Quality in Primary Care Open Access

The Role of Social Support and Dysfunctional Attitude to Determine the Level of Mental Distress among Student in War Area: A Cross- Section Survey Study

Tewodros Hailu^* Department of Psychology, University of Gondar, Gondar, Ethiopia
^*Correspondence: Tewodros Hailu, Department of Psychology, University of Gondar, Gondar, Ethiopia, Email:

Received: 07-Mar-2023, Manuscript No. IPQPC-23-15892; Editor assigned: 20-Mar-2023, Pre QC No. IPQPC-23-15892 (PQ); Reviewed: 03-Apr-2023, QC No. IPQPC-23-15892; Revised: 17-May-2023, Manuscript No. IPQPC-23-15892 (R); Published: 24-May-2023, DOI: 10.36648/1479-1064.23.31.025

Introduction

University students have a significantly higher mental health burden than the general population. According to studies conducted on university students, the most common presenting symptoms among students are depression, anxiety, and stress, with prevalence rates ranging from 39.0% to 80.7%, 23.8% to 98.4 %, and 35.8% to 80.3%, respectively. In Ethiopia, 37.73 percent of university students suffer from common mental disorders, with depression and anxiety being particularly frequent. These emotional distresses are found to negatively align with student functioning.

Early identification and treatment can help students manage the detrimental effects of mental health problems. According to Keyes, et al., students with mental health problems perform poorly in academic activities and exhibit suicidal behavior. Class absenteeism and college dropout are also strongly associated with student mental distress. Moreover, there is a possibility that students' mental health problems will linger throughout their lives, according to Williams-McCorvey A, as a result, maintaining students' mental health is critical for their future success. To provide effective support to students, it is vital to first identify the factors that contribute to their mental distress [1-5].

There are several contributing factors to students' distress, including academic-related factors, psychological factors such as self-esteem and self-confidence, and previous mental health diagnosis and biological factors such as age, gender, and physical disabilities. Furthermore, acute health crises including pandemics, as well as social crises such as war and conflict, are expected to intensify the burden of mental health among students.

As a result, in Ethiopia, incidents such as the COVID-19 epidemic have disturbed university students' everyday life. For instance, public health measures such as lockdowns have forced students to stay at home and attend classes remotely which further compounded problems related to online education platforms. As a consequence, students are forced to remain secluded from college, friends, and academic activities, which have a significant detrimental influence on student mental health. When universities are reopened, the ongoing war in the northern region of Ethiopia led to serious concerns of safety and security issues among university students and their families. Despite the safety concerns, students rejoined universities to continue their education. In light of this, it is expected that, when combined with other academic related factors, these crises will increase the prevalence of mental disorders among first year students at the university of Gondar, because of the institution's proximity to the war area in the north region. It is well established that war and armed conflict have an impact on those who are directly or indirectly exposed to adversity. People who are directly exposed to war face variety of problems, including forced recruitment, injury, family loss, property damage, and displacement, all of which can lead to serious mental health problems such as post-traumatic stress disorder, anxiety, and depression. Although the majority of students who joined the university may not be directly affected by the war, everyday war-related stressors such as a sense of insecurity, family separation, and war related news can have a profound impact on the mental health of students, as suggested by researchers.

Moreover, war is among the major life stressors that lead to dysfunctional attitudes. Dysfunctional attitude refers to having a negative attitude toward self, the world, and the future. A higher prevalence of a range of psychological disorders was found among individuals with dysfunctional attitudes. Studies showed a positive correlation between dysfunctional attitudes and mental distress. In contrast, social support was found to play a protective role during social crises. Various studies also indicated a negative correlation between social support, and depression, anxiety, and stress. But these findings are not conclusive and still little is known about the prevalence of mental health distress among students experiencing severe forms of social crisis such as war. Therefore, the current study aimed to investigate the prevalence of mental distress among freshman students and assess the predictive role of social support and dysfunctional attitude and other factors such as sleep and appetite problems, fear of exams and poor grades, excessive internet use, and previous diagnosis. Based on the findings, recommendations are provided to assist students in coping with the mental health challenge and performing to their full potential [6-10].

Materials and Methods

Study Design

An institution based cross-sectional survey study was conducted among first year undergraduate students at the university of Gondar. Among 3,500 incoming students in the 2021 academic year, 366 participated in this research.

