A systematic review of studies of depression prevalence in university students.pdf

Review
A systematic review of studies of depression prevalence in university students
Ahmed K. Ibrahim a,b,*, Shona J. Kellyc
, Clive E. Adams d
, Cris Glazebrook d
a
Community Health School, Faculty of Medicine, Assiut University, Asyut, Egypt
b
Division of Epidemiology, Community Health Sciences School, D Floor, West Block, Queens Medical Centre, University of Nottingham, Nottingham, UK
c
Social Epidemiology and Evaluation Research Unit, Division of Health Sciences, University of South Australia, Adelaide, Australia
d
Institute of Mental Health, University of Nottingham Innovation Park, Triumph Road, Nottingham NG7 2TU, UK
a r t i c l e i n f o
Article history:
Received 3 June 2012
Received in revised form
28 November 2012
Accepted 28 November 2012
Keywords:
Systematic review
Depression
Prevalence
Students
University
a b s t r a c t
Background: Depression is a common health problem, ranking third after cardiac and respiratory diseases
as a major cause of disability. There is evidence to suggest that university students are at higher risk of
depression, despite being a socially advantaged population, but the reported rates have shown wide
variability across settings.
Purpose: To explore the prevalence of depression in university students.
Method: PubMed, PsycINFO, BioMed Central and Medline were searched to identify studies published
between 1990 and 2010 reporting on depression prevalence among university students. Searches used
a combination of the terms depression, depressive symptoms, depressive disorders, prevalence,
university students, college students, undergraduate students, adolescents and/or young adults. Studies
were evaluated with a quality rating.
Results: Twenty-four articles were identified that met the inclusion and exclusion criteria. Reported
prevalence rates ranged from 10% to 85% with a weighted mean prevalence of 30.6%.
Conclusions: The results suggest that university students experience rates of depression that are substan-
tially higher than those found in the general population. Study quality has not improved since 1990.
Ó 2012 Elsevier Ltd. All rights reserved.
1. Background
Depression is one of the most common health problems for
university students (Lyubomirsky et al., 2003; Vredenburg et al.,
1988). Depression is considered as a multi-problematic disorder
that leads to impairment in inter-personal, social, and occupational
functioning (Sadock and Kaplan, 2007). The basic characteristic of
depression is a loss of positive affect which manifests itself in a range
of symptoms, including sleep disturbance, lack of self-care, poor
concentration, anxiety and lack of interest in everyday
experiences (NICE, 2009). Level of impairment can be classified clin-
ically by standardized diagnostic interview but in prevalence studies
depression is typically identified through a validated, self-report
screening instrument. The prevalence of depression seems to be
affected by many factors including; population studied,
socio-demographic factors (e.g. sex, age) (Steptoe et al., 2007; Kaplan
et al., 2008), place of study (Weissman et al.,1996; Steptoe et al., 2007)
diagnostic tool and sampling used (Weissman et al., 1996; Marsella,
1978). Although there has been an increasing concern about
depression in specific groups such as adolescents or the elderly
(Winter et al., 2011; Springer et al., 2011; Lim et al., 2011; Gladstone
et al., 2011; McKenzie et al., 2010), the problem of university
students’ depression has received relatively little attention, despite
evidence of a steady rise in the number of depressed university
students (Ceyhan et al., 2009). Studies have reported wide variations
in the proportion of students identified as depressed, from relatively
low rates around 10% (Goebertet al., 2009; Vazquez and Blanco, 2006;
Vazquez and Blanco, 2008) to high rates of between 40% and 84%
(Bayati et al., 2009; Garlow et al., 2008; Khan et al., 2006). This wide
variation appears to be influenced by many factors including methods
of assessment (Weissman et al., 1996; Marsella, 1978), geographical
location (Steptoe et al., 2007; Weissman et al.,1996) and demographic
factors such as SES (Kaplan et al., 2008; Steptoe et al., 2007).
The cost of affective disorders can be particularly high in young
people because they represent the future of any community, its
hope and potential leaders (El-Gendawy et al., 2005). Depression
in this early life stage can lead to an accumulation of negative
consequences through adult life through its impact on career pros-
pects and social relationships (Denise et al.,1996; Aalto-Setälä et al.,
2001). Depression has been linked to poorer academic achievements
* Corresponding author. Department of Public Health and Community Medicine,
Medical Faculty, Assiut University, Asyut, Egypt. Tel.: þ20 1127533610; fax: þ20
8823254633.
E-mail addresses: ahmed.khair@yahoo.com, ahmed.ibrahim7@med.au.edu.eg
(A.K. Ibrahim).
Contents lists available at SciVerse ScienceDirect
Journal of Psychiatric Research
journal homepage: www.elsevier.com/locate/psychires
0022-3956/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.jpsychires.2012.11.015
Journal of Psychiatric Research 47 (2013) 391e400

(Hysenbegasi et al., 2005), relationship instability (Whitton and
Whisman, 2010), suicidal thoughts and attempts (Jeon, 2011) and
poorer work performance (Harvey et al., 2011). Although arguably
university students are more likely to be advantaged in socio-
economic terms which is considered protective against depression
(Lowe et al., 2009), there are many factors that might increase
students’ vulnerability to depression. These factors include changes
in life style resulting in sleep and eating disturbances, financial
stressors, family relationship alterations, academic worries and
preoccupation with post-graduation life (NIMH, 2003).
