Received: 10 June 2020 | Revised: 11 November 2020 | Accepted: 30 November 2020

DOI: 10.1111/ppc.12709

ORIGINAL ARTICLE

Psychological distress and mental health literacy in university

students

Şenay Pehlivan PhD,1 Assistant Professor |

Makbule Tokur Kesgiṅ PhD,2 Assistant Professor |
Pelin Uymaz PhD,1 Assistant Professor

1
Department of Public Health Nursing,
Faculty of Health Sciences, Alanya Alaaddin Abstract
Keykubat University, Antalya, Alanya, Turkey
Purpose: This study aimed to assess university students’ levels of psychological
2
Department of Public Health Nursing,
Faculty of Health Sciences, Bolu Abant Izzet
distress and mental health literacy.
Baysal University, Bolu, Turkey Design and Methods: This descriptive and cross‐sectional study using self‐
assessment instruments with 417 volunteer university students was conducted in
Correspondence
Şenay Pehlivan, PhD,1 Assistant Professor, the fall semester of the 2019–2020 academic year.
Department of Nursing, Faculty of Health Findings: More than half of the participants had diagnosable psychological distress
Sciences, Alanya Alaaddin Keykubat
University, Kestel Faculty Street Number: 80 in terms of mental illness. The participants had a low level of mental health literacy,
Alanya, Antalya 07425, Turkey. females and people with a mental illness had higher mental health literacy scores.
Email: senay.pehlivan@alanya.edu.tr
Practice Implications: The results indicated that the scales could be used to develop
interventions to assist Turkish students' transition to healthy adulthood. De-
termining individuals’ psychological distress allows early detection of mental
problems.

KEYWORDS
community mental health, mental health literacy, psychological distress

1 | INTRODUCTION among university students than other groups in a community.2 Al-

though the students experience mental problems, only a few of them
The university years coinciding with the transition period to adult- with mental disorders or low wellbeing are receiving treatment.1,2,5
hood is a sensitive period of time, which commonly includes emo- There are some handicaps for students for receiving treatment or
tional and mental problems.1,2 Considering that nearly 75% of seeking help (sex, self‐stigma, difficulty getting treatment, ignorance
mental problems are seen before the age of 24, this period should be of the current treatments, disbelief of needing treatment, benefit
deemed golden time for individuals to not only reach adulthood more expected from psychological help), and thus, very few struggle to
healthfully but also determine their mental health problems.2,3 This recover.6,7
period, in which the transition to late adolescence or young adult- The deeper the onset of mental disorders goes back to the past,
hood continues, coincides with the university years. Feeling stress the worse the clinical course and the more difficult to solve the
due to the difficulties of transition to young adulthood causes in- consequences seen in an individual.2 The most fatal consequence of
ability to cope with the responsibilities of being a university student students not receiving treatment for their mental problems or
(absenteeism, low academic performance, inability to finish uni- seeking help is that suicide rates among individuals aged 15–25 of
versity), dysfunctional relationships, social pressure, recurrent men- years are the second cause of death.5 Another reason why students
tal health problems, dropout from university, and low personal do not get treatment or help for their mental problems is that mental
income.3,4 Besides this, an increase in risky health behaviors, mental health services for students are not provided on campus5 or the
illness, mental distress, and decrease in wellbeing are more common current services are not at the desired level.1 If these young adults,

Perspect Psychiatr Care. 2020;1–9. wileyonlinelibrary.com/journal/ppc © 2020 Wiley Periodicals LLC | 1

2 | PEHLİVAN ET AL.