Sample Size and Sampling Technique

To determine the sample size, a single population proportion formula was used, where; n1=Zα/22*p*(1-p)/Moe 2, and Zα/2 is the critical value of the normal distribution for a confidence level of 95%, α is 0.05 with a critical value of 1.96, Moe is the margin of error=0.05 (5%), p=52% prevalence of anxiety among university of Gondar students. Because the total population was less than ten thousand, the finite population correction formula was used to get the desired sample size. Consequently, 333 became the desired sample size, and by adding 10% of the non-response rate, the total sample became 366. To enroll the students, a multistage sampling technique was used, the total sample size was proportionally distributed to each campus based on the number of sections, and thereafter participants of the study were selected using simple random sampling. During data checking and cleaning, some questionnaires were discarded for non-response, thus 335 students' data was analyzed and interpreted [11-15].

Data Collect on Tool and Procedure

Data were collected by using a self-administered questionnaire that comprises socio-demographic information, associated factors, and standardized scales, i.e., depression, anxiety, and stress scale-21, dysfunctional attitude scale, and social support questionnaire. The Depression, Anxiety, and Stress Scale (DASS-21) are a self-report tool designed to measure the emotional states of depression, anxiety, and stress over the last week. The scale contains 21 items, and the three sub scales have seven items each. The depression sub-scale contains questions that measure dysphoria, hopelessness, devaluation of life, self-deprecation, lack of interest, and anhedonia. The anxiety sub-scale is intended to assess autonomic arousal, skeletal muscle effects, situational anxiety, and the subjective experience of anxious affect. Additionally, the stress scale assesses difficulty relaxing, nervous arousal, being easily upset, and irritable. The response option ranges from 0 (did not apply to me) to 3 (applied to me very much or most of the time). The score is calculated by adding the scores of items in each sub-scale and multiplying by 2, where the subscale score ranges from 0 to 42 and the total score ranges from 0 to 120. Different studies have validated and checked the reliability of the DASS-21. For instance, Vignola and Tucci, reported good internal consistency with 0.95 Cronbach's alpha for each sub-scale, i.e., 0.92 for depression, 0.90 for stress, and 0.86 for anxiety.

The short version of the dysfunctional attitude scale was used to assess the contribution of negative cognition to student mental distress. The short version of the DAS scale contains nine items with four response formats; 1 (totally agree), 2 (agree), 3 (disagree), and 4 (totally disagree). A higher item's total score reflects greater dysfunctional attitudes. These short forms were found to be highly correlated with the original 40-item DAS-A (α ranged from 91 to.93).

Regarding social support, the Multidimensional Scale for Perceived Social Support (MSPSS) is used. The scale is a brief questionnaire designed to measure perceptions of receiving support from family, friends, and significant others. It contains a total of 12 items, with 4 items for each sub-scale, and the response format ranged from 1 (very strongly disagree) to 7 (very strongly agree). To compute the score, add the scores of all 12 items and then divide by 12, and if the mean scale score ranging from 1 to 2.9 could be considered low support, a score of 3 to 5 could be considered moderate support, and a score from 5.1 to 7 could be considered high support. Various studies have indicated that the MSPSS has good internal consistency and test-retest reliability, good validity, and a fairly stable factorial structure.

Data Analysis

The datasets were checked for completeness and coded prior to the analysis. Data were analyzed through a Statistical Package for Social Science version 26 (SPSS). A descriptive analysis was performed to show the gender distribution of the sample and the levels of depression, anxiety, stress, and social support across genders. An independent sample t-test was performed to determine the mean difference between male and female students across the disorders and the level of social support and dysfunctional attitude. Additionally, multiple linear regression analysis was conducted to examine the predictive ability of the independent variables and to identify the strongest variable in explaining the variation in depression, anxiety, and stress among students. Consequently, a variable with a p-value of less than 0.05 and 0.01 was considered a significant predictor, and a beta coefficient with 95% CI was calculated to determine the strength of association.

