Anxiety predictors among college students in Kosovo

Abstract

This cross-sectional study aimed to investigate the prevalence and anxiety predictors among college students in Kosovo. Participants were 676 randomly sampled college students (M = 21.54, SD = 4.44), selected from three universities (two private) in the 2015/2016 academic year. Pearson chi-square, t-Test, ANOVA, linear and multiple regressions were used. The prevalence of anxiety was 33.6%. The symptoms were significantly related to gender (p = .00), study year (p = .00), family income (p = .00), group age (p = .00) and father’s employment (p = .00). Female students, students living in extended family, first-year students, students whose mothers did not work, showed statistically higher levels of anxiety. Anxiety was predicted by gender, study year, previous study academic achievement and family income. Study findings stress the importance of understanding the relationship of psychosocial factors and anxiety, for the purpose of determining the necessary and adequate interventions and programs.

Keywords:

• College students
• anxiety
• prevalence
• sociodemographic factors

Introduction

A series of studies have already established that mental health problems in student population can be considered a global concern (Eisenberg, Gollust, Golberstein, & Hefner, 2007; Wong, Cheung, Chan, Ma, & Tang, 2006; Zivin, Eisenberg, Gollust, & Golberstein, 2009). Among those mental health problems anxiety disorders can be considered the most prevalent disorder, with a prevalence of more than 20% (Alonso et al., 2004; Kessler, Chiu, Demler, & Walters, 2005; de Graaf, ten Have, van Gool, & van Dorsselaer, 2012). If we refer to the European region, according to Wittchen et al. (2011), mental disorders, including anxiety and depression, are the second largest contributors to the burden of disease.

According to McCarthy, Fouladi, Juncker, and Matheny (2006) and Williams, Galanter, Dermatis, and Schwartz (2008), the most common concerns reported by college students in counseling centers were anxiety, stress and depression. Gallagher (2007), Hunt and Eisenberg (2010) and Pedrelli, Nyer, Yeung, Zulauf, and Wilens (2015) showed in their studies that the prevalence and severity of significant mental health problems are increasing in the college student population. Other studies show that the distribution and the prevalence of mental health problems have shown higher values in the college student population than in the general population (Stallman, 2010; Dyrbye, Thomas, & Shanafelt, 2006).

The incidence of anxiety in college students is relatively high ranging from 13% (Said, Kypri, & Bowman, 2013), 14.3% (Mustafa, Melonashi, Shkembi, Besimi, & Fanaj, 2015), 33.5% (Simić-Vukomanović et al., 2016), 40.2% (Ran et al., 2016), 41% (Wong et al., 2006), 43.9% (Ibrahim & Abdelreheem, 2015), 46% (Singh & Jha, 2013), 47.1% (Bayram & Bilgel, 2008), 52% (Živčić-Bećirević, Smojver-Ažić, Dorčić, & Juretić, 2015) to 65.5% (Mancevska, Bozinovska, Tecce, Pluncevik-Gligoroska, & Sivevska-Smilevska, 2008).

There are a number of factors that have been associated with anxiety level in college students (Ozen, Ercan, Irgil, & Sigirli, 2010). A lot of studies (Bayram & Bilgel, 2008; Ran et al., 2016; Bekker & van Mens-Verhulst, 2007) revealed that female students were more likely than male students to score higher on anxiety, regardless of the instrument used. Eisenberg et al. (2007), also found that females were more than twice as likely as males to screen positive for anxiety disorders.

Bayram and Bilgel (2008) indicated higher anxiety scores among first and second-year students. Bouteyre, Maurel, and Bernaud (2007), Wong et al. (2006) also found that first year students tend to demonstrate higher levels of anxiety.

