Beverlyn Settles-Reaves, Ph.D. Project Director/Research Associate Department of Psychiatry and Behavioral Sciences Howard University, College of Medicine

M3 and SF-12 Correlation Study Beverlyn Settles-Reaves, PhD 1 Kelsey Ball 1, Gerald Hurowitz, MD 2, Bradley N. Gaynes, MD, MPH 3, Joanne DeVeaugh-Geiss, MA, PhD 3, Sam Weir, MD 3, William B. Lawson, MD, PhD 1, 1 Howard University, College of Medicine, Washington, DC, 2 Columbia University College of Physicians & Surgeons, 3 University of North Carolina School of Medicine Chapel Hill, NC Summary The My Mood Monitor (M3) has been identified as an efficient and valid instrument for screening of depression, anxiety disorders, PTSD and bipolar disorder. An additional key characteristic of a good mental health monitoring tool is the ability to reflect levels of functionality. Tools such as the Short Form Health Survey (SF-12) have proven to be valid assessments of functional health. While many instruments serve as a single-disorder screening tool, the M3 provides an integrated assessment across four prevalent diagnostic categories. In this study, correlations were calculated between the individual sub-scores from the M3 (depression, anxiety, PTSD and Bipolar) and the Short Form Health Survey (SF-12). Scores were calculated by weighting the answers to questions in each area (0 to 2). Results showed that each of the four diagnostic subscores was negatively correlated with both the physical and mental components the SF-12, respectively (p < ). The strength of the correlation with physical SF-12 score ranged from -0.2 to -0.3, while the correlation with the mental SF-12 score ranged from to These findings are consistent with previous studies and suggest that the M3 has demonstrative utility for use as a measure of quality of life as it relates to functional health. Major depression and generalized anxiety disorder have been identified as two of the most commonly diagnosed disorders; however, epidemiologic studies highlight the broad spectrum of mental health disorders encountered by health professionals. Misdiagnosis and under recognition of these disorders continues to be a significant concern within primary care settings. Often, mental health assessments and diagnostic tools are too narrowly focused, and they fail to identify patients with comorbid disorders, to include substance abuse. In studies by Kessler et al. (2005), comorbidity of 3 or more disorders was as high as 23%, and depression-screening tools failed to address common anxiety symptoms and disorders, such as obsessive-compulsive disorder (OCD) and post-traumatic stress disorder (PTSD). Conversely, many of the anxiety screening instruments fail to address the broad range of mood disorders. Misdiagnosis of patients with bipolar disorder and depression, for example, results in improper treatment and poor health outcomes and, studies show that, among those with depression, coexisting anxiety disorders can result in more treatment-resistant depressive course. Thus, leading to improper management and treatment and poorer patient prognosis. In this study, correlations between subscores of the M3 Checklist and the SF-12 were calculated to determine the M3 Checklist’s demonstrative use as a measure of quality of life as it relates to functional health. Given the M3 Checklist’s focus on functional impairment and the SF-12’s emphasis on functionality and health related quality of life, it was predicted that the two measures would be negatively correlated, such that higher scores on the SF-12 would be associated with lower scores on the M3 Checklist. Participants: A sample of 647 consecutive participants visiting the Family Medicine Clinic at the University of North Carolina between July 2007 and February 2008 who were at least 18 years of age, English speaking, and mentally competent to provide informed consent. The mean age of the patients was 45.7 years and 60% of were female. White (63%); African American (30%) and Native American, Asian, or other (7%). Before the clinician visit, participants completed the M3 Checklist and returned it to the practice nurse, who attached the checklist to the top of the chart for review by the clinician before entering the examination room. Of the 647 participants who completed the M3 Checklist, 594 also had results from the SF-12. Analytic Strategy : In order to assess the relationship between the physical and mental components of the SF-12 and the M3 Checklist Total Score, correlations were calculated along with their associated p-value. Both parametric and non-parametric correlations were evaluated. Table 1: Summary of Data from SF-12 and M3 Checklist Total Score (N=594) Table 2: Summary of the Correlation-SF-12 Components and the M3 Total Score (N=594) Thank you to Dr. Hurowitz, Dr. Gaynnes, Dr. DeVeaugh-Geiss and Dr. Weir for their guidance and research for this study and in supporting our reporting of this work.. The interactive Web site for the M3 Checklist can be found at Abstract Methods Results: Correlations were calculated between the M3 Checklist Total Score and both the physical and mental components of the SF-12. The results from both the parametric correlations (Pearson’s) and non-parametric correlations (Spearman’s) were consistent, and all p-values were < Specifically, our analysis indicated a significant inverse relationship between both the physical (Pearson’s r = -0.34, p<0.0001) and mental health (Pearson’s r = , p<0.0001) components of the SF-12. Tables 1 and 2 illustrate these findings. The M3 Checklist places emphasis on functional impairment and symptom severity such that high scores are indicative of significant patient risk of illness. The SF-12, however, places more weight on quality of life and functional health. Thus, high scores are associated with good functional heath. The negative correlation between the M3 Checklist and both physical and mental components of the SF-12 suggest that higher scores on the M3 Checklist are correlated with lower scores on the physical and mental components of the SF-12. Overall, the results presented here show that the M3 Checklist has potential to be used as an outcome indicator of health and a useful measure of quality of life as it relates to functional health.. The current study provides valuable information regarding the value and relevance of the M3 Checklist as a new and efficient measure of symptoms of mental disorders and their impact on functional health. Collecting information to understand the mental status of individuals based on self-reported information can be useful in identifying health issues and addressing health needs within our community. Results Conclusion Introduction Acknowledgements Label Minimum MedianMaximumMeanStd. Dev Physical Health Summary Mental Health Summary M3 Checklist Total Score M3 Checklist Total Score Parametric (Pearson) Correlation p-value < <.0001 Non-parametric (Spearman) Correlation p-value < <.0001 Pearson Correlation Coefficients, N = 594 Prob > |r| under H0: Rho=0 Physical Component SF12Mental Component SF12 M3 Total Score < <.0001 Table 3: Correlation coefficients (parametric) for the M3 and SF-12 (N=594)

Research Projects using M3  RIGHT BODY, RIGHT MIND PROJECT – Dr. Danielle Hairston  Comparison of M3 Assessment to Clinical Diagnosis – Dr. Kamal Gandotra, Sharlene Leong, Dr. Settles-Reaves  M3 Assessment in the General Population – Dr. Settles-Reaves  Effects of Perinatal Depression on maternal-infant bonding in a predominately African American population – Dr. Inez Reeves  Ease of Use – M3 – Dr. Mattie Trewe