Common mental disorders and its determinants among epileptic patients at an outpatient epileptic clinic in Felegehiwot Referral Hospital, Bahirdar, Ethiopia: cross-sectional study
Epilepsy is a chronic neurological condition that is highly predisposed to a variety of mental health problems due to its huge biological, social and psychological burdens. Despite this, there is a paucity of research in this area. Therefore, assessing common mental disorders and its determinants among epileptic patients would be of great importance.
Objective
This study was aimed to asses prevalence and associated factors of common mental disorders among people with epilepsy attending Felegehiwot Referral Hospital, Bahirdar, Ethiopia, 2019.
Methods
Institutional based analytic cross-sectional study design was utilized from January to February 2019 at Felegehiwot Referral Hospital among 422 epileptic patients who were diagnosed clinically and on follow up treatment. Systematic random sampling was applied to recruit participants. Interviewer based and pretested Self Reporting Questionnaire‐20 was used to screen common mental illness with a cut-off point 7 and above as having a common mental disorder. Bivariate and multivariable logistic regression analysis with 95% CI were computed and variables with p < 0.05 in the final model were considered as associated factors for common mental disorders.
Result
Four hundred twenty-two patients with epilepsy were included in our study with a response rate of 100% and 64.5% were males. The mean age of participants was 59 ± 13.37 years. Common mental disorder among epileptic patients was found to be 35.8%. There was a statistically significant association between marital status, comorbid medical illness, nicotine dependence, alcohol misuse, and medication non-adherence with common mental disorders at p < 0.05.
Conclusion
The prevalence of common mental distress was high (35.8%) suggesting that it is a public health issue. Marital status, comorbid medical illness, nicotine dependence, alcohol misuse, and medication non-adherence were the factors having an association with a common mental disorder. Therefore, early screening and recognition of mental distress symptoms should be a routine activity while managing epileptic patients.
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Abkürzungen
AED
anti-epileptic drugs
CBE
community based education
CIDI
Composite International Diagnostic Interview
CMD
common mental disorders
EEG
electro encephalon gram
GABA
γ‐amino butyric acid
OPD
out patient department
PWE
patient with epilepsy
SRQ
self reporting questionnaires
USA
United States of America
WHO
World Health Organization
Background
Epilepsy is defined as a neurological condition that is characterized by two or more unprovoked seizures according to the international league against epilepsy [1]. It is a chronic neurological condition estimated to affect 50 million people worldwide according to WHO [2]. Despite the worldwide prevalence of active epilepsy varies from 0.2 to 4.1% [3], higher prevalence and incidence are from low and middle-income countries (LMICs) when compared with developed countries [4, 5]. In fact, more than 85% of the global burden of epilepsy occurs in people living in LMICs [6, 7]. Epilepsy poses a multidimensional effect on the body like physical, mental and behavioral functions limitations and is associated with great risk of premature mortality due to factors like a traumatic injury to the brain, status epilepticus, suicide, pneumonia and sudden death [8, 9].
Common mental disorders define a range of anxiety and depressive disorders. Globally, 150 million individuals are affected by depression and 1 million commit suicide every year. Four of the top six causes of years lived with disability are due to neuropsychiatric disorders and more than 90 million suffer from alcohol or other substance use disorders [10, 11]. Projections to 2030 indicate that depression will be the leading cause of disability globally accounting for 6% of all [12]. The global rate of prevalence for depression ranges from 3.6 to 5.4% in the Western Pacific and African Region respectively. Whereas, anxiety disorders, rates from 2.9% in the Western Pacific Region to 5.8% in the Region of the Americas [13].
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Studies done reported that a high prevalence of psychiatric disorders in people with epilepsy [14‐16] and a higher risk of psychopathology compared with the general population or people with chronic non-neurological disorders [17]. Most (88%) of the patients experienced psychiatric disturbances and the most common psychiatric symptoms were neurovegetative (62%), anxiety (45%), and depression (43%), cognitive difficulties 82% [18]. Other studies showed that the prevalence of psychiatric disorders was 70% in Brazil [19], 25% for anxiety disorders, 19% for mood disorder in Dutch [20], 5.9% in Sweden [21], 52% in Iceland [22], 34.2% for mood disorder and 22.8% for anxiety [14], 50% of patients with epilepsy in United States [23].
