the chance to move to lower-poverty areas. Families were randomly assigned to one of three groups:

1. The low-poverty voucher (LPV) group (also called the experimental group) received Section 8 rental assistance certificates or vouchers that they could use only in census tracts with 1990 poverty rates below 10 percent. The families received mobility counseling and help in leasing a new unit. One year after relocating, families could use their voucher to move again if they wished, without any special constraints on location.

2. The traditional voucher (TRV) group (also called the Section 8 group) received regular Section 8 certificates or vouchers that they could use anywhere; these families received no special mobility counseling.

3. The control group received no certificates or vouchers through MTO, but continued to be eligible for project-based housing assistance and whatever other social programs and services to which they would otherwise be entitled.

Families were tracked from baseline (1994-1998) through the long-term evaluation survey fielding period (2008-2010) with the purpose of determining the effects of "neighborhood" on participating families. These particular files include data from the 3,273 adult interviews completed as part of the MTO long-term evaluation and are comprised of variables analyzed for the article "Neighborhood Effects on the Long-Term Well-Being of Low-Income Adults" that was published in the journal Science on September 21, 2012. Using data from the long-term evaluation, the article reports that moving from a high-poverty to lower-poverty neighborhood leads to long-term (10- to 15-year) improvements in adult physical and mental health and subjective well-being, despite not affecting economic self-sufficiency. Subjective well-being is more strongly affected by changes in neighborhood economic disadvantage than racial segregation, which is important because racial segregation has been declining since 1970, but income segregation has been increasing. The files submitted here contain all outcomes and mediators analyzed for the article as well as a variety of demographic and other baseline measures that were controlled for in the analysis.

The purpose of the study was to assess the impact of Latino ethnicity on pretrial release decisions in large urban counties. The study examined two questions:

• Are Latino defendants less likely to receive pretrial releases than non-Latino defendants?
• Are Latino defendants in counties where the Latino population is rapidly increasing less likely to receive pretrial releases than Latino defendants in counties where the Latino population is not rapidly increasing?

The study utilized the State Court Processing Statistics (SCPS) Database (see STATE COURT PROCESSING STATISTICS, 1990-2004: FELONY DEFENDANTS IN LARGE URBAN COUNTIES [ICPSR 2038]). The SCPS collects data on felony cases filed in state courts in 40 of the nation's 75 largest counties over selected sample dates in the month of May of every even numbered year, and tracks a representative sample of felony case defendants from arrest through sentencing. Data in the collection include 118,556 cases.

Researchers supplemented the SCPS with county-level information from several sources:

• Federal Bureau of Investigation Uniform Crime Reporting Program county-level data series of index crimes reported to the police for the years 1988-2004 (see UNIFORM CRIME REPORTS: COUNTY-LEVEL DETAILED ARREST AND OFFENSE DATA, 1998 [ICPSR 9335], UNIFORM CRIME REPORTING PROGRAM DATA [UNITED STATES]: COUNTY-LEVEL DETAILED ARREST AND OFFENSE DATA, 1990 [ICPSR 9785], 1992 [ICPSR 6316], 1994 [ICPSR 6669], 1996 [ICPSR 2389], 1998 [ICPSR 2910], 2000 [ICPRS 3451], 2002 [ICPSR 4009], and 2004 [ICPSR 4466]).
• Bureau of Justice Statistics Annual Survey of Jails, Jurisdiction-Level data series for the years 1988-2004 (see ANNUAL SURVEY OF JAILS: JURISDICTION-LEVEL DATA, 1990 [ICPSR 9569], 1992 [ICPSR 6395], 1994 [ICPSR 6538], 1996 [ICPSR 6856], 1998 [ICPSR 2682], 2000 [ICPSR 3882], 2002 [ICPSR 4428], and 2004 [ICPSR 20200]).
• Bureau of Justice Statistics National Prosecutors Survey/Census data series 1990-2005 (see NATIONAL PROSECUTORS SURVEY, 1990 [ICPSR 9579], 1992 [ICPSR 6273], 1994 [ICPSR 6785], 1996 [ICPSR 2433], 2001 census [ICPSR 3418], and 2005 [ICPSR 4600]).
• United States Census Bureau State and County Quickfacts.
• National Center for State Courts, State Court Organization reports, 1993 (see NCJ 148346), 1998 (see NCJ 178932), and 2004 (see NCJ 212351).
• Bureau of Justice Statistics Felony Defendants in Large Urban Counties reports, 1992 (see NCJ 148826), 1994 (see NCJ 164616), 1996 (see NCJ 176981), 1998 (see NJC 187232), 2000 (see NCJ 202021), and 2002 (see NJC 210818).

The data include defendant level variables such as most serious current offense charge, number of charges, prior felony convictions, prior misdemeanor convictions, prior incarcerations, criminal justice status at arrest, prior failure to appear, age, gender, ethnicity, and race. County level variables include region, crime rate, two year change in crime rate, caseload rate, jail capacity, two year change in jail capacity, judicial selection by election or appointment, prosecutor screens cases, and annual expenditure on prosecutor's office. Racial threat stimuli variables include natural log of the percentage of the county population that is Latino, natural log of the percentage of the county population that is African American, change in the percentage of the county population that is Latino over the last six years and change in the percentage of the county population that is African American over the last six years. Cross-level interaction variables include percentage minority (Latino/African American) population zero percent to 15 percent, percentage minority (Latino/African American) population 16 percent to 30 percent, and percentage minority (Latino/African American) population 31 percent or higher.