Common mental disorders and associated factors among adult patients admitted in non-psychiatric wards of public hospitals in Harari regional State, Eastern Ethiopia

Abstract

Introduction

Common mental disorders represent psychiatric co-morbidity in medical illness, which leads to poor adherence to treatment, increased exposure to diagnostic procedures and the cost of treatment, longer hospital stay, and increasing the risk of complications that result in morbidity and mortality among patients admitted to non-psychiatric wards. There is a dearth of evidence related to the prevalence of common mental disorders and associated factors among adult patients admitted to non-psychiatric wards, particularly in the study area. This study aimed to assess the prevalence of common mental disorders and associated factors among adult patients admitted to non-psychiatric wards of public hospitals in the Harari region, eastern Ethiopia.

Methods

An institutional-based cross-sectional study was conducted among 640 randomly selected patients admitted to non-psychiatric wards from November 15 to December 15, 2022. A systematic random sampling technique was employed to select the study participants. Data were collected by interviewer-administered structured and semi-structured questionnaires. Self-report questionnaire (SRQ-20) was used to assess the presence of common mental disorders. The collected data were entered into Epi-data version 3.1 and exported to STATA version 14 for analysis. Bivariable and multivariable logistic regression were used to evaluate the association between independent and the outcome variable. Variables with a p-value < 0.05 were taken as statistically significant with an adjusted odds ratio and 95% confidence interval.

Results

The prevalence of common mental disorders among adult patients admitted to non-psychiatric wards was found to be 45.3%, with a 95% CI: of 41.3–49.2. Age 41–51 years (AOR = 1.732, 95% CI: 1.030, 2.913), age 51 and above (AOR = 2.429, 95% CI: 1.515, 3.894), staying at hospital for 1–2 weeks (AOR = 1.743, 95% CI: 1.065, 2.853), staying at hospital for more than 4 weeks (AOR = 2.12, 95% CI: 1.77, 3.29), history of mental illness (AOR = 5.841, 95% CI: 2.274, 15.004), stressful life events (AOR = 1.876, 95% CI: 1.206, 2.9196), current substance use (AOR = 1.688, 95% CI: 1.75, 2.650), and poor social support (AOR = 2.562, 95% CI:1.166, 5.629) were factors significantly associated with common mental disorders.

Conclusion

The prevalence of common mental disorders among patients admitted to non-psychiatric wards was high. It appears to be significantly associated with age, length of hospital stay, history of mental illness, stressful life events, current substance use, and social support. The study suggested that patients who are admitted to non-psychiatric wards should be screened for common mental disorders and its associated factors as part of routine inpatient care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12888-025-06475-2.

Introduction

Common mental disorders (CMD) are a group of mental disorders frequently occuring among primary care patients. They include symptoms of depression, anxiety, and somatization [1] and more common in medical than in community settings [2]. Most patients present at health facilities with medical rather than psychiatric complaints [3] and some chronic medical illnesses may produce somatic symptoms similar with CMD, leading to misdiagnosis [4]. Due to this, CMD became a global health burden that remains under-estimated even by healthcare providers, particularly in non-psychiatric wards [5].

Common mental disoders are neglected co-morbid mental health problems imposing an extra burden on the patients with non-psychiatric diseases as evidenced by worsening of the condition, increased exposure to diagnostic procedures, increased cost of treatment and reduced efficacy of treatment [6, 7]. This in turn leads to inefficient medical services and increases the risk of complications and mortalities among patients admitted to non-psychiatric wards [8, 9].

Globally, over 450 million people are estimated to have CMD, and nearly one in four people meet the diagnostic criteria in their lifes. Prevalence of CMD in the community ranges from 14 to 15% by the year 2020, making it the second leading cause of health disability in undeveloped countries [10]. CMD are frequently misdiagnosed as physical illnesses,where its prevalence ranges from 4 to 46% and 23 to 58% in various inpatients receiving care in a non-psychiatric wards in developed and developing countries respectively, and the majority of the people suffering from these disorders do not receive appropriate treatment and care, especially in developing countries [8].

Even though CMDs are regarded as “invisible disorders,” they are not outwardly visible to others, even by health professionals, and policymakers yet cause significant health burdens, or the attention given is very low across the globe. The burden of CMD is probably underestimated as many patients with CMD complain somatic symptoms and receive less attention in African nations [11]. This is even worse in developing countries like Ethiopia [12, 13].

There is a dearth of research on the prevalence of common mental disorders among patients admitted to non-psychiatric wards in Ethiopia particularly in study area. Few studies those do exist primarily concentrate on community and some institutional-based studies focus on patients in medical and surgical wards [14, 15]. However, patients with burn, gynecologic, orthopedic, or oncologic conditions were excluded from the study. Therefore, the aim of this study was to comprehendly assess the prevalence of common mental disorders and associated factors among patients admitted to non-psychiatric wards.

