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What’s New in the Study of Mental Health and Student Retention?. John Achter, Ph.D. AUCCCD – Fall 2008. Collaborators. Co-Investigators Kristina Gorbatenko-Roth , Ph.D. – Dept. of Psychology Jenna Maas , M.A. – Applied Psychology masters program Assistants

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slide1

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

John Achter, Ph.D.

AUCCCD – Fall 2008

collaborators
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

study 1 introduction
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
study 1 methods
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
study 1 methods5
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)
study 1 results
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
study 1 results7
Study 1 – Results

Retention Comparisons

study 1 results8
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

study 1 results9
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 (-)
study 1 results10
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 (+)
study 1 conclusions
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.
study 1 limitations
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
future research
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
study 2 methods
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
study 2 methods15
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
study 2 results
Study 2 – Results

Retention Rates by Class Status

slide17

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.

study 2 results18
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 (+)
study 2 conclusions
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
study 2 limitations
Study 2 - Limitations
  • Self-report data
  • No information available regarding reasons students were not retained
  • Did not look at reasons for seeking counseling
future research21
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
implications
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?
implications23
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?