Risk factors for common mental disorders among epileptic patients were family history of psychiatric illness [24], comorbidity of medical condition [25], being female, young age, lower-income, worse QOLIE-89 scores, more adverse drug events, unemployment [26], high seizure frequency, and low educational status in southwest Ethiopia [27], duration of illness, seizure frequency, poly-pharmacy, difficulties of adherence to antiepileptic drugs in northwest Ethiopia [28].
Common mental disorders reduce health-related quality of life (HRQOL) in patients with epilepsy [29, 30]. Comorbid depression in epileptic patients had socio-economic and physical consequences like disability in the social domain, cost of drug use and premature death [31, 32]. In addition, it affects the cognitive function of epileptic patients especially if they are not treated early or timely with the antiepileptic drug [33] and common mental disorder increases the risk of developing adverse effects of anti-epileptic medications [34]. Besides, anti-epileptic drugs have a psychotropic effect that affects the brain negatively [35]. Moreover, the suicide rate in epilepsy is five times higher and depression will be a risk factor for seizure [36].
Despite this, there is a paucity of research into this area, especially in the Ethiopian context. Even those studies have done so fare focused mainly on a specific mental disorder like depression. As per the investigators’ knowledge, there is no study done regarding the prevalence and associated factors of common mental disorders among epileptic patients in the study area.
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Therefore this study was aimed to asses common mental disorders in epileptic patients and its associated factors, which would fill the gap in information by generating updated information and services as baseline evidence for future researchers and policymakers.
Methods and materials
Study design and setting
Institution based analytical cross-sectional study was implemented at Felegehiwot Referral Hospital, Bahirdar, Ethiopia from January to February 2019. This study was conducted at the Epileptic clinic of Felegehiwot Referral Hospital. The hospital is located in Bahirdar; which is the Capital City of the Amhara Region. The hospital services a catchment population of more than 5.5 million people [37].
Study participants
Participants were all epileptic patients registered for follow up of anti-epileptic medication in the Epileptic clinic of Felegehiwot Referral Hospital and as evidenced from the registration book, more than 3150 patients have a history of follow up for epilepsy in the clinic. On average 225 epileptic clients visit the clinic weekly so that the total number of epileptic patients estimated to attended follow up during the data collection period is 900. The optimal size of the sample had been calculated using a single population proportion formula; by taking the prevalence of common mental disorder 49.3% from a study conducted in Jimma [38] with a 5% margin of error and 95% confidence interval of certainty (alpha = 0.05) and 10% non-response. Based on these assumptions, the sample size for the study was computed to be 422.
A systematic sampling method was applied to recruit eligible participants. The sampling interval was determined by dividing the average number of epileptic patients attending outpatient follow up monthly (900) by total sample size (422) (N/n (K = 2)). The first participant had been included by the lottery method and every 2nd case of epileptic patients attending care and treatment at Felegehiwot Referral Hospital were considered for the survey.
All follow up epileptic cases in the study period whose age was 18 years and above were allowed to take part in the study whereas those Epileptic patients unable to communicate during the interview were excluded.
Operational definitions
Common mental disorder A score ≥ 7 on Self-reporting questionnaires SRQ-20 [39].
Epilepsy In this study, epilepsy refers to a neurological condition characterized by two or more unprovoked seizures [1].
Ever substance use use of a specified substance for non-medical purposes at least once in their lifetime. Alcohol use problem: For alcohol use disorders CAGE was used which had a score of 0–4 and cutoff point 2 [40].
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Tobacco use problem as assessed by Fagerstrom Test a score 1 was considered as nicotine dependence [41].
Adherence to medication adherence was considered as low, medium and high with a score < 6, 6 and 7, and 8 respectively on 8-Item Morisky 8-item medication adherence scale [42‐45].
