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University of Minnesota –Twin Ci3es Students Katherine Lust, PhD, MPH, RD Boynton Health Service University of Minnesota Alcohol and First Year Students: What You Need to Know as an Advisor/ Staff/Faculty Member Focus on the First Year Conference February 13, 2013

Alcohol)and)First)Year)Students:)) …€¦ · University*of*Minnesota–Twin*Ci3es*Students* Katherine)Lust,)PhD,)MPH,)RD) BoyntonHealthService) University)of)Minnesota) Agenda)

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University  of  Minnesota  –Twin  Ci3es  Students  

Katherine  Lust,  PhD,  MPH,  RD  Boynton  Health  Service  University  of  Minnesota  

Alcohol  and  First  Year  Students:    What  You  Need  to  Know  as  an  Advisor/

Staff/Faculty  Member  

Focus  on  the  First  Year  Conference  February  13,  2013  

University  of  Minnesota  –Twin  Ci3es  Students  

Katherine  Lust,  PhD,  MPH,  RD  Boynton  Health  Service  University  of  Minnesota  

Agenda  

•  IntroducOons  •  Overview  of  College  Student  Health  Survey    &  Health  Minds  Survey    •  Overview  of  NCHIP  (NaOonal  College  Health  

Improvement  Program)    •  Panel  discussion    

Alcohol Use and Mental Health

at the University of Minnesota

Toben F. Nelson, ScD Division of Epidemiology and Community Health

•  2 modules – Mental Health – Alcohol and Other Drugs

•  Focus on service utilization and satisfaction with services

•  Web-based survey •  Part of a national sample •  Conducted in Spring 2012 •  Minnesota response rate = 35%

Minnesota Sample

•  Full-time enrolled students •  Sample drawn in February 2012 •  Includes Undergraduates, Graduate and

Professional School students •  Presented as a survey on Mental Health

and Substance Use •  Response rate = 35% (n=2,835)

•  Male (49%) •  Female (51%)

•  White (75%) •  Af. Amer./Black (4%) •  Asian/Asian Am. (17%)

Minnesota Sample

•  Age –  18-22 (60%) –  23-25 (16%) –  26-30 (15%) –  31+ (9%)

•  Relationship status – Single (52%) –  In relationship (35%) – Married/Dom. Partner (13%) – Divorced (>1%)

Minnesota Sample

Residence – Residence hall (16%) – Fraternity/Sorority house (2%) – Other campus housing (5%) – Off-campus/Non-university housing (67%) – Parent/Guardian home (9%) – Other (1%)

Minnesota Sample

Alcohol Use Patterns are Risky

•  Drink alcohol past yr –  (89%)

•  Binge drinking past 2 wk – 1 or more (36%) – 3 or more (9%)

•  Among drinkers – 10+ drinking occasions past 30 d (18%) – 3+ drunken occasions past 30 d (31%) – Usually binge when drinking (38%)

Alcohol Use Patterns are Risky Pre-gaming 2+ times past yr among drinkers (41%) Pre-gaming occasions

Before: –  House party (84%) –  Bar (63%) –  College football (37%) –  Frat party (32%) –  Other college sport event (26%) –  Pro sport event (24%)

Use energy drink with alcohol 2+ times past 30 d (9%)

Large unmet needs for alcohol misuse

Meet criteria for: Hazardous drinking (24%) Problem drinking (5%) Alcohol dependence (2%)

Proportion receiving counseling/therapy for alcohol abuse Overall (1% past yr; 0.4% current) Hazardous drinking (1%) Problem drinking (5%) Alcohol dependence (7%)

University  of  Minnesota  –Twin  Ci3es  Students  

Katherine  Lust,  PhD,  MPH,  RD  Boynton  Health  Service  University  of  Minnesota  

Demographics  

Age U of M –Twin Cities Survey participants

All

Average age (years) 24.1

Age range (years 18-61

Age groupings

18-24 years (%) 66.0

25+ years (%) 34.0

Demographics  

Gender U of M –Twin Cities Survey participants

(%) All

Male 42.2

Female 57.4

Transgender/ Other 0.2

Unspecified 0.2

Analysis:  Academic  performance  

Grade  Point  Average:  self  report  

High-­‐Risk  Drinking  All  Students  by  Age  Group  and  Gender  

Ages  21  to  24  are  the  peak  years  for  engaging  in  high-­‐risk  drinking  

0  

10  

20  

30  

40  

50  

Campus   18-­‐24  Years   25+  Years  

33.5  

37.5  

25.7  

40.3  43.7  

34.8  28.6  33.5  

17.7  

Percen

t  

All  Students   Males   Females  

High-­‐Risk  Drinking  All  Students  by  Age  Group  

0  

10  

20  

30  

40  

50  

18   19   20   21   22   23   24   25   26   27   28+  

25.6  

32.1  

37.9  

44.0  

41.5  

35.4  36.8   36.5  

28.1  

32.7  

21.2  

Percen

t  

Age  

NegaOve  Consequence  Due  to Alcohol/Drug  Use

Percent  Who  Report  Experiencing  Within  Past  12  Months

Had  a  Hangover 59.8 Performed  Poorly  on  a  Test  or  Important  Project 17.5 Been  in  Trouble  with  Police,  Residence  Hall,  or Other  College  Authori3es

