Article Type : Research Article
Authors : Delvina Beka and Valbona Uka
Keywords : Covid-19; Depression; Age; Pandemic; 18-60 years old; Kosovo
Introduction: The situation of the COVID-19 pandemic from the beginning was and remains very worrying for health in general, with a special focus on the mental health of the population and the consequences that are being seen day by day. Purpose: The purpose of this study is to identify the relationship between age and depression and age group differences in the level of depression in the general population during the COVID-19 pandemic in Kosovo. Methods: The research was conducted through an online survey using the Depression Scale Questionnaire, (DASS-21). The target population of the study is composed of people over 18 years of age and above, and at the same time, citizens of Kosovo. In total 246 participants, 154 females and 92 males participated in this research and it was conducted in the period November-December 2020.
Results: Data analysis was performed through SPSS. Spearman correlation analysis shows that age and depression during the COVID-19 situation has negative non-significant correlation. So the correlation between age and depression is (r =-.120; p =.060). Regarding age differences in the level of depression, there are significant differences ?2(2)=9.338, p =.009 and the first age group, 18-30 years, shows a higher average.
Conclusion: According to the findings of the study, the level of depression in Kosovar society during the COVID-19 situation varies with age, with the age group of 18-30 years being more affected than other age groups.
The outbreak of the COVID-19 pandemic has created an
environment where many determinants of health in general and mental health in
particular are deteriorating. The need for up-to-date information on COVID-19
mental health impacts in a way that informs the health system responses is
imperative. The COVID-19 pandemic is a special and rare situation. It can
affect people physically, but also psychologically. In this context, many
people experience stress reactions, anxiety and depression. Our country is
affected by Virus 19 now 1 year and 8 months, and is still continuing to be a
part of our lives and affecting us in all walks of life. This study is based on
research on depression with the age variable comparing three age groups
affected by depression during the pandemic.
Depression
Depression (major depressive disorder) is a common and
serious medical condition that negatively affects the way you feel, the way you
think and act. Fortunately, it is also treatable. Depression causes feelings of
sadness and / or loss of interest in activities you once enjoyed. It can lead
to a range of emotional and physical problems and can lower your ability to
function at work and at home. (DSM-5, 2013).
·
Symptoms of depression
include the following:
·
Significant weight loss
(not diet related), or increase or decrease or increase in weight appetite.
·
Insomnia
·
Psychomotor agitation or
severe enough delay to be observed by others.
·
Fatigue or loss of
energy.
·
Feelings of
worthlessness, either excessive or inappropriate or excessive guilt.
Redecreased ability to think or concentrate, or
indecision. Repeated thoughts of death, repeated suicidal ideas without a
specific plan, or suicide attempt, or a specific plan to commit suicide [1].
The concept of cognitive triad serves as a framework for in-depth examination of automated thoughts and beliefs of clients. All of their problems can be related to dysfunctional and misplaced beliefs in one of these three areas. The therapists begin therapy by looking at how the client's thoughts are in this framework and intervene to change their thoughts about themselves, the world or others, and the future [2]. Beck’s cognitive triad Beck's cognitive triad, also known as the negative triad, is a cognitive-therapeutic view of the three key elements of a person's belief system present in depression. It was proposed by Aaron Beck in 1967. The triad forms part of his cognitive theory of depression and the concept is used as part of CBT (Figure 1).
Figure 1: Beck’s cognitive triad.
To date, most scientific efforts have been devoted to
the study of the direct effects of the pandemic on mortality and morbidity, but
in addition to physical health, the COVID-19 pandemic has also affected mental
health. New research from around the world shows that fear can lead to anxiety
and depression. As reported, these studies have documented increased levels of
depression, loneliness and anxiety during the isolation period [4,5]. The rate
of depression tripled during the first year of the pandemic, according to a
study by Boston University published in the medical journal The Lancet Regional
Health. Before the pandemic, about 8% of adults in the US experienced
depression. Conducted between March and April 2020, this statistic rose to 28%.