who are far from their families and primary support systems, are 2.2 | Study sample
aware of the symptoms of mental health problems in themselves and
their peers, they will recognize these diseases and receive treatment The participants consisted of 417 students in a public university in
earlier. Thus, protective services will serve students in protecting Turkey in the fall semester of the 2019–2020 academic year. Gpo-
and improving their health. Recognizing the problem is the first step wer 3.1.9.2 software was used to determine the sample size.13 A
to bring about a solution. The second step is to let the students learn power analysis using Gpower computer program (GPower 3.1.9.2)
how to reach resources to get rid of mental health problems. It indicated that a total sample of 406 people would be needed to
should be remembered that most students with symptoms will have detect effect size (d = 0.4) with % 98 power using a t test between
mental health problems before finishing university and carry this into means with alpha at 0.05. The effect size was found to be d = 0.4
adulthood if not intervened in time.4 University years are important based on the values obtained from the results of Marwood and
for taking precautions against mental health problems, early diag- Hearn.14 Thus, the total sample size was calculated as 406. The re-
nosis, and treatment interventions. Hernández‐Torrano et al. (2020) search was completed with 417 participants considering the possible
underlined that provision of service in cooperation of several in- dropouts. An easily accessible sampling method was used to reach
stitutions, professionals, families and professionals of different oc- the participants during the administration of the questionnaire. The
cupations is important to meet university students’ mental health students, either in health‐related programs or in other programs,
requirements.1 They also suggested further studies including differ- who volunteered were included in the study.
ent sectors to provide university students with protective mental
health services.1 The first approach within primary protection in
mental health is to increase the mental health literacy (MHL) levels 2.3 | Procedure and data collection
of university students. The studies conducted with university stu-
dents show that they have low levels of MHL.9,10 According to a The data were collected using the K10, MHL, MHLS scales. An in-
study conducted with university students, moderate or more severe formation form prepared by the researcher. which included demo-
mental distress symptoms were detected in 78% of the students, graphic information, was also used to collect the data. Before the
while the MHL levels were lower than those of other studies.9 It is study was launched, 20 university students in different departments
very important to determine the MHL level of university stu- were included in the preliminary administration. All questions were
dents because many students experience preventable or treatable clear in the preliminary administration of the questionnaires, thus no
1,9,10
mental health problems. change was needed on the questions. The questionnaires were
The most critical intervention strategy for promoting early completed in 18 min on average. For administration of the ques-
diagnosis of and treatment for mental illnesses may be to increase tionnaire, the researchers learned the appropriate course hours of
individuals’ MHL levels. Although the reliability and validity stu- the students by contacting the department officials and they in-
dies of the scales for MHL in Turkey have increased,8,11,12 there formed the students about the research. To prevent students’ in-
haven't been sufficient studies about psychological distress and teraction with each other, they were asked fill out the questionnaires
MHL of university students in Turkey. Therefore, the current based on their own views only. Only students who had volunteered
study was designed to be a resource for further interventional took part in the questionnaire. The researchers left the classroom
research, providing data regarding students’ levels of psychologi- after collecting the pending questionnaires after the students com-
cal distress and MHL. pleted them.

2 | M A TE R I A L S AN D ME TH O D S 2.4 | Measures

2.1 | Study design 2.4.1 | Descriptive information form

This descriptive and cross‐sectional study was conducted with un- The descriptive information form was prepared by the researcher
dergraduate and associate degree students enrolled in a public uni- and included participants’ age, gender, and employment status and
versity in a Mediterranean region of Turkey. The data were collected questions about whether they, their family members, or friends had a
using questionnaires provided to volunteer students between the diagnosis and treatment of mental illnesses.
dates of February 16 and March 13, 2020. The researcher provided
information about the research subject and the questionnaire be-
fore administration. The research was conducted with 347 students 2.4.2 | Kessler Psychological Distress Scale (K10)
in health‐related programs (83.2%) and 70 students enrolled in non‐
health‐related programs (16.8%), and consisted of 417 students in The K10 scale was developed by Kessler et al. it includes 10 ques-
total. The research inclusion criteria were to be a registered student tions about nonspecific psychological distress and aims to measure
of the university and voluntary participation. the level of depressive symptoms experienced by an individual within
PEHLİVAN ET AL.
| 3

