Abstract
Background
The ongoing conflict in Sudan leads to widespread displacement and increased mortality, significantly impacting the mental health of populations in conflict zones. This study aims to fill the gap and assess the level of stress, depression, and anxiety among Khartoum University undergraduate students in war-afflicted regions.
Methods
A cross-sectional study among 443 undergraduate students Was conducted using cluster and stratified sampling techniques. Data was collected using a valid questionnaire in a period of one month and analyzed using SPSS and a regression model to assess factors affecting distress.
Results
The study shows high levels of psychological distress, particularly among female students. Median anxiety and stress levels were 12.50 and 14.00, respectively, for women, significantly higher than those for men (p < 0.001). Faculty, physical health, time management, and support systems were also significantly correlated with distress levels. Students in the Faculty of Forests and Animal Breeding exhibited the highest levels of depression and anxiety. Poor physical health and seeking professional help were strongly associated with increased psychological distress. Regression analysis identified gender (p = 0.001) and time management (p = 0.022) as significant predictors of overall distress.
Conclusion
Undergraduate university students in war regions experience high levels of stress, anxiety, and depression due to conflict situations. These findings reflect the urgent need for interventions such as community-based programs and counselling. We recommended future studies to explore long-term impacts on students' mental health.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12888-025-06591-z.
Keywords: Stress, Anxiety, Depression, University of Khartoum, War-afflicted regions, Sudan, Mental health, Coping mechanisms
Introduction
On April 15, 2023, unexpected violence erupted between the Sudanese Armed Forces and the Rapid Support Forces in Khartoum, Sudan’s capital. This conflict quickly spread to the Al Jazirah State and the Darfur regions, leading to significant humanitarian crises. According to the United Nations, over one million people leave Sudan, and at least 4.3 million have been internally displaced. The crisis has disrupted various aspects of life, including education, with more than 100 universities either severely damaged or completely destroyed. The University of Khartoum, a prominent institution in the region, has faced extensive challenges, including the loss of critical academic resources [1].
The psychological consequences of war include stress, trauma, mental illness, family separation, and the loss of loved ones. Stress, defined as any disruption to stability or internal equilibrium, is often exacerbated in conflict zones, leading to long-term mental health challenges such as anxiety and depression [2]. Evidence from other conflict zones suggests that wars significantly affect mental health, disrupting individuals’ emotional balance and social functioning [3]. For example, mental health disorders, such as anxiety and depression, are among the top three causes of disability for individuals aged 15 to 44 [4].
In addition to directly impacting mental health, conflicts hinder the social and economic development of affected communities. The consequences of war extend beyond physical displacement and include issues such as poverty, malnourishment, and limited access to healthcare services. These challenges create a growing health inequality, particularly for vulnerable groups like college students, who are at an elevated risk of psychological morbidity [5]. There is ample evidence of traumatic occurrences in communities affected by war [6]. Long-term violent events may also have indirect consequences on mental health, according to studies [5, 7]. However, a significant body of research has examined the detrimental impact of conflict on mental health [5, 8–12].
It has been noted that both military personnel and civilians living in conflict and war zones are frequently affected by neuropsychiatric diseases. Emotional response disruption and permanent damage are possible outcomes of these diseases. It is impossible to adequately convey the intense stress, agony, and mental breakdown brought on by the unplanned move, family separation, and murder of friends and family. Years of mental health care are required for the survivors because they have problems including insomnia, repeated memories, anxiety, sadness, and anger too long after the conflict. All of these could make the person more likely to engage in unhealthy coping mechanisms, such as excessive drinking, drug abuse, aggression, or gambling [13]. Anxiety and stress are prevalent mental health issues, especially among college students, and stress is associated with the emergence of anxiety [14]. It is acknowledged that college students are more likely to experience difficult circumstances in contrast to others [4].
In addition to the severe mental health disorders that have been documented as a result of wars worldwide, the lack of data on the psychological damage caused by the war in Sudan, the multi-sectoral negligence of psychological distress before and after the war in Sudan, and the urgent need for intervention in these cases, along with the high risk of developing such psychological morbidities among college students in particular, make this study imperative. The purpose of this study is to evaluate the effects of conflict on anxiety, stress, and depression in University of Khartoum undergraduate students. It is carried out to address and support services, educating legislators, academic administrators, and mental health specialists about the pressing need for all-encompassing approaches to support academic achievement and well-being.
Studies on the mental health of students in conflict areas have been conducted all over the world, but none have specifically examined Khartoum University students living in conflict areas during the ongoing war in Sudan.