There is a strong perception, both in the US and in the UK, that
demands for psychological services by university students have grown
and that university counseling services are also dealing with more
severe mental illness (Hunt and Eisenberg, 2010). Despite this, a recent
literature review of studies on depression and treatment outcomes
among US College students carried out from 1990 to 2009 identified
only four studies and concluded that research on depression and
treatment outcomes among US college students are present but scarce
and inconclusive. They also found wide variability in inclusion and
exclusion criteria and tools for diagnosis of depression and determi-
nation of its severity (Miller and Chung, 2009). Another systematic
review of research published between January 1980 and May 2005
looking at the prevalence of depression, anxiety, and other indicators
of psychological distress among US and Canadian medical students
found higher rates of depression than is seen in the general pop-
ulation. The review also pointed to a lack of research into the causes of
students’ depression and its impact on academic performance,
dropout rates and professional development (Dyrbye et al., 2006).
To our knowledge, no systematic review of studies examining
the prevalence of depression in undergraduate university students
has been published. In the light of this research gap, this review has
two main objectives: (I) to identify studies reporting on rates of
depression among university students (II) to examine the hypoth-
esis that there is an increase in the rates of depression among
undergraduate university students.
2. Method
A systematic literature review of PubMed, PsycINFO, BioMed
Central and Medline databases was carried out to identify peer-
reviewed studies, published between January 1990 and October
2010, reporting on depression among undergraduate university
students. Searches used the keywords depression, depressive
symptoms, depressive disorders, prevalence, university students,
college students, undergraduate students, adolescents and/or
young adults were used in the searches. Additional articles were
identified through the reference lists of the retrieved articles and
previous review studies.
Inclusion criteria were that: 1) the study sample included
exclusively undergraduate students in higher education; 2) the
study included an aim to establish prevalence of depression and;
3) the study reported prevalence rates. The exclusion criteria
were 1) the study did not report response rate; 2) clinical trials
studies and; 3) failure to report a separate prevalence rate for
depression. Demographic data, sample size, diagnostic instrument
used and prevalence data on students’ depression were abstracted.
Searches were limited to articles published in the last two
decades yielding a total of 2303 citations. After examining the titles,
abstracts (if abstract was unavailable, the article was nevertheless
counted) and the reference lists for related articles, 94 articles were
retrieved, including five Non-English articles (French 1, Japanese 1,
Mexican 1, Korean 2) and 89 English language studies were
examined thoroughly. Non-English articles were translated with
the help of PhD students from Japan, Spain, and Korea, studying at
the University of Nottingham, who were expert in both languages;
English and the other language.
After careful reading of these articles, an additional 70 articles
were excluded as a result of the following justifications: the study
population was non-university adolescents or young adults (13),
studies evaluating treatment of depression and/or clinical trials and
either not reporting prevalence rate and/or response rate (14), studies
not reporting response rate and/or prevalence (23), no separate
prevalence rate for depression (8), studies did not aim to establish
prevalence (12). The remaining 24 articles were included and were
evaluated for quality (Fig. 1). Prevalence rates across studies were
calculated as weighted means using RevMan software which takes
into account variation in cut-off used (RevMan, 2011). The prevalence
rate per study was multiplied by the corresponding sample size and
divided by the total sample size to give a weighted prevalence of
depression and 95% CIs were calculated (IBM-SPSS, 2009).
After reviewing the titles
2303 were retrieved
167 were available for examination
70 studies were excluded:
13 studies on Non -university adolescents & young adults
14 studies on treatment of depression and/or clinical trials
11 studies not reporting response rate
12 studies not reporting prevalence
8 studies examined anxiety and depression
12 studies not aimed to establish prevalence
After careful reading of
the online abstracts
94 studies were eligible for examination
24 were eligible for inclusion
Fig. 1. The study flow chart.
A.K. Ibrahim et al. / Journal of Psychiatric Research 47 (2013) 391e400
392

3. Quality evaluation
The 24 articles were read extensively and, as there is no agreed
quality assessment instrument for epidemiological prevalence
studies, we adapted one developed by Parker and colleagues
(Parker et al., 2008). Articles scored one point for each of the
following quality markers: (1) the target population was defined
clearly, (2) complete, random or consecutive recruitment, (3) the
targeted sample is representative or the report presents evidence
that the results can be generalized to the general undergraduate
population (4) the response rate was equal or greater than 70%, (5)
the scale used is a validated measure of depression with valid cut-
offs for classification of depression, (6) the sample size is adequate
with a minimum sample size of 300 (Loney et al., 1998), (7) the
confidence intervals (CI) or standard error (SE) are reported. The
last two quality criteria were added because the larger the sample,
the more precise the results are (Strachan, 1997). Additionally, CI
and SE are important for the reliability assessment of the outcome
of prevalence studies. In the study results either CI or SE should be
computed and always reported (Loney et al., 1998). A full descrip-
tion of the quality assessments for the examined studies is included
in Table 1. In Fig. 2 the quality scores of the included studies from
1990 were plotted against the year of study. The regression line
indicates average quality scores over time.
