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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.

This data collection was created to study agenda-setting and alternative specification in the federal government. It concentrates on two federal policy areas, health and transportation, but the theories generated in the research may be quite widely applicable beyond those two areas. The aim of the work was not to study how issues are decided in some authoritative process like a congressional vote, but instead to study how issues get to be issues in the first place, how items rise and fall on the governmental agenda, and how the alternatives from which choices are made are generated.

The results of the study were published in John W. Kingdon, Agendas, Alternatives, and Public Policies (First Edition, Little Brown, 1984; Second Edition, HarperCollins, 1995; Longman Classics in Political Science Edition, Longman, 2003; Updated Second Edition, with Epilogue on Health Care Reform, Longman, 2011). The study's methods are described in detail in the Appendix to that book, and are included as part of the documentation for this data collection.

The major data source is a set of interviews that John Kingdon conducted in four waves (the summers of 1976, 1977, 1978, and 1979), with well-informed respondents either in the federal government (both congressional and executive) or involved in health or transportation policy around the federal government (e.g., lobbyists, journalists, academics, consultants). "Elite and specialized" interviews, to use Lewis Dexter's terminology (see Elite and Specialized Interviewing, Northwestern University Press, 1969), are conducted differently than standard survey research interviewing. The idea is to have a two-way conversation with a well-informed and highly involved respondent, rather than strict question and response. As such, the list of questions used was not a hard-and-fast interview schedule or questionnaire, but a kind of guide. The questions were not always asked in the same order, and indeed, not all of the questions were always asked. Question wording may have varied slightly from one interview to another. Various ad hoc probes were inserted as they seemed appropriate. Sometimes in this sort of interview, the interviewer makes a statement rather than asking a question. Still, the central questions were usually asked in roughly the same wording. Thus, when the interview write-up says "Q1," that is the first question in the standard list of questions used.

Interviews were not taped or otherwise recorded verbatim, since the principal investigator firmly believed that, with these sorts of respondents, taping dampened their ability and willingness to be candid. The principal investigator did not want respondents to feel that they were on the record, as respondents were accustomed to dealing with reporters, and when a microphone was in their face, they knew the encounter would be on the record. Notes were taken during the interview, and then written up immediately after; hence, the typescripts of the interviews are labeled "write-up" instead of "transcript." All 247 write-ups have a respondent identification number and the date of the interview on the top of the first page.

The principal investigator also coded the interview write-ups into quantitative data files, despite the nonrandom selection of respondents and the fluid conduct of the interviews. He did this to support quantitative judgments (e.g., "this issue was mentioned frequently in 1978 and not frequently in 1979," or "this factor was hardly ever mentioned in the interviews"). Each interview was coded by two coders, and then their judgments were combined. In addition to generic identifying information, there are two general categories of variables. One category, referred to as "global codes" in the codebook, is composed of ratings of the importance of each of several actors (e.g., mass media, president himself, interest groups, congressional staffers). The other category, referred to as "problem codes" is a coding of the problems that respondents discussed in their interviews, and is divided into health and transportation. A full description of coding procedures is contained in the data collection documentation.

Interview data are supplemented by a series of 23 case studies in health and transportation, and by some attention to other sources of data like congressional hearing records and public opinion data. In addition to various nonquantitative uses of the cases in the study, a quantitative dataset of the case studies was created. Two coders worked independently to judge each of a set of hypothesized influences in the case to be very important, somewhat important, of little importance, or not important. For example, after reading all of the materials for a given case study, a coder would rate the importance of congressional staffers as "very, somewhat, of little, or not" important. In contrast to the interviews, differences between the two coders were not resolved by a combination rule. Instead, the principal investigator and the two coders discussed and reached consensus in each instance in which there had been a disagreement. A full description of coding procedures is contained in the data collection documentation.

The American Health Values Survey (AHVS) was conducted by the National Opinion Research Center (NORC) at the University of Chicago in order to develop a typology of Americans based on their health values and beliefs. The survey, of more than 10,000 adults from five individual communities, examined values and beliefs related to health at both the individual as well as societal levels. The community surveys sought to compare differences between the local typologies, but also to investigate any similarities with national typology groups. The survey assessed the importance of health in:

• day-to-day personal life (i.e. the amount of effort spent on disease prevention as well as appropriate seeking of medical care);
• equity, the value placed on the opportunity to succeed generally in life as well as on health equity;
• social solidarity, the importance of taking into account the needs of others as well as personal needs;
• health care disparities, views about how easy/hard it is for African Americans, Latinos and low-income Americans to get quality health care;
• and, the importance of the social determinants of health.

