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Journal of College Student Psychotherapy

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Major Differences: Variations in Undergraduateand Graduate Student Mental Health andTreatment Utilization Across Academic Disciplines

Sarah Ketchen Lipson, Sasha Zhou, Blake Wagner III, Katie Beck & DanielEisenberg

To cite this article: Sarah Ketchen Lipson, Sasha Zhou, Blake Wagner III, Katie Beck & DanielEisenberg (2016) Major Differences: Variations in Undergraduate and Graduate Student MentalHealth and Treatment Utilization Across Academic Disciplines, Journal of College StudentPsychotherapy, 30:1, 23-41, DOI: 10.1080/87568225.2016.1105657

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Major Differences: Variations in Undergraduate andGraduate Student Mental Health and Treatment UtilizationAcross Academic DisciplinesSarah Ketchen Lipson, Sasha Zhou, Blake Wagner III, Katie Beck,and Daniel Eisenberg

University of Michigan, Ann Arbor, Michigan, USA

ABSTRACTThis article explores variations in mental health and service utiliza-tion across academic disciplines using a random sample of under-graduate and graduate students (N = 64,519) at 81 colleges anduniversities. We report prevalence of depression, anxiety, suicid-ality, and self-injury, and rates of help-seeking across disciplines,including results from multivariate logistic regressions. We findsignificant variations: Students in humanities and art and designare significantly more likely to have mental health problems; andfor students with apparent mental health problems, treatmentrates are lowest among those in business and engineering. Notingthese variations could enhance efforts to promote student mentalhealth, particularly within academic departments.

KEYWORDSAcademic disciplines;college students; help-seeking; mental health

Depression, anxiety, suicidality, and self-injury are all growing concerns atcolleges and universities across the country. Over 90% of campus counselingcenter directors report an increase in the prevalence and severity of psychologicalproblems in recent years (Blanco et al., 2008; Gallagher, 2006). Roughly one thirdof students meet diagnostic criteria for a psychiatric disorder (Eisenberg, Hunt, &Speer, 2013). The majority of these students are not receiving mental healthservices (Blanco et al., 2008; Eisenberg, Golberstein, & Gollust, 2007; Eisenberg,Hunt, Speer, & Zivin, 2011). Untreated symptoms often become more frequent,severe, and treatment resistant over time (Wang et al., 2005).

For several reasons, college students have a special significance for mentalhealth policy. Nearly three quarters of lifetime mental illnesses have first onsetby the mid-20s (Kessler et al., 2007). Additionally, mental health in earlyadulthood is linked to several important outcomes, including social connected-ness (Berkman, Glass, Brissette, & Seeman, 2000; Hefner & Eisenberg, 2009;Whitlock, Wyman, & Barreira, 2010), academic performance and retention(Arria et al., 2013; Eisenberg, Golberstein, & Hunt, 2009), and future economicproductivity (Wang et al., 2007). Given the importance of these factors, there isa growing body of research focused on campus mental health.

CONTACT Sarah Ketchen Lipson, EdM sklipson@umich.edu Department of Health Management & Policy,School of Public Health, University of Michigan, 1415 Washington Heights, SPH II, Ann Arbor, MI 48109-2029, USA.

JOURNAL OF COLLEGE STUDENT PSYCHOTHERAPY2016, VOL. 30, NO. 1, 23–41http://dx.doi.org/10.1080/87568225.2016.1105657

© 2016 Taylor & Francis

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To better understand and address what many refer to as the “campusmental health crisis” (Schwartz & Kay, 2009), researchers have tried toidentify risk factors by examining variations in mental health, help-seeking,and related behaviors (e.g., substance use) across demographic groups,including by gender (Nam et al., 2010), race/ethnicity (Davidson,Yakushko, & Sanford-Martens, 2004; Kearney, Draper, & Baron, 2005), andcitizenship (Yakushko, Davidson, & Sanford-Martens, 2008). This researchhas had meaningful implications for campus mental health practice, includ-ing the development of tailored, culturally sensitive intervention and preven-tion programs. There is little research, however, examining if and howmental health and help-seeking vary across academic fields.

There are multiple mechanisms that might result in differences in well-beingand help-seeking across disciplines. Several studies have examined correlationsbetween personality characteristics and choice of academic disciplines (Norman& Redlo, 1952) as well as genetic links between mental illness and intellectualinterests (Campbell & Wang, 2012). A single-campus study of incoming under-graduates found that students aspiring to science, technology, engineering, andmathematics (STEM) fields were more likely to report a sibling with autismspectrum disorder, while prospective humanities majors were more likely toreport a family member with major depressive disorder, bipolar disorder, orsubstance abuse disorder. From these findings, the researchers concluded that“shared genetic (and perhaps environmental) factors may both predispose forheritable neuropsychiatric disorders and influence the development of intellec-tual interests” (Campbell & Wang, 2012).

Students may also face different stressors depending on their choice ofacademic concentration. For example, STEM courses are commonly taughtas large lectures and faculty often employ practices that “weed out” students(e.g., grading on a curve; Astin & Sax, 1996), fostering competition anddiscouraging collaborative learning (Shapiro & Sax, 2011). However, researchon help-seeking among enrolled students has focused primarily on law andmedical school students, who have been found to have higher rates of distress(Dyrbye, Thomas, & Shanafelt, 2006; Reifman, McLntosh, & Ellsworth,2001). Mental health and help-seeking among students in other fields hasbeen studied less frequently. The present article looks at variations in studentmental health and help-seeking across academic disciplines using a nationalsurvey data set from colleges and universities in the United States.

Methods

Data

The Healthy Minds Study (HMS) is an annual web-based survey examiningmental health and service utilization among undergraduate and graduate

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students (Healthy Minds Network, 2007–2013). Colleges and universitieselect to participate (i.e., this is not a random sample of campuses). At eachinstitution with more than 4,000 students, our study team recruited a ran-dom sample of 4,000 students from the full population; on campuses withless than 4,000 students, we recruited all students. Students were asked toparticipate in the survey via e-mail. To engage nonresponders, we sent up tothree reminders over the month-long data collection period. In the presentstudy, we used aggregate data from 2007–2013. These data represent 81unique institutions. For institutions that participated two or more times,we include only their most recent year of data. The sample is comprisedalmost entirely of 4-year institutions (94.9%) and is diverse across manycampus characteristics, including institutional type, enrollment, geographiclocation, and admission selectivity. The overall response rate across all yearsof the study was 25.2% (with a range of 3.3% to 62.7% across institutions).The survey was administered using Illume’s online survey software. HMS wasapproved by the Institutional Review Boards on all participating campuses.

To adjust for potential differences between survey responders and non-responders, we constructed sample probability weights. We obtained admin-istrative data from participating institutions, including gender, race/ethnicity,academic level, and grade point average. We then constructed responseweights, equal to 1 divided by the estimated probability of response, usinga logistic regression to predict the likelihood of response associated with eachof these variables. Weights are larger for respondents with underrepresentedcharacteristics, thus ensuring that estimates are representative of the fullpopulation in terms of the basic characteristics noted previously.

