Daniel Eisenberg, Ph.D.
Department of Health Management and Policy
University of Michigan
(daneis@umich.edu)
Presentation for the UC Davis Center for
Healthcare Policy and Research
April 15, 2013
1
Disclosure Statement
Have you (or your spouse/partner) had a personal
financial relationship in the last 12 months with the
manufacturer of the products or services that will be
discussed in this CME activity?
___ Yes
_X_ No
2
Educational objectives for this seminar
 Describe data on mental health symptoms and
utilization in college populations in the U.S.
 Assess the economic case for interventions to
increase help-seeking and access to mental health
care in college and other youth populations
 Discuss the effectiveness and potential
effectiveness of specific interventions
3
Outline of Seminar
Broad overview of my work (5 minutes)
Help-seeking and utilization in college populations
 General statistics (10 minutes)
 Analysis of barriers to services (10 minutes)
 Economic case for access to services (10 minutes)
 Intervention research (10 minutes)
4
Pediatrics
Family Medicine
Psychiatry
Public Health
Clinical Psychology
Education
Economics
5
Broad Research-Practice Agenda
How to invest most efficiently in health (and longterm success and wellbeing) in youth populations?
Design and evaluate
programs and
interventions
Practice
Collect descriptive
population data
6
Things I Like to Do
 Economic evaluation
 Causal inference in nonexperimental settings
 Bridge between health and social sciences (not
just economics)
 Bridge between health and education policy
 Large-scale survey data collection (and data)
 Online interventions (access and self-efficacy)
 Training and mentoring junior scholars
7
Opportunities for Collaboration
 Economic analyses of policies, programs, services
 Population survey studies
 Broad, preventive approaches to mental health and
health behaviors through primary care settings
 Addressing disparities (by race/ethnicity and SES)
through school settings
 Online interventions: screening, linkage to health
care, supplement to clinical care
8
Help-seeking and Utilization of Mental Health Care
in College Populations: General Statistics
9
Significance of Population
 For adolescents and young adults in the U.S., mental
disorders account for the largest burden of disease 0f any
type of health condition (Michaud et al, 2006, Pop Health
Metrics)
 75% of lifetime mental disorders in the U.S. have first onset
by age 24 (Kessler et al, 2005, Arch Gen Psych)
 Adolescence and young adulthood are periods of intensive
investment in human capital
 School settings offer unique opportunity for public health
approaches with high impact
10
Healthy Minds Study, 2007-2013
Finding #1: High Prevalence of Mental Health
Problems, But also Positive Mental Health
Overall Prevalence Estimates (%)
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
Major
depression
(PHQ-9)
"Minor"
depression
(PHQ-9)
Panic
disorder
(PHQ)
Generalized
Suicidal Non-suicidal
anxiety
ideation (yr) self-injury
(PHQ)
(yr)
Any MH
problem
Data: 2012 Healthy Minds Study (29 schools, ~25,000 survey respondents)
Flourishing
(Diener et
al.)
12
Finding #2: About Half of Students with Mental
Health Problems Receive Treatment
Any Treatment Past Yr (%),
by Mental Health Problem
70%
60%
50%
40%
30%
20%
10%
0%
Major depression
(PHQ-9)
Anxiety (Panic or
Generalized) (PHQ)
Suicidal ideation (yr)
Data: 2012 Healthy Minds Study
Non-suicidal self-injury
(yr)
13
Finding #3: When Provided, Depression Treatment is
Less than “Minimally Adequate” in ~50% of Cases
 Among students with significant depressive symptoms
and some treatment in past year, 57% received
“minimally adequate” depression care (4+
psychotherapy visits or 2+ months of antidepressant
medication)
 Among all students with past-year depression, 22%
received minimally adequate care
Data: 2009 Healthy Minds Study
14
Finding #4a: Variation in Mental Health across
Demographic Groups
Major Depression (%) by Demographic Group
14%
12%
10%
8%
6%
4%
2%
0%
Undergrad. Graduate
Student
Asian
Black
Hispanic
Multi
Other
White
Data: 2012 Healthy Minds Study
15
Finding #4b: Variation in Utilization across
Demographic Groups
Treatment past yr (%) among those with a MH Problem,
by Demographic Group
60%
50%
40%
30%
20%
10%
0%
Undergrad. Grad.
Student
Asian
Black
Hispanic
Multi
Other
White
Data: 2012 Healthy Minds Study
16
Finding #5: Variation by Field of Study
Mental Health Problems (%) by
Graduate Professional Field of Study
35%
30%
25%
20%
15%
10%
5%
0%
Business
n=504
Law
n=233
Medicine
n=563
Data: 2012 Healthy Minds Study
Nursing
n=154
Public Health
n=317
17
Finding #6: Risk/Protective Factors
 Risk factors (negative correlation w/ mental health)
 Financial stress (both past and present)
 Experienced discrimination
 Protective factors (positive correlation)
 Social support
 Religiosity
 Living on campus
Data: 2012 Healthy Minds Study
18
Finding #7: Variation across Campuses
Data: 2012 Healthy Minds Study
Data: 2012 Healthy Minds Study
19
Help-seeking and Utilization of Mental Health Care
in College Populations: Barriers to Services
20
Findings on Stigma
 Personal stigma low among college students
 Only 12% of students agree with statement “I think less
of someone who has received MH treatment”
 Perceived public stigma considerably higher
 64% agree with “Most people think less of someone who
has received MH treatment”
 Personal stigma somewhat higher among: male,
younger, Asian, international, religious, from a poor
family
21
Stigma Findings (cont’d)
 Perceived public stigma not significantly associated
with use of services or support
 In contrast, personal stigma is significantly associated
with lower use of services & support
 Our estimates suggest that lowering the population-
level personal stigma by one half would result in an
increase of service use among students with major
depression from 44% to 60%
22
If Not Stigma, Then What?