Methods

Study setting, and period

Harari regional State is located in the eastern part of Ethiopia, which is 525 km from Addis Ababa. Harar is the capital city of the Harari region, with an area of 1720 km². The region has two general hospitals, one TB center, nine health centers, 17 community health posts, one regional public health laboratory and research center, and one nursing school. Moreover, there are two major public hospitals in Harar town, namely Haramaya University Hiwot Fana Comprehensive Specialized Hospital and Jugel Hospital. Haramaya University Hiwot Fana Comprehensive Specialized Hospital is one of the teaching hospitals in Ethiopia [16, 17]. The data obtained from Liaison and Inpatient Director of the hospital indicates that currently, it has Adult emergency and critical center, Pediatrics, Surgery, Internal medicine, Neurology, Ophtalmology, Psychiatry, Gynecology, Obstetrics, Oncology, Orthopoedics, and Burn unit with 423 bed and 32 outpatient department (OPD) [17]. Jugel Hospital is the first hospital founded in Harar town and it currently contains 9 wards with 93 beds, including Surgical, Medical, Pediatrics, CICU, Adult emergency, Gynecology and Obstetrics wards, Dialysis center, Ophthalmology, and isolation ward. Additionally, it has seven outpatient departments [16]. The study was conducted from November15, to December, 15, 2022.

Study design

An institution-based, cross-sectional study was conducted.

Source population

The source population were all adult patients who were admitted to non-psychiatric wards of public hospital’s in Harari regional state.

Study population

The study population were all adult patients who were admitted to non-psychiatric wards of public hospital in Harari regional state and available during data collections periods.

Inclusion criteria

All individuals who were within an age greater than or equal to 18 years were included.

Exclusion criteria

Participants, who were unable to communicate with critical illnesses that have a known psychiatric illness and post-anesthesia during the data collection period, were excluded.

Sample size determination and sampling method

The sample size was calculated by using the single population proportion formula, considering the following assumptions: $\mathit{n}=\frac{{\left(\mathit{Z},\frac{\mathit{\alpha }}{2}\right)}^2\mathit{p}\left(1,-,\mathit{p}\right)}{{\mathit{d}}^2}$

Where:

n = minimum sample size required for the study.

Z = standard normal distribution (Z = 1.96) with confidence interval of 95% and ⍺ = 0.05.

P = 58.6% previous study conducted at University of Gondar Hospital was used [18].

d = Absolute precision or tolerable margin of error = 0.04.

$\text{n}=\frac{[1.96)20.586\mathbf{\ast }\left(1,-,0.586\right)]}{(0.04)2}=582.$ Then by adding 10% (582 × 0.1 = 58.2≈ 58) of non- respondent, the total sample size for this study is 640.

A systematic sampling technique was used to select the study participants. The sample was taken from both hospitals proportionally, based on the flow of patients’ admissions. About 13,755 and 1,146 patients are admitted to non-psychiatric wards of HFCSH annually and monthly, respectively. Additionally, about 5,393 and 450 patients are admitted to non-psychiatric wards of Jugel hospital on annual and monthly basis, respectively. By dividing total numer of patients admitted to both hospitals each month (N) by final sample size (n), we can get sampling fraction $(\text{K})=\frac{\mathit{N}}{\mathit{n}}=\frac{1596}{640}=2.49$. Hence, the sample interval is two. The first individual was selected by the lottery method, and individuals were chosen every second interval (Fig. 1).

Fig. 1.

Schematic representation of sampling procedure to recruit study participants from non-psychiatric wards of public hospitals in Harari regional State, Eastern Ethiopia, 2022

Study variables and measurements

SRQ-20: is a 20-items instrument used to assess the presence of common mental disorders. For each item, the response will be coded as 1 or 0 with code 1 for presence of symptoms, and 0 for the absence of symptoms. This tool was validated in Ethiopia with sensitivity of 86% and specificity of 84% [19].

For the current study the total score was dichotomized and score less than 8 was considered no CMDs and score more than or equal to 8 was considered as experienced CMDs.

Socio-demographic and Clinical factors, were assessed by using a semi-structured questionnaire’s developed by reviewing similar or related articles.

Social support was measured by the Oslo-3 scale:- validated tool commonly used to assess social support in many countries including Ethiopia [20], and the sum score scale ranges from 3 to 14 and classified into three broad categories, poor support: 3–8, moderate support: 9–11,and strong support: 12–14 [21].

Substance use history was assessed by the yes/no answers of respondents by using the Smoking and Substance Involvement Screening Test (ASSIST) tools of the WHO [22, 23].

Operational definition

A probable case of common mental disorder

Individual who score ≥ 8 by assessing SRQ-20 [24].

Social support

Social-support was assessed by Oslo-3 (social support scale) which has 3 item commonly used to assess social support in many countries in Ethiopia it’s was validated tool (Duko et al., 2019a). Those who are found to score Oslo -3 scales a score 3–8 will be considered as having Poor support, 9–11 as having moderate support and a score 12–14 as having strong support [25].

