OBJECTIVES: To assess the feasibility of the SF-36v2 Mental Health (MH) domain and Mental Component Summary (MCS) scores in the classification of risk for major depressive disorder (MDD), and determine the cutoff scores in a US sample and chronic pain subpopulations. METHODS: Data were analyzed from the 2013 US National Health and Wellness Survey (adults ≥18 years old; N=75,000). Respondents were also classified into subpopulations based on self-report: chronic pain (n=6,679) and chronic pain receiving medication for depression (i.e. with depression) (n=5,814). The primary definition for classifying respondents at risk of MDD was a score > 10 on the Patient Health Questionnaire (PHQ-9). Logistic regression modeling was used to predict at risk for MDD, or not, and receiver operating characteristic curves were produced.  RESULTS: The total sample had MH scores of 48.8 and MCS scores of 48.9, similar to the normative mean for the US adult population. The percent of respondents with a PHQ-9 > 10 were 15.0%, 29.1% and 25.9% for the total sample, chronic pain alone, and chronic pain with depression, respectively. Cutoff scores (PHQ-9>10) in the total sample for the MH domain and MCS were 43.0 and 46.0, respectively. Specificities of recommended cutoff scores for the MH domain and MCS were 77.8% and 76.1%; sensitivities were 84.9% and 88.1%. Among the subpopulation with chronic pain alone, cutoff scores for the MH domain and MCS were 40.4 and 43.1, respectively. Corresponding specificities for the MH domain and MCS were 77.9% and 73.9%; sensitivities were 78.3% and 83.4%. Trends were similar among the chronic pain with depression subpopulation. CONCLUSIONS: The SF36v2 was found to have sufficient specificity and sensitivity to categorize participants at risk for MDD.  It is feasible to use the SF-36v2, a widely used measure to assess health status, to better characterize the mental health of populations.