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
All Rights Reserved.

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.

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 Title

Journal of Child and Family Studies

Volume

28

Issue

3

First Page

753

Last Page

764

ISSN

1573-2843

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