Validity of the mental health component scale of the 12-item Short-Form Health Survey (MCS-12) as measure of common mental disorders in the general population

Patient–Physician Communication in the Primary Care Visits of African Americans and Whites with Depression

“…24 The standard 4-week recall version was used. The SF-12 is scored according to 2 summary measures that separately summarize health-related quality of life (HRQOL) due to physical and mental symptoms, the Physical and Mental Component Summary Scores (PCS, MCS).…”

“…Prior studies indicate that the performance characteristics of the MCS for identifying depression are excellent when compared to the Composite International Diagnostic Interview 24 and other commonly used screening instruments for depression. [24][25][26][27][28][29][30] Additionally, these studies have shown the SF-12 to be a valid measure for assessing health status among persons of different ethnic groups.…”

“…[24][25][26][27][28][29][30] Additionally, these studies have shown the SF-12 to be a valid measure for assessing health status among persons of different ethnic groups. 31 In this study, a high level of depressive symptoms was classified as a score of 42 or lower on the MCS-12 (sensitivity of 74% and specificity of 81% in detecting patients diagnosed with depressive disorder).…”

Overuse of Antidepressants in a Nationally Representative Adult Patient Population in 2005

“…We included a combined measure of fair to poor general health distinct from diagnosis and used self-reported responses on a 5-point scale (rated from 1, excellent, to 5, poor) from the validated Physical Health Index (PHI) derived from the 12-Item Short Form Health Survey (SF-12) (46). Mental health need distinct from a diagnosis was measured with the Kessler 6-Item Psychological Distress Scale (K6), a measure of generalized distress that has shown good agreement with the Composite International Diagnostic Interview in general adult population surveys (47). Odds ratios (ORs) predicting the overuse of antidepressants in this population were constructed with the use of robust standard errors adjusted for clustering at the individual level (48).…”

Estimating local prevalence of mental health problems

“…It has a moderately sized list of demographic, economic, health insurance, physical health, mental health, and health care utilization questions. Among other models, Stern et al (2010) estimate a correlated probit model for depression, 27 allowing for a wide set of personal characteristics, community characteristics, 28 interactions between community and personal characteristics, and site dummy variables. The community dummy variables control for community e¤ects not captured by the observed community characteristics included directly in the model.…”