Help-seeking and Utilization of Mental H ealth C are among Adolescents and Young A dults

1. Help-seeking and Utilization of Mental Health Care among Adolescents and Young Adults 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

2. 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

3. 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

4. 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)

5. Pediatrics Family Medicine Psychiatry Public Health Clinical Psychology Economics Education

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

7. 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

8. 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

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

10. 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

11. Healthy Minds Study, 2007-2013

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

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

14. 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

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

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

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

18. 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

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

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

21. 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

22. 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%

23. If Not Stigma, Then What?

24. 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%)

25. 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!)

26. Behavioral Economics: Time Preferences and Procrastination • Is depression related to present-orientation (discounting of future)? • Is lack of help-seeking a form of procrastination?

27. 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

28. 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?

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

30. 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%)

31. 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

32. Economic Case for Services and Programs for Student Mental Health Reduced depression Increased retention Increased student satisfaction Increased lifetime productivity (earnings) Increased tuition 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

34. “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

35. 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)

36. 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

37. 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)

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