Measures

Academic disciplinesIn HMS, students are asked “What is your field of study?” and are instructed to“select all that apply” from a list of 22 options: humanities, social science,natural science and mathematics, art and design, architecture and urban plan-ning, business, dentistry, education, engineering, information, kinesiology, law,medicine, music, natural resources and environment, nursing, pharmacy, publichealth, public policy, social work, other, and undecided. For the purpose of thepresent analyses, we recategorized students into 14 disciplines: humanities,social sciences (including education and public policy), natural sciences andmathematics (including natural resources and environment), art and design(including music and architecture/urban planning), engineering, business, law,social work, public health, nursing, medicine (including pharmacy and dentis-try), other (including information and kinesiology), multidisciplinary (studentswho selected more than one field of study), and undecided (undergraduatesonly). Academic disciplines were used as independent variables.

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DepressionIn HMS, symptoms of depression in the past 2 weeks are measured using thePatient Health Questionnaire-9 (PHQ-9), a validated screening instrumentbased on the nine core symptoms of a major depressive episode (Spitzer,Kroenke, & Williams, 1999). We created a binary measure (positive/negativescreen) using the instrument’s standard algorithm. Across settings andpopulations, the PHQ-9 has been validated as internally consistent andhighly correlated with clinical diagnosis (Diez-Quevedo, Rangil, Sanchez-Planell, Kroenke, & Spitzer, 2001; Löwe et al., 2004). The PHQ-9 had highinternal consistency in previous studies with college students (Cronbach’salpha = 0.84; Eisenberg, Nicklett, Roeder, & Kirz, 2011), as well as in thissample (Cronbach’s alpha = 0.87).

AnxietyThe PHQ was also used to measure anxiety (symptoms of panic disorder andgeneralized anxiety disorder [GAD]). The PHQ GAD screen begins with thequestion: “Over the last 4 weeks, how often have you been bothered byfeeling nervous, anxious, on edge or worrying a lot about different things?”For students who select “More than half the days,” an additional six symp-toms of anxiety are assessed. Students are then coded as screening positivefor GAD if three or more of the six symptoms are experienced “more thanhalf the days.” The panic disorder screen begins with the question: “In thelast 4 weeks, have you had an anxiety attack—suddenly feeling fear orpanic?”; respondents who answer “yes” are then asked follow-up questionsthat determine criteria for a positive panic disorder screen. The PHQ anxietymodule has been validated in diverse populations (Spitzer et al., 1999) andhas been found to be highly sensitive and specific—81% and 99%, respec-tively, for panic disorder, and 63% and 97% for generalized anxiety (Spitzeret al., 1999). We used the standard algorithm to create a binary measure,categorizing students as screening positive or negative for anxiety. In 2013,the HMS anxiety screen was switched to the Generalized Anxiety Disorder 7-item (GAD-7) (Spitzer, Kroenke, Williams, & Lowe, 2006). In our analysesexploring variations across academic disciplines in anxiety symptoms andhelp-seeking among students with positive screens for anxiety, we use onlythe 2007–2012 sample (64 schools, N = 46,888). A positive screen on theGAD-7 is included in the operationalization of “any mental health problem”(see as follows).

Suicidal ideationA single question measured suicidal ideation: “In the past year, did you everseriously think about committing suicide?” Students answered “yes” or “no”and were categorized accordingly.

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Nonsuicidal self-injury (NSSI)A single question was also used to assess self-injurious behavior:

This question asks about ways you may have hurt yourself on purpose, withoutintending to kill yourself. In the past 4 weeks, have you ever done any of thefollowing intentionally?: Cut myself, burned myself, banged my head or other bodypart, scratched myself, punched myself, pulled my hair, bit myself, interfered withwound healing, other, or no, none of these.

Students are instructed to “select all that apply.” We created a binary measureof NSSI (any vs. none).

Any mental health problemWe created a binary measure of any mental health problem, defined as thepresence of one or more of the previously mentioned problems (a positivescreen or “yes” response to any of the conditions) or the absence of all of thepreviously mentioned problems (all negative screens and “no” responses).

Treatment utilizationWe created a binary measure of any past-year mental health treatmentutilization based on two survey items: “In the past 12 months have youreceived counseling or therapy for your mental or emotional health from ahealth professional?” and “In the past 12 months have you taken any of thefollowing types of prescription medications?” Students who answered “yes”to either are considered treatment users. Treatment utilization is exploredonly for students who meet the aforementioned criteria for any mentalhealth problem.

Analysis

We stratified our sample by degree level: bachelors, masters, and doctoral(including terminal professional degrees, such as JD, MD, PhD). As withacademic disciplines, the survey item for degree level instructed students to“select all that apply”; students who selected more than one degree (e.g.,students in dual degree programs) are included in multiple categories. In thefirst set of analyses, we calculated basic descriptive statistics, reporting pre-valence across academic disciplines for each mental health measure (thedependent variables). Next, we used multivariable logistic regressions toestimate independent correlates of mental health, controlling for students’age, gender, citizenship, race/ethnicity, and parental education. These ana-lyses also include a dummy for field of study; the reference category is socialsciences. In sensitivity analyses, we also included school dummy variables inthe multivariable regressions to confirm that correlations with academicdisciplines were not driven by institutional-level factors or by differences

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across sample years. The magnitude, direction, and significance of all ourmain findings remained consistent (results available upon request). Analyseswere conducted using Stata 12 and were weighted using the sample prob-ability weights described above.

Results

Sample characteristics

Our analyses focus on undergraduate (N = 48,667), masters (N = 9,872),and doctoral (N = 5,980) students. The sample was 56.1% female, 71.3%White, and 6.5% international, characteristics roughly similar to thenational population of both undergraduate and graduate students at 4-year institutions in terms of gender (57%, 60%, and 52% female nationallyfor undergraduate, masters, and doctoral programs, and 56%, 57%, and48% in the survey data for undergraduate, masters, and doctoral programs,respectively), and slightly higher in terms of percent White for under-graduates but roughly similar for graduate students (62% and 69% Whitenationally for undergraduate and graduate programs, and 72% and 66% inthe survey data for undergraduate and graduate programs, respectively)(Aud et al., 2012). In Table 1, we report individual characteristics forstudents in each academic discipline.

Prevalence of mental health problems and service utilization (see Table 2)

Undergraduate studentsOverall, 35.5% of undergraduates met criteria for at least one mental healthproblem, with rates across academic disciplines ranging from 28.3% (publichealth) to 45.3% (art and design). Among undergraduates with an apparentmental health problem, 39.4% received treatment in the past year, with ratesranging from 25.1% (engineering) to 49.9% (social work).

Master’s studentsOverall, 26.2% of master’s students met criteria for at least one mental healthproblem, with rates ranging from 17.6% (nursing) to 38.6% (art and design).Among master’s students with an apparent mental health problem, 40.5%received treatment in the past year, with rates ranging from 20.2% (engineer-ing) to 66.0% (social work).

Doctoral studentsOverall, 26.7% of doctoral students met criteria for at least one mental healthproblem, with rates ranging from 13.7% (nursing) to 54.8% (social work).Among doctoral students with an apparent mental health problem, 40.9%

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Table1.

