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What’s New in the Study of Mental Health and Student Retention? PowerPoint Presentation
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What’s New in the Study of Mental Health and Student Retention?

What’s New in the Study of Mental Health and Student Retention?

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What’s New in the Study of Mental Health and Student Retention?

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  1. What’s New in the Study of Mental Health and Student Retention? John Achter, Ph.D. AUCCCD – Fall 2008

  2. Collaborators Co-Investigators Kristina Gorbatenko-Roth, Ph.D. – Dept. of Psychology Jenna Maas, M.A. – Applied Psychology masters program Assistants Bob Spencer, Jenna Simon, Abby Laib, EmmaLee Ericksen, Katie Hosley, and Sara Grzelak – Applied Psychology program Lindsey Grush and Mark Mittag – Mental Health Counseling program

  3. Study 1 - Introduction • The relationship between mental health and student retention has been understudied, despite a strong focus on uncovering predictors of retention in higher education contexts • Existing research among counseling center samples generally shows a retention advantage for students receiving counseling for personal problems compared to non-counseled students • Limited research exists examining the effect of mental health issues on retention among a general student population

  4. Study 1 - Methods Questions • Does mental health status predict retention rates of college students? • For those with mental health needs, does seeking mental health care predict retention? Sample • 2201 undergraduate students at midsized Midwestern public university • 57% female; 93% Caucasian; equal class representation • Representative in terms of ACT, HS Rank, College GPA

  5. Study 1 - Methods Procedures • Step 1: Assessed undergraduate mental health needs and treatment seeking via electronic health survey to all students (39% response rate) – Spring 2006 • MH Need Status: “As a college student, have you ever needed healthcare services for mental health concerns (e.g. stress, depression, relationship issues)?” • MH Care Seeking Status : “Did you ever actually seek care anywhere for mental health concerns?” • Step 2: Assessed retention status in Spring 2007 (1 year post-survey)

  6. Study 1 – Results Descriptives • Experienced a Mental Health Need During College • 16.8% (N=369) of total sample (N=2201) • Sought Mental Health Care Anywhere • 62.3% (N=230) of people with need sought care • 37.1% (N=137) of people with need did NOT seek care • 0.5% (N=2) no response to item query

  7. Study 1 – Results Retention Comparisons

  8. Study 1 -Results Significant Bivariate Relationships (Test of Independence (2) CΦ: Cramer’s V Black= Negative Relationship (positive on condition = less likely to be retained) Red = Freshmen & Seniors less likely to be retained then Sophomores and Juniors

  9. Study 1 - Results Binary Logistic Regression – Full Sample (n=1402) • Block 1: Academic & demographic predictors • Gender, Minority status, Low income status, 1st Generation status, Year in College, ACT, High School Rank, Cumulative GPA • Nagelkerle R2= .199 • Block 2: Mental health status during college • Nagelkerle R2= .199 • Mental Health need did not account for additional variance • Significant predictors (p ≤ .02) and direction of relationship • Class year (mixed), Cum. GPA (+), high school %ile rank (+), 1st gen. status (-)

  10. Study 1 - Results Binary Logistic Regression – Mental Health Sample (n=219) • Block 1: Academic & demographic predictors • Nagelkerle R2= .272 • Block 2: Mental health care-seeking during college • Nagelkerle R2= .321 • Seeking MH treatment accounts for 5% more retention variance and increases ID of non-retention by 10.8% (full model=18.9%; reduced model=8.1%) • Significant predictors (p ≤ .02) and direction of relationship • Class year (mixed), Care seeking (-), 1st gen. status (-), low inc. status (+)

  11. Study 1 - Conclusions • Mental health (MH) need related to lower retention in bi-variate but not multivariate analyses (possible co-variation effect) • For those with a MH need, seeking care was predictive of retention, above and beyond traditional predictors • 2nd strongest predictor after year in college • Unexpectedly, seeking care was related to lower retention. • Current study is 1st known to look at a population (vs. treatment) sample and to control for other variables related to retention • Hypothesis: seeking MH care is a proxy for MH severity • More research is needed to tease out the complex relationship between mental health needs, treatment, & college persistence.

  12. Study 1 - Limitations • Self-report data • No measure of type or severity of mental health issue • No data on whether treatment was actually received, nor on type or amount of treatment • No information available regarding reasons students were not retained

  13. Future Research • Seek replication of findings among other general university populations • Examine several types of mental health related data, not just self-report data • Examine whether type or amount of treatment impacts retention • Examine whether severity of mental health need relates to retention

  14. Study 2 - Methods Questions • Among counseling center clients, does severity of distress predict retention? • Among counseling center clients, does treatment length predict retention? Sample • 757 undergraduate students at midsized Midwestern public university, seeking counseling from 2003-2007 • No career counseling; no mandated alcohol clients • 69% female; 94% Caucasian; Class year: FR-30%; SO-22%; JR-22%; SR-26% • Representative in terms of ACT, HS Rank, College GPA

  15. Study 2 - Methods Measures • Retention: Students were considered retained if they earned credits or graduated within one year after a treatment episode • Episodes: defined as specific periods of treatment need for each subject • 865 treatment episodes; 80% had 1; 16% had 2 • # of sessions ranged from 1-51; Mean=5.26; Median=3 • Severity: Subject’s maximum score during episode on the “Outcome Questionnaire 45.2” (OQ-45.2) • Mean=75; SD=25

  16. Study 2 – Results Retention Rates by Class Status

  17. Study 2 - Results Retention: Significant bi-variate relationships • Year in College: 2 (3) =58.513, p=.00 • # Treatment Sessions: r =.109, p=.001 • Severity of Mental Health Need: r = -.08 (p=.02) Note: Severity of need and # of sessions also correlated r = .153, p=.001. This suggests a possible interaction and the need to look closer at relationship between these variables and how they impact retention.

  18. Study 2 - Results Binary Logistic Regression • Block 1: Academic & demographic predictors • Age, Gender, Low income status, 1st Generation status, Year in College, ACT, High School Rank • Nagelkerle R2= .142 • Block 2: Severity and treatment length • Nagelkerle R2= .183 • Severity and Treatment Length accounted for 4% more variance and increased ID of non-retention by 11.8% (full model=13.6%; reduced model=1.8%) • Significant predictors (p ≤ .04) and direction of relationship • Freshman status (-), OQ score (-), # of sessions (+)

  19. Study 2 - Conclusions • Results were in expected directions • As severity of distress increased, the likelihood of being retained decreased • As treatment length increased, the likelihood of being retained increased • Treatment length and severity of distress predicted retention above and beyond academic and demographic factors However. . . • Retention rates among counseling center clients is lower than in the general student population

  20. Study 2 - Limitations • Self-report data • No information available regarding reasons students were not retained • Did not look at reasons for seeking counseling

  21. Future Research • Seek replication of findings among other university counseling center populations – include effect sizes • Examine several types of mental health related data • Look at interactions between severity and treatment length variables • Look at changes in distress over time • Control for other variables known to impact retention

  22. Implications • I still can’t explain study 1 results! • Could avoidance be functional? • Are treatment-seeking students more severe? Did they really seek help? • It may not be that counseling centers can boast higher retention rates than the general student population—at least not for those presenting with mental health needs • Nonetheless, studies like Wilson et. al (1997), and the present study, show that for this at-risk population, students who need treatment are more likely to be retained if they get treatment than if they don’t • The more severe the distress, the more intervention may be needed. Are our centers equipped for this?

  23. Implications • Do we have sufficient resources to reach out and identify the most at-risk students, and to provide adequate services once they seek help? • Your thoughts?