Current use

Using at least one of a specific substance for non—medical purpose within the last three months (alcohol, Khat, tobacco, others substance) [26].

Ever use of substance

Using at least one of any specific substance for non-medical purpose at least once in lifetime (alcohol, Khat, tobacco, others substance) [26].

Past and current mental illness history

Previously and currently diagnosed mental illness and weather treated in the past or currently on treatment [27].

Chronic physical illness

Those respondents who will respond having a chronic physical illness which is diagnosed before from any private and public health institution and currently on Admission [28].

Data collection procedures

Data were collected by face-to-face interview using Amharic and Afaan Oromo version, pre-coded and pre-tested questionnaires and reviewing patient medical chart for medical diagnoses. The data were collected by trained two BSc nurses, two Psychiatry professionals and regularly supervised by two MSc psychiatry professionals.

Data quality control

The questionnaires were translated into Amharic and Afaan Oromo by language experts for more clarifications and better understanding. Training was given for data collectors and supervisors before the actual data collection. Daily supervision was held throughout data collection process and completeness of questionnaire was checked daily by supervisors. Pretest study was performed at Bisidimo General Hospital among 5% of the total sample, two weeks before actual data collection.

Data processing and analysis

Data were checked for completeness, entered into version 3.1 of Epi-Data, and exported to STATA version 14 for analysis. Binary logistic regression was carried out to identify the associated factors of CMD. All variables with a P-value ≤ 0.25 in the bi-variable analysis were taken into multi-variable logistic regression to control for all potential confounders.

Finally, the results of multi-variaable logistic regression analysis were presented in crude and adjusted odds ratios with 95% confidence intervals. The level of statistical significance was declared at a P-value < 0.05. The selected model was a good the fit for the logistic regression model as the Hosmer–Lemeshow goodness of fit assumption was fufilled (p-values was 0.68). Multi-collinearity was checked for the overall model by the variance inflation factor (VIF) and were less than five for all independent variables.

Ethical clearance

The study was carried out under consideration of the Helsinki Declaration of medical research ethics. Ethical clearance was obtained from Haramaya University College of Health and Medical Science after an ethical review by the Institutional Health Research Ethics Review Committee (IHRERC/195/22) and a formal letter was was submitted to HFCSH and the JGH head office. Informed, voluntary, written consent was taken from perspective hospitals and each participant. Confidentiality was assured throughout the research process and the investigators committed to the findings that the participants who scored high SRQ-20 and poor social support in Oslo social support-3 scale were consulted, linked to psychiatry clinics, and hospital psychosocial office.

Results

Socio-demographic characteristics of study participants

From a total of 640 participants selected for the study, data were collected from 634 patients, yielding a response rate of 99%. The age of study participants ranged from 19 to 74 years; mean age was 41 years with a standard deviation of (± 13.141). Among the respondents, 373 (58.8%) were male. More than half of them 369 (58.2%) were urban residents and 328 (51.7%) were Muslim religion followers. Out of the total, 342 (53.9%), 157 (24.8%), and 62 (9.78%) were married, unable to read and write, and unemployed respectively. The majority of participants, 389 (61.4%), had an average monthly income greater than 3,192 ETB per month (Table 1).

Table 1.

Socio-demographic and economic characteristics of adult patients admitted tonon-psychiatric wards of public hospitals in Harari region, Eastern Ethiopia, 2022 (n = 634)

Variable	Categories	Frequency (n)	Percent
Sex	Male	373	58.8
	Female	261	41.2
Age	18–30	173	27.3
	31–40	151	23.8
	41–50	170	26.8
	> 51	140	22.1
Religion	Muslim	328	51.7
	Orthodox	219	34.5
	Protestant	85	13.4
	Others (Catholic)	2	0.3
Residence	Urban	369	58.2
	Rural	265	41.8
Marital status	Single	160	25.2
	Married	342	53.9
	Separated	39	6.2
	Divorced	33	5.2
	Widowed	60	9.5
Ethnicity	Oromo	286	45.1
	Amhara	144	22.7
	Harari	102	16.1
	Gurage	52	8.2
	Others (Somale, Tigre, walayita)	50	7.9
Level of education	Un able to read and write	157	24.8
	Grade 1–8	215	33.9
	Grade 9–12	98	15.5
	Diploma	113	17.8
	Degree and Above	51	8
Occupational	Unemployment	62	9.78
	Governmental	117	18.5
	Private worker	160	25.2
	Farmer	93	14.6
	Student	49	7.7
	Merchant	43	6.8
	House wife	80	12.6
	Others (daily labor, retired, house-maid)	30	4.7
Income	Low (< 3191)	245	38.6
	High (> 3192)	389	61.4

Clinical characteristics of the study participants

Among study participants 174 (27.4%) had history of previous admission. Thirty-one (4.9%) had history of mental disorders, and 78 (12.3%) had family history of mental disorders, 114 (22.7%) had co-morbid illness, and 10 (1.6%) were recognized by their treating doctors as having common mental disorders (Table 2).