4. Results
Out of a total of 2303 publications, only 24 studies satisfied all
the inclusion and exclusion criteria Fig. 1. The majority of the
included studies (n ¼ 15) had been carried out in Western coun-
tries. Nine had been carried out in the USA (Eisenberg et al., 2007;
Garlow et al., 2008; Goebert et al., 2009; Hendryx et al., 1991;
Roberts et al., 2010; Rosal et al., 1997; Schwenk et al., 2010;
Thompson et al., 2010; Tjia et al., 2005), one in Canada (Dion and
Giordano, 1990), one in Sweden (Dahlin and Runeson, 2005), one
in Ireland (Curran et al., 2009), two in Turkey (Arslan et al., 2009;
Kaya et al., 2007) and one in Macedonia (Mancevska et al., 2008). In
addition, one study used data from four EU countries (Mikolajczyk
et al., 2008). Five studies sampled East Asian students (two from
Hong Kong (Song et al., 2008; Wang et al., 2010), one from China
(Zong et al., 2010), and two from South Korea (Choi, 2003; Roh et al.,
2010)). Only two studies were carried out in Arabic countries (Egypt
and Lebanon) (El-Gendawy et al., 2005; Mehanna and Richa, 2006).
The remaining study was international in scope and deliberately
sampled university students from high, middle and low-income
countries (Steptoe et al., 2007).
Medical students were targeted in 12 studies (Arslan et al., 2009;
Dahlin and Runeson, 2005; Dion and Giordano, 1990; Goebert et al.,
2009; Hendryx et al., 1991; Kaya et al., 2007; Mancevska et al.,
2008; Roh et al., 2010; Rosal et al., 1997; Schwenk et al., 2010;
Thompson et al., 2010; Tjia et al., 2005), while eleven studies
collected data from a sample of different faculties (Choi, 2003;
Curran et al., 2009; Eisenberg et al., 2007; El-Gendawy et al., 2005;
Garlow et al., 2008; Mehanna and Richa, 2006; Mikolajczyk et al.,
2008; Roberts et al., 2010; Song et al., 2008; Wong et al., 2006;
Zong et al., 2010), and only one study excluded medical students
(Steptoe et al., 2007). The majority of studies (n ¼ 18) used
a convenience sample (Choi, 2003; Curran et al., 2009; Dahlin and
Runeson, 2005; Dion and Giordano, 1990; Garlow et al., 2008;
Goebert et al., 2009; Hendryx et al., 1991; Kaya et al., 2007;
Table 1
Quality assessments of the studies.
SN Source Quality score Sample definition Recruitment Representative sample Response rate Scale Sample size CI or SE
1 Dion et al. 4 1 0 0 1 1 1 0
2 Hendryx et al. 3 1 0 0 1 1 0 0
3 Rosal et al. 3 0 0 0 0 1 1 1
4 Choi, M. 3 0 0 1 0 1 0 1
5 El-Gendawy et al. 6 1 1 1 1 1 1 0
6 Tjia et al. 3 1 0 0 0 1 1 0
7 Dahlin et al. 4 1 0 0 1 1 1 0
8 Mehanna et al. 5 1 1 0 1 1 1 0
9 Wong et al. 3 1 0 0 0 1 1 0
10 Kaya et al. 4 1 0 0 1 1 1 0
11 Steptoe et al. 6 1 0 1 1 1 1 1
12 Eisenberg et al. 6 1 1 1 0 1 1 1
13 Song et al. 4 1 0 0 0 1 1 1
14 Mikolajczyk et al. 6 1 1 1 0 1 1 1
15 Garlow et al. 4 1 0 0 0 1 1 1
16 Mancevska et al. 4 1 0 0 1 1 1 0
17 Goebert et al. 4 0 0 0 1 1 1 1
18 Curran et al. 2 0 0 0 0 1 1 0
19 Arslan et al. 7 1 1 1 1 1 1 1
20 Roh et al. 4 1 0 0 0 1 1 1
21 Thompsom et al. 2 0 0 0 1 1 0 0
22 Roberts et al. 5 1 1 1 0 1 1 0
23 Zong et al. 2 1 0 0 0 1 0 0
24 Schwenk et al. 3 0 0 0 0 1 1 1
0
1
2
3
4
5
6
7
8
1985 1990 1995 2000 2005 2010 2015
Fig. 2. Change of the studies quality scores over time.
