Beyond Income: Expanding our Empirical Toolkit to Better Predict Caregiver Well-Being
Publication Date
3-2019
Document Type
Article
Organizational Units
College of Arts Humanities and Social Sciences, Psychology
Keywords
Low-income, Caregiver well-being, Socioeconomic indicators
Abstract
Objectives
Despite growing concern that income alone does not capture how low-income families are managing financially, it continues to be one of the most commonly used indicators of socioeconomic status and is routinely used as a qualifying factor for government assistance programs. Income can be difficult to measure accurately and alone may not be the best predictor of caregiver well-being, in particular among ethnically diverse families. A more nuanced understanding may be critical for identifying families in need of services and supporting success after enrollment in need-based programming. Thus, the current study investigated the relationship between traditional (low income, low education, unemployment), and less traditional (economic pressure, economic hardship, perceived social status, crowding) socioeconomic indicators and caregiver well-being (caregiver depressive symptoms, anxiety, dysfunction in the parent-child relationship) using data from a multisite study.
Methods
Participants were 978 racially/ethnically diverse caregivers (97% female) of young children enrolled in Early Head Start programming from six sites across the United States.
Results
Exploratory factor analyses resulted in a three-factor model, capturing demographic risk, resource strain, and perceived social status. The Resource Strain factor was most strongly associated with greater caregiver depressive and anxiety symptoms, and dysfunction in the parent-child relationship. Further, hierarchical regression models revealed up to a four-fold increase in variance explained when adding economic strain along with traditional variables to models predicting caregiver well-being.
Conclusions
Results support the need to supplement traditional economic measurement when supporting families experiencing low income and for measuring poverty among ethnically diverse families.
Copyright Date
1-3-2019
Copyright Statement / License for Reuse
All Rights Reserved.
Rights Holder
Springer Science+Business Media, LLC, part of Springer Nature
Provenance
Received from CHORUS
File Format
application/pdf
Language
English (eng)
Extent
12 pgs
File Size
593 KB
Publication Statement
Copyright is held by Springer Science+Business Media, LLC, part of Springer Nature. User is responsible for all copyright compliance. This article was originally published as:
Hurwich-Reiss, E., Watamura, S. E., & Raver, C. C. (2019). Beyond income: Expanding our empirical toolkit to better predict caregiver well-being. Journal of Child and Family Studies, 28(3), 753-764. https://doi.org/10.1007/s10826-018-01304-5
Provided by the Springer Nature SharedIt content-sharing initiative.
Publication Title
Journal of Child and Family Studies
Volume
28
Issue
3
First Page
753
Last Page
764
ISSN
1573-2843
Recommended Citation
Hurwich-Reiss, Eliana; Watamura, Sarah Enos; and Raver, C. Cybele, "Beyond Income: Expanding our Empirical Toolkit to Better Predict Caregiver Well-Being" (2019). Psychology: Faculty Scholarship. 151.
https://digitalcommons.du.edu/psychology_faculty/151
https://doi.org/10.1007/s10826-018-01304-5