the last 4 weeks before the interview. When the two‐page scale is α coefficient was 0.87, while this was 0.89 in the study Tokur Kesgin
administered, the first 10 questions (“a” to “j”) under the general et al.12 The Cronbach's α of the MHLS was 0.71 in the present study.
heading of Q1 are taken into consideration. The Q1 questions are This scale was used to determine students’ MHL levels and the level
scored using a five‐point Likert type scale ranging from one (never) of their educational needs.
to five (always); total possible scores range from 10 to 50 points,
with higher scores indicating more psychological distress. Altun
et al.15 verified the sensitivity to be 90.4% for a score > 20 cut‐off 2.5 | Ethical approval
point, internal consistency to be 0.95, and Cronbach's α to be 0.92 in
the K10. The Cronbach's α in the present study was 0.92. This scale The study design conformed to the Declaration of Helsinki. The study
was used to determine students’ psychological distress levels. was conducted after ethical approval was obtained from the public
university institutional review board (Numbered 16–18; Dated Feb-
ruary 16, 2020). The utilization permits for the K10 and MHL scales
2.4.3 | Data collection tools used to measure MHL were obtained from Özen and Göktaş via e‐mail. Also, institutional
permission was obtained to conduct the study. The participants were
MHL informed of the study's aims and they provided their written consent.
The MHL assessment consists of three subscales with 22 items, in-
cluding 10 knowledge‐oriented, eight belief‐oriented, and four
source‐oriented items. Possible scores range from 0 to 22, with 2.6 | Data analysis
higher scores indicating higher MHL levels. The first 18 items (the
first two subscales) have six possible responses: “I strongly agree,” “I The data were analyzed using the Statistical Package for the Social
agree,” “I am indecisive,” “I disagree,” “I strongly disagree,” and “I do Sciences (Version 17.0; SPSS Inc.). The descriptive categorical data
not know.” The four source‐oriented items are answered as either were analyzed using the number, percentage, median, minimum‐
“Yes” or “No,” with “Yes” scored as 1 point and “No” scored as 0. For maximum values; while the continuous data were analyzed using the
the knowledge‐oriented items, “I strongly agree” and “I agree” are arithmetic mean and standard deviation. The appropriateness of the
each scored “1” point; and all other responses are scored “0”. Belief‐ data to normal distribution was tested using Kolmogorov–Smirnov
oriented items are reverse coded (“I do not know” and “I strongly analysis (p < 0.05); as the data did not show normal distribution,
disagree = 1 point; all others = 0 point). At the end of the study, the nonparametric tests were used. The Spearman correlation was used
Cronbach's α coefficient was found to be 0.62, matching that of for correlation between scale scores, while a comparison of the scale
Goktas et al.11 This scale was added to determine the criteria validity scores and the binary variable was made using the Mann–Whitney U
of the newly developed MHLS and find out how correct the MHLS test. In all cases, p < 0.05 was considered significant, and Cronbach's
measures the data. α was recorded for reliability analysis for all scales.

MHLS
The MHLS allows for assessment of the effectiveness of interven- 3 | RES ULTS
tions to promote the MHL levels. The scale has 35 items scored using
a Likert‐type self‐assessment. The scale items vary, some being 1–4 This study was completed with the participation of 417 university
points and others 1–5 points. The four‐point item (items 1–15) re- students in total. The students were enrolled in health‐related pro-
sponses are “I strongly disagree” (1), “I disagree” (2), “I agree” (3), and grams (n = 347, 83.2%) and non‐health‐related programs (n = 70,
“I strongly agree” (4). The five‐point item (items 16–35) responses 16.8%). The mean age of the participants was 20.19 ± 1.34 years. Of
are “I strongly disagree” (1), “I disagree” (2), “I am indecisive” (3), “I them, 61.2% were female, 11.8 were employed, 82.3% had a middle‐
agree” (4), and “I strongly agree” (5). Although the original scale is range income and 52.0% lived in dormitories. Their reported ex-
unidimensional, it has six subscales, as indicated by Ref.16 The six periences with ever being diagnosed with and treated for mental
subscales include domain 1, diagnosing diseases (items 1–8); domain illnesses included themselves (14.9%), family members (19.7%), and
2, how to access knowledge (items 16–19); domain 3, risk factors and friends (10.1%). Among family members who experienced mental
their causes (items 9 and 10); domain 4, self‐support/treatment in- illnesses, mothers had the highest rate with 78.0% (Table 1).
terventions (items 11 and 12); domain 5, accessing professional Considering participants’ MHLS, MHL, and K10 score distribution,
support (items 13–15); and domain 6, attitudes that facilitate seeking the MHLS median was found to be 90 (Min–Max = 60–115) and the
appropriate support for mental health diseases and attitudes to- MHL median was 12 (Min–Max = 1–20). The MHL sub‐domain median
wards mental health diseases (items 20–35) (stigmatizing). Some scores distributions were 8 in knowledge, 1 in belief, and 3 in the
items in the scale were reverse coded (items 10, 12, 15, 20–28). The resource domain. The K10 median was determined to be 30
total possible score for MHLS ranges from 35 to 160, with higher (Min–Max = 10–50) which shows the psychological distress level. More
scores indicating higher MHL levels. According to the validity and than half of the participants (51.3%) had a serious stress level that
reliability studies of the scale in its original language, the Cronbach's would indicate mental illnesses (Table 2).
4 | PEHLİVAN ET AL.