A.K. Ibrahim et al. / Journal of Psychiatric Research 47 (2013) 391e400 393

Mancevska et al., 2008; Roh et al., 2010; Rosal et al., 1997; Schwenk
et al., 2010; Song et al., 2008; Steptoe et al., 2007; Thompson et al.,
2010; Tjia et al., 2005; Wong et al., 2006; Zong et al., 2010), whereas
random sampling was the strategy in six studies (Arslan et al., 2009;
Eisenberg et al., 2007; El-Gendawy et al., 2005; Mehanna and Richa,
2006; Mikolajczyk et al., 2008; Roberts et al., 2010). Moreover, all
studies adopted a cross-sectional design except for one longitudinal
design (Rosal et al.,1997). A range of measures were used to identify
depression in the articles included in this review. Twenty three
studies used a cut-off score on a depression rating scale to classify
depression status and only one study using a (semi) structured
interview (the Mini International Neuropsychiatric Interview
(MINI)) to establish DSM-IV criteria (Roh et al., 2010).
Quality was evaluated for all the 24 studies according to the
criteria demonstrated in Table 1. According to these criteria the
maximum possible score for quality is 7. Actual scores ranged from
2 to 7, with a mean of 4.04 (SD: 1.4). The number of studies
assessing the prevalence of depression in undergraduate students
increased over time but no substantial increase in the quality of
studies over time was observed, as shown in Fig. 2. The overall
sample size in the current review was 48,650, with a minimum of
102 and a maximum of 17,348 participants. The mean age ranged
from 15 to 26 years. Gender of the participants was reported in all
studies except two (Curran et al., 2009; Thompson et al., 2010).
Percentages of males in the 22 studies reporting on sex ranged from
28% to 64%. The cut-off was defined from the way depression was
defined in each study (Table 2).
The prevalence of depression is shown in Table 2. Overall,
depression was present in nearly one-third of the total students
studied with a weighted mean prevalence of 30.6% (95% CI,
30.2e31.1). Prevalence rates ranged between 10% (95% CI,
7.7e14.3) and 84.5% (95% CI, 80.3e86.7). Reported rates of depres-
sion in undergraduate students fluctuated over the publication time
period with no discernible trend (r ¼ 0.03, p > 0.05) (Figs. 3 and 4).
Eight different scales were used in the 24 articles included in
the review. The Beck Depression Inventory (BDI) was the most
common tool used (n ¼ 12) (Arslan et al., 2009; Curran et al., 2009;
Dion and Giordano, 1990; Hendryx et al., 1991; Kaya et al., 2007;
Mancevska et al., 2008; Mehanna and Richa, 2006; Mikolajczyk
et al., 2008; Roberts et al., 2010; Steptoe et al., 2007; Tjia et al.,
2005; Zong et al., 2010) with a weighted depression prevalence
mean of 24% (95% CI, 23.1e24.9), followed by the Center for
Epidemiological Studies Depression Scale (CES-D) in four studies
(Goebert et al., 2009; Rosal et al., 1997; Song et al., 2008;
Thompson et al., 2010) showed a weighted mean of 36.8 (95% CI,
35.2e38.4) and 47.7% (95% CI, 46.2e49.2) was the weighted mean
in three articles using PHQ-9 (Eisenberg et al., 2007; Garlow et al.,
2008; Schwenk et al., 2010).
Regarding the nature of the studied population, the prevalence
of depression found in studies carried out in medical student
samples (Arslan et al., 2009; Dahlin and Runeson, 2005; Dion and
Giordano, 1990; Goebert et al., 2009; Hendryx et al., 1991; Kaya
et al., 2007; Mancevska et al., 2008; Roh et al., 2010; Rosal et al.,
1997; Schwenk et al., 2010; Thompson et al., 2010; Tjia et al.,
2005) ranged from 10.3% to 59%, with a weighted mean of 25.6%
(95% CI, 23.2e26.6). However, research on prevalence of depression
among a greater range of university students (Choi, 2003; Curran
et al., 2009; Eisenberg et al., 2007; El-Gendawy et al., 2005;
Garlow et al., 2008; Mehanna and Richa, 2006; Mikolajczyk et al.,
2008; Roberts et al., 2010; Song et al., 2008; Wong et al., 2006;
Zong et al., 2010) shows wider variability (range, 14e85%), with
a higher weighted mean of 35.6% (95% CI, 34.9e37.8). For the
sampling methodology; the range of prevalence rates reported for
studies using random sampling technique (Arslan et al., 2009;
Eisenberg et al., 2007; El-Gendawy et al., 2005; Mehanna and Richa,
2006; Mikolajczyk et al., 2008; Roberts et al., 2010) was 14e71%
with a weighted mean of 35.3% (95% CI, 34.3e36.6). This was
higher than the mean rate observed in studies using convenience
sampling (Choi, 2003; Curran et al., 2009; Dahlin and Runeson,
2005; Dion and Giordano, 1990; Garlow et al., 2008; Goebert
et al., 2009; Hendryx et al., 1991; Kaya et al., 2007; Mancevska
et al., 2008; Roh et al., 2010; Rosal et al., 1997; Schwenk et al.,
2010; Song et al., 2008; Steptoe et al., 2007; Thompson et al.,
2010; Tjia et al., 2005; Wong et al., 2006; Zong et al., 2010),
where the prevalence ranged between 10.3% and 84.5% with
a weighted mean at 29% (95% CI, 28.3e29.7). Comparison of studies
with small sample sizes (less than 300) with those with larger
sample sizes found no obvious effect. Additionally, there was
a modest but significant inverse relationship between the depres-
sion prevalence rate and the response rate of the study (r ¼ 0.3,
p < 0.05) with poorer response rates associated with higher prev-
alence rates.