And when researchers surveyed the same people a year later, they saw an
increase to 32% .The ratio of the likelihood of high-income depressive symptoms
to high-income people increased from 2.3 in 2020 to 7.0 in 2021. Over time, the
main drivers of depressive symptoms were low family income, loneliness, and
experiencing multiple stressors during the COVID-19 pandemic [6]. According to
a study in our country found that the more one is afraid of COVID-19, the more
depression will increase. The comparison of the level of depression between
women and men turned out to be higher among females, and they come from urban
areas and belong to the age over 50 years. We conclude that for the Kosovar
population the more they are afraid of COVID-19, the more the level of stress,
anxiety and depression will increase [7]. The situation created by COVID-19 has
led to chaos in the population, causing people to face mental health problems
in addition to depression, so it is considered reasonable to conduct a study on
the level of depression during the COVID-19 situation in Kosovo. Therefore, we
aimed to assess the relationship between age and depression and age group
differences in the occurrence of depression levels during the COVID-19
situation in Kosovo. So our hypotheses are:
H.1:
There is a positive correlation between depression and age.
H.2:
There are differences in the level of depression in terms of age.
Methodology
Participants and samples
The target population of the study is all residents of
Kosovo, more precisely, all citizens of the Republic of Kosovo, targeting
adults over 18 years old. As a method for this research, we used a quantitative
method. There are 246 participants in this research, of which 154 or 62.6% were
female and 92 of them or 37.4% were male, ranging from the age of 18 to the age
of 60 years.
Instruments
A high-reliability instrument was used to measure the
level of depression in participants during the Covid-19 pandemic. The
questionnaire initially contained a series of demographic items (age, gender,
education, employment/student status, place of residence, ethnicity, marital
status, and number of inhabitants), followed by the questionnaire to measure
the level of depression by the DASS-21 questionnaire [8]. This is a 21-point
self-report questionnaire, in which we used only depression questions which
assess recent experiences of depression (I felt valuable as a person or I felt
hopeless). Questions are rated on a 4-point Liquid scale ranging from 0 (It was
not like that at all) to 3 (It was like that most of the time). The lowest
scores represent normal or mild levels while the highest scores represent
higher or severe levels.
Organization and
procedure of the research
An online survey was distributed between
November-December 2020 for approximately one month through social media
channels, targeting adults over 18 years old. The questionnaire was translated
into Albanian following the translation procedure. The online survey procedure
was more appropriate for data collection and also appropriate for the time when
our study was conducted. In the survey, respondents were informed that their
participation in the study was voluntary and they could choose to withdraw from
the study whenever they saw fit. The procedure for completing the
questionnaires took about 10 minutes. In terms of ethical consideration,
participants were informed that the questionnaire was anonymous, the data was
confidential and would never be published for various interests that would harm
them. All participants had the right to complete the questionnaire only once.
For any ambiguity, participants had the opportunity to contact the email
provided.
Data analysis
Data was analysed using IBM SPSS v.20. Relevant
analyses were performed upon completion of the SPSS data entry procedure. The
normality test was used as a starting point to look at the data distribution
where abnormal distributions resulted. Spearman correlation analysis was used
to explore the relationship between depression and age. To explore age-based
changes in the level of depression, participants were divided into three age
groups: 18-30 years old (n = 110), 31-45 years old (n = 97) and over 46 years
old (n = 39). The Kruskal–Wallis H test, or one-way ANOVA on ranks, is a
non-parametric method to test age-based differences in the level of depression.
Cronbach's Alpha coefficient level, was used to determine the reliability or
consistency of the proposed questionnaires. Reliability for 246 participants
for the questionnaire resulted in this value: for depression ? = .920 with 7
questions.
Data analyses were performed through the SPSS Statistical Package. In the beginning, descriptive statistics were performed, which show the total number, minimum, maximum, average and standard deviation of the main variables. Spearman correlation was used in order to see the correlation between the variables. The average age of the participants in this study is 32.88 with DS = 10,487 (Tables 1,2).
Table 1: Descriptive statistics for all study variables.
|
N |
Minimum |
Maximum |
Mean |
Std.
Deviation |
Gender |
246 |
- |
- |
- |
- |
Age |
246 |
18.00 |
60.00 |
32.88 |
10.487 |
Depression |
246 |
.00 |
21.00 |
7.9431 |
5.43503 |
Note: DS = standard deviation.
N = number of participants. M = mean. Min=minimum. Max = maximum |
Table 2: Demographic structure of the sample.