Due to this gap in the literature, we don't fully understand how students in these particular situations deal with stress, anxiety, and sadness. Instead of addressing the ongoing mental health issues that students in war areas confront, the majority of studies concentrated on post-conflict healing. Our research will close this knowledge gap and assess the level of stress, depression, and anxiety among Khartoum University undergraduate students in war-afflicted regions.
Methodology
Study design
This is a descriptive cross-sectional analytical study conducted to assess the level of stress, depression, and anxiety among Khartoum University undergraduate students who stay in war-afflicted regions in Sudan in 2024.
The University of Khartoum was founded in 1902. It has a rich history of academic excellence, innovation, and leadership in Sudan and the region. As the oldest and most prominent university in the country, it also provides high–quality education across a wide range of disciplines [14].
Sample size & sample technique
The University of Khartoum contains a total of 43,890 students. The sample size was calculated to be 399 students using the equation n = N/(1 + N e2).
n = sample size, N = population size (43,890), E = level of precision (0.05).
Due to the drawbacks of convenient sampling and online surveying, a 10% non-response rate was added, and the final sample size was 443 students.
The cluster sampling technique was used to select the required number of students from each college based on its number of students, with each faculty representing a cluster. The number of students in each faculty, besides the sample size and the total number of Khartoum University students, were used to measure the number of students needed from each faculty. The number of students from each faculty = (Number of students in the faculty / Total number of students in Khartoum University) multiplied by sample size. Then random stratified sampling is used to select several students needed from each batch in each college based on the number of students by dividing faculty into cohorts, with each cohort representing a stratum. The needed number of students from each cohort was measured by an equation, and random selection was used among those staying in war regions.
Inclusion: undergraduates Khartoum University students who stay in war-afflicted regions during the data collection period and agreed to participate. Exclusion: students who don’t agree to participate or Khartoum University students who don’t reside in war regions.
Data collection tool
The data was collected for one month using self-administered questionnaires; a modified version of the validated questionnaire Depression Anxiety Stress Scale (DASS42) was used as a reference to design the study’s questionnaire [15]. The questionnaire was sent via WhatsApp, Facebook, and Telegram (Fig. 1).
Fig. 1.
The flow diagram of the study according to STROBE guidelines
DASS-42 is a 42-item questionnaire that contains three self-report scales formulated to measure the conditions of depression, anxiety, and stress. Every scale includes 14 items, with subscales of 2–5 items with the same content. The depression scale appraises dysphoria, hopelessness, devaluation of life, self-deprecation, lack of interest/involvement, anhedonia, and inertia. The Anxiety Scale appraises autonomic arousal, skeletal muscle effects, situational anxiety, and subjective experience of anxious affect. The stress scale (items) is sensitive to levels of chronic non-specific arousal. It assesses difficulty relaxing, nervous arousal, being easily upset/agitated, irritable/over-reactive, and impatient. The scores of depression, anxiety, and stress scales are measured by adding the scores of the associated items. The Cronbach alpha values for depression, anxiety, and stress scales are 0.96, 0.89, and 0.93, respectively.
We conducted a pilot study to evaluate the questionnaire's applicability to our war settings. According to the pilot results, 2 items were deleted from the depression scale, and 3 items were deleted from the stress scale. The final version was composed of 37 items (Supplementary File 1).
Data analysis plan
The data was collected using an Excel sheet, and then SPSS version 21 was used. Data cleaning was performed using the SPSS software. Missing value analysis was performed, which yielded that the total percentage of missing cases was 25.96%, which is higher than 20%. Also, the missing data wasn’t completely random, as the p-value of EM was 0.000. The variables—excluding scales—with the highest missing percentages were excluded from the scales and subsequent analysis: "I was unable to become enthusiastic about anything" with a 15.3% percentage of missing, "I found myself getting upset by quite trivial things with 7.7%, and” I felt that I had lost interest in just about everything with a 7.7% percentage of missing. These 3 questions have other similar questions in the questionnaire, and that is why omitting them was possible. After omitting the variables, the total percentage of missing values went down to 4.06%, which is less than 5%. The rest of the missing cases were mainly in the ‘faculty’ variable, with 14 missing cases, but multiple imputation wasn’t used due to the low percentage of total missing. When assessing normality, age and all psychometric scales weren’t normally distributed (p-values < 0.01).
In data analysis, frequency tables and descriptive statistics were used to illustrate the socio-demographic factors and also the answers in depression, anxiety, and stress items. Mann–Whitney and Kruskal–Wallis tests were used in univariate analysis to determine the extent of differences between categories of socio-demographic variables. Multiple regression analysis was also used by including variables with p-values > 0.25 in univariate analysis against the full distress scale.
