Data in Brief (Dec 2022)

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

  • Cal J. Halvorsen,
  • Bruce Kelley,
  • Jim Emerman,
  • Stefanie Weiss,
  • David Gleicher,
  • Jacob Stolmeier,
  • Mark Lush

Journal volume & issue
Vol. 45
p. 108753

Abstract

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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.

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