Overweight and obesity have also shown correlation with anxiety symptoms (Erermis et al., 2004; Anderson, Cohen, Naumova, Jacques, & Must, 2007) and the study carried out by Lanza, Echols, and Graham (2012) revealed that overweight and obese females scored higher than their peers. Negative correlation with the high level of anxiety among students was revealed with the education background of the father (Nerdrum, Rustøen, & Rønnestad, 2006)

Researchers looking at the correlation between anxiety and academic performance, suggest that students with high level anxiety achieve low academic performance (Vitasari, Wahab, Othman, Herawan, & Sinnadurai, 2010; Nadeem, Ali, Maqbool, & Zaidi, 2012).

The goals of this study were (a) to investigate the prevalence of anxiety among 676 college students, (b) to explore possible differences and associations between interest variables, and (c) to determine whether demographic and socioeconomic variables are significant predictors of anxiety.

Methods

Participants and procedure

This was a cross-sectional study. There were 676 students attending three Universities (two private) in Kosovo in the academic year 2015/2016. The students (M = 21.54, SD = 7.44), were randomly sampled from every study year of several faculties.

There were significant distribution differences in most of the demographic variables in the study: gender distribution; place of residence; year of study; order of birth; BMI scales; family income; and family type. The sample sociodemographic characteristics are summarized in Table 1.

Table 1. Sample characteristics.

		Frequency (N)	Percentage %	Distribution differences
Gender	Male	227	33.6	χ²(1, N = 676) = 72.91, p = .00
	Female	449	66.4
Place of residence	Village	201	29.7	χ²(1, N = 674) = 109.77, p = .00
	City	473	70.0
	Missing	2	.3
Study year	I Year	328	48.5	χ²(2, N = 676) = 73.72, p = .000
	II Year	194	28.7
	III Year	154	22.8
Birth order	I	311	46.0	χ²(5, N = 676) = 505.38, p = .00
	II	144	21.3
	III	88	13.0
	IV	74	10.9
	V	48	7.1
	VI	11	1.6
BMI scales	Underweight	72	10.7	χ²(3, N = 676) = 1061.22, p = .00
	Normal	534	79.0
	Overweight	55	8.1
	Obese	15	2.2
Family type	Nuclear	498	73.7	χ²(1, N = 597) = 266.67, p = .00
	Extended	99	14.6
	Missing	79	11.7
Family income	Less than 200 €	30	4.4	χ²(3, N = 676) = 382.40, p = .000
	201–350 €	97	14.3
	351–500 €	180	26.6
	Over 501 €	369	54.6
Father’s education	Elementary school	46	6.8	Not significant
	High school	225	33.3
	Faculty	385	57.0
	More	20	3.0
Mother’s education	Elementary school	168	24.9	Not significant
	High school	296	43.8
	Faculty	202	29.9
	More	10	1.5
Father’s employment	Yes	424	62.7	Not significant
	No	64	9.5
	On occasion	165	24.4
	Pensioner	23	3.4
Mother’s employment	Yes	225	33.3	Not significant
	No	419	62.0
	On occasion	16	2.4
	Pensioner	16	2.4
AA		M	SD
	Previous study	8.14	.81
	Faculty (till now)	7.54	.98
Age	Female	21.14	3.95
	Male	22.39	5.24

The students’ participation was completely voluntary and informed consent was obtained. Ethical approval for the research was obtained from the scientific committee of AAB College.

Instruments

A self-administered questionnaire with demographic and socioeconomic variables was used. Demographic variables included: group age (18–21, 22–25, 26–29, 30–33, 34–37, 38+), gender (male, female), place of residence (city, village), year of study, BMI scale (underweight, normal, overweight, obese), previous study’s AA, faculty’s AA and birth order, while the socioeconomic variables included father’s education, mother’s education, father’s employment status, mother’s employment status and family status (nuclear, expanded).

In the present study the examination scores of the students in their previous study and at the moment of the study, were considered as their academic achievement (AA). The Body Mass Index (BMI) was also calculated. The majority of the students (79%) had normal weight, 10.7% were underweight, and 10.3% were overweight or obese.

