What do we mean when we talk about socioeconomic status? Implications for measurement, mechanisms and interventions from a critical review on adolescent mental health

Abstract

Low socioeconomic status (SES) is a well-established risk factor for general and mental health problems. However, there is no widely accepted definition or operationalisation for SES, leading to varied interpretations in research. In a critical review of the child and adolescent mental health literature, we map how SES is defined and measured. We examined 334 relevant papers from 2013 to 2024 and found significant variability in the operationalisation of SES. Our analysis revealed fundamental problems such as the lack of clear definitions, insufficient detail on variables used and limited measures directly reported by adolescents. We discuss issues related to measurement techniques and their impact on reproducibility, policy development and intervention design. Based on our findings, we recommend using SES measures that directly assess the socioeconomic position of children and adolescents. Additionally, we recommend researchers improve transparency and specificity in reporting the measures used and the rationale behind their selection. The wide range of distinct measures used to represent SES, coupled with insufficient reporting, likely hampers our understanding of which underlying factors truly drive observed effects and impedes the establishment of causal relationships. This, in turn, makes the path to effective health interventions more challenging.

Keywords: Child Development; Mental Health; Methods; Psychological Theory.

Figure 1. (A) The proportion of papers using different types of socioeconomic status (SES) measures from our included sample. (B) The proportion of papers using different types of measures from the papers using composite metrics for SES. As composite metrics include more than one measure, the sum of all the measures exceeds 1.

Figure 2. (A) The proportion of papers using socioeconomic status (SES) variables on different levels from our included sample. (B) The proportion of papers using different levels from the papers using multiple levels.

Figure 3. Illustrative case for the selection of a candidate socioeconomic status (SES) measure. In this example, researchers wish to identify a suitable single-item question to measure SES for use in a short Qualtrics survey of university students aged 17–19 years, where SES is considered as a risk factor for mental health. Here, we showcase how researchers might evaluate candidate measures in terms of their fit with the research framework and context, what each measure’s advantages and disadvantages are, and offer recommendations for selection and reporting.

Figure 4. Illustrative case for the selection of a candidate socioeconomic status (SES) measure. In this example, researchers wish to identify a suitable measure of SES of school-going children (11–17 years) for a secondary analysis of the Global School-based Student Health Survey (GSHS), with the purpose of examining SES as a risk factor for mental health. Potential measures may come from the dataset itself (a single-item question about experiencing hunger, or questions about sanitation) or from external sources (such as country-level indicators). The Gini coefficient is referred to simply as GINI. GDP, gross domestic product.