Social support Poor social support, Moderate social support, and Good social support were operationalized at cut-off points 3–8, 9–11, and 12–14 points respectively on the Oslo-3 social support scale [46].
Data collection procedure
Questionnaires prepared in English and translated to Amharic were used to collect the data. An interviewer based questionnaire was used to collect data regarding common mental disorders using a standardized and valid SRQ questionnaire having 20 items was used to assess common mental disorders [39]. A cutoff point 7 and above was considered for delineating the presence of common mental disorders. SRQ-20 asses common mental symptoms in the past 30 days as Yes/No and Its Amharic version had been validated in Ethiopia [47] and used in several institutions based [48‐51] as well community-based studies in Ethiopia [52‐54].
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Alcohol misuse was assessed using CAGE 4 items questions which had a score of 0–4 and with sensitivity 0.71 and specificity 0.90 at a cutoff point ≥ 2 [55] and used in several previous studies [56‐59] for screening people who have problem drinking.
Nicotine dependence was assessed by Fagerstrom Test, a score ≥ 1 indicates tobacco use problem reliability coefficient(a) = 0.8 [41]. Morrisk-8 medication adherence scale was used to asses adherence to medication: low-adherence if a score is < 6, medium adherence if a score is 6 and 7, and high adherence if a score is 8 on 8-Item Morisky medication adherence scale [42‐45]. Social support as assessed by Oslo-3 social support scale Poor social support, Moderate social support, and Good social support were operationalized at cut-off points 3–8, 9–11, and 12–14 points [46].
Data quality assurance
The questionnaire was pre-tested on 22 (5%) of the sample at Borumeda hospital 1 week before the actual data collection period. Data was collected by BSc psychiatry nurses after adequate training was given about research aims, procedures, and ethical issues. The collected questionnaire was checked for clarity, consistency, and completeness by the investigators every day and necessary corrections were made before the start of the next day’s work. Double data entry was done for reliability and correctness and computer data cleaning was undertaken.
Data processing, analysis, and interpretation
Epi-info version 7, was used as a data entry tool and the Statistical Packages for Social Sciences version 20 (SPSS-20) was utilized to analyze data after it was exported. Descriptive statistics (percentages, mean, median, standard deviation and crosstabs) were utilized to summarize common mental disorder and its predictor variables. A logistic regression model was fitted to asses potential risk factors for a common mental disorder. Variables with p value < 0.25 in bivariate analysis were pooled into multivariable logistic regression. Odds ratio with 95% CI was employed to measure the strength of association and statistical significance was set at a p-value of < 0.05 in the final model.
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Result
Socio-demographic characteristics of the respondents
A total of 422 patients with epilepsy on follow-up treatment and evaluations at Felegehiwot Referral Hospital participated in the study with a response rate of 100%. The mean age of the participants was 30.7 years, with a Standard Deviation of 10.28 years and most of, 120 (28.4%) were between the age of 25–34 years. More than half (55.2%) of the respondents were males. A higher proportion (67%) of study participants had urban residency. Nearly two-thirds (62.6%) of the study participants were Muslims. About 229 (54.3%) of the participants were married and nearly one-fourth (25.6%) are farmers (Table 1).