The Beck Anxiety Inventory (BAI; Beck & Steer, 1993), as one of the most popular screening and outcome research instruments for measuring the construct of anxiety (Bardhoshi, Duncan, & Erford, 2016), was used. The BAI scale consists of 21 items, scored on a scale ranging from 0 to 3. A total score of 0 to 7 is interpreted as ‘minimal’, 8–15 as ‘mild’, 16–25 as ‘moderate’, and 26–63 as ‘severe’ level of anxiety. The internal consistency, was α = .873 (Female = .870; Male = .863). Our results are slightly lower than the coefficient alpha reported by Bardhoshi et al. (2016) α = .91, k = 56, n = 25,917, and by De Ayala et al., (2005) in their reliability generalization study, which determined an internal consistency (coefficient alpha) estimate across 43 articles of .91.

Data analysis

All analyses were conducted using SPSS Version 21. Cronbach’s α coefficient was used as an index of internal consistency for the BAI. Descriptive statistics for all demographic and socioeconomic variables and anxiety symptoms were calculated. Pearson’s chi-square test was used to discover if there is a relationship between the categorical variables. T-test and analysis of variance (ANOVA) were used to explore differences between groups, while linear and multiple regressions were used to examine the possible contribution of demographic and socioeconomic variables in students’ anxiety. The level of significance was set at p < .05.

Results

The table below represents the socioeconomic and demographic characteristics of participants. Most of them were female, living in the city in their nuclear family with an income of over 501 euro, in the first year of study.

The mean BAI score for anxiety symptoms was 13.23 (SD = 8.15). There were 41.1% (N = 278) of students who showed mild anxiety level, 24.1% (N = 163) showed moderate anxiety level, and 9.5% (N = 64) who revealed severe anxiety level.

As indicated in Table 2, anxiety symptoms were significantly related to gender (p = .00), study year (p = .00), family income (p = .00), group age (p = .00) and father’s employment (p = .00). No statistically significant relationship was found between anxiety symptoms and other interest variables in the study.

Table 2. Association of anxiety symptoms with demographic and socioeconomic variables.

		Anxiety level (%)
		Minimal	Mild	Moderate	Severe	Association values
Gender	Male	37.9	38.3	17.6	6.2	χ²(3, N = 676) = 31.97, p = .00
	Female	18.9	42.5	27.4	11.1
Place of residence	Village	23.9	42.8	25.9	7.5	χ²(3, N = 674) = 2.10, p = .552
	City	26.0	40.4	23.3	10.4
Study year	I Year	17.1	40.9	31.4	10.7	χ²(6, N = 676) = 47.15, p = .00
	II Year	25.3	43.8	21.6	9.3
	III Year	42.9	38.3	11.7	7.1
Birth order	I	28.9	39.9	23.5	7.7	χ²(15, N = 676) = 19.19,p = .21
	II	20.8	42.4	20.1	16.7
	III	18.2	45.5	27.3	9.1
	IV	24.3	40.5	28.4	6.8
	V	29.2	39.6	25.0	6.3
	VI	27.3	36.4	36.4	0.0
Group age	18–21 years	21.3	43.0	25.3	10.4	χ²(15, N = 676) = 40.17,p = .00
	22–25	25.0	41.7	25.0	8.3
	26–29	45.5	32.7	20.0	1.8
	30–33	85.7	14.3	0.0	0.0
	34–37	37.5	12.5	37.5	12.5
	38–46	42.1	36.8	5.3	15.8
BMI scales	Underweight	15.3	54.2	22.2	8.3	χ²(9, N = 676) = 8.87, p = .449
	Normal	27.2	38.8	24.5	9.6
	Overweight	20.0	45.5	23.6	10.9
	Obese	26.7	46.7	20.0	6.7
Family type	Nuclear	22.3	42.6	25.9	9.2	χ²(3, N = 597) = 5.03, p = .170
	Extended	15.2	41.4	28.3	15.2
Family income	Less than 200 €	13.3	26.7	46.7	13.3	χ²(9, N = 676) = 23.88, p = .00
	201 – 350 €	20.6	41.2	27.8	10.3
	351 – 500 €	20.6	40.6	30.0	8.9
	Over 501 €	29.8	42.5	18.4	9.2
Father’s employment	Yes	19.3	44.1	25.2	11.3	χ²(9, N = 676) = 31.76, p = .00
	No	26.6	34.4	32.8	6.3
	On occasion	38.2	35.2	20.0	6.7
	Pensioner	39.1	47.8	8.7	4.3
Mother’s employment	Yes	31.6	41.8	18.7	8.0	χ²(9, N = 676) = 14.12, p = .12
	No	22.0	40.6	27.4	10.0
	On occasion	18.8	37.5	25.0	18.8
	Pensioner	31.3	50.0	12.5	6.3
Father’s education	Elementary school	15.2	50.0	19.6	15.2	χ²(9, N = 676) = 10.75, p = .29
	High school	27.1	36.9	27.1	8.9
	Faculty	24.7	43.4	22.9	9.1
	Higher	40.0	25.0	25.0	10.0
Mother’s education	Elementary school	20.2	43.5	21.4	14.9	χ²(9, N = 676) = 15.24, p = .09
	High school	28.7	38.9	26.4	6.1
	Faculty	24.3	42.1	23.3	10.4
	Higher	30.0	50.0	20.0	0.0