Table 2.

Clinical characteristics of adult patients admitted to non-psychiatric wards of public hospitals in Harari region, Eatern Ethiopia, 2022 (n = 634)

Variable	Categories	Frequency (n)	Percent
Previous hospital admission	Yes	174	27.4
	No	460	72.6
History of known chronic medical illness	Yes	144	22.7
	No	490	77.3
History of mental illness	Yes	31	4.9
	No	603	95.1
Family history of Mental illness n	Yes	78	12.3
	No	556	87.7
Physician detected as mental illness	Yes	10	1.6
	No	624	98.4

Among the clinical area study participants, the majority of the clinical diagnoses were medical (41.5%), followed by surgical, 136(21.5%) (Fig. 2).

Fig. 2.

Areas of clinical diagnosis among adult patients admitted to non-psychiatric wards of public hospitals in Harari regional state, Eastern Ethiopia, 2022 (n = 634)

Regarding length of stay, 232 (36.6%) of the participants stayed being hospitalized for one to two weeks (Fig. 3).

Fig. 3.

Length of hospital stay among adult patients admitted to non-psychiatric wards of public hospitals in Harari regional state, Eastern Ethiopia, 2022 (n = 634)

Regarding the duration of illness, 401 (63.1%) of the participants were those who have been suffering from illness for less than 6 months (Fig. 4).

Fig. 4.

Duration of illness among adult patients admitted to non-psychiatric wards of public hospitals in Harari regional state, Eastern Ethiopia, 2022 (n = 634)

Psychosocial characteristics of the study participants

Among the study participants, 236 (37.2%) of them had poor social support, 354 (55.8%) had moderate social support, and 44 (7%) had strong social support.

Regarding stressful life events, 174 (27.5%) of the study participants had recently experienced at least one stressful-life event. Among these, 58 (9.1%) had major personal injuries (Table 3).

Table 3.

Frequency distribution of stressful life events of adult patients admitted to non-psychiatric wards of public hospitals in the Harari regional state, Eastern Ethiopia, 2022 (n = 634)

Variable	Categories	Frequency (n)	Percent
Recent life events	Yes	174	27.4
	No	460	72.6
Death of spouse	Yes	41	6.5
	NO	593	93.5
Major personal injury or illness	Yes	58	9.1
	NO	576	90.9
Retirement from work	Yes	25	3.9
	No	609	96.1
Major change in living condition (new home, deterioration of neighborhood, remodeling	Yes	42	6.6
	No	592	93.4
Sexual difficulties	Yes	36	5.7
	No	598	94.3
A Death of a close family member (parent, brother.)	Yes	24	3.8
	No	610	96.2
Major change in responsibilities at work (promotion, demotion)	Yes	14	2.2
	No	620	97.8
You have been separated from your wife/husband for more than a month because of marital difficulties	Yes	18	2.8
	No	616	97.2
You are pregnant with an unwanted pregnancy? (Women only)	Yes	0	0
	No	634	100
You had an abortion or miscarriage (Women Only)	Yes	8	1.3
	No	626	98.7

Substance-related characteristics of the study participants

Among the study participants, 272 (42%) had used atleast one psychoactive substance during their life time. Among these, 235 (42.9%) were chewing Khat. Out of total study participants, 180 (28.4%) had history of atleast one psychoactive substance use within the past three months and out of them, 172 (27.1%) were chewing khat (Fig. 5).

Fig. 5.

Substance related factors among adult patients admitted to non-psychiatric wards of public hospitals in Harari regional state, Eastern Ethiopia, 2022 (n = 634)

Prevalence of common mental disorders

The prevalence of common mental disorders among adult patients admitted to non-psychiatric wards was found to be 45.35% (95% CI: 41.3–49.2). Regarding the distribution of the symptoms, headache 347 (58.5%), poor appetite 353 (55.7%), easily tired 347 (54.7%) was the most complained symptom followed by feel tired all the time 316 (49.8%) and sleep badly 315 (49.7%) (Table 4).

Table 4.

Distribution of SRQ symptoms among adult patients admitted to non-psychiatric ward of public hospitals in Harari region, Eastern Ethiopia, 2022

Variables	Response(n = 634)
	Yes		No
	Frequency	Percent	Frequency	Percent
Do often have a head ache	371	58.5	287	41.5
Poor appetite	353	55.7	281	44.3
Easily tired	347	54.7	287	45.3
Feel tired all the time	316	49.8	318	50.2
Sleep badly	315	49.7	319	50.3
Uncomfortable Feeling in stomach	306	48.3	328	51.7
Easily frightened	288	45.4	346	44.6
Feel nervous, tense, or worried	275	43.4	359	56.6
Poor digestion	266	42.0	368	58
Thought of ending life	264	41.6	370	58.4
Difficult of enjoying in daily activities	261	41.2	373	58.8
Difficulty in decision making in day to day life	259	40.9	375	49.1
Daily work suffering	257	40.5	377	59.5
Feel worthless person	255	40.2	379	59.8
Loss of interest in things	247	39	387	61
Feel unhappy	245	38.6	389	61.4
Trouble in thinking	237	37.4	397	62.6
Hand shake	237	37.4	397	62.6
Un able to play a useful part in life	226	35.6	408	64.4
Cry more than usual	223	35.2	411	64.8

Factor associated with common mental disoder

In the bivariable analysis, variables such as age, sex, marital status, residence, level of education, occupational status, duration of illness, previous admission history, length of hospital stay, history of mental illness, family history of mental illness, having co-morbi chronic illness, life time and current substance use, stressful life events, social support and monthly income had a p-value score of less than 0.25 and entered into the multivariable analysis (Table 5).