TABLE 1 Participants’ general characteristics/variables (n: 417) TABLE 2 Distribution of participants’ MHLS, MHL, and K10
scores
Characteristics/variables n %*
Scales Median Min–Max
Age x̄ ± SD (Min.–Max.) = 20.19 ± 1.34 (18–32)
≤20 320 76.7 MHLS 90 60–115
≥21 97 23.3 F1: Ability to recognize disorders (Q1–8) 24 8–32
Gender F2: Knowledge of where to seek information 14 4–20
Female 255 61.2 (Q16–19)
Male 162 38.8
F3: Knowledge of risk factors and 5 2–8
Departments of university students causes (Q9–10)
Health‐related programs 347 83.2 F4: Knowledge of self‐treatment (Q11–12) 5 2–8
Non‐health‐related programs 70 16.8
F5: Knowledge of professional help available 9 3–12
Employment status (Q13–15)
Working 49 11.8 F6: Attitudes that promote recognition or 33 13–45
Not working 368 88.2 appropriate help‐seeking behavior
(Q20–35) (Stigmatization)
Financial situation
Bad 30 7.2 MHL 12 1–20
Moderate 343 82.3 Knowledge‐oriented 8 0–10
Good 44 10.5
Belief‐oriented 1 0–10
Cohabiting people
Resource‐oriented 3 0–14
Alone 27 6.5
With family 33 7.9 K10 30 10–50
With friends 140 33.6 K10 n %
In dormitory 217 52.0 <20 no stress 91 21.8
Psychiatric disease diagnosis/treatment (himself/herself) 20–24 mild stress 53 12.7
Yes 62 14.9 25–29 moderate stress 59 14.2
No 355 85.1 30–50 severe stress (mental illness) 214 51.3

Psychiatric disease diagnosis/treatment (family Abbreviations: n, number; %, percentage; Min–Max, minimum–maximum.

members)
Yes 82 19.7
No 335 80.3
scale according to age variable were lower and statistically sig-
Family member diagnosed/treated (n = 82)
nificant in the age group of 20 years and below compared with the
Mother 64 78.0
age group of 21 years and above (U: 11652.0, p < 0.001, z: −4.745).
Brother 10 12.2
The median values of the scores from the MHLS scale were lower
Sister 8 9.8
and statistically significant in the age group of 20 years and below
Psychiatric disease diagnosis/treatment (friend) compared with the age group of 21 years and above (U: 14793.0,
Yes 42 10.1
p < 0.05, z: −1.972) (Table 4).
No 375 89.9
The median values of the scores from the K10 scale were sig-
Abbreviations: x̄ ± SD, mean ± standard deviation; n, number, %, nificantly higher in males than females (U: 17597.0, p < 0.05, z:
percentage; Min.–Max, minimum‐maximum. −2.550). The median values of the scores from the MHL scale did not
*The percentages are based on the number of respondents.