Results
Socio-demographic and lifestyle data
Four hundred forty-three participants were included in the study. The majority of them, 311(70.2%), were females with a median age of 21 ± 3. Nearly all of them (97.3%) were single and more than half of them (58.7%) were living in Sudan-area of the study-. Only 28 (6.1%) students were studying medicine (Further details in Table 1).
Table 1.
The socio-demographic characteristics of the participants and the univariate analysis regarding full distress scales among the participants (N = 443)
| Characteristic | Frequency(%) | Full distress Scale | |
|---|---|---|---|
| M ± IQRa | P-value | ||
| Age | 21.00 ± 3.00a | 38.00 ± 29.75c | |
| Gender: | 0.000** | ||
| Male | 132(29.8%) | 29.00 ± 26.00 | |
| Female | 311(70.2%) | 41.00 ± 29.00 | |
| Marital Status: | 0.327 | ||
| Single | 431(97.3%) | 38.00 ± 29.00 | |
| Married | 12(2.7%) | 44.00 ± 35.00 | |
| Residency: | 0.064 | ||
| Inside Sudan | 260(58.7%) | 36.50 ± 30.00 | |
| Outside Sudan | 183(41.3%) | 40.00 ± 29.00 | |
| In which faculty do you study: | 0.044* | ||
| Education | 59(13.3%) | 38.00 ± 30.00 | |
| Agriculture | 12(2.7%) | 31.50 ± 43.75 | |
| Animal breeding | 11(2.5%) | 51.00 ± 11.00 | |
| Architecture | 17(3.8%) | 36.00 ± 19.50 | |
| Arts | 51(11.5%) | 43.00 ± 32.00 | |
| Dentistry | 28(6.3%) | 33.50 ± 34.25 | |
| Economic And Social Studies | 36(8.1) | 33.50 ± 39.50 | |
| Engineering | 63(14.2%) | 30.00 ± 21.00 | |
| English language and literature | 1(0.2%) | 22.00 ± 45.25 | |
| Geographical and Environmental sciences | 6(1.4%) | b | |
| Information Technology | b | b | |
| Law | 1(0.2%) | 48.00 ± 24.50 | |
|
Mathematical science and Informatics |
8(1.8%) | 42.50 ± 31.75 | |
| 6(1.4%) | 48.00 ± 26.00 | ||
| Medical Laboratory Sciences | 15(3.4%) | 35.00 ± 38.00 | |
| Medicine | 28(6.1%) | 17.50 ± 25.75 | |
| Nursing | 6(1.4%) | 33.00 ± 32.00 | |
| Pharmacy | 31(7.00) | 39.00 ± 16.00 | |
| Public and environmental health | 15(3.4%) | 36.00 ± 30.00 | |
| School of math | 7(1.6%) | 46.00 ± 33.25 | |
| Science | 16(3.6%) | 50.00 ± b | |
| The Forests | 3(0.7%) | 47.00 ± 41.00 | |
| Veterinary Medicine | 9(2.0%) | b | |
| Missing | 14(3.2%) | b | |
aMedian ± Interquartile range
bNot applicable
cMedian and interquartile ranges of scales alone regardless of the age
*P-value < 0.05
**P-value < 0.01
Almost 40% of the sample rarely participate in physical activities and only 11.3% practice daily activities. Almost 65% of participants didn’t have a support system or just preferred to deal with things independently. Less than a third of the participants (28.2%) were able to manage their time effectively.40% of the sample didn’t try relaxation techniques, but almost 42% got enough sleep and ate healthy to maintain physical health. Only 9.7 of the participants had sought professional help before with 21% of them didn’t know even where to find help (Further details in Table 2).
Table 2.