In addition, the survey also explored views about how active government should be in health; collective efficacy, the ease of affecting positive community change by working with others; and health-related civic engagement e.g. the support of health charities and organizations working on health issues.

There are public-use and restricted-use versions of the data provided for each of the five sentinel communities participating in this study. Although each site differs on the number of respondents as listed below, each data file contains the same 143 variables for each site and version of the data. The only difference between the public-use versus restricted-use versions of the data is the variable ZIP, which was MASKED in the public-use version.

• DS1 and DS2 - Baltimore, Maryland: 2,139
• DS3 and DS4 - Maricopa County, Arizona: 2,247
• DS5 and DS6 - Stockton, California: 2,127
• DS7 and DS8 - Mobile, Alabama: 1,821
• DS9 and DS10 - North Central counties in Nebraska: 2,846

The Robert Wood Johnson Foundation (RWJF) has a vision to build a Culture of Health (CoH) by making health a shared national priority, one valued and advanced by multiple stakeholders across all sectors of society. This vision embraces a very broadly integrated and comprehensive approach to health, one where well-being lies at the center of every aspect of American life. In 2014, the RWJF commissioned NORC at the University of Chicago to plan and conduct the first American Health Values Survey (AHVS) to understand the extent to which United States adults held views consistent with this vision. The idea was to explore which types of United States adults were more supportive and less supportive of the goal and what the differences were between the more and less supportive groups. To aid in the understanding of these differences, NORC developed a typology of United States adults based on their values and beliefs related to the CoH vision.

Using a large-scale national survey fielded in late 2015 and early 2016, NORC identified six major segments of the population of adults in the United States based on their differing health values and beliefs and developed detailed profiles of each segment that described their pattern of values and beliefs as well as their demographic, political and other characteristics. NORC subsequently replicated the typology development work in five RWJF Sentinel Communities across the nation and also developed a typology of rural America. The same segments, or similar ones, were common across various geographic areas of the United States. Four years have since passed, in which changes occurred in the country. RWJF in 2019 commissioned NORC to conduct a second national, cross-sectional survey (AHVS II) in late 2019 and early 2020.

This is a collection of 2,888 clinical MRIs of patients admitted at a National Stroke Center, over ten years, with clinical diagnosis of acute or early subacute stroke. The collection includes diverse MRI modalities and protocols. The infarct core was manually defined in the diffusion weighted images; the images are provided in native subject space and in standard space (MNI), in Neuroimaging Informatics Technology Initiative (NIfTI) format. The data format and organization follows Brain Imaging Data Structure (BIDS) guidelines. The collection includes diverse metadata, comprised of demographic information, basic clinical profile (NIH Stroke Scale/Score (NIHSS), hospitalization duration, blood pressure at admission, BMI, and associated health conditions), and expert description of the acute lesion. This resource provides high quality, large scale, human-supervised knowledge to feed artificial intelligence models and enable further development of tools to automate several tasks that currently rely on human labor, such as lesion segmentation, labeling, calculation of disease-relevant scores, and lesion-based studies relating function to frequency lesion maps.

The dataset is divided in folders with 60-70 subjects. Each folder contains the "raw data" (multimodal MRIs, in native space), "DWI-mask" (manually-defined lesion masks, brain masks, and 3D DWI, b0, and recalculated ADC), "DWI-MNI-IntensityNormalized" (DWI and lesion masks in MNI coordinates), and "phenotype" (individual ".tsv" files with metadata of each subject). The "templates" folder contains images averages and lesion frequency maps. The "documentation" contains comprehensive data documentation, the phenotypes of the whole dataset, and the data dictionary.

The Annual Health Survey (AHS), conducted by the Government of India between July 2010 and May 2013, investigates maternal and child health in nine states: Assam, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttarakhand, and Uttar Pradesh. These states constitute about 70 percent of neonatal deaths in India and about one-in-five neonatal deaths globally. The AHS consists of a three-round panel that interviewed over 4 million households in each round, as well as a one-time Clinical, Anthropometric, and Bio-Chemical Survey (CAB). The data were originally released to the public in 2015 as a set of 45 .csv files. The .csv files are included in a restricted-use zipped package as part of the ICPSR release (see dataset 21).