Gender |
|
N |
Percent % |
|
Female |
154 |
62.6% |
|
Male |
92 |
37.4% |
Where
do you live |
|
|
|
|
Urban |
171 |
69.5% |
|
Rural |
75 |
30.5% |
Level
of education |
|
|
|
|
High school |
42 |
17.0% |
|
Faculty |
102 |
41.5% |
|
Specialization |
18 |
7.30% |
|
Master |
72 |
29.30% |
|
Doctoral |
12 |
4.90% |
Total |
|
246 |
100.0% |
Table 3 shows the distribution of participants
depending on the severity level of depression, resulting in lower values for
lower levels of severity and vice versa. Depending on the values of the
severity levels of the depression questionnaire, the participants resulted in
the following levels of depression: As a result, for depression 138 (56%)
people were found to have depression with values considered normal, 39 (16%)
mild depression, 67 (27%) people with moderate depression, and only 2 (1%)
person with severe depression (Table 3).
From the correlation analysis of Spearman, it is seen
that age and depression have a negative correlation which means they have a low
negative correlation, so with the increase of one variable the other variable
decreases but not significant correlation (r =-.120; p =.060) (Tables 4,5).
Test results show that there are significant age
differences in depression level ?2 (2) =9.338, p =.009. While in terms of the
average level of depression from 246 participants, 110 are aged 18-30 with an
average of M = 136.62, 97 participants are between the ages of 31-45 and have
an average of M = 106.73, and 39 people over the age of 46 have an average of M
= 128.21. As a result of depression level, people age of 18-30 show the highest
average, while second age group 31-45 show the lowest average.
Table 3: Statistics on levels of conventional severity of depression.
Variable |
|
N |
Percent % |
Depression |
|
|
|
|
Normal |
138 |
56% |
|
Mild |
39 |
16% |
|
Moderate |
67 |
27% |
|
Severe |
2 |
1% |
|
Extremely Severe |
|
|
|
|
|
|
Table 4: Spearman correlation analysis between depression and age.
Spearman’s
rho |
Depression |
Age |
Depression Correlation Coefficient Sig. (2-tailed) N |
1.000 |
-.120 .060 |
Age Correlation Coefficient Sig. (2-tailed) N |
-.120 |
1.000 |
Table 5: Kruskal-Wallis analyze for age difference on depression level.
|
Depression |
|
9.338 |
Df |
2 |
Asymp. Sig. (2-tailed) |
.009 |
Here is a summary of the results obtained from the
research, i.e. the results which are supposed to be possible answers to our
hypotheses. To prove the first hypothesis, we used Spearman correlation
analysis. From Spearman correlation analysis for age and depression, it is seen
that they have a low, non-significant negative correlation (r =.-120; p =.060).
From this result, it follows that the first hypothesis is not accepted due to
the non-significant result. Kruskal Wallis analysis has shown that there is a
difference between these age groups of participants in terms of the level of
depression. The Kruskal-Wallis H test shows that there is a statistically
significant difference in the result, ?2 (2) = 9.338, p = .009. While in terms
of the average level of depression from 246 participants, 110 are aged 18-30
with an average of M = 136.62, 97 participants are between the ages of 31-45
and have an average of M = 106.73, and 39 people over the age of 46 have an
average of M = 128.21. As a result of depression level, people age of 18-30
show the highest average, while second age group 31-45 show the lowest average.
We had hypothesized that because older age was more affected by the situation
with COVID-19 and felt more underestimated during the situation, then the news
on all sides that the number of deaths was higher in late adulthood, it was
expected that the elderly would show higher levels of depression, but it turned
out to be the opposite. This result may also be due to the unequal distribution
of participants by age group, given that 110 are aged 18-30, almost half of the
total number. Another reason could be that young people are not used to being
isolated at work, in society, or for a variety of other reasons that older
people are, and this situation has influenced these results to some extent.
This study has brought new results in the current
Kosovar context but does not mean that the study had no limitations. Regarding
the limitations of this research, we can mention the way of filling in the
questionnaires online. This may affect giving the answer incorrectly, as we
were not present (physically) during the filling in of the questionnaire. Mail
and internet surveys are less costly but have much lower response rates, which is
a limitation. But given the situation we are in, then this was the best way to
collect data and complete the online questionnaire. Perhaps one of the
limitations may be the unequal division of age groups. Therefore, the findings
related to this study objective should be treated with fewer reservations.
However, these findings pave the way and represent the need or recommendation
for further studies with a more comprehensive sample and introduction of other
variables. Regarding the recommendations, this study was done in a way that
fits the situation we are in due to the pandemic and due to the distribution of
the online survey, we recommend that next time the distribution be done
physically.
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