Transcript M3 and SF-12 Correlation Study by Dr. Beverlyn Settles

Beverlyn Settles-Reaves, Ph.D.
Project Director/Research Associate
Department of Psychiatry and Behavioral Sciences
Howard University, College of Medicine
Abstract
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 < 0.0001). 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 -0.58 to -0.72. 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.
Introduction
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.
Methods
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.
M3 and SF-12 Correlation Study
Beverlyn Settles-Reaves, PhD1 Kelsey Ball1, Gerald Hurowitz, MD2,
Bradley N. Gaynes, MD, MPH 3, Joanne DeVeaugh-Geiss, MA, PhD3,
Sam Weir, MD3, William B. Lawson, MD, PhD1,
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
Results
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 <0.0001. 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 = 0.72, p<0.0001) components of the SF-12. Tables 1 and 2 illustrate these findings.
Table 1: Summary of Data from SF-12 and M3 Checklist Total Score
(N=594)
Label
Physical Health Summary
Mental Health Summary
M3 Checklist Total Score
Minimum
11.2
13.8
0.0
Median Maximum
47.7
65.5
50.7
69.1
27.0
88.0
Mean
Std. Dev
44.3
11.9
47.1
11.4
29.8
17.8
Table 2: Summary of the Correlation-SF-12 Components and the M3
Total Score (N=594)
Non-parametric (Spearman) Correlation
p-value
-0.34
<.0001
-0.72
<.0001
-0.29
<.0001
-0.70
<.0001
Table 3: Correlation coefficients (parametric) for the M3 and SF-12
(N=594)
Pearson Correlation Coefficients, N = 594
Prob > |r| under H0: Rho=0
M3 Total Score
.
Conclusion
M3 Checklist Total Score
Parametric (Pearson) Correlation
p-value
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.
Physical Component
SF12
Mental Component SF12
- 0.34261
- 0.71501
<.0001
<.0001
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.
Acknowledgements
. The interactive Web site for the M3 Checklist can be
found at http://www.whatsmym3.com/.
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.
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