The study was conducted as a cross-sectional study, and sample was collected during a 6th months period (from November 2020 to April 2021) with consecutive patients during outpatient visits at the Clinic of Neurology, University Clinical Center of Vojvodina, Novi Sad, Serbia. All participants were already diagnosed with epilepsy according to the current clinical criteria suggested by the International League Against Epilepsy (ILAE) and were classified according to the recent classification of epilepsy and seizure types [11, 12].
The study was approved by the Independent Ethical Committee of the University Clinical Center of Vojvodina and all patients gave their written informed consent to participate.
Inclusion criteria were: 1. Age ≥ 18 years, 2. Interictal period, at least 24 hours after the last epileptic seizure, 3. Stable antiseizure therapy regime in the last 3 months
Exclusion criteria were: 1. Patients < 18 years, 2. The presence of other significant psychiatric (acute psychotic conditions, psychosis), neurological and somatic diseases (active malignant diseases), as well as cognitive impairment (diagnoses of intellectual disability and dementia), including psychogenic non-epileptic seizures, 3. Severe head injury or craniotomy in the past year.
In order to collect data, structured scales were created for the clinical characteristics of the disease and sociodemographic data.
The following clinical data were analyzed: age at the onset of epilepsy, duration of epilepsy, number of types of epileptic seizures, types of epileptic seizures, type of epilepsy (active epilepsy-occurrence of epileptic seizures in the previous two years, inactive epilepsy-no epileptic seizures in the previous two years), frequency and intensity of seizures in the past year (no seizures, low, moderate, high)*, etiology of epilepsy, presence of a symptomatic lesion on brain imaging, current antiseizure medication therapy, comorbidities and concomitant therapy, past history of depression or the presence of a depressed mood in any period of life, previous or current antidepressant therapy, data on febrile seizures in childhood, positive heredity for epilepsy and depressed mood.
The following demographic data were analyzed: age, gender, marital status, place of living, level of education, employment status, possession of a driver's license.
*To assess the severity of epilepsy, we used the severity of the seizures, which, according to the recommendation of Baker et al. was defined as a composite measure of frequency and type of seizures. The assessment of the frequency and intensity of epileptic seizures was carried out on the basis of anamnestic data, a diary (calendar) of seizures, as well as a scale for measuring the intensity of seizures. According to the severity of the disease, patients were divided into 4 groups, which were defined on the basis of a composite measure that included the type and frequency of epileptic seizures (no seizures, low, moderate, high) [13].
The following self-assessment scale was used to assess depressive symptoms:
Beck Depression Inventory-II, BDI-II [14]- created in 1996 and represents the second edition, is the most widely used instrument for determining depression in the world. It is in wide clinical use with satisfactory psychometric characteristics (α = 0.92). It belongs to the group of self-assessment scales and is completed relatively quickly (5 to 10 minutes). The scale consists of 21 descriptive items, where the offered answers are presented in the form of a four-point Likert scale, with higher total score indicative of greater severity of symptoms. The degree of expressiveness of depressive symptoms can be quantified as follows: 14–19 indicate mild depressive symptoms, 20–28 indicate moderate depressive symptoms, 29–63 indicate severe depressive symptoms. This scale was developed as an indicator of the presence and severity of depressive symptoms, and not as an instrument for specifying a clinical diagnosis. The scale was validated on our patient population. It was administered to each patient on individual basis during the study.
In the present study, the reliability of BDI-II based on Cronbach alpha coefficient (α = .960) was high, as found in previous studies [15]
Data analysis
SPSS 20.0 software package was used for data entry and processing. For the purposes of analysis and description of the structure of the sample according to relevant variables, frequency and percentage displays were used, in order to show the representation of a certain category or response. Numerical characteristics of observations were processed using standard procedures of descriptive and comparative statistics for the analysis of numerical characteristics. Descriptive statistics methods were used to determine measures of central tendency (arithmetic mean), measures of variability (standard deviation) and extreme values (minimum and maximum) of observed numerical characteristics. Within the methods of comparative statistics, to determine the differences between two independent samples, the following were used: Student's t-test or Mann-Whitney's U-test (if the size of the subsample was insufficient); to test the differences of several independent samples, the following were used: One-way analysis of variance or the Kruskal-Wallis H test (if the subsample size was insufficient). The existence of a statistically significant difference between the frequency distributions of individual groups was checked using the Chi-square test. In order to determine the relationship between different variables, Pearson's linear correlation coefficient was applied. Using Binary Logistic Regression, the predictive significance of various factors/parameters on depressive status was assessed.
The statistical analysis of the data was also performed by analyzing the so-called ROC (Receiver Operating Characteristic) curves. The ROC aimed to establish the discriminative power (sensitivity and specificity) of various parameters/measures in separating patients who are depressed from those who are not. In the applied tests, the limit values of the probability of risk are at the significance level of 95% (p < 0.05) (difference in statistical parameters significant) and 99% (p < 0.01) (difference in statistical parameters highly significant). To check the reliability of the BDI-II scale as a whole, the measure of internal consistency expressed by Cronbach's alpha coefficient was used.