A positive and weak statistically significant correlation was TABLE 3 Correlation between participants’ K10, MHL, and MHLS
found between the scores from the MHL scale and the scores from scores
the MHLS scale (Spearman's ρ = 0.335, p < 0.01, ρ2 = 0.11. The ana- Scales K10 MHL MHLS
lyses also found that there is a negative and moderate significant
K10 1
correlation between students’ MHL and K10 (Spearman's ρ = −0.58,
MHL −0.096** 1
p < 0.05, ρ2 = 0.33) (Table 3).
The study results indicated that the group below the age of 20 MHLS −0.049 0.335** 1
years obtained a higher median value that is statistically significant Note: Bold values difference statistically significant.
compared with the age group 21 years and above (U: 13471.0, *Spearman's correlation analysis.
p < 0.01, z: −3.001). The median values of the scores from the MHL **p < 0.05.
PEHLİVAN ET AL.
| 5

TABLE 4 Distribution of participants’ scale scores according to some variables

Scales
K10 MHL MHLS
Characteristics/variables Median (Min‐Max) Median (Min‐Max) Median (Min‐Max)

Age (year)
≤20 31 (10–50) 12 (1–19) 89 (60–115)
≥21 26 (10–50) 13 (6–20) 91 (67–115)
U, p, z 13471.0, <0.001, −3.001 11652.0, <0.001, −4.745 14793, <0.05, −1.972

Gender
Female 29 (10–50) 12 (1–20) 91 (62–112)
Male 31 (10–50) 12 (1–18) 86 (60–115)
U, p, z 17597.0, <0.05, −2.550 18445.5, >0.05, −1.900 14123.0, <0.001, −5.449

Employment status
Yes 34 (14–47) 12 (1–17) 9 0 (71–115)
No 29 (10–50) 12 (1–20) 90 (60–115)
U, p, z 6331.0, <0.001, −3.390 8233.0, >0.05, −1.019 8089.5, >0.05, −1.170

Psychiatric illness diagnosis and treatment (herself/himself)

Yes 29 (10–50) 13 (5–19) 93 (67–112)
No 30 (10–50) 12 (1–20) 89 (60–115)
U, p, z 10443.0, >0.05, −0.642 10119.0, >0.05, −0.986 8350.5, <0.001, −3.034
Psychiatric illness diagnosis and treatment (Family Members)
Yes 29 (10–50) 13 (3–17) 93 (70–112)
No 30 (10–50) 12 (1–20) 89 (60–115)
U, p, z 13442.0, >0.05, −0.426 13245.5, >0.05, −0.594 10108.5, <0.001, −3.821

Departments
Related to Health 28 (10–50) 12 (1–20) 91 (60–115)
Non‐Health 37 (13–50) 11 (1–18) 87 (62–112)
U, p, z 7633.0, <0.001, −0.995 8794.5, <0.001, −2.117 10252.0, <0.05, −2.898

Note: Bold values difference statistically significant.

Abbreviation: U, Mann–Whitney U test.