Table 1
Sociodemographic characteristics of epileptic patients attending Felegehiwot Referral Hospital epileptic clinic (n = 422), Bahirdar, Ethiopia, February 2019
Characters
Classification
Frequency
Percent
Have no mental distress N (%)
Have mental distress N (%)
Sex
Male
233
55.2
151 (64.8)
82 (35.2)
Female
189
44.8
120 (63.5)
69 (36.5)
Age
18–24 years
120
28.4
79 (65.8)
41 (34.2)
25–34 years
170
40.3
115 (67.6)
55 (32.4)
35–44 years
92
21.8
54 (58.7)
38 (41.3)
45 and above
40
9.5
17 (42.5)
13 (57.5)
Marital Status
Married
229
54.3
150 (65.5)
79 (34.5)
Single
176
41.7
111 (63)
65 (37)
Divorce/separate/widowed
17
4
10 (58.8)
7 (41.2)
Religion
Orthodox
128
30.3
75 (58.6)
53 (41.4)
Muslim
264
62.6
177 (67)
87 (33)
Protestant
29
6.9
19 (65.5)
11 (34.5)
Address
Urban
266
63.0
171 (64.3)
95 (35.7)
Rural
156
37.0
100 (64)
56 (36)
Educational Status
Illiterate
54
12.8
36 (66.7)
18 (33.3)
Can read and write
71
16.8
42 (59)
29 (41)
Primary
78
18.5
49 (62.8)
29 (37.2)
Secondary
146
34.6
103 (70.5)
43 (29.5)
College and above
73
17.3
41 (56)
32 (44)
Occupational Status
Farmer
108
25.6
69 (63.9)
39 (45.1)
Gov’ t employers
97
23.0
63 (64.9)
34 (35.1)
Self-employee
101
23.9
64 (63.4)
37 (36.6)
Student
93
22.0
60 (64.5)
33 (35.5)
Other
23
5.5
15 (65.2)
8 (34.8)
Monthly income
< 700
215
50.9
193 (78.8)
22 (20.2)
700–1499
24
5.7
22 (91.7)
2 (8.3)
> 1500
183
43.4
163 (89)
20 (11)
Clinical characteristics of epileptic patients
One hundred ninety-seven (46.7%) of epileptic patients were taking anti-epileptic medication for less than 5 years and the type of anti-epileptic medications most study participants using was phenobarbitone 148 (73.3%). Regarding the controllability of seizure, most 375 (88.8%) had controlled seizure by current medication and did not complain epileptic fits in spite of taking their medications, 40 (9.5%) were having 1–2 seizure attacks while taking medication in the last 30 days and 7 (1.7%) of the respondents had 3–12 seizure attack even though they were on medication (Table 2).
Table 2
Clinical characteristics of epileptic patients attending Felegehiwot Referral Hospital epileptic clinic (n = 422), Bahirdar, Ethiopia, February 2019
Variables
Category
Frequency
Percent
Number of seizure attack the last 30 days
1–2
40
9.5
3–12
7
1.7
Never
375
88.9
Duration on AED medication
< 5 years
197
46.7
5–10 years
119
28.2
> 10 years
106
25.1
Epileptic fits
Yes
42
9.9
No
380
90.1
History of chronic medical illness
Yes
15
3.6
No
407
96.4
Lifetime substance use
Yes
186
44.1
No
236
55.9
Substance use in the last 30 days
Yes
94
22.3
No
328
77.7
Alcohol misuse
CAGE ≥ 2
36
8.5
CAGE < 2
386
91.5
Nicotine dependence
Yes (FTND ≥ 1)
30
7.1
No (FTND < 1)
392
92.9
Medication adherence
Low
394
93.4
Intermediate
24
5.7
High adherence
4
0.9
Family history of mental illness
Yes
7
1.7
No
415
98.3
Social support
Poor
82
19.4
Moderate
254
60.2
High
86
20.4
CAGE Cut down, Annoyed, Guilty feeling and Eye opener; FTND Fagerstrom Test of Nicotine Dependence
Prevalence of common mental disorders among epileptic patients at Felegehiwot Referral Hospital
A cut-off point 7 on the self-reporting questionnaire-20 was used [39]. epileptic patients who scored 7 and above on the SRQ-20 were categorized as having common mental disorders while those scoring less than 7 on the SRQ-20 classified as not having common mental disorders. The prevalence of the common mental disorder in this study was 35.8% (95% CI 30.8, 40.4) (Fig. 1). The high common mental disorder was observed in the age group 45 years and older (57.5%) and divorced/widowed groups had high CMD (41.2%). The most prominent common mental disorder symptoms in this study were a headache (43.6%), poor appetite (41.5%), poor sleeping conditions (34.6%) and feeling tired all the time (24.6%). Suicidal ideation was complained by 74 (17.5%) of participants (Table 3).