DescriptiveStatistics.

Social

Sciences

(N=10,678)

Hum

anities

(N=3,392)

Natural

Sciences

(N=5,989)

Art&

Design

(N=4,613)

Engineering

(N=4,287)

Business

(N=6,191)

Law

(N=1,142)

Social

Work

(N=1,154)

Public

Health

(N=1,101)

Nursing

(N=2,111)

Medicine

(N=1,873)

Other

(N=7,626)

Multid

isciplinary

(N=12,381)

Und

ecided

(N=1,172)

Female

66.43

57.54

48.14

58.97

18.11

44.73

45.10

82.55

73.73

85.68

58.87

57.02

59.79

59.11

International

4.42

3.29

8.18

12.22

16.57

11.25

5.74

1.51

6.67

1.85

4.30

3.64

3.80

2.27

Und

ergraduate

78.54

83.08

82.80

88.64

77.85

83.06

38.37

57.40

59.77

86.72

46.56

81.89

91.76

100.00

Masters

15.96

9.18

6.36

10.77

13.55

17.07

6.02

40.85

34.80

10.35

11.02

16.42

7.41

—Doctoral

6.40

8.30

11.40

0.81

10.17

0.84

56.10

2.28

5.73

3.47

44.01

2.27

3.39

—White

73.16

79.66

72.45

65.40

62.43

67.73

69.82

65.29

62.95

70.03

61.22

73.84

75.53

74.24

African

American

9.19

6.92

6.28

3.88

3.57

7.77

10.37

16.20

12.68

12.31

10.67

8.41

7.83

7.31

Asian

6.65

4.14

12.88

20.86

22.10

13.72

8.18

4.20

13.16

9.26

16.79

6.59

9.91

9.76

Latin

o/a

10.34

8.29

7.46

8.20

9.85

9.52

8.42

11.51

8.76

7.71

19.05

10.65

7.67

8.74

Other

race

5.48

5.26

5.48

6.65

7.70

4.07

6.44

6.83

6.21

3.53

7.76

5.35

6.79

5.47

Note.Percentages(reportedin

parentheses)arethepercentage

ofeach

academ

icdiscipline.ThecolumnforUnd

ecided

includ

eson

lyun

dergradu

ates.

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Table2.

Prevalence

ofMentalH

ealth

Prob

lemsandTreatm

entUtilization.

Und

ergraduate

Stud

ents

Master’s

Stud

ents

DoctoralS

tudents

Dep

Anx

SINSSI

Any

TxDep.

Anx.

SINSSI

Any

TxDep.

Anx.

SINSSI

Any

Tx

SOC

17.58

10.50

8.03

16.31

34.17

44.47

10.72

8.33

4.00

9.62

23.81

43.34

14.55

9.34

7.43

10.20

29.11

45.67

HUM

20.92

12.82

10.75

20.51

39.54

42.17

19.78

6.77

8.22

16.43

36.20

38.87

21.06

14.05

9.81

13.41

35.40

54.05

NAT

18.74

8.10

8.58

17.66

35.75

37.04

13.07

6.17

7.04

11.77

25.94

41.23

14.02

6.35

4.92

11.54

27.29

31.14

ART

26.85

15.35

10.72

23.18

45.26

43.15

20.01

11.20

7.44

14.48

38.62

44.38

25.52

13.58

8.66

10.44

32.11

46.13

ENG

17.58

6.52

6.00

14.75

31.66

25.09

19.32

4.30

5.16

13.43

30.56

20.23

15.83

4.17

4.81

9.17

26.16

27.73

BUS

15.65

7.55

5.27

11.71

28.64

31.26

10.76

5.15

2.28

5.33

18.58

31.41

10.40

11.34

5.29

7.39

22.01

35.20

LAW

23.26

4.65

6.96

13.89

36.22

26.36

14.56

13.83

6.40

5.22

26.80

29.21

12.37

9.47

4.55

11.00

25.20

48.81

SW18.40

14.46

10.33

16.32

37.53

49.94

10.50

9.22

3.24

8.94

23.06

66.03

46.00

5.51

5.30

8.47

54.83

26.68

PH16.41

10.24

6.89

8.81

28.29

38.63

8.68

6.47

3.56

7.18

19.21

48.06

13.94

0.00

5.23

8.70

18.64

36.38

NUR

16.53

11.54

5.19

9.23

29.12

39.10

8.29

10.17

1.55

4.13

17.64

47.39

9.49

0.00

3.65

0.99

13.72

56.22

MED

21.83

11.76

9.91

15.54

37.92

30.89

17.30

13.58

4.44

9.50

29.38

48.38

9.19

5.44

3.60

6.88

20.49

39.61

OTH

17.31

9.69

7.24

15.02

32.02

37.64

11.87

7.98

3.79

7.94

23.77

41.34

9.97

6.87

3.50

6.62

23.82

46.28

MULT

19.13

11.41

8.85

20.44

38.41

42.55

17.86

10.62

6.55

12.75

33.74

38.91

16.14

11.14

6.76

13.92

31.31

38.14

UNDEC

25.99

10.75

10.59

21.17

41.68

36.99

——

——

——

——

——

——

Note.Dep

=Depression;

Anxiety(Anx)exclud

es2013;SI=

suicidalideatio

n;NSSI=

nonsuicidalself-injury;A

ny=An

yMentalH

ealth

Prob

lem;TreatmentUtilization(Tx)

isam

ong

stud

entswith

atleaston

eapparent

mentalhealth

(MH)p

roblem

;SOC=SocialSciences;H

UM=Hum

anities;N

AT=NaturalSciences;A

RT=Art&

Design;EN

G=Engineering;BU

S=Bu

siness;LAW

=Law;SW

=SocialWork;PH

=PublicHealth

;NUR=Nursing

;MED

=Medicine;OTH

=Other;M

ULT

=Multid

isciplinary;UNDEC

=Und

ecided.

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received treatment in the past year, with rates ranging from 26.7% (socialwork) to 56.2% (nursing). Given that there were only 10 doctoral social workstudents that met criteria for at least one mental health problem, it may bemore important to note the second lowest rate of help-seeking: Of the 160doctoral engineering students with an apparent mental health problem, just27.7% received treatment in the past year.

Independent correlates of mental health problems and service utilization

As follows, we report selected results significant at p ≤ .01 from the multi-variable logistic regression models, which control for a set of individualcovariates (age, gender, citizenship, race/ethnicity, and parental education).