Results

Among the 335 students who participated in this research, 56.4% (189) of them were males and the remaining 43.6% (146) were females. The mean age was 19.93. (SD: 1.28). A total of 10.1% of students were previously diagnosed with mental illness. When 28.7% of the students have a poor appetite, 34% have sleep problems. Similarly, 54.3% and 69.6% of the students, respectively, expressed fear of exams and fear of poor grades. However, only 37.9% of the students reported to use the internet excessively. With respect to the prevalence of mental health problems, the descriptive statistics showed a high prevalence of depression (72.8%), anxiety (69.3%), and stress (57.3%). As a result, 30% of students reported severe depression, 21.5% reported moderate depression, and 20.9% reported mild depression. In addition, 42.5% of the students experienced severe anxiety, 20.2% indicated moderate anxiety, and 6.5% indicated mild anxiety. Regarding the magnitude of stress, approximately 10% of students reported severe stress, 23.5% moderate stress, and 23.4% mild anxiety. The prevalence of depression (M=7.31, SD=3.97) and anxiety (M=6.78, SD=4.19) was slightly higher among male students compared to female students' scores for depression (M=7.74, SD=4.34) and anxiety (M=6.64, SD=4.38). However, female students reported a higher level of stress with M=8.56, SD=4.34, compared to male students with M=7.91, SD=3.67 (Table 1).

Table 1: Prevalence and level of depression, anxiety and stress across gender.

Concerning social support, the survey found that 24.5% of students received high social support, while 50.4% reported receiving moderate social support; the remaining 25.1% reported receiving low social support. Students reported receiving the highest support from their families (M=17.81, SD=6.69). Female students received more social support (M=50.77, SD=17.90) than male students (M=47.46, SD=14.72). A significant mean difference in the level of social support received from friends was found between males (M=14.97, SD=4.90) and females (M=17, SD=5.77; t (22)=-2.02646, p=.001, d=-0.376). Nonetheless, there is no statistically significant difference between the sexes when it comes to receiving support from family or significant others.

On other hands, 67% of the students reported a high level of dysfunctional attitudes, but there is no statistically significant mean difference between male and female students with dysfunctional attitudes (Table 2).

Table 2: Social support and dysfunctional attitude and their distribution across gender.

The multiple regression analysis revealed that fear of poor grades, excessive internet use, appetite problems, sleep problem, and previous mental disorder diagnosis together significantly explained 10.4% of the variance with small effect size in the incidence of depression, anxiety, and stress among firs year students (R²=.105, F=.626, P<0.05, f²=0.12). Sleep problem is found to be the strongest predictor for depression (β=.258, t=4.866, p<0.05), anxiety (β=.135, t=2.491, p<0.05) and stress (β=.221, t=4.144, p<0.05), and apatite problem is the second factor to strongly predict the variation in depression (β=.195, t=3.631, p<0.05), anxiety (β=.132, t=2.439, p<0.05) and stress (β=.186, t=3.462, p<0.05). Whereas, previous mental disorder diagnosis significantly predicted depression and anxiety with β=.146, t=2.700, p<0.05 and β=.114, t=2.103, p<0.05 respectively. And students fear of poor grade significantly predicted depression (β=.120, t=2.202, p<0.05) and anxiety (β=.121, t=2.226, p<0.05). Excessive internet use predicted students anxiety with β=.178, t=3.295, p<0.05 (Table 3).

Table 3: The predictive role of associated factors across diagnosis.

The results of multiple regression also indicated that social support and dysfunctional attitudes significantly predicted depression, anxiety, and stress among students. The regression showed that the two predictors explained 20% of the variance in depression (adj. R²=.210, F=43.729, p<.05), 14% of the variance in anxiety (adj. R²=.139, F=26.946, p<.05) and 8% of the variance in stress (adj. R²=.072, F=13.379, p<. 05). In this study, social support is found to be the stronger predictor of mental distress, in which depression level increases by 41% when students receive low social support (β=-.406, t=-8.279, p<0.05). Similarly, low social support increases the incidence of anxiety and stress by 36%. On the other hand, dysfunctional attitude predicts the occurrence of depression by 18 % (β=.179, t=3.647, p<0.05) and stress by 14 % (β=.135, t=2.555, p<0.05). However, the association between student anxiety and dysfunctional attitudes is not statistically significant, with only 9% of the variance in anxiety explained by dysfunctional attitudes (Table 4).

Table 4: The predictive role of dysfunctional attitude and social support across diagnosis.