show a significant difference between genders (U: 18445.5, p > 0.05, who did not from the MHLS scale (U: 8350.5, p < 0.01, z: −3.034)
z: −1.900). The median values of the scores from the MHLS scale (Table 4).
were higher in females than males (U: 14123.0, p < 0.001, z: −5.449) The K10 scale median of those with a family member who had
(Table 4). In the current study, the mean scores of females from the psychiatric disease diagnosis/treatment was lower than those who
K10 and MHLS were found to be significantly higher than males did not (U: 13442.0, p > 0.05, z: −0.426). Similarly, there was no
(p < 0.05, p < 0.01). significant difference between the scores obtained from the MHL
When it came to comparing the scores of participants based on scale (U: 13245.5, p > 0.05, z: −0.594). However, the median of the
their employment status, the median values of the scores of un- MHLS scores was found to be higher in the participants with a family
employed participants from the K10 scale were significantly higher member who had psychiatric disease diagnosis/treatment than those
than those of employed participants (U: 6331.0, p < 0.05, z: −3.390). who did not (the median was found to be significantly higher) (U:
There was no significant difference between the median of the 10108.5, p < 0.01, z: −3.821) (Table 4).
scores of unemployed participants from the MHL and MHLS scales The median of the scores of those enrolled in health‐related
(MHL, U: 8233.0, p > 0.05, z: −1.019 and MHLS, U: 8089.5, p > 0.05, z: programs from the K10 scale was significantly higher than those
−1.170) (Table 4). enrolled in non‐health‐related programs (U: 7633.0, p < 0.001, z:
There was no significant difference between the scores from −0.995). The median of the scores of those enrolled in health‐related
the K10 and MHL scales of those who had psychiatric disease programs from the MHL scale was significantly higher than those in
diagnosis/treatment and those who did not (K10, U: 10443.0, non‐health‐related programs (U: 8794.5, p < 0.001, z: −2.117). The
p > 0.05, z: −0.642 and MHL, U: 10119.0, p > 0.05, z: −0.986). median of the scores of those enrolled in health‐related programs
However, the median of the scores of those who had psychiatric from the MHLS scale was significantly higher than those in non‐
disease diagnosis/treatment was significantly higher than those health‐related programs (U: 10252.0, p < 0.05, z: −2.898) (Table 4).
6 | PEHLİVAN ET AL.

The MHLS scores were significantly higher in individuals aged diagnosis, and treatment, and manage their mental health status.
21 years and above compared with 20 years and below, in females Thus, university students should have information about MHL. Ac-
compared with males, in those who had psychiatric disease diag- cording to a study conducted in India, there is an increase in the
nosis/treatment (himself/herself or a relative) compared with those prevalence of depression. However, the most worrying aspect is that
who did not, and in those enrolled in non‐health‐related departments the problem is generally unnoticed and untreated. The researchers
compared with health‐related departments. state that the lack of MHL is one of the most important reasons
for this problem.23 The mean MHL score was 123.5 ± 15.5 in the
study conducted by Gorczynski et al.9 with university students,
4 | DI SCUSSION 127.69 ± 11.82 in the study conducted by Marwood and Hearn14
with medical students, and the mean MHLS score was
12
The aim of students’ primary prevention studies for mental health is 107.37 ± 15.94 in the study conducted by Tokur Kesgin et al. with
to prevent mental health problems before they occur or to de- students and individuals from different segments of the society. Al-
termine the problems earlier. This study suggests that university though the MHL 12 (1–20) and MHLS 90 (60–115) median scores
students are substantially at‐risk group in terms of mental health were low in this study, the MHLS median scores 12 (0–22) and 17
problems. Their MHL scores were found to be lower (females and (10–22) were similar to the study conducted by Goktas et al.11 This
those with mental illness have little higher scores). The studies re- result suggests that the rest of the students (78.2%) aside from those
port that university students’ academic success is negatively affected who stated to have no stress (21.8%) might have difficulty in
due to mental health problems such as stress, anxiety, insomnia, and managing their mental health problems. Thus, MHL stands out in