The survey focused on topics such as household composition, caste, fertility, family planning, pre- and post-natal care, breastfeeding, infant mortality, illness, disease, disability, and health care practices. Demographic information includes sex, age, education, occupation, marital status, household size, and religion. The CAB files contain biometric data including but not limited to height, weight, blood pressure, hemoglobin, pulse, and blood glucose.

Potential data users should note that the public-use and restricted-use versions of the datasets are the same except for the masking of day component variables for certain dates in the public-use versions of the files (please see the Description of Variables section for full details). Therefore, only researchers with a limited set of research questions that require full birth, marriage, and death dates will need to apply for the restricted-use versions of the data files.

Additionally, because the final data files are very large and potentially very time consuming to analyze on personal computers, researchers have the option to download ten-percent samples of each file (see datasets 3, 4, 7, 8, 11, 12, 15, 16, 19, and 20). These samples contain the same variables as the original files but only ten percent of the records. The samples were determined by taking a randomly selected ten percent of households in each district. P.I. codebooks were not produced for these samples. Please note that the ten-percent samples for each dataset were selected independently, so it is not advised to merge across datasets within the AHS using these samples, as the match rates will be very low.

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The Army Study to Assess Risk and Resilience in Servicemembers (STARRS) is an extensive study of mental health risk and resilience among military personnel. Army STARRS consists of eight separate but integrated epidemiologic and neurobiologic studies. Survey data for three of the Army STARRS study components are available via Secure Dissemination or via the ICPSR Virtual Data Enclave: New Soldier Study (NSS); All Army Study (AAS) and Pre-Post Deployment Study (PPDS). Also available are data for the STARRS-Longitudinal Study (STARRS-LS), which are follow-up surveys conducted with Army STARRS participants from AAS, NSS and PPDS studies. Lastly, baseline administrative data from the Army/Department of Defense (DoD) and blood sample flags for Soldiers who had blood drawn as a part of their participation in NSS or PPDS are available.

The AAS component of Army STARRS assesses soldiers' psychological and physical health, events encountered during training, combat, and non-combat operations, and life and work experiences across all phases of Army service. The AAS data includes data on soldiers' psychological resilience, mental health, and risk for self-harm.

The NSS data are drawn from new soldiers who have just entered the Army. The data contain information on soldier health, personal characteristics, and prior experiences. Results from a series of neurocognitive tests are also included in the NSS data.

The PPDS data are drawn from active duty soldiers who were interviewed at four points in time: 3-4 months prior to deployment to Afghanistan; within 1-2 weeks after return from deployment; 1-3 months after return from deployment; and 9-12 months after return from deployment. The PPDS data contain information on soldiers' psychological resilience, mental health, deployment experiences, and risk for self-harm.

The STARRS-LS data are from multiple follow-up interviews with individuals who previously participated in the AAS, NSS and PPDS study components of Army STARRS. STARRS-LS data contain follow-up information on soldiers' and veterans' physical and mental health, resilience and risk for self-harm, military and employment status, deployment experience, and personal characteristics as they move through their Army careers and after they leave the Army.

The main objective of this pragmatic randomized clinical trial (PCT) is to identify the optimal dose of aspirin for secondary prevention in atherosclerotic cardiovascular disease (ASCVD). A total of 15,076 high-risk patients with a history of a myocardial infarction (MI) or documented ASCVD were randomized in a 1:1 ratio to receive 81 mgs versus 325 mgs of aspirin every day. This trial addressed the following specific aims:

1. To compare the effectiveness of two doses of aspirin (81 mg and 325 mg) in reducing a composite of all-cause mortality and hospitalization for nonfatal MI, or nonfatal stroke, and the primary safety endpoint of major bleeding. Secondary endpoints include the components of the primary endpoint and hospitalization for transient ischemic attack, unstable angina, or coronary revascularization procedures.
2. To compare the effects of aspirin in selected subgroups of patients by sex, age, race, Internet users vs. non-users, and those with diabetes or advanced chronic kidney disease (CKD).
3. To develop and refine the infrastructure for PCORnet to conduct multiple comparative effectiveness trials in the future.
4. To explore biological mediators of heterogeneity of response to aspirin and of impact on clinical events.

