Risk Factors for Depression in the Emerging Adulthood

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Risk Factors for Depression in the Emerging Adulthood

Sándor Lisznyai

a

, Katalin Vida*

a

, Marietta Németh

b

, Zsolt Benczúr

c

[a]Department of Psychology of Counselling, Faculty of Education and Psychology, Eötvös Loránd University, Budapest, Hungary.[b]Student Counselling Centre, Corvinus University of Budapest, Hungary.[c]Department of Computer Science, Faculty of Business Administration, Corvinus University of Budapest, Hungary.

Abstract

Emerging adulthood is a period from the late teens through the twenties, when individuals are faced with more transitions and life-decisions than at any other stage of life. For the majority, psychological well-being is improved in this period, but for a significant number of individuals these challenges and contingencies entail many controversies, which in turn can lead to depression or anxiety. This paper focuses on the background of, and risk factors behind, high level depression among university students, who are typically in this life stage, in order to identify the typical client characteristics of a university counselling centre. 773 university students completed an online survey measuring depression symptoms, socioeconomic status, distal and proximal social capital, bullying, substance abuse and indirect aspects of mental health as mediate variables. 13.6% of the participants reported moderate or major depression symptoms. Using hierarchical multiple regression, male gender and poor financial situation were found to predict higher depression. After controlling for the effects of background variables, social capital factors, identity status and life skills made a significant contribution to the prediction of lower depression. This supports the idea of the importance of social skills in enabling the individual to create their own social circle and joining the community of young people at the university.

Keywords:depression, emerging adulthood, social capital, counselling client profile

The European Journal of Counselling Psychology, 2014, Vol. 3(1), 54–68, doi:10.5964/ejcop.v3i1.22 Received: 2013-07-01. Accepted: 2014-01-21. Published (VoR): 2014-03-28.

*Corresponding author at: Korompai utca 21-23/A, 1124, Budapest, Hungary. E-mail: vidakatalin@caesar.elte.hu This is an open access article distributed under the terms of the Creative Commons Attribution License

(http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Youth has always been a critical scientific and social issue in Hungary. Just like an emerging economy, emerging generations experience the challenges of an economically and socially unstable environment, with an exposure

to both eastern and western problems (Kovács, Horváth, & Vidra, 2011). This study focuses on the mental health

of Hungarian university students. As the Hungarian higher education system is in a state of transition (in terms of

the Bologna transition process and the current changes in the financing of the higher education system [Gerő,

2012]), this provides an unstable context for identity development and important career decisions.

We use the concept „emerging adulthood” as it was developed byArnett (2000): a transitional phase in the life

span that extends the period of identity, career and relationship formation, and corresponds to increased flexibility

and potential for changes. For many, this period of life is filled with possibilities (Arnett, 2005), and the majority

of students has been found to experience improvements in their psychological well-being between the age of 18

and 25 (Galambos, Barker, & Krahn, 2006). For others, however, this turbulent period entails great difficulties.

Procrastination (Schouwenburg, 1995), social anxiety (Russell & Shaw, 2009;Russell & Topham, 2012), binge

drinking (Ham & Hope, 2003;Wechsler, Dowdall, Davenport, & Castillo, 1995) and eating disorders (Eisenberg,

Nicklett, Roeder, & Kirz, 2011) have all been identified in the literature as possible mental health risks for this age-group. The large-sample research of Eisenberg and his colleagues estimated the prevalence of any depressive

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or anxiety disorder as 15.6% for undergraduates and 13.0% for graduate students (Eisenberg, Gollust, Golberstein, & Hefner, 2007). Depression is associated with impaired functioning across multiple life domains, including

pro-ductivity and educational outcomes (Wittchen, Nelson, & Lachner, 1998), romantic involvement, life satisfaction

(Paradis, Reinherz, Giaconia, & Fitzmaurice, 2006) and self-esteem (Reinherz, Giaconia, Hauf, Wasserman, &

Silverman, 1999).

