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Unpacking the link between socioeconomic status and behavior problems: A second-order meta-analysis
Kevin M Korous1, José M Causadias1, Robert H Bradley1
1Arizona State University.
Socioeconomic status (SES) shows small links to internalizing behaviors, particularly with income and education. Associations with externalizing behaviors were minimal across income, education, and overall SES.
Area of Science:
- Psychology
- Sociology
- Public Health
Background:
- Socioeconomic status (SES) is linked to internalizing and externalizing behavior problems.
- The precise relationship between specific SES components (income, education, occupation) and these behaviors is not fully understood.
Purpose of the Study:
- To conduct a second-order meta-analysis on the associations between SES components and behavior problems.
- To estimate the average effect sizes for income, education, occupation, and overall SES with internalizing and externalizing behaviors.
- To investigate potential moderators such as age, sex, and race/ethnicity.
Main Methods:
- A systematic search was performed across major academic databases (PsycINFO, PubMed, Google Scholar, Web of Science, ProQuest).
- Included 12 meta-analyses comprising approximately 474 primary studies and 327,617 participants.
- Second-order meta-analysis was used to synthesize findings and examine moderation.
Main Results:
- Small average associations were found between SES components and internalizing behaviors (e.g., income: r+ = -.18; education: r+ = -.12).
- Associations between SES components and externalizing behaviors were minimal and not statistically significant (e.g., income: r+ = -.02; education: r+ = -.03; overall SES: r+ = -.05).
- Sample sex composition was the only significant moderator for externalizing behaviors.
Conclusions:
- SES, particularly income and education, has a small but significant association with internalizing behavior problems.
- The link between SES and externalizing behavior problems is weak and requires further investigation.
- Future research should focus on refining measurement and exploring underlying mechanisms for these associations.
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