The lifestyle characteristic of the participants and the univariate analysis regarding full distress scales among the participants (N = 443)
| Characteristic | Frequency(%) | Full distress Scale | |
|---|---|---|---|
| M ± IQRa | P-value | ||
| How often do you engage in physical activity (eg exercise yoga)? | 0.094 | ||
| Daily | 50(11.3%) | 31.00 ± 19.75 | |
| Several times a week | 102(23.0%) | 37.50 ± 27.00 | |
| Occasionally | 120(27.1%) | 37.50 ± 31.00 | |
| Rarely | 171(38.6%) | 41.00 ± 31.00 | |
| Do you have a strong support system of friends and family? | 0.019* | ||
| I don't have anyone to talk to | 21(4.7%) | 49.00 ± 19.00 | |
| I have some people I can talk to | 190(42.9%) | 38.00 ± 28.00 | |
| I prefer to deal with things on my own | 96(21.7%) | 39.00 ± 28.50 | |
| Yes, I have a strong support system | 136(30.7%) | 33.00 ± 31.00 | |
| How well do you manage your time and prioritize tasks in your day? | 0.013* | ||
| I am very organized and manage my time effectively | 125(28.2%) | 36.00 ± 32.00 | |
| I don't pay much attention to time management | 56(12.6%) | 38.00 ± 23.25 | |
| I struggle with time management and prioritizing tasks | 165(37.2%) | 36.00 ± 31.00 | |
| I tend to procrastinate and feel overwhelmed with tasks | 97(21.9%) | 46.00 ± 28.00 | |
| Do you practice relaxation techniques such as deep breathing and meditation? | 0.580 | ||
| I have never tried relaxation techniques | 177(40.0%) | 38.00 ± 30.00 | |
| I have tried them but don't find them helpful | 68(15.3%) | 41.00 ± 27.00 | |
| I occasionally practice relaxation techniques | 139(31.4%) | 38.00 ± 31.00 | |
| Yes, I regularly practice relaxation techniques | 59(13.3%) | 37.00 ± 29.00 | |
| How well do you take care of your physical health through proper nutrition and adequate sleep? | 0.000** | ||
| I don't pay much attention to my diet and sleep habits | 114(25.7%) | 36.00 ± 29.25 | |
| I have poor eating habits and struggle with sleep issues | 65(14.7%) | 51.00 ± 23.50 | |
| I prioritize my physical health and make sure to eat well and get enough sleep | 79(17.8%) | 33.00 ± 28.00 | |
| I try to eat healthy and get enough sleep, but sometimes struggle | 185(41.8%) | 35.00 ± 30.50 | |
| Have you sought professional help or therapy to address your stress and depression? | 0.000** | ||
| I am not sure where to find help | 93(21.0%) | 36.00 ± 29.25 | |
| I don't feel the need for professional help | 206(46.5%) | 51.00 ± 23.50 | |
| I have considered seeking help but haven't done so yet | 101(22.8%) | 33.00 ± 28.00 | |
| Yes, I have sought professional help and therapy | 43(9.7%) | 35.00 ± 30.50 | |
aMedian ± Interquartile range
*P-value < 0.05
**P-value < 0.01
Factors affecting depression, anxiety, stress and full distress scales
The full distress scale was found to cause significant differences across categories of gender, faculty, having a support system, management of time and tasks, taking care of physical health and treatment-seeking behaviour (p-value = 0.000,0.044,0.019,0.013,0.000 and 0.000 respectively) (Further details in Tables 1, 2).
Females were found to have significantly higher medians in depression scale (Median = 14.00, p-value = 0.001), anxiety scale (Median = 12.50, p-value = 0.000), stress scale (Median = 14.00, p-value = 0.001) compared to males. Students in the faculty of the forest had significantly higher medians on the depression scale (Median = 18, p-value = 0.010) while animal breeding faculty students had significantly higher medians on the anxiety scale (Median = 18, p-value = 0.042) compared to other faculties students (Further details in Table 3).
Table 3.
Univariate analysis for socio-demographic variables regarding depression, anxiety and stress scales among the participants (N = 443)