This paper focuses on the background of, and risk factors behind, the high prevalence of depression among uni-versity students. An important aim of studies like these is to explore the factors behind a decline in the academic performance of students.

The Current Study

The Hungarian Association for Counselling in Higher Education (FETA)ihas been researching the characteristics

of emerging adulthood for numerous years. This has been done through the analysis of college students’ and young adults’ mental health, psychological problems, coping strategies, their attitudes for seeking help, their competencies and life skills and the development of their autonomy. Since 1999, FETA has conducted several

’screenings’ of the mental health of Hungarian young adults (Kiss & Lisznyai, 2004;Lisznyai, 2006;Lisznyai, 2010;

Lisznyai, Kiss, Vajda, & Kabai, 2009; Lisznyai, Ritoók, Vajda, & Monostori, 1999;Perczel Forintos, Lisznyai, &

Kiss, 2003). All of them were based on the same methodological structure to get comparable results for drawing

a complex picture of these factors in the sensitive period of transition to adulthood.

Our goal was to identify the risk factors and background variables of depression in order to have a profile of the students who would come to seek psychological help in a counselling centre. Knowing the characteristics of this group is essential for being able to pay special attention to those particularly at risk and for the provision of better quality service. We assessed 4 groups of indicators. First, we measured background variables such as gender,

age, year of study, faculty and socioeconomic status. Based onBassani’s (2007)subdivision we also measured

social capital on both the proximal (relationship with peers) and on the distal (university atmosphere and engagement of civic action) dimensions.

It is well documented that being a victim of bullying is significantly associated with childhood depression (Hawker

& Boulton, 2000;Mills, Guerin, Lynch, Daly, & Fitzpatrick, 2004; Neary & Joseph, 1994; Slee, 1995a, 1995b).

Also, a recent study proved that previous experience of bullying is also correlated with adult depression (Copeland,

Wolke, Angold, & Costello, 2013). As a result, we included this factor in our analysis.

As mediate variables we measured indirect aspects of mental health such as life skills, satisfaction with sexual

life and occupational identity status. Based on Egan’s (1984) theoretical suggestions, Kiss (2009) created a

questionnaire to assess life skills, the Life Skills Scale. These skills refer to a type of ‘working’ or practical knowledge which is an aspect of successful social integration. This scale proved to be a good predictor of depression in

Lisznyai and colleagues’ latest research (Lisznyai, Kiss, Vajda, & Kabai, 2009). Satisfaction with sexual life is an

important part of mental health, especially in this period of life (Higgins, Mullinax, Trussell, Davidson, & Moore,

2011), therefore we measured it as an indirect aspect of mental health. In addition to the mental health aspects

of the well-being of the student sample, we measured their occupational identity status (based on the theoretical

assumptions ofMarcia, 1966) using the translated and modified Occupational Identity Scale (Melgosa, 1987).

Results from previously conducted research (Kiss & Lisznyai, 2004;Lisznyai, 2006;Lisznyai, 2010;Lisznyai, Kiss,

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Since the correlation between substance abuse and depression has been documented (Swendsen & Merikangas,

2000), we included the smoking, alcohol and drug consumption patterns of students as the fourth groups of

indic-ators.

Method

Participants and Procedure

An invitation to take part in research on mental health (containing the link of the online questionnaire) was sent to all students at the Corvinus University of Budapest. This was done via the administrative online interface of the university during the spring semester of 2011. Participation was voluntary, however as incentive, participants were entered into a prize draw for taking part. 773 students (491 female, 63.51%) completed the questionnaire. Informed consent was given for participation in the research. The questionnaire package was presented online and it was accessible for the students with their student ID number.