Fig. 1
Prevalence of common mental disorders among Epileptic patients attending Felegehiwot Referral Hospital epileptic clinic (n = 422), Bahirdar, Ethiopia, February 2019
Table 3
Common mental disorder symptoms of epileptic patients attending Felegehiwot Referral Hospital epileptic clinic (n = 422), Bahirdar, Ethiopia, February 2019
Characters
Classification
Frequency
Percent
Do you often have headache?
Yes
184
43.6
No
238
56.4
Is your appetite poor?
Yes
175
41.5
No
247
58.5
Do you sleep badly?
Yes
146
34.6
No
276
65.4
Are you easily frightened?
Yes
75
17.8
No
347
82.2
Do your hands shake?
Yes
60
14.2
No
362
85.8
Do you feel nervous, tense or worried?
Yes
86
20.4
No
336
79.6
Is your digestion poor?
Yes
71
16.8
No
351
83.2
Do you have trouble thinking clearly?
Yes
82
19.4
No
340
80.6
Do you feel unhappy?
Yes
75
17.8
No
347
82.2
Do you cry more than usual?
Yes
87
20.6
No
335
79.4
Do you find it difficult to enjoy your daily activities?
Yes
82
19.4
No
340
80.6
Do you find difficult to make decision?
Yes
78
18.5
No
344
81.5
Is your daily work suffering?
Yes
88
20.9
No
334
79.1
Are you unable play a useful part in life?
Yes
89
21.1
No
333
78.8
Have lost interest in things?
Yes
78
18.5
No
344
81.5
Do you feel that you are a worthless person?
Yes
67
84.1
No
355
15.9
Has the thought of ending your life been on your mind?
Yes
74
17.5
No
348
82.5
Do you feel tired all the time?
Yes
104
24.6
No
318
75.4
Are you easily tired?
Yes
80
81
No
342
19
×
Factors associated with common mental disorders among epileptic patients
Variables which pass into multivariate analysis with p-value < 0.2 on bivariate regression were age, marital status, educational level, religion, current epileptic medication, duration of epilepsy, mental illness in family, comorbid medical illness, alcohol dependence, nicotine dependence, medication non adherence and frequency of seizure but only marital status, comorbid medical illness, alcohol dependence, nicotine dependence, medication non adherence were significantly associated in final model with p-value < 0.05.
Participants who were divorced, widowed and separated as a group were about two times more likely (AOR = 1.95, 95% CI 1.67, 5.67) to develop the common mental disorder as compared to participants with a sustained marital relationship. The odds of study participants to develop a common mental disorder in the presence of comorbid medical illness was three times higher relative to participants with no comorbid medical condition (AOR = 2.99, 95% CI 1.95, 9.39).
Alcohol dependence was significantly associated with a common mental disorder. Participants with Alcohol dependence as measured by CAGE ≥ 2 were 2.2 times more likely to have mental disorder as compared to those who score CAGE < 2(AOR = 2.20, 95% CI 1.78, 3.93). The odds of developing mental disorder among nicotine-dependent participants was slightly higher (AOR = 1.52, 95% CI 1.46, 4.62) relative to those participants with no nicotine dependence. Poor medication adherence was 2 times higher a risk factor to predispose to common mental disorder than good medication adherence (AOR = 1.9, 95% CI 1.72, 3.56) (Table 4).
Table 4
Bivariate and multivariable Logistic Regression analysis Result of the factors for common mental disorder among epileptic patients at Felegehiwot Referral Hospital, Bahirdar, Ethiopia, 2019 (n = 422)
Explanatory variable
CMD
COR (95% CI)
AOR (95% CI)
Yes
No
Marital status
Married
79
150
1.00
1.00
Single
65
111
1.12 (0.74, 1.67)
1.37 (0.76, 2.44)
Divorced/separated
7
10
1.34 (1.17, 3.63)
1.95 (1.67, 5.67)a
Age of participants
18–24
41
79
1.00
1.00
25–34
55
115
0.9 (0.56,1.52)
1.04 (0.54, 2.03)
35–44
38
54
1.36 (0.78, 2.38)
1.37 (0.57,3.18)
45 and above
13
17
1.43 (0.68, 2.96)
1.8 (0.67, 4.85)
Duration epileptic rt.
