Open Access | Peer-reviewed | Research Article
Department of Psychiatry, college of health science, Dilla University, Dilla, Ethiopia, P.O. Box 419.
Department of Psychiatry, Faculty of Medical Sciences, Institute of Health, Jimma University, Jimma, Ethiopia, P.O. Box 378.
Published: February 11, 2021 DOI: 10.5281/zenodo.4564123
Social support is a vital part of mental health treatment, which helps patients to address the affected psychosocial domain of life due to illness. Patients with upright social support show better recovery and functionality. So this study aimed to see the association of social support with sociodemographic and clinical factors of mentally ill patients at Jimma psychiatry out patient clinic. Hospital-based cross-sectional study design and census sampling was used for one month period of time to select participants. This study include 300 mental ill patients attending their treatment at Jimma medica center, outpatient clinic. Data collected through face to face interviews by using the Oslo three items social support scale. Data was entered and analyzed using Epi-data 3.1 and Statistical package for social science 22.0 respectively. The pearson correlation coefficient used to identify associated variables with the outcome variable at a 95% confidence interval (CI), p< 0.05. Three hundred respondents have participated in this study. Among respondents, 185 (61.7%) of them were males and 115 ( 38.3%) females. Out of all mental ill patient participated in the study, 92 (32%) of them had schizophrenia diagnosis. More than two-third, 206 (68.7%) of them had moderate social support. Variables which were associated with social support were self stigma (r=- 0.220 ), lifetime relapse (r=-.120), disability score ( r=-.222 ), family history of chat use (r=-.155) and current job status (r= .115 , p= .047) at 95% confidence interval and p< 0.05. This study found that two-thirds of respondents had moderate social support. Self-stigma, lifetime relapse, disability, and current job status were variables associated with social support. Therefore working to boost the social support part mentally ill patients is essential for better functioning and quality of life.
Keywords: Social support, stigma, relapse, disablity, mental illness.
|Citation: Chalachew kassaw and LiyewAgenagnew (2021) The relationship between social support with sociodemographic and clinical factors among mentally ill patients, Journal of PeerScientist 4(1): e1000031.|
|Received: August 09, 2020; Accepted: February 06, 2021; Published: February 11, 2021.|
|Copyright: © 2021 Chalachew kassaw and LiyewAgenagnew, This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.|
|Data Availability: All relevant data are within the paper and its Supporting Information files.|
|Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.|
|Competing interests: The authors have declared that no competing interests exist.|
|* E-mail: firstname.lastname@example.org | Phone: +251937096759|
Social support is a vital part of mental health treatment, which helps patients to address the affected psychosocial domain of life due to illness . Activities such as showing right mind-set, helping in the day to day dwelling expenses including meals, shelter, and transportation, supporting in symptom control and drug adherence, and aiding to contain in distinct social, criminal services are the part of social support . It may be given via any person who have either blood relation or non-blood relation with the affected person and mostly patients expect social support from their families than from others . Social support has physical, and mental blessings for those who face pressure or stressful physical and mental occasions and is one among proposed intervention which turned into used to reduce the impact of an event specified in causing mental illness [4-5]. The most affected groups of mentally ill patients due to social support were women, elders, workers, and students . World Health Organization (WHO ) emphasizes the importance of strengthening social support for preventing the impact of mental illness and minimizing barriers to accessing mental health service . Patients with poor social support had bad outcomes in terms of adherence, response, recovery and functionality [8-9]. However, patients with strong social support have a better quality of life, capacity to cope stress, self-esteem and efficacy, help-seeking behavior, medication adherence, have less chance of relapse, and suicide attempts [10–17]. From previous literature it was evident that social support plays a vital role in day to day activities, treatment progress, relapse and medication adherence of mentally ill patient. Despite the critical importance, there is a shortage of evidence on the impact of social support on the treatment outcome of mental ill patient attending treatment health organizations. In this scenario, this study is aimed to evaluate the relationship between patients’ social support status with patients’ sociodemographic and clinical factors on mentally ill patients at Jimma psychiatry out patient clinic.