Table 5.

Bivariable analysis to identify factors associated with common mental disorders among adult patients admitted to non-psychiatric wards of public hospitals in the Harari regional state, Eastern Ethiopia, 2022 (n = 634)

Variable	Category	CMD		COR [95%CI]	P-value
		Yes	No
Sex	Male(ref)	177	196
	Female	111	150	0.6982 [0.509, 0. 9577]	0.026
Age	18–30	54	119	0.651 [0.4123, 1.028]	.0.066
	31–40(ref)	62	89
	41–50	84	86	1.402[0.901, 2.181]	0.134
	> 51	88	52	2.429 [1.515 3.894]	0.000
Residence	Urban (ref)	165	204
	Rural	123	142	1.071 [ 0.780 1.470]	0.672
Marital status	Married (ref)	146	196
	Single	66	94	0.942[ 0.644, 1.379]	0.761
	Separated	24	15	1.148 [0.088, 4.2389]	0.628
	Divorced	19	14	1.822 [0.884, 3.754]	0.104
	Widowed	33	27	1.641 [0.945, 2.849]	0.079
Educational status	Degreea nd above (ref)	19	32
	Unable to read and write	76	81	1.580 [0.826, 3.0217]	0.167
	Elementary school	101	114	1.492 [0.796, 2.795]	0.211
	Secondary school	35	63	0.936 [0.464, 1.888]	0.853
	Diploma	57	56	1.714 [0.871, 3.373]	0.119
Occupational status	Governmental employee(ref)	54	63
	Unemployment	27	43	0.842 [0.452 1.569]	0.589
	Private	79	80	1.178[0 .705, 1.834]	0.596
	Farmer	44	44	1.093 [0.633, 1.887]	0.747
	Student	15	32	0.547[0.268, 1.115]	0.079
	Merchant	22	21	1.222 [0.60715, 2.461]	0.574
	Housewife	30	30	0.732[0.391, 1.250]	0.228
	Others*	17	13	1.525 [0.679, 3.424]	0.306
Duration of illness	< 6 month(ref)	171	230
	7 to 12 month	45	51	1.186 [0.759, 1.855]	0.453
	> 12 month	72	65	1.489 [1.009, 2.199]	0.045
Admission history	No(ref)	191	269
	Yes	97	77	1.774 [1.247, 2.522]	0.001
Having other co-morbid chronic illness	No(ref)	63	283
	Yes	81	207	1.757[1.208, 2.557]	0.003
Length of hospital stay	< 1 week(ref)	55	104
	One to two weeks	109	123	1.675 [1.105 2.540]	0.015
	Three to four weeks	98	87	1.536 [0.833, 2.833]	0.169
	More than four weeks	26	32	2.123 [1.377,3.294]	0.001
History of mental illness	No(ref)	26	339
	Yes	24	7	4.402 [1.868, 10.374]	0.001
Family History of mental illness	No(ref)	40	306
	Yes	38	250	1.1628[0.7235, 1.8686]	0.533
Stressful life events	No(ref)	67	279
	Yes	107	181	2.461 [1.720, 3.522]	0.000
Life time substance use	No(ref)	65	281
	Yes	173	115	2.281 [1.654, 3.145]	0.000
Current substance use	No(ref)	281	65
	Yes	173	115	2.873[2.008, 4.112]	0.000
Social support	Strong social support(ref)	15	29
	Poor social support	124	112	2.140 [1.091, 4.198]	0.027
	Moderate social support	149	205	1.405 [0.727, 2.713]	0.311
Monthly income	> 3192 (ref)	182	207
	< 3191)	106	139	1.152[.8357, 1.5905]	0.386

ref indicate for reference group

Other^*: daily laborer, house-maid, retired

In the multivarible logistic regression analysis:- age, length of hospital stay, history of mental illness, stressful life events, current substance use, and social support were found to be significantly associated with common mental disorders among adult patients admitted to non-psychiatric wards at a p-value of < 0.05, while marital status, sex, residence, educational status, occupational status, history of admission,family history of mental illness, duration of illness, having comorbid another illness, monthly income, and life-time substance use were not significantly associated with common mental disorders.