< 5 Years
79
118
1.00
1.00
5–10 Years
41
78
1.62 (0.96, 2.69)
0.78 (0.46, 1.33)
> 10 years
31
41
1.27 (0.73, 2.24)
0.50 (0.27, 0.91)
Type of AEM
Phenobarbitone
110
190
1.00
1.00
Phenytoine
30
48
1.74 (0.56,5.52)
1.18 (0.63, 2.19)
Carbamazipine
7
21
1.88 (0.55,6.35)
0.55 (0.21, 1.42)
Valporic acid
4
12
1.02 (0.24, 4.13)
0.73 (0.22,2.46)
Comorbid illness
Yes
8
7
2.1 (1.75, 5.93)
2.99 (1.95, 9.39)b
No
143
264
1.00
1.00
Alcohol misuse
CAGE score ≥ 2
20
131
2.43 (1.91, 4.85)
2.20 (1.78, 3.93)b
CAGE score < 2
16
255
1.00
1.00
Nicotine dependence
FTND score ≥ 1
14
16
1.63 (1.77, 6.44)
1.52 (1.46, 4.62)b
FTND score < 1
137
255
1.00
1.00
Medication adherence
Good
11
29
1.00
1.00
Poor
140
242
1.53 (1.24, 3.15)
1.9 (1.72, 3.56)b
Mental illness in family
Yes
5
2
4.6 (0.88, 24.00)
4.88 (0.79,29.8)
No
146
269
1.00
1.00
ap-value < 0.05, bp-value < 0.01, Model Chi square = 2.96, df = 8 and sig = 0.937
Discussion
Common mental disorders were prevalent in 35.8% of participants in this study. Comorbidity of a medical condition, nicotine dependence, alcohol dependence, medication non-adherence, and divorce/widow were the factors significantly associated with common mental disorders. This magnitude implied that large numbers of epileptic patients had not yet received an adequate intervention for psychiatric disorders specifically for a common mental disorder. So this result revealed that intervention has to be given for such comorbid-psychiatric problems in the epileptic clinic. Moreover, this finding strengthens the need for linkage of services between a psychiatric and neurological service for epileptic patients.
The prevalence of Common mental disorder in this study was in line with studies conducted so far in the USA (36.5%) [26], two Europe studies (37%) [60], (28.6%) [61], Iceland (35.5%) [62] and Ethiopia (35%) [63].
On the other hand, finding of current study was lower than the studies in Brazil (54.1%) [64], USA (70%) [65], (47%) [66] and (78%) [67], Netherlands (75.2%) [20], Iceland (54.8%) [22], Europe (54.8%) [68] and Italy (80%) [69], Ethiopia (45%) [28].The variation in prevalence might be due to the difference in sample size and assessment instruments used. Only 94 participants were included in Brazilian study [64], 60 participants in USA [65], 131 participants USA [67], 88 participants in Europe [68], and 38 participants in Italy [69] and 209 participants in the Netherlands study [20]. Methodological differences like DSM-IV in Brazilian [64], Iceland [22] and USA studies [65], Kessler-6 in the USA [66] and health style interview in the USA [67], CIDI in Netherlands study [20] would also contribute to the difference. Moreover, the study population in which the current study asses all forms of epilepsy but only temporal lobe epilepsy in other studies that had a higher risk of mental disorders [70‐72] might cause the variation.
The result of the study was higher than the studies conducted in Canada (23.5%) [14], in northern Sweden (5.9%) [73], in two European studies (11.2%) and (29%) [74, 75]. The different would be attributed to variation in sample size. In the northern Sweden study, a larger sample size of 713 patients with epilepsy was included. The difference in assessment instruments; Hospital anxiety and depression scale was used in European study [74], CIDI was used in Canadian [14] study and unstructured psychiatric interview in European study [73] might also contribute to the variation in the prevalence of the common mental disorder.