Sixteen articles reported gender difference, the majority of them
(n ¼ 9) (Dahlin and Runeson, 2005; Dion and Giordano, 1990;
Goebert et al., 2009; Roberts et al., 2010; Roh et al., 2010; Rosal
et al., 1997; Schwenk et al., 2010; Song et al., 2008; Steptoe et al.,
2007) found higher prevalence among female compared to male
students, six articles could not detect any statistically significant
gender differences (Arslan et al., 2009; Eisenberg et al., 2007;
El-Gendawy et al., 2005; Kaya et al., 2007; Tjia et al., 2005; Zong
et al., 2010) and one found that males had a higher rate of
depression (Wong et al., 2006). For the 16 studies reporting on
gender female participants reported higher rates of depression
with a weighted mean average of 29.6% (95% CI, 29.2e30.1)
compared to 24.9% (95% CI, 24.4e25.4) in males.
The influence of student age on depression prevalence was
discussed in seven studies. Three found higher prevalence among
younger students (Arslan et al., 2009; Eisenberg et al., 2007; Roh
et al., 2010), two articles stated that older students have higher
rates (El-Gendawy et al., 2005; Schwenk et al., 2010), and no
difference by age was found in two articles (Kaya et al., 2007; Tjia
et al., 2005). As regards the year of study, higher prevalence rates
were observed in earlier years of study (which is consistent with
higher rates among younger students) in six articles (Arslan et al.,
2009; El-Gendawy et al., 2005; Goebert et al., 2009; Mancevska
et al., 2008; Mehanna and Richa, 2006; Roh et al., 2010), while
equal rates over the university study years were observed in two
studies (Roberts et al., 2010; Tjia et al., 2005). Socio-economic
determinants of prevalence were recorded in seven publications
which, concluded that the greater the family income the lower the
prevalence of depression (Eisenberg et al., 2007; El-Gendawy et al.,
2005; Kaya et al., 2007; Mancevska et al., 2008; Mikolajczyk et al.,
2008; Roh et al., 2010; Steptoe et al., 2007), however two of these
seven studies reported higher prevalence rates among students
whose parents had higher education (Kaya et al., 2007; Steptoe
et al., 2007).
5. Discussion
The current review included studies published between January
1990 and October 2010 and reporting on depression among
undergraduate university students including medical students.
According to this current review the average depression prevalence
is 30.6%, a higher rate than the 9% found in the general population
rates of the US (range 6e12%) (Gonzalez et al., 2010). Moreover,
a community-based cross-national survey of depression prevalence
carried out in 10 countries in North America, Latin America, Europe,
and Asia and using the Composite International Diagnostic (CIDI),
reported a mean prevalence of 9.8%, again much lower than the
weighted mean in this systematic review of studies confined to
394

student populations (Andrade et al., 2003). Another community-
based study carried out in Australia to track the changes in
depression prevalence over 10 years period found that the preva-
lence was 10.3% in 2008 (Goldney et al., 2010). Previous studies on
young adult populations also found a lower prevalence compared
with the current results (10.8e22%) (Denise et al., 1996; Aalto-
Setälä et al., 2001). This might be due to the fact that students
experienced more stresses concerning their futures and employ-
ment or that they were less satisfied with their studies. It might also
indicate that being a student is one of the factors that predispose to
depression (separation from home and lack of family support)
(NIMH, 2009).
However, a large cross-sectional study of a representative
sample carried out in the USA as part of the National Epidemiologic
Survey on Alcohol and Related Conditions (NESARC) could not
detect any significant difference in the prevalence of depression
between college students (7.85%, 95% CI 6.33e9.82) and their
matched non-college attendants (7.79, 95% CI 6.37e9.60) using the
DSM-IV diagnostic criteria (Blanco et al., 2008).
It has been suggested that rates of depression in undergraduate
student have increased over time (Ceyhan et al., 2009; Denise et al.,
1996), but the current review could not detect this trend. This could
be explained by differences in the study methods, tools used, or the
cultural differences of the studied population. Still a growing
Table 2
Demographics and methodologies employed in 22 studies examining depression among university students from 1990 to 2010.