Our sample was heterogeneous in terms of age, covering the university population from the first to the fifth year

of study (Mage= 21.33,SD= 3.22,Min= 18,Max= 44). The majority, 74.8%, of the sample were BA students,

17% were MA students and 6.2% studied in the previous non-divided higher education system. The sample was relatively representative of the Corvinus University student population in terms of faculties and majors.

Materials

Depressive Symptoms —Depressive symptoms were assessed by using a revised and 9-item-shortened version ofBeck’s Depression Inventory(Beck, Ward, Mendelsohn, Mosck, & Erlaugh, 1961; short version:Perczel Forintos, Kiss, & Ajtay, 2007). The participants were not asked to choose one of the four alternatives of 21 sets of items, as in the original version, but rather to rate the 9 items (e.g., ‘‘I often feel sad’’) on a 4-point Likert scale ranging from ‘Not at all true of me’ to ‘Very true of me’. The depressive symptomatology score was calculated by the

fol-lowing formula:(total points-9)x2and therefore is comparable to the original band scale: 0-9 score – no depression

syndrome; 10-18 score – mild depression syndrome; 19-25 score – moderate depression syndrome; 25 and above – major depression syndrome. The Cronbach alpha for BDI is 0.9.

Background —Background information was measured by age, gender, year of study, faculty and socioeconomic status. The latter was assessed with two indicators: financial situation and parental education.

Financial situationwas measured with a question concerning the perceived financial situation of the participant

compared with peers. The answers were coded on a 3-point ordinal scale.Wickrama, Noh, and Elder (2009)

found an equalization in adolescent health across levels of Socio-economic Status (SES) but significant disparities in depression re-emerged as adolescents entered adulthood, supporting the view that young adults from families of higher SES responded more effectively to transition related risks and challenges during emerging adulthood.

Parental educationwas measured using mother’s education on an ordinal scale from 1 to 5, where 1 represented eighth grade or less education and 5 represented one or more university degrees. Maternal education has been

suggested to be a very good proxy for the education level of both parents (Entwisle & Astone, 1994). Parental

education has been found to be a predictor of depression in adolescents distinct from the influence of income

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Social Capital —Several questions were asked to measure social capital, covering (1) relationship status, (2) proximal social capital: quality of relationships, (3) distal social capital: (3a) civic action and engagement and (3b) the perception of the university atmosphere.

Relationship statuswas measured with two questions: ‘Have you ever had a relationship?’ which was coded into a yes (score 1)/no (score 0) variable. If the participant answered yes, the next question assessed the current re-lationship status on a nominal scale from 0 to 4, where 0 =‘I have never had a rere-lationship’, 1 = ‘Rere-lationships are problematic for me’, 2 = ‘I have casual relationships without strong attachments’, 3 = ‘I live alone, no relationship’, and 4 = ‘I live in a long-term relationship’.

The proximal social capital, the quality of relationshipswas assessed with two questions. The first question was ‘How many close friends do you have?’ (Answers were coded separately for male and female close friends). In case of the second question, ‘How satisfied are you with your friendships?’, participants were asked to rate statements on a 5-point Likert scale (from 1, ‘Absolutely not’, to 5, ‘Absolutely yes’).

Distal social capitalwas measured with two indicators: involvement in civic activities and the perception of the

university atmosphere.Civic action activities were measured by two questions on participation in community

activities and student organizations. Both questions were coded into a yes (score 1)/no (score 0) variable. Perception ofthe university atmospherewas assessed on an ordinal scale where the question, ‘What do you think about the atmosphere of the university?’ was coded on a 4-point Likert scale.

Victimization of Bullying —Participants’ previous experience of being a victim of bullying was measured with the following question: ’Have you ever been a victim of bullying?’ rating their answers on a 5-point scale (1-never, 5-more than five times).