Accordingly, odds of having CMD is 1.74 times higher among those with age 41–50 as compared to those in age category of 31–40 years (AOR = 1.732, 95% CI:1.030,2.91), keeping other variables constant. Odds of having CMD is 2.42 times higher among those with 51 years and above as compared to those in age category of 31–40 years (AOR = 2.429, 95% CI 1.515, 3.894), keeping other variables constant.

Regarding length of hospital stay, odds of having CMD is 1.74 times higher among those stayed for one to two weeks as compared to those stayed less than a week (AOR = 1.743, 95% CI:1.065, 2.853), keeping other variables constant. Odds of having CMD is 2.12 times higher among those stayed for more than four weeks as compared to those stayed less than a week (AOR = 2.12, 95% CI:1.77,3.29), keeping other variables constant.

With regard to history of mental illness, odds of having CMD is 5.8 times higher among those with previous history of mental illness as compared to their counterparts (AOR = 5.841, 95% CI:2.27, 15.00), keeping other variables constant.

With regard to stressful life events, odds of having CMD is 1.8 times higher among those experienced stressful life events as compared to their counterparts (AOR = 1.876, 95% CI: 1.206,2.919), keeping other variables constant.

Regarding psychoactive substance use, odds of having CMD is 1.6 times higher among those with current psychoactive substance use as compared to their counterparts (AOR = 1.688,95% CI:2.076, 2.650), keeping other variables constant.

Regarding social support, odds of having CMD is 2.5 times higher among those with poor social support as compared to those with strong social support (AOR = 2.562,95% CI: 1.166, 5.629), keeping other variables constant (Table 6).

Table 6.

Multivariable analysis to identify factors associated with common mental disorders among adult patients admitted to non-psychiatric wards of public hospitals in Harari regional state, Eastern Ethiopia, 2022 (n = 634)

Variable	Category	C MD		AOR 95% CI	P-value
		Yes	No
Sex	Male(ref)	177	196
	Female	111	150	1.374 [0.9079, 2.082]	0.134
Age	18–30	54	119	0.779 [0.450,1.348]	0.373
	31–40(ref)	62	89
	41–50	84	86	1.732 [1.030,2.913]	0.038*
	> 51	88	52	2.429 [1.326,4.449]	0.004*
Residence	Urban (ref)	165	204
	Rural	123	142	1.204 [0.813 1.783]	0.353
Marital status	Married (ref)	146	196
	Single	66	94	1.002 [ 0 .621,1.615]	0.993
	Separated	24	15	1.937 [0.875, 4.237]	0.512
	Divorced	19	14	1.034 [0.436, 2.451]	0.938
	Widowed	33	27	0.718 [0.357,1.443]	0.353
Educational status	Degree and above (ref)	19	32
	Unable to read and write	76	81	1.130 [0.471, 2.888]	0.789
	Elementary (1–8)	101	114	1.211 [0 .5182,2.829]	0.658
	Secondary (9–10)	35	63	0.857 [.344, 2.133]	0.741
	Diploma	57	56	1.605 [0.717, 3.594]	0.250
Occupational status	Governmental employee(ref)	54	63
	No job	27	43	0.778 [0.343, 1.766]	0.549
	Private	79	80	1.072 [0.557 2.0609]	0.835
	Farmer	44	44	1.105 [.519, 2.351]	0.795
	Student	15	32	0.896 [.3595 2.237]	0.815
	Merchant	22	21	1.198 [.499,2.873]	0.686
	Housewife	30	30	0.819 [0.388, 1.729]	0.602
	Others*	17	13	1.376 [0.5172, 3.661]	0.522
Duration of illness	< 6 month(ref)	171	230
	7 to 12 month	45	51	1.055 [0.617, 1.803]	0.844
	> 12 month	72	65	1.242 [0.765,2.017]	0.379
Admission history	No(ref)	191	269
	Yes	97	77	1.318 [0.854,2.033]	0.211
havig comorbid illness	No(ref)	63	283
	Yes	81	207	1.28 [0.794,2.072]	0.309
Length of hospital stay	< 1 week(ref)	55	104
	One to two weeks	109	123	1.743 [1.065, 2.853]	0.027*
	Three to four weeks	98	87	1.681 [0.999, 2.830]	0.051
	More than four weeks	26	32	2.12 [1.77,3.292]	0.032*
Historyof mental illness	No(ref)	26	339
	Yes	24	7	5.841 [2.274, 15.004]	0.000*
Stressful life event	No(ref)	67	279
	Yes	107	181	1.876 [1.206,2.9196]	0.005*
Life time substance use	No(ref)	65	281
	Yes	173	115	1.569 [0.992, 2.482]	0.054
Current substance use	No(ref)	281	65
	Yes	173	115	1.688 [1.075,2.650]	0.023*
Social support	Strong social support(ref)	124	112
	Poor social support	149	205	2.562 [1.166, 5.629]	0.019*
	Moderate social support	124	112	1.728 [0.810, 3.6901]	0.157

ref indicate for reference group

^*Significant association at P-value < 0.05

Discussion

This study showed that the overall prevalence of common mental disorders among study participants was 45.3%, which is similar with studies done among patients admitted to non-psychiatric wards in Nigeria 45.3% [28, 29] Austria 46% [30, 31], Brazil 44.1% [32], Korea 48.0% [33], Kenya 43.7% [34], Qatar 43% [35], Uganda 42% [5], Kuwait 41.4 [28, 29], and Gondar, Ethiopia 46.7% [36].