| Characteristic | Depression Scale | Anxiety Scale | Stress Scale | |||
|---|---|---|---|---|---|---|
| M ± IQRa | P-value | M ± IQRa | P-value | M ± IQRa | P-value | |
| Age | 13.00 ± 10.75c | 12.00 ± 12.00c | 13.00 ± 10.00c | |||
| Gender: | 0.001** | 0.000** | 0.001** | |||
| Male | 10.00 ± 10.00 | 9.00 ± 10.75 | 11.00 ± 9.00 | |||
| Female | 14.00 ± 10.00 | 12.50 ± 12.00 | 14.00 ± 10.00 | |||
| Marital Status: | 0.657 | 0.195 | 0.314 | |||
| Single | 13.00 ± 10.00 | 12.00 ± 12.00 | 13.00 ± 10.00 | |||
| Married | 14.50 ± 13.50 | 16.50 ± 11.25 | 15.50 ± 10.75 | |||
| Residency: | 0.091 | 0.243 | 0.023* | |||
| Inside Sudan | 12.00 ± 11.00 | 12.00 ± 11.00 | 12.00 ± 10.00 | |||
| Outside Sudan | 14.00 ± 10.00 | 12.00 ± 11.00 | 14.00 ± 10.00 | |||
| In which faculty do you study: | 0.010* | 0.042* | 0.298 | |||
| Education | 14.00 ± 8.00 | 12.00 ± 12.00 | 13.00 ± 10.00 | |||
| Agriculture | 10.00 ± 15.75 | 12.00 ± 16.00 | 10.50 ± 13.75 | |||
| Animal breeding | 17.00 ± 8.00 | 18.00 ± 11.00 | 15.00 ± 7.00 | |||
| Architecture | 13.00 ± 8.00 | 11.00 ± 8.00 | 13.00 ± 8.50 | |||
| Arts | 15.00 ± 11.00 | 14.00 ± 10.00 | 14.00 ± 12.00 | |||
| Dentistry | 12.00 ± 13.50 | 10.00 ± 15.25 | 11.00 ± 10.25 | |||
| Economic And Social Studies | 12.00 ± 11.75 | 11.00 ± 11.00 | 12.00 ± 15.75 | |||
| Engineering | 10.00 ± 8.0 | 9.00 ± 8.00 | 11.00 ± 8.00 | |||
| English language and literature | 8.00 ± 17.75 | 7.50 ± 13.25 | 6.50 ± 13.75 | |||
| Geographical and Environmental sciences | b | b | b | |||
| Information Technology | b | b | b | |||
| Law | 16.00 ± 10.50 | 15.50 ± 12.25 | 15.50 ± 8.50 | |||
| Mathematical science and Informatics | 12.50 ± 11.50 | 10.50 ± 14.00 | 17.00 ± 14.50 | |||
| Medical Laboratory Sciences | 16.00 ± 4.00 | 14.00 ± 13.00 | 16.00 ± 8.00 | |||
| Medicine | 12.50 ± 15.00 | 7.50 ± 13.75 | 11.50 ± 11.75 | |||
| Nursing | 5.50 ± 9.50 | 6.00 ± 6.50 | 6.00 ± 11.25 | |||
| Pharmacy | 9.00 ± 12.00 | 12.00 ± 14.00 | 14.00 ± 12.00 | |||
| Public and environmental health | 13.00 ± 8.00 | 13.00 ± 5.00 | 11.00 ± 6.00 | |||
| School of math | 14.00 ± 12.00 | 11.00 ± 10.00 | 14.00 ± 11.00 | |||
| Science | 16.00 ± 8.75 | 12.50 ± 11.25 | 15.50 ± 9.50 | |||
| The Forests | 16.00 ± b | 19.00 ± b | 15.00±b | |||
| Veterinary Medicine | 18.00 ± 9.50 | 13.00 ± 15.50 | 16.00 ± 15.00 | |||
| Missing | b | b | b | |||
aMedian ± Interquartile range
bNot applicable
cMedian and interquartile ranges of scales alone regardless of age
*P-value < 0.05
**P-value < 0.01
Regarding lifestyle, students who rarely perform physical activities were found to have significantly higher medians on the depression scale (Median = 14, p-value = 0.000) and stress scale (Median = 14, p-value = 0.029) compared to those who performed more physical activities. Students with no one as their support system had significantly higher medians in depression scale (Median = 16, p-value = 0.017) and stress scale (Median = 17, p-value = 0.024) compared to students with support systems. Moreover, Students who tend to procrastinate their tasks had significantly higher medians in the depression scale (Median = 15, p-value = 0.011) and stress scale (Median = 15, p-value = 0.000) compared to students with good management skills. Students with poor eating habits had also significantly higher medians across depression, stress and anxiety scales (Median = 17, p-value = 0.000 for all scales) compared to students who put more effort into their physical health. Students who didn’t feel the need for professional help had significantly higher medians across the depression scale, anxiety scale and stress scale (Median = 17, p-value = 0.000 for all scales) compared to other forms of treatment-seeking behaviour (Further details in Table 4).
Table 4.