The Bangladesh Environment and Migration Survey (BEMS) collects detailed retrospective information about migration trips in southwest Bangladesh, including the first, last, and second-to-last to internal destinations, India, and other international destinations. BEMS collects information about the year, origin, destination, and duration of all trips. Furthermore, BEMS includes information on migration and livelihood histories, socioeconomic conditions, agricultural resources and practices, disasters and perceptions about environment, and self-reported health.

Dataset 1 is a household-level file with information about household composition, economic and migratory activity of household members, land ownership/usage, business ownership, household environmental perceptions, environmental conditions, agricultural activities, and physical and psychological health/well-being of household members. Dataset 2 is an individual-level file containing details of internal and international migration trips, as well as measures of economic and social activity during those trips. It also contains information provided by household heads, spouses, and other migrants in the household. Dataset 3 is an individual-level data file that provides general demographic information and brief migration history for each member of a surveyed household. It also includes health information for the head of household and spouse.

The overall goal for this project was to reduce the incidence of COVID-19, hospitalization, and mortality among adults with serious mental illness (SMI) and intellectual disabilities/developmental disabilities (IDD) in congregate living settings (i.e., group homes) in Massachusetts, as well as to reduce COVID-19 incidence among staff who work in these settings. The research team was guided by two comparative effectiveness questions:

1. With the goal of prioritizing and making actionable best practices available as resources, what is the comparative effectiveness of various types and intensities of preventative interventions (e.g., screening, isolation, contact tracing, hand hygiene, physical distancing, use of face masks) in reducing rates of COVID-19, related hospitalizations, and related mortality in this population?
2. With the goal of effectively implementing best practices, what is the most effective implementation strategy to reduce rates of COVID-19 in this population: using tailored best practices (TBP) with SMI/IDD residents and staff of group homes in mind, or general best practices (GBP) from state and federal standard guidelines for all congregate care settings?

The specific aims of this study were as follows:

Aim 1a. Synthesize existing baseline data collected by 6 state behavioral health agencies on COVID-19 rates, hospitalization, mortality, and use of infection prevention practices.

Aim 1b. Collect stakeholder input via surveys and virtual focus groups on staff and resident experiences and on barriers/facilitators to implementing recommended preventative practices.

Aims 2a and 2b. Determine the comparative effectiveness of various COVID-19 preventative practices by (Aim 2a) using a validated simulation model to estimate COVID-19 spread in group homes and (Aim 2b) obtaining stakeholder input on prioritizing and defining tailored best practices for implementation.

Aim 3. Compare the effectiveness of TBPs with GBPs by using a hybrid effectiveness-implementation cluster randomized controlled trial.

Data collected to answer Aims 1 and 2 served as the foundation for designing the Aim 3 trial. Data for the trial were collected in 3-month intervals beginning January 2021 (baseline) until October 2022 (15-month follow-up). Residents and staff were sampled from approximately 400 group homes. Primary implementation outcome measures were COVID-19 vaccination rates and fidelity scores. The primary effectiveness outcome measure was COVID-19 infection.

Notes: This collection contains only data from Aim 1a and Aim 3. Throughout the data and documentation, "intellectual and/or developmental disabilities" is abbreviated as both IDD and ID/DD.

The Black Rural and Urban Caregivers Mental Health/Functioning data collection includes survey data collected in 2000-2002 from African American females age 65 and older, who provide unpaid care for older African American adults in the St. Louis Metropolitan area and seven rural Missouri counties (Butler, Dunklin, Mississippi, New Madrid, Pemiscot, Scott, and Stoddard).

Because of inadequate recruitment knowledge about rural African American caregivers and persistent reports of challenges when involving African Americans elders in research, this study focused on the involvement of African American rural elders and recruitment of their female informal caregivers in a study of caregivers' well-being and service use. African Americans comprise the largest group of ethnic and racial minority elders aged 65 and older in the U.S. population thus making up one half of all ethnic and racial minority elders. Numerical changes in population size and increasing longevity of older African Americans direct attention to African American informal female caregivers- persons most likely to assist African American elderly with daily living tasks, personal needs, and long-term care. More disabled and chronically ill African American elders portend continuing need from informal or unpaid caregivers for dependent care.

There are two datasets associated with this study, a public-use (da36349-0001) and restricted-use (da36349-0002) version of the same survey data. Both data files contain 521 cases and 1438 variables. However, the restricted file contains continuous as opposed to categorical values for age variables rounded to the nearest whole number.