On the contrary, the finding of this study is slightly higher than the studies conducted in southern Southern Brazil 40.2% and USA 38% The possible explanations for the variation may be due to use of different tools and cut-off point, and difference in baseline characteristic of study populations. In study done in USA, for instance, the participants were acutely injured trauma survivors and they were used Hamilton Rating Scale for Depression (HRSD) Southern Brazil study was conduct among menopausal women [28, 29]. Additionally it might be due that better quality of mental health care, health seeking behavior and economic development may contribute to lower the common mental disorder in USA, and Brazil [37].

The current study finding is higher than studies done in Brazil and UK which reported prevalence of common mental disorders was 31.4% and 32.5% [38] respectively. This discrepancy might be attributed to the differences in socio-demographic characteristics, data collection tool, cut-off points to measure common mental disorders, and difference in baseline characteristics of study population. A study in Brazil were conducted in primary health care and used SRQ-20 with cut-off point greater than or equal to seven where as the study in UK were conducted among patients admitted in medical and surgical wards and used a 12-item General Health Questionnaire which used identify the presence of depression only [38]. Another possible justification for this difference is that these reports are from developed countries where the better quality of the mental health care system, and the effectiveness of the health care services provided to early detection ad intervention might explain the low prevalence of common mental disorders among patients admitted in non-psychiatric ward of these countries [28, 39].

The finding is also higher than the studies conducted in Worabe 39.2% [40], Hawasa 38% [41], Addis Ababa 23.21% [42], and Harari region 14.9% [14]. This discrepancy might be attributed to the differences in socio-demographic characteristics, data collection tool, cut-off points to measure common mental disorders. Possible justification for this difference is the time gap between study periods, study population, and cut-off point variations to assess common mental disorders. This might be difference in study population among internal medicine in Woreba, Hawassa, and glaucoma patients attending out patient services in Addis Ababa. Additionally, the previous research done in Harari region conducted among adult residents. This might be supported by different studies reported that common mental disorders is more common in a hospital setting than in a community setting. Another reasons might be in fact, there may being hospitalization, severity and complications associated with chronic medical illness among inpatient maymore prone to common mental disorders [43].

However, the result of this study was lower than study conducted in Canada 57.3% [44], Tanzania 61% [45], Uganda 61%,Addis Ababa 53%, and Gondar 58.6. The possible reasons for the discrepancy might be the differences in the study setup and data collection instrument. In Tanzania, study conducted was national survey among orthopedic patients and using the Patient Health Questionnaire’s-9 (PHQ9) tool to assess symptoms of depression. And SRQ-25 was used to assess common mental disorders with a cut off of 5/6 in Uganda, Gondar and Addis Ababa.

Additionally the time of study period is another reasons for instance, in Canada study was conducted during the COVID-19 pandemic and post pandemic in Addis ababa which pandemic is claimed to be increase in the global prevalence of common mental disorders specially in population’s with underlying medical conditions [46, 47], and different studies showed that mental disorders were worsened during and post COVID-19 pandemic,compared to before the pandemic and it has resulted that never happened before in psychological, social and economical crisis leading to a significant symptoms of common mental disorders [47, 48].

Regarding associated factors: age, length of hospital stay, history of mental ilness, stressfull life events, current substance use, and social support of the study participant’s were significantly associated with common mental disorders among adult patients admitted to non psychiatric ward of public hospitals.

In this study, being in age 41 and above was significantly associated with common mental disorders. This study was consistent with other studies in Nigeria [49], Malaysia [50], India [51], and South Africa [52]. The reasons might be the high risk of worsening physical illnes sand psychiatric co-morbidity at this age groups [53] than other age groups.Second reasons might be that a chronic illnesses like cardiovascular disease and disabling physical conditions are markedly increasing with age or may be the result of increasing stress, cumulative life events, or declining physical health with the advancement of age may more prone to common mental disorders [51]. Additionally cumulative impacts of earlier life experiences and specific stressors related to ageing, significant loss or decline in functional ability and more likely to experience adverse events such as bereavement, or a drop in income or reduced sense of purpose with retirement, can all result in increased common mental disorders among those age group [54].

This study revealed that length of hospital stays, first to weeks of admission was associated with common mental disorders. This finding is in agreement with the study in Gondar and Harar [36, 55]. This may be related to that patiets distressed during the first two weeks of admissions related to leaving their home or families, an interruption of their daily routine activities [56] and stressful hospital environment including fear of medical procedures and pain may increases feelings of symptoms of common mental disoders [57].