Univariate analysis for lifestyle activities regarding depression, anxiety and stress scales among the participants (N = 443)
| Characteristic | Depression Scale | Anxiety Scale | Stress Scale | |||
|---|---|---|---|---|---|---|
| M ± IQRa | P-value | M ± IQRa | P-value | M ± IQRa | P-value | |
| How often do you engage in physical activity (eg exercise yoga)? | 0.333 | 0.215 | 0.029* | |||
| Daily | 11.00 ± 8.25 | 10.00 ± 9.50 | 10.00 ± 7.50 | |||
| Several times a week | 13.00 ± 9.00 | 12.00 ± 9.25 | 12.50 ± 8.00 | |||
| Occasionally | 13.00 ± 12.00 | 11.00 ± 13.75 | 13.00 ± 10.00 | |||
| Rarely | 14.00 ± 11.00 | 12.00 ± 13.00 | 14.00 ± 12.00 | |||
| Do you have a strong support system of friends and family? | 0.017* | 0.056 | 0.024* | |||
| I don't have anyone to talk to | 16.00 ± 7.00 | 16.00 ± 6.50 | 17.00 ± 9.00 | |||
| I have some people I can talk to | 13.00 ± 9.00 | 12.00 ± 12.00 | 13.00 ± 9.00 | |||
| I prefer to deal with things on my own | 13.00 ± 10.00 | 11.00 ± 10.75 | 13.50 ± 11.75 | |||
| Yes, I have a strong support system | 11.00 ± 11.00 | 11.00 ± 11.75 | 11.00 ± 10.00 | |||
| How well do you manage your time and prioritize tasks in your day? | 0.011* | 0.241 | 0.000** | |||
| I am very organized and manage my time effectively | 12.00 ± 10.00 | 11.00 ± 12.00 | 11.00 ± 10.50 | |||
| I don't pay much attention to time management | 14.00 ± 8.00 | 11.00 ± 9.50 | 12.00 ± 8.75 | |||
| I struggle with time management and prioritizing tasks | 13.00 ± 11.00 | 12.00 ± 10.00 | 12.00 ± 9.50 | |||
| I tend to procrastinate and feel overwhelmed with tasks | 15.00 ± 10.00 | 13.00 ± 13.00 | 15.00 ± 10.00 | |||
| Do you practice relaxation techniques such as deep breathing and meditation? | 0.759 | 0.318 | 0.118 | |||
| I have never tried relaxation techniques | 13.00 ± 10.00 | 11.00 ± 11.00 | 13.00 ± 10.50 | |||
| I have tried them but don't find them helpful | 13.50 ± 8.00 | 11.00 ± 13.75 | 14.50 ± 9.50 | |||
| I occasionally practice relaxation techniques | 13.00 ± 11.0 | 12.00 ± 10.00 | 13.00 ± 11.00 | |||
| Yes, I regularly practice relaxation techniques | 14.00 ± 9.00 | 12.00 ± 11.00 | 11.00 ± 7.00 | |||
| How well do you take care of your physical health through proper nutrition and adequate sleep? | 0.000** | 0.000** | 0.000** | |||
| I don't pay much attention to my diet and sleep habits | 14.00 ± 10.25 | 10.00 ± 9.25 | 12.00 ± 10.25 | |||
| I have poor eating habits and struggle with sleep issues | 17.00 ± 9.50 | 17.00 ± 11.00 | 17.00 ± 11.50 | |||
| I prioritize my physical health and make sure to eat well and get enough sleep | 11.00 ± 11.00 | 11.00 ± 11.00 | 10.00 ± 8.00 | |||
| I try to eat healthy and get enough sleep, but sometimes struggle | 12.00 ± 1.00 | 11.00 ± 11.50 | 13.00 ± 10.00 | |||
| Have you sought professional help or therapy to address your stress and depression? | 0.000** | 0.000** | 0.000** | |||
| I am not sure where to find help | 14.00 ± 10.25 | 10.00 ± 9.25 | 12.00 ± 10.25 | |||
| I don't feel the need for professional help | 17.00 ± 9.50 | 17.00 ± 11.00 | 17.00 ± 11.50 | |||
| I have considered seeking help but haven't done so yet | 11.00 ± 11.00 | 11.00 ± 11.00 | 10.00 ± 8.00 | |||
| Yes, I have sought professional help and therapy | 12.00 ± 10.00 | 11.00 ± 11.50 | 13.00 ± 10.00 | |||
aMedian ± Interquartile range
bNot applicable
cMedian and interquartile ranges of scales alone regardless of age
*P-value < 0.05
**P-value < 0.01
Regression model for distress scale
Multiple socio-demographic factors have been plotted against the full distress scale as dependent variables using multiple linear regression. The variables used were: age, gender, residency, faculty, engaging in physical activity, having a support system, management of time and tasks, taking care of physical health and seeking professional help. The model was statistically significant (p-value < 0.001) with an adjusted R squire of 0.075. Only gender and management of time/tasks were found to be significantly affecting the distress scale in the model (p-value = 0.0.001 and 0.022 respectively) (Further details in Table 5).
Table 5.