Life Skills —This scale contains items on health related lifestyle (e.g. ‘I care about a quality of nutrition’, or ‘I am limiting my smoking’), social relations (e.g. ‘I like working in a group’ or ‘I can cooperate easily’), persistence and planning (e.g. ‘I am persistent in implementing my plans’ or ‘I have good time-management’), a well-defined value system (e.g. ‘I have a strong political value system’), etc. The scale has 80 items and the participants were asked to rate statements on a 5-point Likert scale (from 0, ‘Strongly disagree’, to 4, ‘Strongly agree’). The Cronbach alpha reliability for the Life Skills Scale was 0.96.

Sexual Life —In order to measure the satisfaction of sexual life, the question ofHow is your sexual life (including masturbation)?’ was added to the life skills and rated on a 4-point Likert scale.

Occupational Identity —Participants were asked to rate the 28 items of the questionnaire on a 5-point Likert scale (from 0, ‘Strongly disagree’, to 4, ‘Strongly agree’). The scale has 4 subscales: Identity Achievement, Identity Moratorium, Identity Foreclosure and Identity Diffusion. The Cronbach alpha is 0.83.

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= ‘4 or more times’. Drug abuse was measured with the question, ‘Have you used any of the following substances in the past 12 months?’ Categories included marihuana, speed, ecstasy, opium, medication, medication and alcohol, cocaine, LSD and other type of drugs. Participants were asked to rate each category on a 7-point Likert scale.

Results

Explorative Analysis

Figure 1presents the distribution and descriptive statistics of the Beck’s Depression Inventory (M = 8.26,SD=

9.72). The majority of the participants showed no depression symptoms (67.4%), less than one fifth of the sample belonged to the mild depression group (19%), the third group consisted of 5% of the participants showed moderate depression and the fourth group showed symptoms of major depression (8.6%).

Figure 1.Distribution and descriptive statistics of Beck’s Depression Inventory.

In the explorative analysis the association between nominal variables and depression were measured with one way analysis of variance (ANOVA). Male gender, faculty and the relationship status emerged to be significant

factors in depression. Results of the analysis are shown inTable 1.

Descriptive statistics and intercorrelations between ordinal variables examined in the study are presented in the

Appendix (Table A1). Correlations were generally small to moderate, with the strongest associations observed

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Table 1

Results of the ANOVA Test Measuring the Effect of the Nominal Variables to Depression

F

Mean Square

df

Sum of Squares Variable

1

Gender 366.22 366.22 3.69*

6

Faculty 1407.79 234.63 2.38*

1

Status of employment 74.05 74.05 0.74

5

Housing condition 586.63 117.32 1.18

1

Relationship status 567.78 567.78 5.74**

1

Civic engagement 181.55 181.55 1.82

*p< .05. **p< .01.

Hierarchical Multiple Regression

A hierarchical multiple regression analysis was performed with depression as the dependent variable. Those variables which showed significant effect in the exploratory analysis were entered in the model. Gender, faculty and the financial situation were entered in the first step to examine the effects of background factors. In the second step, social capital indicators were added: relationship status, proximal social capital as number of girl close friends and satisfaction with the quality of friendships, distal social capital as perception of the university atmosphere and being a victim of bullying. In the third step occupational identity status, life skills, satisfaction with sexual life and medication consumption were also included.

The final model (seeTable 2) accounted for a significant 31.8% of the variance in depression (F(15,675) = 20.93,

p< .001). In the first step, male gender and financial situation emerged as significant antecedents of depression

in early adulthood, explaining only 4.2% of the variance (F(1,689) = 25.07,p< .001). Financial situation remained

significant in each of the subsequent steps, although the effect of gender did not, suggesting that it had an effect through other variables. In the second step, social capital and previous experience with bullying were included in

the analysis adding 10.8% to the explained variance (F(2,688) = 15.04,p< .001). Satisfaction with the quality of

friendships and perception of university atmosphere emerged as significant antecedents of higher level depression. Both of these factors remained significant in the subsequent step. In the third step occupational identity status, life skills, sexual life and medication consumption were entered into the model, contributing to an additional 16.8%

of the variance (F(9,681) = 13.25,p < .001). Identity status and life skills emerged as significant predictors of

