A nationally representative dataset of 1,549 Americans aged 18 to 94 on interest in, experience with, and barriers to cogeneration, defined as working with older and younger people for social good.

This dataset focuses on Americans' interest in, experience with, and perceived barriers to working with members of other generations to improve the world around them. It includes responses from a March 2022 survey of 1,549 people between the ages of 18 and 94 who lived in the U.S. using the NORC at the University of Chicago AmeriSpeak® Panel. To increase the representativeness of the sample, the survey was offered both online and by phone. The sample is drawn from a probability-based panel designed to be representative of the U.S. household population. Questions focused on respondents' efforts (paid or volunteer) to improve the world around them, with a particular focus on cogenerational work with people at least 25 years older and younger than themselves. Respondents answered questions about their interest in and experience with cogenerational work as well as perceived barriers to it. Respondents were also asked to identify specific issues that they would like to work on with people of different generations (e.g., mental health, education, environment), their beliefs on if and how younger and older people working together might reduce divisions in society, and their engagement with people of different generations outside of their families. The complete dataset with 189 variables (10 of which are string/text variables from open-ended responses) is available both as a Stata .do file as well as in two .csv files. Two codebooks (one simplified, one full) and a project report from NORC that details the dataset's weighting and other methodological information are also available. This point-in-time dataset can be used for univariate, bivariate, and multivariate analysis and may be useful to researchers, social sector leaders, and policymakers interested in multigenerational efforts to solve social problems.

Association between changes in health risk status and changes in future health care costs: a multiemployer study.

OBJECTIVE: To assess the influence of health risk change on changes in health care costs. METHODS: Multivariate regression models examined change in health care costs concurrent with and following completion of two health assessments (HAs) approximately 1 year apart. Final models examined changes in costs for individuals with and without chronic conditions. RESULTS: After controlling for chronic condition status, health risk changes between the first and second HA were associated with health care cost changes in the year following the second HA. Those with chronic conditions experienced reductions of $129 for each risk reduced and increases of $210 for each risk added. CONCLUSIONS: Changes in health care costs were preceded by changes in health risk status, supporting the use of HA and biometric screening measures as leading indicators of the cost impact of health management programs.

Information access: will make or break consumer-driven health plans.

Consumer-driven health plans offer employers potentially significant cost savings. Yet such potential cannot be realized without greater consumer access to price, quality and treatment information. This article describes why consumer-based strategies have taken hold and how consumer-driven plan design and financial incentives are of only limited value in controlling costs. After reviewing the importance and availability of existing health care information, the authors suggest actions employers can take to ensure consumer-driven plans reach their potential.