Similarly, patients who stayed more than four weeks in the hospital were more likely having common mental disoders than those stayed less than one weeks. This agrees with study conducted in Austria [58, 59], Gondar [18, 60]. This association can be justifiable by the fact that staying longer in the hospital may have devastating employment opportunities and financial effects for patient’s as well as families [61], weakening of social support, threatening living arrangements, stress or fear of developing hospital acquired disease and complication may more contribute to the development of common mental disorders [62].

In addition, significant association was observed between having history of mental illness and common mental disorders. The finding is supported by studies from Brazil [63], China [64], Qatar [65], South Africa [66], Gondar [18], and Addis Ababa [67]. The possible justification for this might be due to history of mental illnesses are more sensitive to external stressors, including chronicity of illness and being hospitalized may lead to more likely to having common mental disorders [68].

Likewise, participants who reported stressfull life events were more likely to have common mental disorders compared to their counterparts.This finding is supported by study conducted in Kombelcha [16]. A possible justification might be that any single stress may lead to biochemical changes in the brain, which in turn induce symptoms of common mental disorders [69], and stressfull life events are independent factors for common mental disorders [70].

Furthermore, the finding from the current study revealed the significant association between poor social support and CMDs. This study result has been found to be consistent with other studies in, China [71], Nigeria [72], Worabe hospital [40], Oromia region [73], and Addis Ababa [74]. The possible justification for this might be that lack of effective social support result in more experienced common mental disorders [75]. An other reason’s might be the feeling of loneliness or having no close who easily understand their illness or suffering, and share the day-to-day life stress and tendency of stress to damage several organs and systems that might result in the occurrence of CMD [76].

Finally, these studies releaved that current substance use were associated with CMD. This supported by studies conducted in, Worabe hospital [40], Walaita sodo, South Ethiopia [77]. This might be due to the patients with a chronic medical illness were more risky to use substance to relieve stress or anxiety related to medical problems or used as a method to relieve emotional,and some kind of emotional distress prior to consumption effective in the long term, as consumption tends to capable of altering brain functioning, causing changes in the mental state which alter dopamine and serotonin neurotransmitter that result in symptoms of CMDs [78, 79].

Surprisingly, from 45.3% respondents experienced CMDs, only 1.6% of patients were recognized by their treating doctors as having common mental disorders. This finding is lower than studies done in Germany and Austria 2–3%, Nigeria 2.8%, Uganda 6% and Gondar, Ethiopia 3.3% [5, 30, 80, 81]. The difference may be due to professionals’ individual knowledge about common mental disorders, shortage of mental health specialists, poor intera-deparmental consultation between services area [28, 30].

Strengths and limitations of the study

This study came up with perspicuous findings regarding prevalence and associated factors of common mental disorders among study participants with relatively higher sample size and by using validated instruments in Ethipian context. However, some limitations are considered, including cross-sectionality of the study design which makes it difficult to establish a causal relationship between dependent and independent variables. Additionally, the measurement of some variables might have been devoted to recalling bias and social desirability bias. Furthermore, the study was quantitative in nature and lacks qualitative interviews which may encourage participants to liberally highlight their concerns.

Conclusion

Nearly half of the patients admitted in non-psychiatric wards suffered from common mental disorders in the study area. In the current study age, length of hospital stays, history of mental illness, stressfull life event, current use of psychoactive substance, and poor social support were significantly associated with common mental disorders. Therefore, it is better if healthcare professionals working in non-psychiatric wards routinely assess patients for common mental disorders and special considerations have to be given for those with older age, longer hospital stay, previous history of mental illness, stressfull life events, current use of psychoactive substance, and poor social support.

Abbreviations

ASSIST

Assessments of Smoking and Substance Involvement Screening Test

CMD

Common mental disorder

HFCSH

Hiwot fana comprehensive specialized hospital

ICCAS

Interactive computers –assisted client assessment survey

ICU

Intensive Care Unit

IPD

Inpatients Department

JGH

Jugol General Hospital

OPD

Out Patient Department

PHQ

Patient Health Questionnaires

PSTD

Posttraumatic stress disorder

Authors’ contributions

H A was the principal investigator of the study and contributed to conceiving the original idea, designing and conducting the study, performed analyzing, and interpretation of data, drafting and editingof the manuscript. TA,I M,T M,D A,A Z,Were involved in the reviewing of the proposal, tool evaluation, interpretation, and critical review of the draft manuscript. All authors read and approved the final manuscript.

Funding

Not applicable.

Data availability

The raw data analyzed during the current study will be made available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was carried out under consideration of the Helsinki Declaration of medical research ethics. Ethical clearance was obtained from Haramaya University College of Health and Medical Science after an ethical review by the Institutional Health Research Ethics Review Committee (IHRERC/195/22) and a formal letter was was submitted to HFCSH and the JGH head office, voluntary, written consent was taken from perspective hospitals and each participants. The right was given to the study participant to refuse, discontinue their participation at any time they wanted and chance to ask any questions regarding the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.