A Mental Health Literacy Approach to Supporting First-Generation Community College Student Mental Health: The REDFLAGS Model

Abstract

Objective:

First-generation community college students face unique risks for mental health distress, which can place them at risk for attrition and a myriad of other negative consequences. The aim of the present quantitative investigation was to test the utility of the REDFLAGS model, a mental health literacy based tool for supporting mental wellness, with a national sample of first-generation community college students.

Method:

Confirmatory factor analysis (CFA), logistic regression analysis, and a factorial analysis of variance (ANOVA) were computed to test the utility of the REDFLAGS model as a tool for promoting first-generation community college students’ mental health.

Results:

The CFA demonstrated that the dimensionality of the REDFLAGS model was estimated adequately with first-generation community college students. First-generation community college students’ recognition of the REDFLAGS as warning signs for mental distress emerged as a significant positive predictor of making a peer-to-peer referral to the counseling center. The factorial ANOVA revealed that first-generation community college students who were members of a Greek Organization were more likely to identify the REDFLAGS as warning signs for mental distress.

Contributions:

Previous investigators established multiple strategies for supporting the mental health needs of either first-generation or community college students. First-generation community college student mental health, however, has received little attention. This study demonstrates the utility of the REDFLAGS model with first-generation community college students. Considering the dearth of literature on first-generation community college student mental health, the REDFLAGS model offers novel implications for promoting the mental health needs of first-generation students enrolled in community colleges.