T-test analyses revealed statistical gender differences t (674)=5.47, p = .000, with female students showing higher mean (M = 14.43, SD = 8.23) than male students (M = 10.87, SD = 7.46). Same results were found for students living in extended family (M = 15.37, SD = 7.83) versus students living in nucleus family (M = 13.60, SD = 8.10). The ANOVA did not reveal statistical differences.

Nevertheless, we entered the groups of sociodemographic variables in a linear regression analysis. The first model for the demographic variables indicated that anxiety was significantly predicted by three variables: gender, study year and previous study AA: (R² = .099, R² _adj = .091), F (6, 645) = 11.72, p = .000. The second model, with the socioeconomic variables, indicated that anxiety was significantly predicted by family income only: (R² = .025, R² _adj = .015), F (6, 590) = 2.55, p = .019. Regression models are shown in Table 3.

Table 3. Linear regression analyses predicting anxiety.

Model 1	B	t	Sig.	95.0% Confidence interval for B
				Lower bound	Upper bound
Gender	−3.085	−4.698	.000	−4.374	−1.796
Study year	−1.293	−3.196	.001	−2.087	−.499
Previous study AA	1.424	3.452	.001	.614	2.235
Model 2
Family income	−.787	−2.055	.040	−1.539	−.035

Discussion

This study aimed to investigate the prevalence of anxiety among 676 college students, to explore possible differences and associations between interest variables, and to determine whether demographic and socioeconomic variables might serve as a significant predictor of anxiety.

The results indicated that the prevalence of anxiety symptoms in our sample was 33.6%. Compared to the study of Mustafa et al. (2015), a study that compared the level of anxiety of students from Kosovo and Albania, our results are lower. This may have come as a result of the considerable difference in the sample size in research (62 students participated at Mustafa et al.) and the use of different instruments. Another reason may be that in calculating the prevalence we referred to moderate and severe values of anxiety symptoms. These reasons may be valuable also for the difference in anxiety prevalence level of Albanian students (14.3%) and Kosovar students (32.3%).

Our results are similar with some studies (33.5% in Serbia – Simić-Vukomanović et al., 2016; (31.40% in Romania – Tomşa, Ortiz, Sedano, & Jenaro, 2014), but lower compared to other studies (47.1% in Turkey – Bayram & Bilgel, 2008) and much lower compared to 65.5% in FYR Macedonia (Mancevska et al., 2008), or 64.3% in Egypt (Abdel Wahed & Hassan, 2016).

The present study reported statistically significant differences in anxiety symptoms by gender, with a higher prevalence among female student. These results are consistent with studies of Ran et al. (2016), Abdel Wahed and Hassan (2016), Simić-Vukomanović et al. (2016) and Bayram and Bilgel (2008).