Multiple regression analysis of socio-demographic and lifestyle characteristics regarding full distress scale as dependent variable (N = 443)
| Variables | Unstandardized Coefficients | Standardized Coefficients | t | P-value | 95.0% Confidence Interval for B | ||
|---|---|---|---|---|---|---|---|
| B | Std. Error | Beta | Lower Bound | Upper Bound | |||
| (Constant) | 2.586 | 11.162 | .232 | .817 | −19.355 | 24.528 | |
| age | .744 | .406 | .089 | 1.831 | .068 | -.055 | 1.543 |
| Gender | 7.356 | 2.138 | .171 | 3.441 | .001** | 3.154 | 11.558 |
| Residency | 2.293 | 1.913 | .057 | 1.199 | .231 | −1.468 | 6.054 |
| Faculty | -.102 | .128 | -.038 | -.795 | .427 | -.354 | .150 |
| How often do you engage in physical activity (eg exercise yoga)? | 1.176 | .928 | .061 | 1.267 | .206 | -.648 | 2.999 |
| Do you have a strong support system of friends and family? | −1.526 | 1.015 | -.073 | −1.504 | .133 | −3.521 | .468 |
| How well do you manage your time and prioritize tasks in your day? | 1.986 | .864 | .113 | 2.299 | .022* | .288 | 3.684 |
| How well do you take care of your physical health through proper nutrition and adequate sleep? | −1.331 | .765 | -.084 | −1.741 | .082 | −2.835 | .172 |
| Have you sought professional help or therapy to address your stress and depression? | 2.114 | 1.084 | .094 | 1.951 | .052 | -.016 | 4.244 |
| a. Dependent Variable: Full Distress Scale | |||||||
*P-value < 0.05
**P-value < 0.01
Discussion
This study is among the first to examine anxiety, stress, and depression in Khartoum University students residing in Sudan's war-affected areas. The study discovered a high relationship between stress, anxiety, and general discomfort levels and sociodemographic variables.
Psychological distress level was the main area of interest in this study. Higher levels of distress were shown among those with fewer physical activities and support networks and those who were unaware of the importance of professional help. These results are consistent with those of related studies, including research conducted in Northern Ethiopia and on the Inter-Taliban generation in Northern Afghanistan [16, 17]. Also, a higher level of distress is shown among students from the faculty of Forestry and Animal Feeding. This may be due to the specific stressors in such faculties. Moreover, this study shows that females remarkably had higher distress scales. This result is consistent with a study that found females tend to have two times higher risk for getting depression and anxiety compared to males. However, no difference was reported in terms of stress [18].
Another significant factor reflected by this study is the unusual practice of physical exercises among students. Only 11.3% of participants said they participate in these activities daily, and almost 40% said they do so occasionally. This lack of activity is linked with higher depression and stress scales. This finding is consistent with a study that showed exercise to have a dose–response negative correlation with all markers of mental health disorders; the greatest odds ratios were seen for the frequency of physical activity; for example, women who never exercised had about three times the odds of self-reported depression and of scoring higher than women who exercised nearly daily. For men, the correlations were even more significant [19]. Physical activities are a well-known method of lowering stress and anxiety; their low level among students highlights the significant challenges that those students face in conflict areas. This may be due to restricted access to safe areas or low awareness about the benefits of exercise.
Also, the lack of a support system further increases mental health challenges, as shown in this study. Nearly 65% of participants said that they lacked support networks or preferred to deal with difficulties by themselves, and this factor was found to be associated with higher stress and depression. This finding was supported by a study that showed participants who lack an adequate support system have a 1.90 times higher risk of getting depression, as low social support can expand feelings of loneliness and worsen the depression course [17].
Additionally, this study showed a decrease in professional help-seeking behaviour, with only 9.7% of participants had sought help before and nearly 21% of participants unaware of where to seek help. This finding is in line with a similar study that reported a small number of students, 123 (19%), tended to seek mental care in contrast to 454 (71%) who didn't. Stigma, lack of awareness, and limited service are significant barriers to seeking mental care [14].
Another critical factor that affects the mental health of students is poor time management; the result shows less than 28.2% manage their time effectively. Those students who tended to procrastinate their tasks had significantly higher depression and stress scales compared to students with good management skills. This figure is consistent with a study that revealed a negative association between students' time management skills and test anxiety [20]. The regression model identified this to be an important factor in stress and anxiety (Fig. 1).
These challenges are exacerbated by inadequate mental health treatments in Sudan, and because mental health is not given enough priority and resources are scarce. There was limited coordination among centers and a lack of mental health services before and throughout the conflicts [8]. For instance, the Sudanese Psychiatrists Association (2006) documented insufficient coverage of mental health care, particularly outside of Khartoum, where there were few resources and stigma associated with mental illness, which caused patients to seek treatment only later in their disease [8].
This ongoing conflict left many students without support. Displacement, death, and trauma have maximized psychological distress, comparable to the Darfur study, which reveals that 54% of individuals experienced displacement, material loss, and psychological suffering [21]. A comparable finding in South Sudan indicates that worse physical and mental health was linked to more traumatic experiences [22]. Furthermore, stigma, mistrust of psychiatric systems, inadequate training for primary health caregivers, and disruptions of pharmaceutical supplies have increased the gap in detecting and treating mental health conditions despite their high prevalence [23].
