National Wellbeing Survey, United States, 2021 (ICPSR 38879)

Version Date: Jul 25, 2023

Principal Investigator(s):
Shannon M. Monnat, Syracuse University

Series:

https://doi.org/10.3886/ICPSR38879.v1

Version V1 ()

  • V5 [2024-08-28]
  • V4 [2024-06-03] unpublished
  • V3 [2023-12-04] unpublished
  • V2 [2023-08-14] unpublished
  • V1 [2023-07-25] unpublished

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Alternate Title

NWS

Summary

The National Wellbeing Survey (NWS) is a population-based survey on the wellbeing of adults aged 18 to 64 in the United States. Specific survey domains include psychological well-being, social relationships and support, physical health, mental health, health behaviors, COVID-19 experiences and impacts, socioeconomic measures, political orientation, and demographic measures.

Citation

Monnat, Shannon M. National Wellbeing Survey, United States, 2021. Inter-university Consortium for Political and Social Research [distributor], 2023-07-25. https://doi.org/10.3886/ICPSR38879.v1

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Funding

Syracuse University Lerner Center for Public Health Promotion, United States Department of Health and Human Services. National Institutes of Health. National Institute on Drug Abuse (1U01DA055972-01), United States Department of Health and Human Services. National Institutes of Health. National Institute on Drug Abuse (1U01DA055972-02)

Subject Terms

Geographic Coverage

Smallest Geographic Unit

County

Restrictions

Access to these data is restricted. Users interested in obtaining these data must complete a Restricted Data Use Agreement, specify the reason for the request, and obtain IRB approval or notice of exemption for their research.

Distributor(s)

Inter-university Consortium for Political and Social Research
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Time Period(s)

2021

Date of Collection

2021-02-01 -- 2021-03-18

Data Collection Notes

  1. The restricted-use version of the data include geographic identifiers and variables for states (N = 51) and counties (N = 1,430). The public-use data have these variables masked.

  2. For additional information on this study, please visit the Syracuse University Maxwell School of Citizenship and Public Affairs website.
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Study Purpose

The purpose of this study was to develop an overall understanding of wellbeing of adults aged 18 to 64 in the United States.

Study Design

Sample participants were recruited online through Qualtrics Panels. The sample design included an oversample of rural residents; 28.3 percent of respondents (N = 1,136) reside in a non-metropolitan county.

Sample

Non-probability, opt-in, online panel of 4,014 adults in the United States administered through Qualtrics Panels.

Time Method

Cross-sectional

Universe

Noninstitutionalized adults in the United States who ranged in age from 18 to 64 years old and who were able to read English.

Unit(s) of Observation

Individual

Data Type(s)

Mode of Data Collection

Description of Variables

The variables in this study pertain to psychosocial wellbeing, social relationships and support, participation in social activities, physical health, mental health, health behaviors, health care use, employment quality and experiences, COVID-19 experiences, socioeconomic measures, political orientation, and demographic measures (race/ethnicity, sex/gender, and age).

Response Rates

Of the 11,580 Qualtrics Panel members who accessed the landing page and reviewed the informed consent, 4,014 met the age eligibility criteria and data quality threshold, resulting in a completion rate of 40.4 percent.

Presence of Common Scales

  • Diemer Satisfaction with Life Scale
  • Patient Health Questionnaire-4 (PHQ-4)
  • Brief Resilience Scale (BRS)

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Original Release Date

2023-07-25

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Weight

A post-stratification final person weight (FINAL_WGT) is included to make the analyses nationally representative of the United States working-age population by age, sex, race, Hispanic ethnicity, educational attainment, and rural-urban continuum. Educational attainment was not incorporated into the weight for respondents ages 18-24. Because of the rural oversample built into the sampling design, users should apply the weight to all analyses.

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