Undergraduate studentsControlling for covariates and relative to their peers in the social sciences,undergraduates in art and design were significantly more likely to screenpositive for depression and anxiety, to report suicidal ideation and NSSI, andto meet criteria for at least one mental health problem (see Table 3). Similarly,undergraduates in the humanities were significantly more likely to screenpositive for depression and anxiety, to report suicidal ideation and NSSI, andto meet criteria for at least one mental health problem. Multidisciplinaryundergraduates were significantly more likely to report NSSI and to meetcriteria for at least one mental health problem. Undecided undergraduateswere significantly more likely to screen positive for depression and to meetcriteria for at least one mental health problem. Undergraduates in businesswere significantly less likely to screen positive for depression, to report suicidalideation and NSSI, and to meet criteria for at least one mental health problem.Nursing undergraduates were significantly less likely to report suicidal ideationand NSSI and to meet criteria for at least one mental health problem.Engineering undergraduates were significantly less likely to report suicidalideation, while public health undergraduates were significantly less likely toreport NSSI. Compared to undergraduates with an apparent mental healthproblem in the social sciences, the following academic disciplines were asso-ciated with significantly decreased likelihood of seeking help: natural sciences,engineering, business, and “other discipline.”

Master’s studentsControlling for covariates and relative to their peers in the social sciences,masters students in art and design were significantly more likely to screenpositive for depression and to meet criteria for at least one mental healthproblem (see Table 4). Humanities students were significantly more likely toscreen positive for depression, to report suicidal ideation, and to meet criteriafor at least one mental health problem. Multidisciplinary masters students

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Table3.

MultivariableCo

rrelates

ofMentalH

ealth

Prob

lemsAm

ongUnd

ergraduate

Stud

ents,Log

istic

Regression

s.Dep

Anx

SINSSI

Any

Tx

OR

p95%

CIOR

p95%

CIOR

p95%

CIOR

p95%

CIOR

p95%

CIOR

p95%

CI

SOC

——

——

——

——

——

——

——

——

——

——

——

——

HUM

1.32

<.001

1.13

1.54

1.40

.001

1.14

1.73

1.37

.002

1.12

1.68

1.33

<.001

1.14

1.55

1.31

<.001

1.16

1.49

0.88

.25

0.72

1.09

NAT

1.10

.15

0.97

1.25

0.85

.12

0.70

1.04

1.04

.69

0.87

1.24

1.08

.26

0.95

1.23

1.07

.19

0.97

1.19

0.73

<.001

0.62

0.87

ART

1.72

<.001

1.52

1.95

1.76

<.001

1.49

2.07

1.31

.002

1.11

1.56

1.54

<.001

1.36

1.75

1.59

<.001

1.44

1.76

0.97

.73

0.82

1.15

ENG

0.96

.64

0.83

1.12

1.00

.99

0.75

1.34

0.66

<.001

0.53

0.83

0.89

.15

0.76

1.04

0.90

.09

0.79

1.02

0.53

<.001

0.42

0.67

BUS

0.82

.004

0.72

0.94

0.79

.02

0.65

0.96

0.62

<.001

0.51

0.76

0.70

<.001

0.60

0.80

0.76

<.001

0.69

0.85

0.63

<.001

0.52

0.76

LAW

1.15

.52

0.74

1.79

0.52

.09

0.24

1.12

0.86

.58

0.49

1.49

0.85

.56

0.50

1.45

0.96

.84

0.67

1.39

0.60

.14

0.31

1.18

SW1.04

.79

0.79

1.35

1.06

.72

0.77

1.45

1.35

.08

0.97

1.88

1.03

.83

0.78

1.36

1.08

.50

0.87

1.34

1.15

.42

0.82

1.62

PH0.85

.35

0.62

1.18

0.90

.59

0.60

1.34

0.90

.70

0.53

1.53

0.56

.01

0.36

0.87

0.74

.02

0.57

0.95

0.73

.13

0.49

1.10

NUR

0.90

.34

0.72

1.12

0.99

.96

0.77

1.28

0.64

.003

0.48

0.86

0.56

<.001

0.45

0.70

0.79

.01

0.67

0.94

0.79

.11

0.60

1.05

MED

1.18

.28

0.88

1.58

1.28

.29

0.81

2.01

1.15

.58

0.71

1.86

0.86

.38

0.61

1.20

1.08

.54

0.85

1.36

0.75

.16

0.50

1.12

OTH

0.97

.65

0.86

1.10

0.97

.68

0.82

1.13

0.86

.09

0.72

1.02

0.90

.12

0.80

1.03

0.90

.04

0.82

0.99

0.74

<.001

0.63

0.87

MULT

1.13

.03

1.02

1.25

1.15

.05

1.00

1.32

1.05

.52

0.91

1.20

1.25

<.001

1.12

1.38

1.18

<.001

1.08

1.28

0.92

.22

0.80

1.05

UNDEC

1.66

<.001

1.36

2.04

1.19

.30

0.86

1.64

1.32

.06

0.98

1.77

1.25

.05

1.00

1.55

1.39

<.001

1.17

1.66

0.90

.48

0.67

1.20

Constant

0.28

<.001

0.23

0.33

0.06

<.001

0.05

0.08

0.11

<.001

0.09

0.15

0.23

<.001

0.20

0.28

0.56

<.001

0.49

0.65

0.30

<.001

0.23

0.38

N46,433

33,794

46,315

45,566

45,631

15,672

Note.CI

=confidence

interval;O

R=od

dsratio

;Dep

=Depression;

Anxiety(Anx)exclud

es2013;SI=suicidal

ideatio

n;NSSI=no

nsuicidalself-injury;A

ny=An

yMentalHealth

Prob

lem;TreatmentU

tilization(Tx)isam

ongstud

entswith

atleasto

neapparent

mentalhealth

(MH)p

roblem

;SOC=SocialSciences;H

UM=Hum

anities;N

AT=NaturalSciences;

ART=

Art&Design;

ENG

=Engineering;

BUS=

Business;LAW

=Law;SW

=Social

Work;

PH=

Public

Health

;NUR=

Nursing

;MED

=Medicine;

OTH

=Other;MULT

=Multid

isciplinary;UNDEC

=Und

ecided.A

llmod

elscontrolforsurvey

year

andstud

ents’age,

gend

er,citizenship,

race/ethnicity,and

parental

education.

Referencecatego

ryis

Social

Sciences.

32 S. K. LIPSON ET AL.

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Table4.