depression and they tend to leave university or commit suicide.8,17,18 managing students’ mental health problems. The analyses also found
The biggest tragedy is that very few ofthose committing suicide (one that there is a negative and moderate significant correlation between
quarter) have received mental health services from official institu- students’ MHL and K10 (Spearman's ρ = −0.58, p < 0.05, ρ2 = 0.3364).
tions. Thus, the students who do not have a clinical diagnosis but In brief, as students’ MHL increases, their experience of psycholo-
experience distress influencing their health and academic perfor- gical distress decreases. A positive and weak statistically significant
mance should be monitored.19 There are findings stating that this correlation was found between the scores from the MHL scale and
suggestion is important for this study too. Considering the distribu- the MHLS scale.
tion of K10 scores, only 21.8% of the participants reported no stress. The MHLS scores were significantly higher in individuals aged 21
This means that the students felt mild stress (12.7%), moderate years and above compared with 20 years and below, in females
stress (14.2%), and severe stress (51.3%) which makes 78.2% in total. compared with males, in those who had psychiatric disease diag-
The students reporting severe stress, in particular, are highly likely to nosis/treatment (himself/herself or a relative) compared with those
be diagnosed with mental illness. The K10 severe stress level of this who did not, and in those enrolled in non‐health‐related departments
study (51.3%) is higher than those reported in other stu- compared to health‐related departments. Similar to this study, two
dies.8,16,17,20 This result shows that many more need professional different studies conducted by Gorczynski et al.16 with university
support than the students reporting having been diagnosed or re- students in 2017 and 2020 suggested that the mean MHL scores of
ceiving treatment for the psychiatric disease (14.9%). The K10 scores women and those who were previously diagnosed with mental health
were found to be higher and significant in the age group of 20 years problems were high and statistically significant.9,16 In the current
and below compared with 21 years and above, in males compared study, the mean scores of females from the K10 and MHLS were
with females, in the employed group compared with the unemployed, found to be significantly higher than males (p < 0.05, p < 0.01). In the
and in those enrolled in non‐health‐related departments compared study of Marwood and Hearn,14 the MHL levels were found to be
with health‐related departments. Unlike this study, Goktas et al.11 higher in women who had previously received psychiatric diagnosis
stated that MHL scores in the Turkish reliability and validity study of and treatment.
the MHL scale did not show a difference in the university students’ The results of this study showed similarities with other studies.
gender and age. Unlike these studies, the study by Gorczynski et al.9 Among people aged 18–24 years, half of all health concerns are
indicated that K10 mean scores were significantly higher (F (1, related to mental illness. Also, the onset is generally at the age of 24.
298) = 55.344, p < 0.001) in individuals who had a history of mental The lack of life experiences and MHL knowledge of the younger ones
disorders (31.7 ± 7.9) compared with those who did not (23.8 ± 8.4). puts them into more stress.24 This is an important obstacle for the
As in other studies, this study also underlines that conducting young in seeking professional help in time.25 University years are
mental health screening at universities is necessary to determine the best period to detect and treat mental health problems. When
students’ mental health problems at an early stage, to consultancy the university administrators manage this time in the best way
them to professional support and to diagnose or treat them, as ap- possible, this may promote students' mental health, academic suc-
4,21
plicable. Although mental health screenings allow early determi- cess, substance addiction, and interpersonal relationships.
nation of students who need help, screening all students is difficult in The study results and findings from the related literature state
terms of time and economy.8,22 Therefore, it is important that stu- that men experience more psychological distress and have less
dents be aware of the symptoms of their mental problems, seek help, knowledge of MHL.9,14 These results state that men should be
PEHLİVAN ET AL.
| 7

