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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 Behavioral Risk Factor Surveillance System (BRFSS) is a system of health-related telephone surveys that collect state data about U.S. residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. Established in 1984 with 15 states, BRFSS now collects data in all 50 states as well as the District of Columbia and three U.S. territories. BRFSS completes more than 400,000 adult interviews each year.

These data were collected as part of the evaluation of the Healthy School Program (HSP), a program that provides support to elementary, middle, and high schools in the United States as they work to create healthy school environments that promote physical activity and healthy eating for students and staff. HSP was created in 2006 by the Alliance for a Healthier Generation with funding from the Robert Wood Johnson Foundation. The HSP evaluation addressed both process and impact outcomes:

1. Is the HSP technical assistance and training model effective in increasing the implementation of policies and programs that promote and provide access to healthier foods and more physical activity before, during and after school?

2. Are there distinctive or common school-level characteristics that hasten or hinder school-level implementation of policies and programs that promote and provide access to healthy foods and physical activity in the school setting in HSP schools?

3. Does participation in HSP contribute to an increase in healthy eating behaviors and physical activity participation among students? Does participation in HSP contribute to a decrease in body mass index (BMI) among students?

The evaluation used a mixed-method design incorporating both quantitative and qualitative components. The quantitative component of the evaluation was a longitudinal design that measured student changes in eating and physical activity behaviors and BMI and schools' implementation of policies and practices promoted by HSP. For the qualitative component the evaluation team conducted site visits in a sample of HSP schools.

Nine data files constitute this data collection:

1. HSP Participation and Inventory Data File, 2006-2011 (originally called the Inventory Data File)

2. Pilot Student Survey Data File

3. Pilot Student Height and Weight Measurements Data File

4. Survey of Students in Boston and Miami-Dade Public Schools Data File

5. HSP Participation and Inventory Data File, 2006-2014

6. Arizona, Prince George's County and Nevada Healthy Schools Youth Survey Data File

7. Arizona and Prince George's County Youth Height and Weight Measurements Data File

8. Arizona Academic Achievement Data File

9. Prince George's County School Wellness Coordinator Survey Data File

Dataset 1 contains data on school characteristics, HSP engagement indicators, baseline and follow-up responses to the Healthy Schools Inventory, and indices derived from the Inventory for all HSP schools as of August 2011. The Inventory collected information about each school's adherence to the Healthy Schools Program Framework, a set of best practice guidelines that promote physical activity and healthy eating among students and staff.

Datasets 2, 4 and 6 contain data from baseline and follow-up administrations of the Healthy Schools Youth Survey questionnaire in three samples of HSP schools: students in grades 5-12 in the initial pilot cohort of HSP schools; students in grades 5, 8 and 10 in the 2007-2008 cohort of HSP schools in Boston, Massachusetts and Miami-Dade County, Florida; and students in grades 5, 8 and 10 or 11 in HSP schools in Arizona, Nevada and Prince George's County, Maryland. Topics covered by the Healthy Schools Youth Survey questionnaire include eating and physical activity habits, attitudes about healthy eating and physical activity, health knowledge, and school food environments.

Datasets 3 and 7 contain baseline and follow-up height and weight measurements and derived BMIs, the former for students in grades 4-12 in schools sampled by the Pilot Student Survey and the latter for students in grades 5, 8, and 10 in Arizona and grades 1-12 in Prince George's County in schools sampled by the Arizona, Prince George's County and Nevada Healthy Schools Youth Survey.

Dataset 5 is an update to Dataset 1. Like Dataset 1 it contains data on HSP participation and engagement and school characteristics. Dataset 5 covers 8,500 schools that participated in HSP through fall 2014. It includes 4,028 of the 4,542 schools in Dataset 1.

Dataset 8 contains average math, reading and language scores for grades in HSP and comparable non-HSP schools in Arizona. Every record in the data file represents a grade (one or more of the grades 2-9) within a school (150 schools) for a given school year (up to seven years 2007-2008 to 2013-2014).

Dataset 9 contains data from a survey of HSP school coordinators in Prince Georges County. The coordinators were interviewed about the implementation of HSP in their schools.

ICPSR did not receive the site visit data.

This survey was conducted as part of the New Jersey Childhood Obesity Study, a project designed to provide vital information for planning, implementing, and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. Conducted among households with 3-18 year old children in the 5 cities, the survey interviewed the adult who made most of the decisions about food shopping in each household. The survey examined perceptions about food and physical activity environments in the five cities, investigated barriers related to access to healthy food and physical activity facilities, and collected information on the height and weight and food and physical activity behaviors of the cities' 3-18 year old children and the adult respondents. In addition, the survey collected demographic information about the household members.

Four linkable datasets contain the survey data: the Household File, Index Child File, Adult File, and All Child File. The Household File covers household and neighborhood characteristics, while the Index Child File describes the characteristics and behaviors of a randomly selected 3-18 year old child in the household, who is designated the "index child" and is the primary unit of analysis. The Adult File comprises characteristics and behaviors of the adult respondent, and, lastly, the All Child File covers a few characteristics of all children aged 3-18 in the household.

Prescription for Health was an initiative funded by the Robert Wood Johnson Foundation in collaboration with the Agency for Healthcare Research and Quality. Under this initiative, primary care practice-based research networks (PBRNs) -- groups of ambulatory practices devoted principally to the primary care of patients -- developed, tested, and evaluated innovative strategies to improve the delivery and effectiveness of health behavior change services in primary care practice. The strategies targeted four health risk behaviors: tobacco use, unhealthy diet, lack of physical activity, and risky alcohol use. Prescription for Health was conducted in two rounds. Round one awarded grants to 17 PBRNs to test the feasibility of implementing the strategies, while round two awarded grants to ten PBRNs to measure the strategies' effectiveness and the expenses associated with them. More than a 100 primary care practices from the ten PBRNs participated in the evaluation.

This data collection comprises the data from one of the data collection efforts carried out by the second round: the responses to the Practice Information Form (PIF), a Web-based instrument which captured key organizational attributes of the participating practices. The PIF data were collected at two time points. Baseline data were collected from each practice before the intervention was implemented and follow-up data were collected approximately one year after the start of the intervention.

Information about the practices collected by the PIF include practice type and ownership; characteristics of each clinician and non-clinician staff person; number of vacancies for clinicians and non clinicians; number of exam rooms and volume of office visits; average number of new patients per month; percentages of patients in various age, race, Hispanic origin, and payer categories; and the predominant type of payment arrangement with health plans. In addition, the PIF asked whether a specific health plan controlled over half of the practice's total business; whether the practice had a pay-for-performance program; whether any payers or organizations publicly reported practice level performance information, such as patient satisfaction, chronic care/disease management, and/or preventive service delivery; and whether practices had a formal process for routinely measuring satisfaction among patients, clinicians, and other staff. The PIF also investigated how practices motivated their clinicians and staff; the level of competition among practices in local markets; the use of computers, electronic medical record systems, and patient registries; major changes that affected each practice's ability to make improvements in patient care; factors that prevented practices from translating the results of research into changes in medical practice; and the use of health risk assessment protocols or questionnaires to identify patients who may benefit from counseling or interventions. Questions about the four Prescription for Health behaviors -- physical activity, healthy eating, smoking cessation, and addressing risky drinking -- asked how practices linked patients to outside resources for each of the four behaviors; how practices used evidence-based guidelines and informed patients about recommendations for the behaviors; and which approaches practices used to support patients ready to engage in a behavior change for each of the behaviors.