Daniel Eisenberg, Ph.D. Department of Health Management and Policy University of Michigan Presentation for the UC Davis Center for Healthcare Policy and Research April 15,

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

5 Economics Public Health Psychiatry Clinical Psychology Education Pediatrics Family Medicine

Broad Research-Practice Agenda 6 How to invest most efficiently in health (and long- term success and wellbeing) in youth populations? Design and evaluate programs and interventions Collect descriptive population data Practice

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

9 Help-seeking and Utilization of Mental Health Care in College Populations: General Statistics

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,

Finding #1: High Prevalence of Mental Health Problems, But also Positive Mental Health 12 Data: 2012 Healthy Minds Study (29 schools, ~25,000 survey respondents)

Finding #2: About Half of Students with Mental Health Problems Receive Treatment 13 Data: 2012 Healthy Minds Study

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 14 Finding #3: When Provided, Depression Treatment is Less than “Minimally Adequate” in ~50% of Cases Data: 2009 Healthy Minds Study

Finding #4a: Variation in Mental Health across Demographic Groups 15 Data: 2012 Healthy Minds Study

Finding #4b: Variation in Utilization across Demographic Groups 16 Data: 2012 Healthy Minds Study

Finding #5: Variation by Field of Study 17 Data: 2012 Healthy Minds Study

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 18 Data: 2012 Healthy Minds Study

19 Data: 2012 Healthy Minds Study Finding #7: Variation across Campuses Data: 2012 Healthy Minds Study

20 Help-seeking and Utilization of Mental Health Care in College Populations: Barriers to Services

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 needN% Group 1XXX492% Group 2XX412% Group 3XX743% Group 4X472% Group 5XX34813% Group 6X32312% Group 7 X86833% Group %

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

29 Help-seeking and Utilization of Mental Health Care in College Populations: Economic Case

Mental Health and Academic Outcomes Mental health as predictor of academic outcomes in 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 tuition Increased lifetime productivity (earnings) Increased student satisfaction Increased institutional reputation & alumni donations Benefits to institution Benefits to students and society

33 Help-seeking and Utilization of Mental Health Care in College Populations: Intervention Research

“Gatekeeper Training” Programs Evaluation of Mental Health First Aid training for resident advisors (RAs) Co-PIs: Daniel Eisenberg and Nicole Speer Funder: NIMH ( ) 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 ( ) 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 ( ) 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 ( Pilot RCTs to begin in summer 2013 (funded by UM Comprehensive Depression Center) 37

Broad Research-Practice Agenda 38 How to invest most efficiently in health (and long- term success and wellbeing) in youth populations? Design and evaluate programs and interventions Collect descriptive population data Practice