In areas affected by violence, there is an immediate need to increase and enhance mental health services. We suggest adding physical activity into mental health programs, for instance, by providing safe places to be practical and attainable methods to improve overall well-being. Additionally, we propose community-based, peer support programs to make students more reliant on challenges in conflict areas. Time management workshops can be introduced to help students deal with difficulties and academic obligations more effectively, which would lower stress and increase output. Furthermore, counselling workshops specific to each faculty may be a crucial solution. Finally, setting up mobile mental health units, especially in areas with limited mental health facilities, can promote treatment-seeking behaviour and raise awareness of mental health issues. These interventions align with WHO's Mental Health Gap Action Program (mhGAP-IG), which provides clinical recommendations for evidence-based treatment [24].
In conclusion, while several studies have examined the mental health of students in conflict zones, this study uniquely addresses the impact of war on university students in Sudan, a context that has been underrepresented in the existing literature. The findings provide crucial insights for mental health interventions for Sudanese university students and in regions experiencing ongoing conflict, offering potential applications to similar settings across Africa and beyond. Future investigation and long-term studies are required to better understand the impact of the Sudanese war on different populations.
Conclusion
This study demonstrates that undergraduate students at the University of Khartoum who live in war-afflicted areas frequently experience anxiety, stress, and depression. These findings are related to the difficult circumstances and displacement that these students face. Notably, females make up the bulk of impacted students, with 65% lacking a support network. These results shed light on the importance of mental health issues. Especially during difficult situations like the war in Sudan.
Further examination of sociodemographic variables could provide more focused interventions; for example, gender-specific mental health programs might benefit female students. Mental health groups, psychologists, and public health policymakers need to develop strategies and plans. All people in war-afflicted areas must have easy and affordable access to psychological counselling and mental health services through community-based programs, support networks, and interventional initiatives. Mandatory mental health training for university staff should be part of policy initiatives so they can identify and address signs of distress among students early.
These interventions can play a critical role in mitigating the psychological impact of prolonged exposure to conflict and improving the well-being of students in similar contexts globally.
The study aims to raise awareness of this issue to improve the mental health of such populations and empower students to cope successfully in areas affected by conflict by practicing self-care and finding social support. The study acknowledged limitations including measurement problems, sample representativeness, and possible mistakes. Therefore, we recommend that future studies examine the long-term impacts of trauma caused by war on the academic achievement and career trajectories of students from conflict zones.
Strength of the study
Despite the challenges of carrying out research in conflict-affected settings, this study demonstrates that it was possible to conduct a community survey under very difficult circumstances.
Limitation
There are several limitations to this study. Firstly, the study is limited to undergraduate Khartoum University students; other population sectors were not studied. Secondly, it is a cross-sectional study that focuses only on a snapshot of the student’s mental health at one point in time; thirdly, we miss adding two questions in our questionnaire; fourthly, we are not 100% sure about the population in each college; fifthly, measurement problems, sample representativeness, and possible mistakes.
Supplementary Information
Acknowledgements
We would like to acknowledge the support and contributions of Roaa Omer, Ammar Tarig, and the following collaborators*: Leen Abdulaziz Mohammed Abdulmoniem, Nazik Hamid Osman Hummad, Walaa Abdelaziz Tageldin Elbashir, Dania Adil Abdalfattah Ahmad, and Shahd Esam Alden Osman.
Informed consent
Informed consent was taken from all of the participants. Anonymity of data and confidentiality were ensured throughout the study.
Clinical trial number
Not applicable.
Authors’ contributions
H.S.: Proposal writing, literature review, data collection, report writing, monitoring; S.I.: Data collection monitoring; M.A: Report writing; M.E: Analysis and interpretation of data, report writing; L.O: data collection and review of the report; M.M: data collection and review of the report.
Funding
The authors received no funding for this study.
Data availability
All Data used for this research will be made available upon reasonable request to the corresponding author.
Declarations
Ethics approval and consent to participate
The consent was obtained through a clear opt-in process, where participants were asked if they agreed to participate before filling out the questionnaire.
The study was administered among undergraduate students from the same university without any intervention.
The data collected is anonymous, and no personally identifiable information was recorded. Since the study involves minimal risk to participants and adheres to standard ethical guidelines for informed consent, including the Declaration of Helsinki. We have determined that formal ethical approval is not required.
Consent for publication
All participants in the study gave consent for the publishing of the manuscript.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Mohamed H. Elbadawi, Email: mohamed.h.elbadawi@gmail.com
Group of collaborators:
Leen Abdulaziz Mohammed Abdulmoniem, Nazik Hamid Osman Hummad, Walaa Abdelaziz Tageldin Elbashir, Dania Adil Abdalfattah Ahmad, and Shahd Esam Alden Osman
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Supplementary Materials
Data Availability Statement
All Data used for this research will be made available upon reasonable request to the corresponding author.