MultivariableCo

rrelates

ofMentalH

ealth

Prob

lemsAm

ongMaster’s

Stud

ents,Log

istic

Regression

s.Dep

Anx

SINSSI

Any

Tx

OR

p95%

CIOR

p95%

CIOR

p95%

CIOR

p95%

CIOR

p95%

CIOR

p95%

CI

SOC

——

——

——

——

——

——

——

——

——

——

——

——

HUM

2.15

.001

1.35

3.42

0.98

.94

0.55

1.73

2.10

.01

1.19

3.72

1.58

.03

1.05

2.37

1.70

.003

1.20

2.41

1.02

.95

0.61

1.68

NAT

1.22

.33

0.82

1.82

0.76

.33

0.43

1.33

1.77

.03

1.07

2.94

1.12

.57

0.76

1.66

1.10

.54

0.81

1.49

1.13

.64

0.67

1.91

ART

1.95

<.001

1.39

2.72

1.44

.12

0.91

2.27

1.61

.05

1.01

2.56

1.32

.13

0.93

1.87

1.80

<.001

1.39

2.33

1.09

.71

0.70

1.70

ENG

1.35

.08

0.97

1.89

0.62

.11

0.34

1.11

1.07

.80

0.66

1.71

1.12

.54

0.77

1.63

1.15

.32

0.88

1.49

0.54

.02

0.33

0.89

BUS

0.90

.55

0.64

1.27

0.71

.10

0.48

1.06

0.49

.003

0.31

0.78

0.47

<.001

0.34

0.66

0.68

.002

0.53

0.87

0.66

.07

0.42

1.03

LAW

0.79

.52

0.40

1.59

1.20

.76

0.38

3.79

0.58

.38

0.17

1.96

0.44

.14

0.15

1.31

0.64

.15

0.34

1.18

0.55

.32

0.17

1.81

SW0.88

.66

0.49

1.56

1.10

.69

0.69

1.73

0.71

.30

0.36

1.37

0.87

.49

0.59

1.29

0.86

.40

0.60

1.23

2.13

.004

1.27

3.56

PH0.72

.15

0.47

1.13

0.79

.36

0.48

1.31

0.78

.43

0.43

1.43

0.53

.01

0.33

0.83

0.60

.001

0.44

0.82

1.30

.37

0.74

2.30

NUR

0.82

.47

0.47

1.41

1.05

.88

0.55

2.00

0.42

.06

0.17

1.04

0.37

.01

0.19

0.74

0.66

.05

0.44

1.01

0.93

.87

0.40

2.17

MED

1.62

.05

1.00

2.64

1.35

.31

0.75

2.43

0.98

.97

0.44

2.21

0.68

.23

0.36

1.28

1.06

.77

0.71

1.58

1.13

.73

0.57

2.23

OTH

1.07

.68

0.77

1.50

0.99

.95

0.68

1.43

0.90

.62

0.60

1.36

0.70

.02

0.52

0.94

0.95

.67

0.76

1.20

0.94

.75

0.64

1.38

MULT

1.75

.001

1.24

2.47

1.39

.13

0.91

2.14

1.34

.18

0.87

2.07

0.92

.59

0.67

1.25

1.32

.03

1.02

1.70

0.95

.80

0.64

1.41

Constant

0.17

<.001

0.10

0.29

0.09

<.001

0.04

0.19

0.06

<.001

0.02

0.15

0.35

<.001

0.20

0.60

0.54

.004

0.35

0.82

0.22

<.001

0.10

0.47

N9,282

6,866

9,275

9,171

9,157

2,346

Note.CI

=confidence

interval;O

R=od

dsratio

;Dep

=Depression;

Anxiety(Anx)exclud

es2013;SI=suicidal

ideatio

n;NSSI=no

nsuicidalself-injury;A

ny=An

yMentalHealth

Prob

lem;TreatmentU

tilization(Tx)isam

ongstud

entswith

atleasto

neapparent

mentalhealth

(MH)p

roblem

;SOC=SocialSciences;H

UM=Hum

anities;N

AT=NaturalSciences;

ART=

Art&Design;

ENG

=Engineering;

BUS=

Business;LAW

=Law;SW

=Social

Work;

PH=

Public

Health

;NUR=

Nursing

;MED

=Medicine;

OTH

=Other;MULT

=Multid

isciplinary.Allm

odelscontrolfor

survey

year

andstud

ents’age,g

ender,citizenship,race/ethn

icity,and

parental

education.

Referencecatego

ryisSocial

Sciences.

JOURNAL OF COLLEGE STUDENT PSYCHOTHERAPY 33

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were more likely to screen positive for depression. Business students weresignificantly less likely to report suicidal ideation and NSSI, and to meetcriteria for at least one mental health problem. Public health students weresignificantly less likely to report NSSI and to meet criteria for at least onemental health problem, while nursing students were significantly less likely toreport NSSI. Compared to masters students with an apparent mental healthproblem in the social sciences, students in social work were significantlymore likely to receive treatment.

Doctoral studentsControlling for covariates and relative to their peers in the social sciences,doctoral students in the humanities and social work were significantly morelikely to screen positive for depression (see Table 5). Medical students weresignificantly less likely to screen positive for depression, to report suicidalideation and NSSI, and to meet criteria for at least one mental healthproblem. There were no significant differences across academic disciplinesin help-seeking among doctoral students.

Discussion

This article complements a growing body of research examining variations inmental health and help-seeking across student characteristics. Where recentresearch has typically concentrated on differences across demographic char-acteristics, this study makes a unique contribution by focusing on variationsacross academic disciplines. There are several notable trends in terms ofprevalence of mental health problems, which likely reflect a combination ofpre-existing risks as well as effects of stressors within each field. First, acrossall degree levels, we consistently found an increased likelihood of mentalhealth problems among students in the humanities and art and designrelative to other students. Overall, 38.9% of students in the humanities and44.4% of art and design students met criteria for at least one mental healthproblem, which is significantly higher than the overall rate of 33.8%. Second,we find that students in nursing, business, and public health were less likelyto have mental health problems. Overall, 27.5% of nursing students, 26.9% ofbusiness students, and 24.5% of public health students met criteria for amental health problem.

There are several potential explanations for these findings. Art and designstudents, for one, face a unique set of stressors. In many other concentrations(e.g., engineering), completion of an undergraduate degree involves trainingto be competent in the field, but with no expectation of making an originalcontribution. Art students receive a certain level of technical training as well,but have constant pressure towards innovation and originality. Instructorcritiques may also be quite harsh and sometimes delivered in a public setting.

34 S. K. LIPSON ET AL.

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Table5.