Divorce/separation was associated with CMD in this study, which was two times higher risk to develop common mental disorders as compared to married study participants who live together. This was supported by the study done at Emanuel specialized hospital, Addis Ababa, Ethiopia [63] and other studies outside Ethiopia [32, 76]. Divorce is a major psychosocial stressor predisposing to chronic stress which might disturb the social and emotional domains finally leading to common mental disorders.
Comorbidity of medical condition was also associated with a common mental disorder, three times higher risk as compared to participants with no comorbid medical illness. The finding is consistent in previous studies [25, 32] This might be due to medical conditions affecting the quality of life epilepsy patients as supported with a study [77].
Being alcohol dependence had a 2.2 times higher risk of developing a common mental disorder as compared with epileptic patients who had no alcohol dependence. This was supported by comparable studies in the USA [78, 79], New Zealand [80]. The reason might be alcohol consumption causing increased GABAergic neurotransmission and nervous system depression since GABA is inhibitory neurotransmitter [81]. Alcohol might also reduce seizure threshold and increase seizure frequency by affecting calcium and chloride flux through the ion‐gated glutamate and GABA receptors [82] and this might affect patients’ quality of life.
Having poor medication adherence was two times a higher risk factor for common mental disorder than good medication adherence. This was supported by a study outside Ethiopia [83] and in Ethiopia [28]. Non-adherence will lead to reduced seizure control, lowered quality of life, decreased productivity, seizure-related job loss [84] and recurrence of seizures might complicate to mental disorders [85] and since bidirectional interaction between epilepsy and mental disorders; up to 60% of epileptic patients develop depression and depression increase the risk of epilepsy [86, 87].
Nicotine dependence was a risk factor for CMD in this study, which was 1.5 times higher risk to develop common mental disorders as compared to participants who have no nicotine dependence. This was supported by a study finding that asses smoking as a risk factor for major depression [88] and mental illness in general [89] The reason might be due to cigarette smoking increases risk of seizure recurrence [90] which might, in turn, lowers quality of life of epileptic patients.
Conclusion
This study found that common mental distress among epileptic patients was high. Divorce from socio-demographic variables, clinical variables such as comorbidity of medical illness, medication non-adherence and substance-related factors like alcohol misuse and nicotine dependence were risk factors for common mental disorder in this study. Early screening and treatment of epileptic patients have to be a routine activity to be conducted in epileptic clinics.
Acknowledgements
We would like to express our gratitude to Wollo University College of medicine and health science and Felegehiwot Referral Hospital for all forms of non-financial support provided throughout the study procedures. Furthermore, we thanks data collectors, supervisors and participants of the study for their participation.
Ethics approval and consent to participate
The study was approved by the ethical review board of Wollo University. Participants were fully informed about the study and verbal consent was received from each participant before the start of the interview. Information was collected anonymously and kept confidential throughout the study.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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Common mental disorders and its determinants among epileptic patients at an outpatient epileptic clinic in Felegehiwot Referral Hospital, Bahirdar, Ethiopia: cross-sectional study
Wenn Demenzkranke aufgrund von Symptomen wie Agitation oder Aggressivität mit Antipsychotika behandelt werden, sind damit offenbar noch mehr Risiken verbunden als bislang angenommen.
Die Kombination aus Medikamenten und Psychotherapie gilt als effektivster Ansatz bei Depressionen. Das ist bei betagten Menschen nicht anders, trotz Besonderheiten.
Um Menschen nach der Flucht aus einem Krisengebiet bestmöglich medizinisch betreuen zu können, ist es gut zu wissen, welche Erkrankungen im jeweiligen Herkunftsland häufig sind. Dabei hilft eine Internetseite der CDC (Centers for Disease Control and Prevention).
Update Psychiatrie
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