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Table 2

Results of the Hierarchical Linear Regression Predicting Depression in Early Adulthood: Financial Situation, Social Capital Factors, Life Skills and Identity State

p

Beta

SD. Error

Variable

Step 1

Gender -1.754 0.79 -.08

Faculty 0.045 0.18 .01

Financial situation -3.152 0.63 -.19

Step 2

Gender -0.504 0.81 -.02

Faculty -0.108 0.17 -.02

Financial situation -2.722 0.60 -.16

Relationship status -1.208 1.33 -.03

Number of close friends (girl) -0.707 0.45 -.06

Satisfaction with the quality of friendships -2.500 0.42 -.22

Perception of the university atmosphere -2.222 0.62 -.13

Victim of bullying 1.939 1.02 .06

Step 3

Gender 0.117 0.75 .00

Faculty 0.131 0.15 .02

Financial situation -1.541 0.56 -.09

Relationship status 0.713 1.27 .01

Number of close friends (girl) -0.578 0.41 -.05

Satisfaction with the quality of friendships -1.597 0.39 -.14

Perception of the university atmosphere -1.454 0.56 -.08

Victim of bullying 1.749 0.92 .06

Identity Moratorium 0.199 0.05 .12

Identity Foreclosure 0.319 0.06 .18

Identity Diffusion 0.143 0.08 .06

Life skills -0.073 0.00 -.30

Sexual life -0.436 0.34 -.04

Medication consumption 1.839 0.94 .06

Note. R2= .042 for Step 1 (p< .001);R2= .15 for Step 2 (p< .001);R2= .318 for Step 3 (p< .01).

Discussion

The majority of the participants showed no depression symptoms (67.4%), less than one fifth of the sample belonged to the mild depression group (19%), moderate depression (5%) and the major depression group (8.6%) added

up to 13.6% of the sample, which remains consistent with the international results (Eisenberg et al., 2007).

Gender differences in depression are a well-established fact in the scientific literature, with studies usually showing

female dominance (Smith & Blackwood, 2004). Our results also showed clear gender differences, however male

participants reported higher scores (9.20 vs. 7.73) on the Beck Depression Inventory. This has been observed

several times by a series of previous research on Hungarian samples (Lisznyai, 2006,2010;Lisznyai et al., 1999).

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be one of the reasons behind this result. For example,Galambos, Barker, and Krahn (2006)found that depressive symptoms for women were higher at the age of 18 but declined more rapidly across emerging adulthood compared with men (at age 25 there were no gender differences), which indicated different psychological well-being traject-ories for the two genders.

The results indicate that key factors of the social environment such as quality of friendships and university

atmo-sphere, are critical to youth depression, in accordance with the results ofO’Connor et al. (2011). However, it must

be taken into consideration that no casual order can be established among these variables, i.e., depression can overshadow the perception of university environment in general. The role of the other important factor, perceived

quality of friendships, has been supported by a series of previous research in Hungary (Lisznyai, 2006), which

emphasized that "social loneliness" is the most important type of crisis among university students. Through the transition to a more autonomous form of study development, the Hungarian higher education system brought about the task for students to create social environments and form communities. This was beneficial for those who were skilled in this task, but left others in a hopeless situation.

The above relationship has been supported by another critical variable in the regression analysis: „life skills” were important contributors to depressive symptom development. This also highlights the importance of social skills in enabling the individual to create their own social circle and join the community of fellow students at the university. As expected, the three factors of identity diffusion correlated with depression, indicating that the period of emerging

adulthood is a prolonged identity crisis for many (Arnett, 2010).