MultivariableCo

rrelates

ofMentalH

ealth

Prob

lemsAm

ongDoctoralS

tudents,LogisticRegression

s.Dep

Anx

SINSSI

Any

Tx

OR

p95%

CIOR

p95%

CIOR

p95%

CIOR

p95%

CIOR

p95%

CIOR

p95%

CI

SOC

——

——

——

——

——

——

——

——

——

——

——

——

HUM

1.76

.01

1.13

2.76

1.14

.68

0.62

2.10

1.29

.40

0.71

2.33

1.36

.16

0.89

2.07

1.38

.05

1.00

1.91

0.99

.98

0.53

1.87

NAT

0.86

.43

0.59

1.25

0.86

.66

0.45

1.64

0.74

.42

0.35

1.54

1.08

.76

0.68

1.71

0.93

.63

0.70

1.24

0.57

.04

0.33

0.98

ART

2.40

.02

1.16

4.95

2.08

.19

0.69

6.30

1.46

.52

0.46

4.57

0.96

.93

0.38

2.42

1.40

.32

0.73

2.69

1.19

.74

0.43

3.31

ENG

1.04

.85

0.68

1.61

0.78

.58

0.33

1.86

0.76

.41

0.39

1.48

0.87

.58

0.54

1.41

0.97

.84

0.71

1.33

0.78

.44

0.41

1.47

BUS

0.38

.10

0.12

1.22

0.50

.30

0.14

1.83

0.47

.24

0.13

1.68

0.52

.32

0.15

1.89

0.54

.10

0.27

1.12

0.65

.50

0.19

2.25

LAW

0.85

.45

0.56

1.29

1.02

.95

0.52

2.00

0.62

.10

0.35

1.10

0.85

.48

0.54

1.34

0.81

.16

0.60

1.08

0.81

.47

0.45

1.44

SW5.30

.01

1.65

17.07

0.45

.49

0.05

4.42

0.55

.54

0.08

3.65

0.80

.78

0.17

3.79

3.12

.04

1.05

9.22

0.34

.25

0.05

2.14

PH1.19

.67

0.53

2.70

1.00

1.00

0.00

1.00

0.79

.68

0.25

2.49

0.96

.93

0.37

2.49

0.69

.29

0.35

1.36

0.34

.06

0.11

1.05

NUR

0.61

.34

0.22

1.68

1.00

1.00

0.00

1.00

0.45

.32

0.09

2.18

0.10

.03

0.01

0.79

0.40

.03

0.17

0.93

0.45

.26

0.11

1.79

MED

0.58

.01

0.38

0.89

0.62

.18

0.31

1.25

0.46

.01

0.26

0.84

0.51

.01

0.32

0.81

0.62

.002

0.46

0.84

0.61

.09

0.34

1.08

OTH

0.73

.27

0.42

1.28

0.84

.68

0.37

1.93

0.57

.16

0.26

1.24

0.56

.05

0.31

1.01

0.89

.55

0.59

1.32

0.63

.19

0.32

1.26

MULT

1.02

.93

0.62

1.70

1.54

.31

0.67

3.54

0.98

.95

0.54

1.77

0.97

.89

0.59

1.59

1.03

.88

0.73

1.44

0.70

.30

0.35

1.39

Constant

0.43

.06

0.18

1.02

0.10

.003

0.02

0.46

0.21

.004

0.07

0.60

0.35

.03

0.14

0.90

0.83

.55

0.45

1.53

0.36

.09

0.11

1.16

N5,664

3,568

5,652

5,596

5,576

1,428

Note.CI

–confidence

interval;O

R=od

dsratio

;Dep

=Depression;

Anxiety(Anx)exclud

es2013;S

I=suicidal

ideatio

n;NSSI=no

nsuicidalself-injury;A

ny=An

yMentalHealth

Prob

lem;TreatmentU

tilization(Tx)isam

ongstud

entswith

atleasto

neapparent

mentalhealth

(MH)p

roblem

;SOC=SocialSciences;H

UM=Hum

anities;N

AT=NaturalSciences;

ART=

Art&Design;

ENG

=Engineering;

BUS=

Business;LAW

=Law;SW

=Social

Work;

PH=

Public

Health

;NUR=

Nursing

;MED

=Medicine;

OTH

=Other;MULT

=Multid

isciplinary;UNDEC

=Und

ecided.Allmod

elscontrolforsurvey

year

andstud

ents’age,

gend

er,citizenship,race/ethn

icity,andparental

education;

referencecatego

ryis

Social

Sciences.

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Furthermore, some art students may be negatively affected by a highlycompetitive environment, with a culture of antagonistic ambition encouragedby faculty, who often run classes like employers and not as educators (Grant,2010). The combined forces of competition and long periods of solitudeduring project compilations result in many socially isolated art students(Grant, 2010). The broader literature around creativity and mental illnesssupports the finding that art and design students are at greater risk. In onestudy, for example, the prevalence of mental illness among first-degreerelatives of creative writers was found to be five times that of matchedcontrol subjects (Ludwig, 1992). Other research points to the cognitivedemands that artists use intuition, subjectivity, and emotion, which areassociated with higher levels of emotional dysregulation as compared toprofessions that select for logic, objectivity, and more formal means ofexpression—and so may promote emotional stability (Ludwig, 1998).

Our finding of lower rates of mental health problems among nursingstudents is consistent with the limited research in this area. In a previousstudy, nursing students reported lower rates of psychological distress andwere found to score lower on self-oriented perfectionism and impostersyndrome scales (Henning, Ey, & Shaw, 1998). We may speculate thatnursing students have lower rates of mental health problems because ofthese shared personality traits.

Results also indicate important variations in terms of service utilization.Overall, we find a significantly increased likelihood of help-seeking amongsocial work students and a significantly decreased likelihood among businessand engineering students. Slightly more than half of social work studentswith apparent mental health problems have sought help in the past yearrelative to about two fifths in the overall sample. Conversely, less than onequarter of engineering students and less than one third of business studentswith apparent mental health problems have sought help.

There are several potential mechanisms that might explain these variationsin mental health service utilization. Greater utilization by social work stu-dents may be related to more positive attitudes towards help-seeking, giventhe therapeutic orientation of their curriculum and awareness of the benefitsof mental health services. Yet, while social work students used services moreoften, students from other disciplines exposed to mental health orientedcurricula (e.g., nursing and medicine) did not. However, in contrast tonursing and medical students, social work students tend to have a moreintense focus on mental health (Barnes, Carpenter, & Dickinson, 2000;Benbassat, 2013; Lacasse & Gomory, 2003). Another factor that couldaccount for medical student treatment utilization is the stigma of mentalhealth services within the medical profession. Physicians’ attitudes tend todiscourage admission of health vulnerabilities, which likely creates reluctanceto seek mental health care (Center et al., 2003; Wallace & Lemaire, 2009). In

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previous studies, medical students have noted lack of confidentiality and fearof documentation on their academic record as major barriers to mentalhealth service utilization (Givens & Tjia, 2002). There is even evidence thatmedical students who have received psychological counseling are less likelyto secure residency positions (Wallace, 2010). Further, one study found thatphysicians view themselves as “invincible caregivers first and foremost whomust look after others before looking after themselves, who believe that theydo not need help from others” (Wallace & Lemaire, 2009, p. 545). Medicalstudents have been shown to be reluctant in seeking mental health treatmentfor fear of being seen as weak in a culture of medicine that teaches futurephysicians to place low priority on their own health (Wallace, 2010). All thismay explain the difference between social workers as above average help-seekers and other health-focused disciplines (e.g., medical students).

There are limited studies on help-seeking among business students. Onestudy found that rates of mental health service utilization were loweramong business students relative to medical students (Dahlin, Nilsson,Stotzer, & Runeson, 2011). There is also evidence that alcohol abuse ismore common among business students (Curran, Gawley, Casey, Gill, &Crumlish, 2009; Dahlin et al., 2011). There is limited research on mentalhealth and help-seeking among engineering students. One study of inter-national graduate students (Curran et al., 2009) found that science andengineering students were actually more likely to use services, though thefinding was not statistically significant. Another study found that stresslevels were higher and exercise rates lower among engineers (Hyun,Quinn, Madon, & Lustig, 2007). Noting the curricular demands of engi-neering, which tend to leave little room for electives, the authors empha-sized a need for mental and physical health education for engineers (Hyunet al., 2007).