SN Source Year Country Period of Study Samplea
Scaleb
Cut-off Quality score
1 Dion et al. 1990 Canada 1988 1a 21-BDI Normal 5
2 Hendryx et al. 1991 USA NR 1a 21-BDI-I Normal 4
3 Rosal et al. 1997 USA 1987e1989 1a 20-CES-D Normal 4
4 Choi, M. 2003 S. Korea 2002 2a 20-ZSRDS Normal 3
5 El-Gendawy et al. 2005 Egypt 2004 2b 52-ZDS Normal 7
6 Tjia et al. 2005 USA 2001e2002 1a 13-BDI-II 7 mild 4
7 Dahlin et al. 2005 Sweden 2001e2002 1a 12-MDI Normal 5
8 Mehanna et al. 2006 Lebanon 2003e2004 2b 13-BDI-II Normal 5
9 Wong et al. 2006 Hong Kong 2003 2a 42-DASS Normal 5
10 Kaya et al. 2007 Turkey NR 1a 21-BDI-II 17 5
11 Steptoe et al. 2007 23 EU 1999e2001 3a 13-BDI-II 8 8
12 Eisenberg et al. 2007 USA 2005 2b PHQ-9 Normal 8
13 Song et al. 2008 Hong Kong 2006 2b 20-CES-D Normal 6
14 Mikolajczyk et al. 2008 4 EU 2005 2b 20-M-BDI Normal 8
15 Garlow et al. 2008 USA 2002e2005 2b PHQ-9 Normal 5
16 Mancevska et al. 2008 Macedonia 2007e2008 1a 21-BDI-II 17 5
17 Goebert et al. 2009 USA 2003e2004 1a 20-CES-D 16 Mild 6
18 Curran et al. 2009 Ireland NR 2a 21-BDI-I Normal 2
19 Arslan et al. 2009 Turkey 2007e2008 1b 21-BDI-I 19 8
20 Roh et al. 2010 S. Korea 2006e2007 1a 9-MINI-RR Normal 6
21 Thompsom et al. 2010 USA 2002e2003 1a 20-CES-D Normal 2
22 Roberts et al. 2010 USA NR 2b 21-BDI-II 20 5
23 Zong et al. 2010 China NR 2a 21-BDI-II 14 3
24 Schwenk et al. 2010 USA 2009 1a PHQ-9 Normal 4
SN Sample size Response rate Sex male% Mean age Prevalence Covariates measuredc
1 432 82% 33% 20.3 y 34% Sex-women[, ethnicity[
2 110 74.8% 64% 24 y 19% Alexithymia[
3 300 48e88% 53% NR 18e39% Sex-women[, perceived stress[
4 298 45.1% 56% NR 26.8% Coping flexibilityY, number of stressful life events[, perceived controlY,
psychological sym. somatic symptoms
5 1000 82.4% 52% 19.3 y 71% Sex¼, age[, family structure[, SES[, Residence-rural[
6 564 57.1% 54.4% 25 y 15.2% Sex¼, age¼, year of study¼
7 342 90.4% 40.9% 26.1 y 12.9% Sex-women[, stress-A
8 677 74.9% 62.2% 21.7 y 52.7% Study subject¼, study yearY
9 7915 27.5% 37% 20 y 35.1% Sex-males[, psychiatric problems history[
10 754 80.5% 42.6% 21.9 y 26.9% Sex¼, age¼, family structure[, father educ.¼, mother educ.[, family incomeY,
History of general health or psychiatric problems[
11 17,348 90% 43% 23.5 y 21% Sex-women[, parent educ.[, family wealthY, sense of controlY
12 2843 56.6% 50% 20 y 13.8% Sex¼, ageY, financial struggle[, race; white[, family setting[
13 1677 55.7% 50.3% 18.5 y HK ¼ 43.9%
B ¼ 24.6%
Sex; HK¼, B-women[, neuroticism level[, self-esteemY, perfectionism[
14 2146 60e95% 36.8% Y23 y 29.5% Sex-A, income-A, country, depression; Poland Bulgaria Germany Denmark
15 729 8.1% 28.3% 14.7 y 84.5% Suicidal ideation-A, stress-A, anxiety-A
16 354 75e92% 33.9% 19.3 y 10.4% Study yearY, family incomeY, stress-A substance use-A
17 1343 88% 48% NR 25% Sex-women[, ethnicity¼, study yearY, psychiatric problems history[, suicidal ideation[
18 338 62.7% NR NR 13.9% Faculty-medicals[, social supportY, suicidal ideation[, stress[, alcohol abuse¼
19 822 80.8% 45.9% 20.8 y 21.8% Sex¼, ageY, study yearY, BMI¼
20 7357 52.2% 36% 21 y 10.3% Sex-women[, ageY, living alone[, financial difficulty[, academic performanceY
21 102 85% NR NR 59.1% Before; 59% depression, 30% suicidal ideation.
After; 24% depression and 3% suicidal ideation
22 428 18% 35% 19 y 22% Sex-women[, year of study¼, aggression (scale)[, cigarette smoking[, alcohol abuse¼
23 266 62% 55% 18.5 y 21% Sex¼, coping flexibilityY, number of stressful life events[, perceived controlY
24 505 65.7% 41.6% NR 44% Sex-women[, age[, suicidal ideation[ quitting school ideas[, depression history[
NR ¼ not reported, þCI ¼ 95% confidence interval, SE ¼ standard error.
a
1 ¼ Medical sample, 2 ¼ university sample, 3 ¼ university sample except medicals. a ¼ Convenience sample, b ¼ random.
b
See the study coding in Appendix 1.
c
[ e Increase, Y e decrease, ¼ e equal, A ¼ adjusted (details in Appendix 1).