The variable of „financial status” revealed a relatively strong connection with depression. Previous Hungarian

re-search reported mixed results this issue: more recently,Lisznyai (2010)found no effect of financial status, but

back in 1999 – based on 1997 data – the same author warned that financial status had a strong effect on mental

health among Hungarian university students (Lisznyai et al., 1999)ii. Almost all international investigations find

that SES and social support are both inversely associated with depressive symptoms during adolescence and

young adulthood (Brown, Meadows, & Elder, 2007;Eisenberg et al., 2007;Gore & Aseltine, 2003;Miller & Taylor,

2012; Wickrama et al., 2009). There is also evidence that SES is positively related to social support (Huurre,

Eerola, Rahkonen, & Aro, 2007;Marmot et al., 1998), which suggests that SES may influence psychological

well-being indirectly through its association with social support (Miller & Taylor, 2012).

An important future task is the follow up investigation of students who could successfully cope with this situation either alone or with the aid of professional services. After developing clients’ profiles, we should also find the

evidence based mapping of the treatment profile to improve therapeutic services (Kendall, Holmbeck, & Verduin,

2004). This is particularly important because, as emphasized byEisenberg and Chung (2012), students with

de-pression symptoms often do not receive adequate treatment: in their research, minimally adequate treatment was received by only 22% of depressed students, even though these students often have nowhere else to go for

as-sistance (Lichtenberg, Goodyear, & Genther, 2008).

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community activities with counselling services and group counselling activities. The authors believe that in this isolating world of mass education, counselling psychologists should apply more methods of community psychology

during their everyday work (Rappaport & Seidman, 2000).

Limitations

In our survey the data were self-reported and may therefore under- or overestimate the prevalence of depression among university students. Furthermore, although our sample was relatively representative of the Corvinus Uni-versity student population in terms of faculties and majors, it was not representative in terms of gender. Therefore we cannot draw any conclusions about the whole university population. Also, it should be remembered that the presented correlations between depression and other factors do not imply that one causes the other: for example financial difficulties can lead to depression as well as depression can also affect the perception – and even the reality – of current financial situation.

Notes

i) The Hungarian Association for Counselling in Higher Education (FETA) was founded in 1995 to incorporate various organizations and individuals dealing with counselling at higher education institutions in Hungary. Functioning as an umbrella organization for all those who promote or practice student counselling, FETA strives to generate a student-centred attitude at universities, colleges and social institutions. For more information about FETA, see the website:http://www.feta.hu/english

ii) This important finding from the 1997 data, however, could possibly be attributed to the 1994/1995 Hungarian financial crisis, which had an especially strong deteriorating effect on the living conditions of university students. The importance and almost immediate presence of societal factors in the mental health sphere indicate a strong Durkheimian explanation of depressive symptom formation.

Funding

The authors have no funding to report.

Competing Interests

The authors have declared that no competing interests exist.

Acknowledgments

The authors have no support to report.

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About the Authors

Sándor Lisznyaiis a clinical psychologist, and a senior lecturer at the Department of Psychology of Counselling. His main research interest is counselling young people, measuring the effectiveness of counselling and psychotherapy and finding evidence-based practice solutions. In his PhD research he focused on the symptoms of depression among young people who participate in university counselling.

Katalin Vidais a PhD student at the Department of Psychology of Counselling, some of her main research interests are the age of emerging adulthood and the quarter life crisis. She has gained considerable experience in different methods of quant-itative research in psychology, while she has conducted several studies in the area of the mental health of young adults.

Marietta Némethis a clinical psychologist and a psychotherapist, as well as the Head of the Student Counselling Centre at Corvinus University. She has accumulated a huge practical expertise through working with student clients in the university counselling centre in the past 10 years.

Zsolt Benczúris a PhD student at the Department of Computer Science at Corvinus University. In addition of his research

Figure

Figure 1 presents the distribution and descriptive statistics of the Beck’s Depression Inventory (M = 8.26, SD = 9.72)

Figure 1

presents the distribution and descriptive statistics of the Beck’s Depression Inventory (M = 8.26, SD = 9.72) p.5