Discussion

The study aimed to assess the prevalence of depression, anxiety, and stress among first year students. A high prevalence rate of depression, anxiety, and stress was reported, with 72.8% experiencing moderate to severe levels of depression, and approximately 69.3% and 57.3% reporting moderate to severe levels of anxiety and stress, respectively. And 28% of students reported extremely severe levels of anxiety, followed by 7% and 1.6% of extremely severe levels of depression and stress. This figure falls within the prevalence rates reported across different studies in a similar population. Accordingly, compared to the finding of the current study, a higher prevalence rate of depression, anxiety, and stress was found among students from Uganda, Bangladesh, and Malaysia. In contrast, research conducted in Ethiopia reported a lower incidence of the disorders among university students. The high prevalence rate of depression, anxiety, and stress reported in this study can be explained by the ongoing war conflict in the university area, which can increase the burden of mental distress among students, as other research suggests.

Though there is no statistically significant difference in depression, anxiety, and stress across gender, the mean score of male students in depression and anxiety is slightly higher. This might be due to the instance that male students receive a lower-level of social support. However, consistence with previous research female students reported a higher level of stress compared to their counterparts.

Among the associated factors, sleep and appetite problems were found to be the strongest predictors of mental distress among the students. While previous mental disorder diagnosis and fear of poor grades significantly correlated with depression and anxiety, excessive internet use only predicted anxiety levels among students. Similarly, the research of Fauzi, et al., revealed that low sleep quality and fear of poor grade significantly correlates with psychological distress. Research conducted by Alfian, et al., found a strong predictive role of sleep problems on mental health variation among Indonesian students. Regarding excessive internet use and its role in influencing students' mental health, recent studies indicated a significant correlation between excessive internet use and depression and anxiety. In this study, students reported receiving high levels of social support, with friends providing the most support, and females revealing a greater predisposition to seek support from friends. Similarly, a study by Spitz, found that as adolescents grow older, they relied more on friend support rather than family support, and this tendency is higher among females [16-20].

Comparing to dysfunctional attitude, social support was found to be a stronger predictor of all types of mental distress, with higher levels of social support predicting lower levels of depression, anxiety, and stress among students. Similar findings were reported by the research conducted on university students. However, only depression and stress were substantially correlated with dysfunctional attitude. The findings also suggested that the level of social support explained more of the students' depression than the dysfunctional attitude, which might be attributable to the depression level not being clinical, as reported by Horiuchi, et al. Alternatively, studies suggested that a lack of social support promotes feelings of alienation, loneliness, and depression, whereas adequate support fosters resilience and reduces the prevalence of psychological disorders such as depression.

Conclusion

First year students report high levels of depression, anxiety, and stress, indicating the need for an intervention plan to assist students in managing their psychological distress and becoming successful in their academic lives. The study also identified factors associated with students' mental distress, such as a fear of poor grades, sleep and appetite problems, a previous diagnosis of a mental disorder, and excessive internet use. The level of social support received was found to highly predict depression, anxiety, and stress among university students, indicating that the intervention offered to students should focus on expanding students' social networks and access to social support.

Ethical Consideration

Ethical clearance was received from department of psychology, university of Gondar. A written consent was taken from students who participated in the survey, and to maintain privacy and confidentiality, identifier question are not included in the questionnaire.

Acknowledgment

I would like to express my sincere gratitude to the students who voluntarily participated in this study. I would also like to thank the teachers for their cooperation during data collection.

References

1. Alfian SD, Ng H, Destiani DP, Abdulah R (2018) Psychological distress induces poor sleep quality: A cross-sectional study of pharmacy students in Bandung city, Indonesia. Open Public Health J. 11(1):369–375.

   [Crossref] [Google Scholar]

2. Alsubaie MM, Stain HJ, Webster LAD, Wadman R (2019) The role of sources of social support on depression and quality of life for university students. Int J Adolesc Youth, 24(4):484–496.

   [Crossref] [Google Scholar]

3. Arsandaux J, Montagni I, Macalli M, Texier N, Pouriel M, et al. (2021) Mental health condition of college students compared to non-students during COVID-19 lockdown: The CONFINS study. BMJ Open. 11(8):e053231.

   [Crossref] [Google Scholar] [PubMed]

4. Beck AT, Haigh EAP (2014) Advances in cognitive theory and therapy: The Generic Cognitive Model. Annu Rev Clin Psychol. 10(1):1–24.