Oral contraceptive (OC) users living in El Paso, Texas were interviewed to assess motivations for patronizing a United States clinic or a Mexican pharmacy with over-the-counter (OTC) pills and to determine which women were likely to use the OTC option. The experiences of OC users who obtained their contraception from Mexican pharmacies were compared with those of women who obtained their pills from family planning clinics in El Paso, Texas, where eligible low-income women often pay nothing. 532 clinic users and 514 pharmacy users were surveyed about background characteristics, motivations for choosing their oral contraception source, and satisfaction with this source. For more information, please see the Border Contraceptive Access Study website.

The Boston Reentry Study (BRS) was a mixed-methods, longitudinal study of 122 men and women released from Massachusetts state prisons to the Boston area, that focused on the transition into the community during participants' first year after prison release. The original data collection combined a panel survey, qualitative interviews, interviews with family members, and administrative records on criminal history. The BRS examined the complexity of integration after incarceration drawing from participants' life histories, including childhood experiences, to understand how individual biographies shape the transition into the community. This collection includes responses to 5 survey waves: (1) baseline, about one week before release from prison, (2) 1 week after prison release, (3) 2 months after prison release, (4) 6 months after prison release, and (5) 12 months after prison release. The survey collected information on housing, employment, income, health, family relationships, and criminal justice system contact.

CCPC's long term vision is to use pragmatic comparative effectiveness methods, linked to an extensive primary care practice data repository, to establish evidence about best practices for complex real world patients and deliver appropriate, real-time decision support at point of service for primary care practitioners (PCPs) in a way that will account for individualized management of conditions and choice of treatments in order to provide optimal care.

The primary aim of BICEP was to advance analytical methods of observational Comparative Effectiveness Research (CER) to support evidentiary needs of primary care practitioners in answering important questions related to care of patient populations with Multiple Complex Conditions (MCCs).

The secondary aim of BICEP was to conduct a pilot study to demonstrate the feasibility and value of using the analytic methods for conducting CER among complex patients.

BICEP sought to answer the following clinical research questions: In adults with Type 2 Diabetes Mellitus (T2DM) coupled with additional chronic diseases,

1. What is the comparative effectiveness of T2DM medications in achieving glycemic control?
2. What is the comparative effectiveness of T2DM medications on intermediate outcomes, adverse events, side effects, tolerability?
3. Does the effectiveness and safety of the diabetic treatment options differ across subgroups of patients based on patient demographic characteristics, complex co-morbidities, or the use of other concurrent therapies?

The Burn Injury Model Systems National Longitudinal Database is a prospective, longitudinal, multicenter research study that examines functional and psychosocial outcomes following burns for over 3,000 adults and 2,000 children. The BMS National Database consists of data collected from individuals with moderate to severe burn injury; these data are collected by institutions across the country to learn more about long term outcomes after a burn injury.

The objective of the database is to provide a core set of variables which support rigorous research that:

1. Contributes to improved care and outcomes of individuals (both adult and pediatric) with severe burns.
2. Contributes to evidence-based rehabilitation interventions and clinical and practice guidelines that improve the lives of individuals with severe burns.
3. Studies the longitudinal course of severe burn injuries and their secondary effects and factors that affect that course.
4. Identifies and evaluates trends over time in etiology, demographics, injury severity characteristics, treatment of burns, health services delivery, and short-term and long-term outcomes of persons who incur a severe burn.
5. Establishes expected rehabilitation outcomes for persons with severe burns.
6. Facilitates other research such as the identification of potential persons for enrollment in appropriate burns clinical trials and research projects or as a springboard to population-based studies.

This study is the current arm of the Caribbean Migration Project, designed to generate a database of Jamaicans, returned residents and those with no international migration history, across the income classes and residential areas in Kingston and St. Andrew, Manchester and St. Ann. Jamaica was chosen as the inaugural country for investigation as a pilot for the processes involved in the data collection and fine-tuning the protocols to be extended to other Caribbean countries. The four parishes in Jamaica were purposively selected because of their proportion of returning residents in comparison with the country's other parishes. Respondents were thought to represent a sample of persons from a range of parishes in which there is a high proportion of returned residents (St. Andrew and Manchester) to others in which the majority of the population has no international migration history (St. Ann and Kingston). Demographic variables in this study include age, family size and structure, ethnicity, education, and travel and migration history.