5.0

Damaged  Property,  Pulled  Fire  Alarm,  etc. 2.0 Got  Into  an  Argument  or  Fight 18.0 Got  Nauseated  or  Vomited 41.1 Driven  a  Car  While  Under  the  Influence 13.6 Missed  a  Class 21.4 Been  Cri3cized  by  Someone  I  Know 19.4 Thought  I  Might  Have  a  Drinking  or Other  Drug  Problem

8.0

Had  a  Memory  Loss 24.6 Done  Something  I  Later  RegreTed 26.7 Been  Arrested  for  DWI/DUI 0.7 Have  Been  Taken  Advantage  of  Sexually 3.2 Have  Taken  Advantage  of  Another  Sexually 0.7 Tried  Unsuccessfully  to  Stop  Using 2.6 Seriously  Thought  About  Suicide 2.5 Seriously  Tried  to  Commit  Suicide 0.3 Been  Hurt  or  Injured 9.2

NegaOve  Consequences  of  Alcohol/Drug  Use  All  Students  

Average  Number  of  NegaOve  Consequences  All  Students  by  Average  Number  of  Drinks  and  High-­‐Risk  Drinking  

0  

5  

10  

15  

20  

5  or  Fewer  Drinks  per  Week   6  or  More  Drinks  per  Week   Non-­‐High-­‐Risk  Drinkers   High-­‐Risk  Drinkers  

5.0  

19.2  

4.3  

17.7  

Average  Num

ber  of  NegaO

ve  Con

sequ

ences  

Associa3on  High  Risk  Drinking  and  Nega3ve  Consequences  

0

10

20

30

40

Males Females

3.9 4.7

17.5 17.3

Num

ber

of N

egat

ive

Con

sequ

ence

s

Did not engage in HRD Engage in HRD

P  <  0.0001   P  <  0.0001  

2010  CSHS-­‐  aggregate  data  

High  Risk  Drinking    and  Grade  Point  Average  

3.35 3.38

3.27

3.19

3.12 3.11

3

3.1

3.2

3.3

3.4

3.5

Do not drink None Once Twice 3-5 times 6+ times

Gra

de P

oint

Ave

rage

Frequency within past two weeks

33.5% of U of M (TC) students report they engaged in high risk drinking within the past two weeks

Engage in HRD: Mean= 3.21

Do not engage: Mean= 3.37

P< 0.0001

2010  CSHS-­‐  aggregate  data  

High  Risk  Drinking  and  GPA  By  Gender  

3.28

3.15

3.41

3.27

3.1

3.2

3.3

3.4

3.5

3.6

Did not engage in HRD Engage in HRD

Gra

de P

oint

Ave

rage

Males Females

P  <  0.0001  2010  CSHS-­‐  aggregate  data  

Associa3on  High  Risk  Drinking  and  Marijuana  Use  

0

10

20

30

40

Did not engage in HRD Engage in HRD

5.1

24.1

Perc

ent

P  <  0.0001  

Marijuana  Use  refers  to  use  within  the  past  30  days  2010  CSHS-­‐  aggregate  data  

Mental Health Diagnosis

0  

5  

10  

15  

20  

25  

30  

Any  Diagnosed

 Men

tal  D

isorde

r  

Any  Dep

ression  

Major  Dep

ression  

Dysthym

ia  

Bipo

lar  

Cyclothymia  

Any  Anxiety  

Any  Sub

stance  Abu

se  

Disorde

r  

Alcoh

ol  Abu

se  

Disorde

r  

MH Treatment

•  Psychiatric medication past yr (14%) •  Therapy/counseling for mental health past

yr (16%)

•  Therapy or medication among those who screen positive for depression or anxiety (41%)

Whom Would You Talk to About Mental Health Issues Affecting Your

Academic Performance? •  Professor (28%) •  Academic advisor (44%) •  Another faculty member (5%) •  Teaching assistant (6%) •  No one (32%)

Supportiveness with Mental Health Issues by Academic Personnel

•  Very supportive (54%) •  Supportive (33%)

– Very supportive/Supportive (87%)

Stronger than other schools- Clear evidence of the important role that academic personnel can play

Religiosity may overlooked Students reported they are:

– Very religious (11%) – Fairly religious (28%)

Several  comments  about  the  lack  of  integra5on  of  religious  beliefs  in  addressing  mental  health  and  

alcohol  issues  on-­‐campus.  

Finances are a concern for students that may contribute to mental health

or substance use issues Current financial situation:

–  It’s a financial struggle (17%) –  It’s tight, but I’m doing fine (60%)

Financial situation growing up – Very poor, not enough to get by (2%) – Enough but not many extras (31%)

Cost  and  5me  constraints  (due  to  work)  may  impact  mental  health  status,  use  and  interven5on/

treatment.  

Final Thoughts

•  Much more to learn from analysis of data •  Plans to find analytic support •  Rapid response surveys •  2013 administration

Toben  F.  Nelson,  ScD  Assistant  Professor  Division  of  Epidemiology  &  Community  Health    School  of  Public  Health  hTp://umn.edu/~anelson  [email protected]  

QuesOons  and  Comments