BARRIERS:
stigma
high
treatment
not helpful
no
perceived need
N
%
Group 1
X
X
X
49
2%
Group 2
X
X
41
2%
Group 3
X
74
3%
Group 4
X
47
2%
348
13%
323
12%
868
33%
894
34%
X
Group 5
X
Group 6
X
Group 7
Group 8
X
X
What is Going on with Groups 7 & 8?
 Group 7 (low stigma, believes tx helpful, no perceived need):
 prefer to deal with problems on one’s own (53%)
 thinks stress is normal in school (47%)
 gets support from family/friends (42%)
 questions how serious issues are (36%)
 doesn't have time (29%)
 Group 8 (low stigma, believes tx helpful, perceives need):
 questions how serious issues are (62%)
 prefers to deal with problems on one’s own (60%)
 doesn't have time (59%)
 thinks stress is normal in school (59%)
 gets support from family/friends (44%)
 financial reasons (38%)
24
Interventions for Groups 7 & 8?
 Anti-stigma, education, and awareness campaigns may
have little impact
 May be useful to borrow lessons from other contexts
where people do not have strong objections, yet fail to
engage in “healthy” behaviors (e.g., exercise, diet,
preventive screening, even saving for retirement!)
25
Behavioral Economics: Time
Preferences and Procrastination
 Is depression related to present-orientation
(discounting of future)?
 Is lack of help-seeking a form of procrastination?
26
Empirical Analysis of these
Questions
 Healthy Minds Study (2011)
 Large, cross-sectional (N=8,806, 11 institutions)
 College Transition Study Replication (CTSR)
 Panel with five monthly surveys (Aug-Dec 2010) at
one institution (Univ. Michigan)
 281 first-year and transfer undergraduates
 PI: Steve Brunwasser
27
Findings
 Depressive symptoms significantly associated with
present-orientation (discounting the future) and
procrastination tendencies
 Procrastination tendencies associated with lower
likelihood of receiving treatment
 Implications for help-seeking interventions?
28
Help-seeking and Utilization of Mental Health Care
in College Populations: Economic Case
29
Mental Health and Academic Outcomes
 Mental health as predictor of academic outcomes in 2005-
2008 Healthy Minds data
 Depression (PHQ-9 score) is a significant predictor of
dropping out
 10 point lower PHQ-9 score
reduction in risk of dropping out by a
multiple of 0.6 (e.g., from 10% to 6%)
Mental Health and Grade Point Average (GPA)
 Depression (PHQ-9 score) is also a significant negative
predictor of same-semester GPA
 10 point lower PHQ-9 score
9 point increase in GPA percentile
 Co-occurrence of depression and anxiety associated with a
significant additional drop in GPA.
 Symptoms of eating disorders also associated with lower
GPA
Economic Case for Services and
Programs for Student Mental Health
Reduced depression
Increased
retention
Increased student
satisfaction
Increased
institutional
reputation & alumni
donations
Increased tuition
Benefits to
institution
Increased lifetime
productivity
(earnings)
Benefits to
students and
society
Help-seeking and Utilization of Mental Health Care
in College Populations: Intervention Research
33
“Gatekeeper Training” Programs
 Evaluation of Mental Health First Aid training for
resident advisors (RAs)
 Co-PIs: Daniel Eisenberg and Nicole Speer
 Funder: NIMH (2009-2011)
 32-campus randomized trial to assess impacts on
student communities
34
Peer-based Approaches to Help-seeking
 Peer effects in mental health among college students
 PI: Daniel Eisenberg (University of Michigan)
 Funder: W.T. Grant Foundation (2009-2011)
 Study design based on “natural experiment” of
randomly assignment of students to roommates and
resident advisors (RAs)
35
Online Screening and Linkage to Treatment
 e-Bridge to Mental Health online intervention
 PI: Cheryl King (University of Michigan)
 Funder: NIMH (2009-2012)
 Brief risk screen -> personalized feedback ->
correspondence with counselor using motivational
interviewing
36
Online Video-based Intervention
 Brief (3-4), highly engaging videos based on CBT and
resilience and self-efficacy skills
 Based on inkblots video series (www.inkblots.tv)
 Pilot RCTs to begin in summer 2013 (funded by UM
Comprehensive Depression Center)
37
Broad Research-Practice Agenda
How to invest most efficiently in health (and longterm success and wellbeing) in youth populations?
Design and evaluate
programs and
interventions
Practice
Collect descriptive
population data
38