Implications

There are several notable implications from the present study. While manycampus-based interventions capitalize on social and residential structures ofthe college environment (e.g., residence halls, sports teams, Greek life), fewhave targeted students in their academic departments, representing anuntapped possibility for engaging students in treatment and prevention.Counseling centers may choose to do targeted outreach to certain depart-ments during orientation or throughout the academic year. These effortsneed to be tailored to the unique needs and stressors of students within eachdepartment. With limited resources, campus mental health practitioners maychoose to focus on departments with particularly high rates of difficulties(e.g., art and design and humanities) and/or low rates of help-seeking (e.g.,business and engineering). Additionally, the findings are relevant to faculty

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and staff in academic departments in their daily work, advising, teaching, andinteracting with students.

The findings also suggest future directions for intervention and research.Recognizing variations in mental health and help-seeking across academicdisciplines, as noted in this study, may motivate institutions to understandacademic factors that affect students’ well-being and, in turn, lead toimprovements via targeted intervention, prevention, and outreach programs.Given that there are likely several mechanisms driving the relationshipsreported here (e.g., differential academic competition and expectationsaround help-seeking), future research should explore these mechanisms inorder to improve service outreach.

Limitations

This study has several limitations. First, across all years of data included here,the survey had an overall response rate of just over 25%. Sample probabilityweights adjust for potential differences between responders and nonrespon-ders along known characteristics, but these adjustments do not necessarilycorrect for response bias due to unobserved characteristics. In particular, oneconcern is whether students with mental health concerns may be significantlymore or less likely to respond to the survey. To address this concern, ourteam conducted a follow-up survey sent to roughly 500 randomly selectednonresponders from the main survey; 55% responded and we found, relativeto the main sample, significantly lower prevalence of positive screens fordepression and significantly less use of mental health services, suggesting thatwe may be overestimating the prevalence of mental health problems andconsequently overestimating rates of help-seeking (Eisenberg et al., 2007).

A related concern is that there may be different response rates acrossacademic disciplines. While nearly all schools provided basic information onthe full initial sample (e.g., gender, race, degree level), only some schoolsprovided administrative data on students’ academic disciplines. An analysisof one school that provided information about majors for the full list ofrecruited students showed general consistency in the proportion of studentsin each disciplinary category when we compared the full sample to thesample of respondents. A third concern is that in this cross-sectional analysiswe cannot infer causality about the relationship between academic disciplinesand mental health outcomes (i.e., we cannot claim that certain academicdisciplines cause increased prevalence of mental health problems ordecreased rates of help-seeking). Certain departments may attract studentswith different mental health predispositions, and/or impact, either positivelyor negatively, mental health and help-seeking throughout the course ofdegree completion. Fourth, while we measured mental health conditionswith validated screens and widely used survey items, these assessments do

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not represent clinical diagnoses. This limitation would not necessarily affectour estimation of differences across fields, however, since any inaccuracies inthe screening tools should operate similarly across disciplines.

Conclusion

Despite its limitations, this study sheds light on important, previously unex-plored variations in mental health and help-seeking across academic disci-plines. With these findings in mind, campuses may better support studentsby partnering with academic departments to optimize the reach and effec-tiveness of mental health services and resources.

References

Arria, A. M., Caldeira, K. M., Vincent, K. B., Winick, E. R., Baron, R. A., & O’Grady, K. E.(2013). Discontinuous college enrollment: Associations with substance use and mentalhealth. Psychiatric Services, 64(2), 165–172. doi:10.1176/appi.ps.201200106

Astin, H. S., & Sax, L. J. (1996). Developing scientific talent in undergraduate women. In C.-S.Davis et al. (Eds.), The equity equation: Fostering the advancement of women in the sciences,mathematics, and engineering (pp. 96–121). Jossey-Bass.

Aud, S., Hussar, W., Johnson, F., Kena, G., Roth, E., Manning, E., . . . Zhang, J. (2012). Thecondition of education 2012 (NCES 2012-045). Washington, DC: U.S. Department ofEducation, National Center for Education Statistics. Retrieved from http://nces.ed.gov/pubsearch

Barnes, D., Carpenter, J., & Dickinson, C. (2000). Interprofessional education for communitymental health: Attitudes to community care and professional stereotypes. Social WorkEducation, 19(6), 565–583. doi:10.1080/02615470020002308

Benbassat, J. (2013). Undesirable features of the medical learning environment: A narrativereview of the literature. Advances in Health Sciences Education, 18(3), 527–536. doi:10.1007/s10459-012-9389-5

Berkman, L. F., Glass, T., Brissette, I., & Seeman, T. E. (2000). From social integration tohealth: Durkheim in the new millennium. Social Science & Medicine, 51(6), 843–857.doi:10.1016/S0277-9536(00)00065-4

Blanco, C., Okuda, M., Wright, C., Hasin, D. S., Grant, B. F., Liu, S. M., & Olfson, M. (2008).Mental health of college students and their non–college-attending peers: Results from thenational epidemiologic study on alcohol and related conditions. Archives of GeneralPsychiatry, 65(12), 1429–1437. doi:10.1001/archpsyc.65.12.1429

Campbell, B. C., & Wang, S. S. (2012). Familial linkage between neuropsychiatric disordersand intellectual interests. Plos One, 7(1), e30405. doi:10.1371/journal.pone.0030405

Center, C., Davis, M., Detre, T., Ford, D. E., Hansbrough, W., Hendin, H., . . . Silverman, M. M.(2003).Confronting depression and suicide in physicians: A consensus statement. Journal ofAmerican Medical Association, 289(23), 3161–3166. doi:10.1001/jama.289.23.3161

Curran, T. A., Gawley, E., Casey, P., Gill, M., & Crumlish, N. (2009). Depression, suicidalityand alcohol abuse among medical and business students. Irish Medical Journal, 102(8),1–2. Retrieved from http://www.drugsandalcohol.ie/12383/1/IMJ_2009_Depression%2C_suicidality_and_alcohol_abuse.pdf

JOURNAL OF COLLEGE STUDENT PSYCHOTHERAPY 39

Dow

nloa

ded

by [

Uni

vers

ity o

f M

ichi

gan]

at 1

1:47

10

Janu

ary

2016

Dahlin, M., Nilsson, C., Stotzer, E., & Runeson, B. (2011). Mental distress, alcohol use andhelp-seeking among medical and business students: A cross-sectional comparative study.BMC Medical Education, 11(1), 92.

Davidson, M. M., Yakushka, O. F., & Sanford-Martens, T. C. (2004). Racial and ethnicminority clients’ utilization of a university counseling center: An archival study. Journalof Multicultural Counseling and Development, 32, 259.

Diez-Quevedo, C., Rangil, T., Sanchez-Planell, L., Kroenke, K., & Spitzer, R. L. (2001).Validation and utility of the patient health questionnaire in diagnosing mental disordersin 1003 general hospital Spanish inpatients. Psychosomatic Medicine, 63(4), 679–686.doi:10.1097/00006842-200107000-00021

Dyrbye, L. N., Thomas, M. R., & Shanafelt, T. D. (2006). Systematic review of depression,anxiety, and other indicators of psychological distress among US and Canadian medicalstudents. Academic Medicine, 81(4), 354–373. doi:10.1097/00001888-200604000-00009

Eisenberg, D., Golberstein, E., & Gollust, S. E. (2007). Help-seeking and access to mentalhealth care in a university student population. Medical Care, 45(7), 594–601. doi:10.1097/MLR.0b013e31803bb4c1

Eisenberg, D., Golberstein, E., & Hunt, J. B. (2009). Mental health and academic success incollege. The BE Journal of Economic Analysis & Policy, 9(1), 1–35.