considered an important risk group regarding mental illnesses. Tra- relatives who received treatment, the majority of mothers sug-
ditional gender roles expected of men are an important obstacle to gested that being a woman meant being in the risk group in terms
their help‐seeking behavior with respect to mental problems. of mental illnesses. As discovered in this study too, gender is an
Topkaya et al.7 stated that men who receive psychological help have important determinant of mental health and illness all around the
a higher self‐stigmatization compared with women. world. Gender generally determines socioeconomic determinants,
The results of the research show that employed students and social status, and exposure to mental health risks. For example,
those who are enrolled in non‐health‐related departments should depression and anxiety disorders are more common in women,33
also be considered a risk group in terms of psychological stress. whereas the fear of being stigmatized for seeking help due to
However, individuals with little knowledge of MHL also have limited mental problems is higher in men.7
skills in taking preventive measures for mental health problems and At this point, MHL training, which is one of the best ways to
14,23,26
disease management. MHL training should be provided to prevent stigma towards mental illnesses and facilitates seeking
those individuals as primary preventive health care. As a secondary professional help, should be provided at university as a health‐
preventive health service, they should be screened for mental promoting intervention and health measure. In particular, interven-
symptoms/diseases. At the tertiary preventive level, the treatment tion groups should be created for women.34 The results of this study
26,27
plan should be followed, and their health should be maintained. have shown that the majority of the participants’ mothers have been
In this study, the lower stress levels of the students enrolled in diagnosed with or treated for mental illnesses. This study found that
health‐related departments and their high MHL scores may be due to the independent factors affecting the MHLS score of the participants
their departments being related to health issues. MHL knowledge were gender, high MHL score, and relatives who had a psychiatric
may positively affect the attitudes of students studying in health‐ diagnosis. The MHL scores are affected by MHLS scores and age
related departments towards mental health problems, and thus, re- variables. Independent factors affecting the K10 scores were found
duce their stigmatizing attitudes.7,8,15,16 However, students in non‐ to be age and gender.
health‐related departments may not be as lucky as the students in
health‐related departments regarding stress management and MHL
knowledge. Therefore, university administrators and school health 4.1 | Research limitations
nurses in the university should develop intervention programs to
promote students' MHL.28,29 The development of MHL in uni- The research was conducted at one university. Thus, the results of
versities is deemed an important step in increasing the mental health the research cannot be generalized to all university students.
welfare of both students and the society.29 Another limitation of the research is the low number of students
A valid and comprehensive measure is needed to adequately of non‐health programs in the study. It is recommended that other
30
identify the level of MHL and the need for mental health education. studies be conducted at other universities and with larger sample
MHL and MHLS scales of this study were observed to measure MHL groups
levels similarly. This study showed that Turkish version of the MHLS
meets the criterion‐related validity. This validity reveals the corre-
lation of the scale score that has been validated with some known 5 | CO NC L USIO N
external criteria measuring the same concept and the scales that
have been validated.31 This study has shown that the school (uni- This study found that more than half of the participants had psy-
versity) nurses can use the MHLS scale safely in intervention pro- chological distress to some degree; however, very few of them re-
grams to increase mental health literacy level. MHL includes four ceived diagnosis/treatment. Also, the students' MHL levels were
distinct but related components: (1) understanding how to obtain found to be low. These findings highlight that university students
and maintain good mental health, (2) understanding mental disorders should be screened for mental illnesses and protective mental health
and related treatments, (3) reducing the stigma related to mental services should be provided for increasing their MHL level. In par-
disorders, and (4) enhancing help‐seeking efficacy (i.e., knowing when ticular, to prevent decreases in the functionality of individuals and
and where to obtain evidence‐based mental health care and having continue their follow‐up and treatment, universities should be in-
the competencies to enhance self‐care.32 cluded in the scope of the Community Based Mental Health Con-
Although psychiatric diagnosis/treatment did not significantly cept.35 This aims to meet the basic life needs of patients in their
affect the median scores of K10 and MHL, it significantly affected home, neighborhood, or workplace to develop skills to cope with
the MHLS scores. High level of MHL in those experiencing mental problems and activate necessary support systems.
health problems may be related to becoming skilled in managing
the process and recognizing the illness.8,14 Having a psychiatric
diagnosis/treatment one of a family member's had a significantly 5.1 | Implications for nursing practice
higher effect in MHLS scores. The study showed that females and
those who received psychiatric diagnosis/treatment had higher The authors recommend establishing the necessary programs in
MHL and MHLS median scores. Additionally, considering the universities using a community‐based approach, which can also be
8 | PEHLİVAN ET AL.

considered within the scope of preventive mental health. Al- (RSOY scale). Konuralp Medical Journal. 2019;11(3):424‐431. https://
though further studies are needed to explore the generalizability of doi.org/10.18521/ktd.453411
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the study results, community health advocates and practitioners may
bility of the Mental Health Literacy Scale in Turkish. Anatolian
refer to this study for developing mental health interventions pro- Journal of Psychiatry. 2020;21(Suppl 2):5‐13. https://doi.org/10.
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20982/tqmp.03.2.p051
larly important for the current study because of the limitation of a 14. Marwood MR, Hearn JH. Evaluating mental health literacy in medical
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[Anatolian Journal of Psychiatry]. 2019;20:23‐31. https://doi.org/10.
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The authors declare that there are no conflict of interests. health literacy, help seeking behaviours, and mental health outcomes in
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Makbule Tokur Kesgiṅ https://orcid.org/0000-0003-2729-8612 Akademik Başarıya Etkisi [Effect of depression on family‐friend re-
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