The lower anxiety level in males than in females could be due to societal expectations. Males are not expected to admit their weaknesses, therefore are less likely to be sincere on reporting anxiety. Nevertheless, our findings are not in line with the findings of Singh and Jha (2013) and Živčić-Bećirević, Jakovćić, and Juretić (2011), who did not reveal any differences in anxiety prevalence associated with gender.

Relations between material conditions and socio-psychological processes and behavior have been seen as determinants of health and life expectancy (Kunst et al., 1998). The relation between anxiety and social status carries particular importance in countries like Kosovo, because the low social level is accompanied by a high social tension, caused by rapid class differentiation influenced by the black economy. The relation between social class and income may have little meaning in this study, since incomes in Kosovo are so narrow that they make the creation of class groups difficult.

Certainly, incomes serve as markers for class inequality in the national structure of a country by creating a curvilinear link between personal income and health (Wilkinson & Pickett, 2006). This study is unique in its nature, since the socio-economic status determined to be associated with access to material and social assets, including income, wealth and education background (Gallo & Matthews, 2003), has major discrepancies in our sampling.

Our findings are comparable with a number of studies that have analyzed the link between SES and anxiety, that have had mixed conclusions. In their comparison of 6 studies on the relation between anxiety and SES, Gallo and Matthews (2003) found that only 17% of them supported reverse connectedness, while 33% found no connections.

Psycho-social factors related to income are known to be affected by economic stress caused by economic powerlessness. This powerlessness is closely linked to the feeling of worthlessness and helplessness in controlling individual and family life. One assumption is that this might have led to the finding that individuals from larger families have experienced more anxiety than those from nuclear families. This finding could also have been affected by the fact that students who live in larger families may face more financial problems related to covering the study costs, or even the living costs.

Anxiety has been shown for sure to interfere with people’s overall wellbeing. Early detection of mental health problems is very essential for the purpose of determining the necessary interventions and programs. Since, according to the Strategy 2020 by the World Health Organization (World Health Organization, 2013) strengthening mental health promotion programmes is highly relevant, other in depth studies are needed to examine more thoroughly other factors related to anxiety.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Mimoza Kamberi is a lecturer at the AAB College at the faculty of Psychology. She earned a master degree in Psychology from the University of Pristina, and currently she is a doctoral student at the Faculty of Education. Her research interest covers the educational psychology and organizational psychology.

Fatbardha Hoxha is currently the dean of the Faculty of Education at the University of Mitrovica “Isa Boletini”. She earned a master degree in Albanian Language from the University of Prishtina, and currently she is a doctoral student. Her research interest covers the educational psychology and educational literature.

Merita Shala is a lecturer at the University of Mitrovica ‘Isa Boletini’. She earned a Doctor of Psychology Degree at the European University of Tirana, Albania. She is a specialist in child development, with a sub-specialty in motor and emotional development. Her research interest covers the children and adolescent mental health and education.

Mimoza Shahini is a lecturer at the University of Mitrovica ‘Isa Boletini’. She earned a Doctor of Medical Sciences at the University of Vienna, Austria. She is a specialist in Adult Psychiatry, with a sub-specialty in Child and Adolescent Psychiatry and Family Therapy. She is an international advisor to the World Association of Psychiatry for the Global Programme on Children.

Shemsedin Vehapi holds the position of deputy rector for teaching and he is a lecturer at the AAB College. He earned a doctor degree in Physical education and Sport from the University of Pristina. His research interest covers the physical education and sport and the psychological factors related within.

Acknowledgements

The researchers acknowledge with gratitude the support and cooperation extended by the rector of University of Mitrovica ‘Isa Boletini’ and the rector of AAB College. Also, we thank for the cooperation the students who participated in this research for their contribution: Ardiana Karameta, Elona Karaqica, Anda Pallaska, Fletë Hoxha.