   [Crossref] [Google Scholar] [PubMed]

5. Beevers CG, Strong DR, Meyer B, Pilkonis PA, Miller IW (2007) Efficiently assessing negative cognition in depression: An item response theory analysis of the dysfunctional attitude scale. Psychol Assess. 19(2):199–209.

   [Crossref] [Google Scholar] [PubMed]

6. Bibi A (2020) Dysfunctional attitudes and automatic thoughts among university students of Pakistan. Open access J Complement Altern Med, 2(4):1-7.

   [Crossref] [Google Scholar]

7. Boyraz G, Granda R, Baker CN, Tidwell LL, Waits JB (2016) Posttraumatic stress, effort regulation, and academic outcomes among college students: A longitudinal study. J Couns Psychol. 63(4):475–486.

   [Crossref] [Google Scholar] [PubMed]

8. Bum C, Jeon I (2016) Structural relationships between students' social support and self- esteem, depression, and happiness. Soc Behav Pers int J. 44(11):1761-1774.

   [Crossref] [Google Scholar]

9. Chernomas WM, Shapiro C (2013) Stress, depression, and anxiety among undergraduate nursing students. Int J Nurs Educ Scholarsh. 10(1):1-8.

   [Crossref] [Google Scholar] [PubMed]

10. de Nutte L, Okello J, Derluyn I (2015) Social relationships and social support among post-war youth in Northern Uganda. Int J Psychol. 52(4):291–299.

    [Crossref] [Google Scholar] [PubMed]

11. Denis A, Callahan S, Bouvard M (2014) Evaluation of the French version of the multidimensional scale of perceived social support during the postpartum period. Matern Child Health. 19(6):1245–1251.

    [Crossref] [Google Scholar] [PubMed]

12. Eisman A, Stoddard S, Heinze J, Caldwell C, Zimmerman M (2015) Depressive symptoms, social support, and violence exposure among urban youth: A longitudinal study of resilience. Dev Psycho. 51(9):1307-1316.

    [Crossref] [Google Scholar] [PubMed]

13. Elhadi M, Buzreg A, Bouhuwaish A, Khaled A, Alhadi A, et al. (2020) Psychological Impact of the civil war and COVID-19 on Libyan medical students: A Cross-Sectional Study. Front Psychol. 11:570435.

    [Crossref] [Google Scholar] [PubMed]

14. Fauzi MF, Anuar TS, The LK, Lim WF, James RJ, et al. (2021) Stress, anxiety and depression among a cohort of health sciences undergraduate students: The prevalence and risk factors. Int J Environ Res Public Health. 18(6):3269.

    [Crossref] [Google Scholar] [PubMed]

15. Finning K, Ukoumunne OC, Ford T, Danielson-WE, Shaw L, et al. (2019) Review: The association between anxiety and poor attendance at school-a systematic review. Child Adolesc Ment Health. 24(3):205–216.

    [Crossref] [Google Scholar] [PubMed]

16. Fortney JC, Curran GM, Hunt JB, Cheney AM, Lu L, et al. (2016) Prevalence of probable mental disorders and help seeking behaviors among veteran and non-veteran community college students. Gen Hosp Psychiatry. 38:99–104.

    [Crossref] [Google Scholar] [PubMed]

17. Garcia GPA, Fracarolli IFL, dos Santos HEC, de Oliveira SA, Martins BG, et al. (2022) Depression, anxiety and stress in health professionals in the COVID-19 context. Int J Environ Res Public Health. 19(7):4402.

    [Crossref] [Google Scholar] [PubMed]

18. Habihirwe P, Porovecchio S, Bramboiu I, Ciobanu E, Croituru C, et al. (2018) Depression, anxiety and stress among college students in three European countries. Eur J Public Health. 28(4):1-2.

    [Crossref] [Google Scholar]

19. Hefner J, Eisenberg D (2009) Social support and mental health among college students. Am J Orthopsychiatry. 79(4):491–499.

    [Crossref] [Google Scholar] [PubMed]

20. Horiuchi S, Aoki S, Takagaki K, Shoji F (2017) Association of perfectionistic and dependent dysfunctional attitudes with subthreshold depression. Psychol Res Behav Manag. 10:271–275.

    [Crossref] [Google Scholar] [PubMed]