concern has been expressed about university students’ mental
health (Ceyhan et al., 2009), this was evident in our findings as the
quantity of publications show an increase over time. However, the
quality of study was more or less stable across time with a mean
quality score of 4/7.
The BDI was most frequently reported outcome measure and
although rates based on BDI were lower than those based on the
CES-D or the PHQ, the weighted depression rate in the current
review for studies used the BDI was high (24%) compared to studies
carried out in community-based samples (ranged between 5 and
15%) (Yeung et al., 2002; Kuan-Pin et al., 2007; Katon and
Schulberg, 1992; Poole et al., 2009). In addition, the European
Outcome of Depression International Network (ODIN) used the BDI
to explore the prevalence of depression in representative samples
of the general population (n ¼ 8764) in five European countries
(UK, Spain, Netherlands, Norway, and Greece). The overall preva-
lence of depression was estimated at 8.6% (95% CI 7.05e10.37), with
10.05% (95% CI 7.80e12.85) of females affected and 6.61% of males
(95% CI 4.92e8.83) (Ayuso-Mateos et al., 2001), markedly lower
than weighted mean prevalence rates reported for students in the
present review. Similarly community studies adopting the PHQ-9 to
screen for depression also found lower rates (4.2e9.2%) (Martin
et al., 2006; Yu et al., 2011) in comparison to our results where
the weighted prevalence mean was 47.7%. Furthermore, a compar-
ison of two studies of the prevalence of depression in Egyptian
samples using the Zagazig Depression Scale (ZDS) (Fawzy et al.,
1982; Ibrahim et al., 2010, 2012) found a much lower rate in the
general population (26%), (Fawzy et al., 1982) compared to
university students 71% (Ibrahim et al., 2011). This was supported
by another using a comparable scale (CDS), which found only a 9%
prevalence of depression in the general population (Carroll et al.,
1981).
Gender difference in vulnerability to depression was evident in
the current study, consistent with other studies carried out both in
general populations (Velde et al., 2010; Van de Velde et al., 2010;
Angst et al., 2002) and in university students (Young et al., 2010;
Ovuga et al., 2006; Ghodasara et al., 2011). Although the difference
was statistically significant, it was not large. This was supported by
a previous study which concluded that gender differences are
markedly evident in the prevalence rate for major depression but
less so for minor depression, and this relation persisted across all
age groups (Van de Velde et al., 2010).
Many could argue that these high figures reflect an extreme
dose of normality as the majority of university student are
emerging from the hormonal and psychosocial chaos of
Fig. 4. Forest plot of studies on depression among college students.
0
10
20
30
40
50
60
70
80
90
1985 1990 1995 2000 2005 2010 2015
Fig. 3. Change of the depression prevalence rate over time.
396

adolescence into adulthood and that there is an inflation of figures,
but in the current review we included studies that that used well-
validated tools. The use of screening tools such as the PHQ may pick
up psychological distress rather than clinical depression and so
may inflate rates of disorder. They may also miss young people with
an atypical presentation of depression. In view of the high mean
rate of depression found in this systematic review of studies which
have used well established depression scales it is important to
validate these measures in student populations. Also, as a screening
tool there is the possibility of fallacies (positive or negative) and
this should be considered when interpreting the results. The above
indicated that each measure should be tested for validity and reli-
ability in this vulnerable group before its implementation for
depression screening. Alternatively, a well-validated and reliable
tool for depression screening among university students, as
a distinguish group in the community, should be developed and
validated cross-culturally to avoid any diagnostic bias and to enable
the researcher to identify the depression probability among the
studied group accurately.
An earlier review of depression among US and Canadian Medical
students has been published (Dyrbye et al., 2006). It was part of
a more extensive review that also investigated the other sources of
psychiatric distress such as anxiety. A similar search technique to
this review was used but the older review did not include a quality
assessment of the selected articles and had a more limited scope,
including only students in medical faculties. Of the 40 included
studies, 23 articles evaluated depression among medical students,
of those only 10 studies reported depression prevalence, in which
a slightly lower overall prevalence rate of 22.3% was reported
compared to the 25.6% found in our review. This difference is
probably due to the fact that most of the studies included in the
review were excluded from our review due to failure to meet one or
more of the more stringent inclusion criteria for example studies
were published before 1990 or response rates were not reported
(Dyrbye et al., 2006).