Eisenberg, D., Hunt, J., & Speer, N. (2013). Mental health in American colleges and uni-versities: Variation across student subgroups and across campuses. The Journal of Nervousand Mental Disease, 201(1), 60–67. doi:10.1097/NMD.0b013e31827ab077

Eisenberg, D., Hunt, J., Speer, N., & Zivin, K. (2011). Mental health service utilization amongcollege students in the United States. The Journal of Nervous and Mental Disease, 199(5),301–308. doi:10.1097/NMD.0b013e3182175123

Eisenberg, D., Nicklett, E. J., Roeder, K., & Kirz, N. E. (2011). Eating disorder symptomsamong college students: Prevalence, persistence, correlates, and treatment-seeking. Journalof American College Health, 59(8), 700–707. doi:10.1080/07448481.2010.546461

Gallagher, R. (2006). National survey of counseling center directors. Alexandria, VA: NationalAssociation of Counseling Services.

Givens, J., & Tjia, J. (2002). Depressed medical students’ use of mental health services andbarriers to use. Academic Medicine, 77(9), 918–921. doi:10.1097/00001888-200209000-00024

Grant, D. (2010). Art students’ mental health: A complicated picture. The Chronicle of HigherEducation. Retrieved from http://www.chronicle.com/blogs/arts/art-students-mental-health-a-complicated-picture/27923

Healthy Minds Network. (2007–2013). The Healthy Minds study. Retrieved from http://healthymindsnetwork.org/hms

Hefner, J., & Eisenberg, D. (2009). Social support and mental health among college students.American Journal of Orthopsychiatry, 79(4), 491–499. doi:10.1037/a0016918

Henning, K., Ey, S., & Shaw, D. (1998). Perfectionism, the impostor phenomenon andpsychological adjustment in medical, dental, nursing and pharmacy students. MedicalEducation, 32(5), 456–464. doi:10.1046/j.1365-2923.1998.00234.x

Hyun, J., Quinn, B., Madon, T., & Lustig, S. (2007). Mental health need, awareness, and use ofcounseling services among international graduate students. Journal of American CollegeHealth, 56(2), 109–118. doi:10.3200/JACH.56.2.109-118

Kearney, L. K., Draper, M., & Barón, A. (2005). Counseling utilization by ethnic minoritycollege students. Cultural Diversity and Ethnic Minority Psychology, 11(3), 272–285.doi:10.1037/1099-9809.11.3.272

40 S. K. LIPSON ET AL.

Dow

nloa

ded

by [

Uni

vers

ity o

f M

ichi

gan]

at 1

1:47

10

Janu

ary

2016

Kessler, R. C., Amminger, G. P., Aguilar-Gaxiola, S., Alonso, J., Lee, S., & Ustun, T. B. (2007).Age of onset of mental disorders: A review of recent literature. Current Opinion inPsychiatry, 20(4), 359. doi:10.1097/YCO.0b013e32816ebc8c

Lacasse, J., & Gomory, T. (2003). Is graduate social work education promoting a criticalapproach to mental health practice? Journal of Social Work Education, 39(3), 383–408.

Löwe, B., Gräfe, K., Zipfel, S., Witte, S., Loerch, B., & Herzog, W. (2004). Diagnosing ICD-10depressive episodes: Superior criterion validity of the Patient Health Questionnaire.Psychotherapy and Psychosomatics, 73(6), 386–390.

Ludwig, A. (1992). Creative achievement and psychopathology: Comparison among profes-sions. American Journal of Psychotherapy, 26(3), 330–356.

Ludwig, A. M. (1998). Method and madness in the arts and sciences. Creativity ResearchJournal, 11(2), 93–101. doi:10.1207/s15326934crj1102_1

Nam, S. K., Chu, H. J., Lee, M. K., Lee, J. H., Kim, N., & Lee, S. M. (2010). A meta-analysis ofgender differences in attitudes toward seeking professional psychological help. Journal ofAmerican College Health, 59(2), 110–116. doi:10.1080/07448481.2010.483714

Norman, R. D., & Redlo, M. (1952). MMPI personality patterns for various college majorgroups. Journal of Applied Psychology, 36(6), 404–409. doi:10.1037/h0053909

Reifman, A., McLntosh, D. N., & Ellsworth, P. C. (2001). Depression and affect among lawstudents during law school: A longitudinal study. Journal of Emotional Abuse, 2(1), 93–106.doi:10.1300/J135v02n01_07

Schwartz, V., & Kay, J. (2009). The crisis in college and university mental health. PsychiatricTimes, 26(10), 32–32.

Shapiro, C. A., & Sax, L. J. (2011). Major selection and persistence for women in STEM. NewDirections for Institutional Research, 152, 5–18. doi:10.1002/ir.404

Spitzer, R. L., Kroenke, K., Williams, J. B., & Patient Health Questionnaire Primary CareStudy Group. (1999). Validation and utility of a self-report version of PRIME-MD: ThePHQ primary care study. JAMA : The Journal of the American Medical Association, 282(18), 1737–1744. doi:10.1001/jama.282.18.1737

Spitzer, R. L., Kroenke, K., Williams, J. B., & Löwe, B. (2006). A brief measure for assessinggeneralized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10),1092–1097. doi:10.1001/archinte.166.10.1092

Wallace, J., & Lemaire, J. (2009). Physician well being and quality of patient care: Anexploratory study of the missing link. Psychology, Health, & Medicine, 14(5), 545–552.doi:10.1080/13548500903012871

Wallace, J. E. (2010). Mental health and stigma in the medical profession. Health, 16(1), 3–18.Wang, P. S., Berglund, P., Olfson, M., Pincus, H. A., Wells, K. B., & Kessler, R. C. (2005).

Failure and delay in initial treatment contact after first onset of mental disorders in thenational comorbidity survey replication. Archives of General Psychiatry, 62(6), 603–613.doi:10.1001/archpsyc.62.6.603

Wang, P. S., Simon, G. E., Avorn, J., Azocar, F., Ludman, E. J., McCulloch, J., . . . Kessler, R.C. (2007). Telephone screening, outreach, and care management for depressed workersand impact on clinical and work productivity outcomes: A randomized controlled trial.JAMA: The Journal of the American Medical Association, 298(12), 1401–1411. doi:10.1001/jama.298.12.1401

Whitlock, J. L., Wyman, P. A., & Barreira, P. (2010). Connectedness and suicide prevention incollege settings: Directions and implications for practice (Unpublished manuscript).Cornell University.

Yakushko, O., Davidson, M. M., & Sanford-Martens, T. C. (2008). Seeking help in a foreignland: International students’ use patterns for a US university counseling center. Journal ofCollege Counseling, 11(1), 6–18. doi:10.1002/(ISSN)2161-1882

JOURNAL OF COLLEGE STUDENT PSYCHOTHERAPY 41

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