The majority of studies identified were carried out in the West
(68%), and only two studies of those included used data from
developing Arabic countries. This may reflect both a publishing bias
and a general lack of research in developing countries which is
unfortunate given the potentially higher vulnerability to depres-
sion in people in less economically developed countries due to
financial struggles and the poorer quality of health care (Ben-Ezra
and Essar, 2004; Patel et al., 2001; Licinio et al., 2008). Mental
health studies have suggested that medical education may have an
inevitable negative effect on mental health and increase the risk of
depression (Dyrbye et al., 2006; Nguyen, 2011). As a result, many
Medical Schools adopt screening programs for depression for all 1st
year students, which is not the case in other faculties. In the current
review we could not find any evidence of increased risk of
depression in studies recruiting medical students only, but
controversially we found that studies with more heterogenous
student samples had a higher weighted mean (36%) compared to
medical student studies (26%). This may be due to the fact that
medical students are well-acquainted with mental disorders and
they are exposed to mental cases and learn how to deal with these
disorders. We also feel that the frequent recruitment of medical
students in psychological studies was due to the accessibility of
students and good response rates.
It is well-known that probability sampling strengthen the
external validity (generalizability) of the study results, conclusions
and inferences, however it is time-consuming, costly and requires
a level of skill (Nutbrown, 2007). In this review, it was noticed that
articles adopting probability sampling reported a substantially
higher prevalence of depression compared to studies using less
rigorous sampling (35% vs. 29%), perhaps because those suffering
from depression are less likely to volunteer in studies using
a convenience sample. This suggests that many studies may
underestimate the prevalence of depression in university samples.
It was also concluded that there was an inverse relationship
between prevalence on one hand and sample size and response rate
on the other. As sample size and response rate are crucial for any
prevalence study, special attention should be drawn to their
determination and reporting (Bonita et al., 2006).
This review encountered several limitations. The major limita-
tion was the possibility of missing studies not directly reporting on
depressive prevalence (i.e. studies examining the prevalence of
general distress and using measures that screen for depression as
one of the elements of general distress e.g. the General Health
Questionnaire of Symptom Checklist (SCL-90)). Additionally the co-
morbidity of anxiety and depression may lead to over-estimation of
the prevalence rates in the studied papers. Publication bias is the
main drawback in any systematic review where it is proposed that
extreme results are more likely to be published especially in highly
respected journals so conclusions exclusively based on published
studies (Dubben and Beck-Bornholdt, 2005), therefore, can be
misleading. Secondly, the average prevalence of depression in the
current review (30.6%) may have been attenuated by including
some studies that reporting only rates of major depressive disorder
rather than minor depressive states. Another limitation is that
a limited number of studies were included in this review as many
studies reported the prevalence of depression prevalence but did
not report a response rate. This is important because the lower the
response rate, the less valid (for both external and internal validity)
the study as differences between non-respondents and respon-
dents may exist (non-response bias) in other perspectives than just
their willingness to take part in a survey (Denscombe, 2008, 2009).
Excluding articles reanalyzing data from the same database could
be considered a strength since it avoids including the same data
many times. At the same time researcher may have not been aware
of this double counting. Finally, any systematic review is affected by
the weaknesses and limitations of the included studies themselves
such as small sizes and poor response rates. Although all studies
used validated measures only one used a clinical interview. Relying
on self-report of symptoms is likely to impact on the sensitivity and
specificity of the classification of depression.
6. Conclusion and recommendations
Although there is a need for more in-depth research to confirm
the findings of this review, there is accumulating evidence to
suggest that depression represents a significant health concern in
university populations with, on average, nearly a third of students
affected. Furthermore the weighted mean prevalence of depressive
disorders in students of 30.6% is considerably higher than rates
reported in general populations. This systematic review empha-
sizes that depression is a common mental health problem in
university students. Although females are more at risk, the high
rates for male students are particularly concerning since they are
typically less willing to access support. The results of this review
suggest that more attention should be given to the identification
and management of depression in university settings. With current
economic pressures, vulnerability may increase further unless
research is conducted to establish effective interventions for
management of depression in students.
In light of the results of this review, a proposed design for future
research on the prevalence of depression among Higher Education
students could consider the following; a longitudinal study design
with a considerable sample size (300) and a randomly-selected
representative sample of students from different study disciplines
and from variable socio-economic backgrounds. This could

encompass several nested cross-sectional studies that include
comparative general population samples. A well-validated and
reliable tool for depression screening designed for university
students should be implemented. Additionally, more research
should investigate the validity and reliability of well-known
depression diagnostic tools in university student samples.
Conflict of interest
None.
Contributors
Authors contributed equally to the work.
Role of funding source
None.
Acknowledgments
I am very grateful for the Ministry of Higher Education, Egyptian
Government specially Assiut University for sponsoring my whole
studies. It is a pleasure to express my deepest gratitude and grateful
appreciation to the University of Nottingham for supporting this
study.
Appendix 1
Coding of the systematic review
Association
Tool
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b 21-BDI-I (Beck Depression Inventory)-1st revision
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6 PHQ-9 (Patient Health Questionnaire) (0e4) minimal depression or no, (5e9) mild depression
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7 ZSRDS (Zung Self Rating Depression Scale) (20e49) Normal range, (50e59) mildly depressed
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The modification of the original BDI included two approaches: (a) the four items per symptom which assessed the specific symptom’s intensity in the original BDI, were
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[ Increase factor is associated with increased risk of depression
Y Increase factor is associated with decreased risk of depression
¼ No difference
A Adjusted
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