Results & Discussion:
Socio demographic result
The mean age of respondents was 34 with (SD ± 11) years, and the mean number of family members was 4 with (SD ± 2). The mean income of respondents was 503 with (SD±225) Ethiopian Birr. Nearly two third of respondents were males (61.7%,185), single (60.7%, 182), and living with their family (70.6 %, 212) (Table 1).
Table 1: Sociodemographic result of respondents who were attending their treatment at Jimma university medical center , south west Ethiopia , Jimma , 2020 (N=300):
Clinically related factors of respondents
The mean(SD) age onset and treatment duration of illness among respondents was 26(SD±11) years and 8.1 (SD± 5.5) years respectively. The mean(SD) treatment delay and duration of treatment among respondents was 1.16 (SD ±2) year and 5.75 (SD ± 5.3 )years respectively . From all respondents, 84(28%) had a high self-stigma score, and 65(36.5%) had a high mean score of disability. From all respondents, 95 (31.7%) of them had khat use family history. Among respondents, 96 (32%) of them had schizophrenia diagnosis, and more than half 162 (54%) of respondents had no history of admission (Table 2).
Table 2: Distribution of clinical related factors of respondents in Jimma university medical center psychiatry outpatient clinic, southwest Ethiopia, Jimma 2020, (N= 300):
From all respondents assessed for social support, 55( 18.3%) poor, 206 (68.7%) moderate, and 39(13%) strong social support.
Factors related to social support scale
Variables which were associated with social support were self stigma (r= -0.220, p=0.000), life time relapse (r= -.120, p= 0.038) , disability score ( r= -.222, p=.000), family history of chat use (r= -.155 , p= 0.007) and current job status (r=.115 , p=.047) (Table 3).
Table 3: Pearson coefficient of social support with independent variables among respondents who were attending their treatment at Jimma university medical center, south west Ethiopia, Jimma, 2020 (N=300).
This study found that social support decreases the self stigma of patient and this study finding was similar with the studies conducted in Europe , China  and India . It might be explained by social support to address all supports, which enables patients not to feel alone and increase the self-efficacy of patients. This study found that social support had significant impact on the relapse of patients and this study finding was consistent with the studies done in London  and Nigeria . It might be due to the contribution of strong social support on the illness management domain of patients, especially on symptoms management and medication adherence, which directly linked to the relapse of patients. This study found that good social supports increase the functionality and job opportunity of patients, which was in line with the studies done in Singapore , Taiwan , and Ethiopia . It has a role in addressing the affected domain of day to day living activities and participation in the society, which all helps patients to re-gain their functionality, enhance their confidence to involve in different opportunity job and acceptance in the community.
Since the study design was cross sectional study, there is limitation of exactly showing the causal relationship between the independent and outcome variable. Most of the respondents were males, single and 505 ETB monthly income which all needs support from friends, neighbors and blood relations for their day to day activities, medication adherence and mental well being. This study found that two-third of respondents had moderate social support and those with family history of khat use had poor social support which has a direct impact for medication adherence, relapse, functionality and recovery among mental ill patients. This study found that as there is a strong and positive relationship between social support and recovery, self-stigma and functional impairment among mental ill patient. Social support has components of emotional, psychological and economic support for patients with mental illness which all facilitates the recovery and better treatment outcome. This study implies that social support is a pillar for the future better quality of life and treatment outcome of mental ill patients. Therefore there should be social support component as one psychosocial treatment plan for patients attending treatment at the health organization. So working on strengthening social support is mandatory to enhance patients functioning, better recovery, and quality of life. There should be a collaboration work with government delegated social workers, community supporting groups, religious supporting groups and care giver supporting groups for the treatment outcome and functionally among patients with mental illness. Government and private stakeholders working on mental illness and its recovery should build mental illness helping groups, anonyms, volunteer organizations, rehabilitations center and funding organizations. For future researchers, it is better to have a qualitative study to identify further importance of social support on the management of mentally ill patients on sustainable manner.
Materials & Methods
Study area and period
The place of this study was Jimma university medical center (JUMC) psychiatric outpatient clinic from January 12, 2020, to February 12, 2020, which was found in southwest Ethiopia and 352 km far from Addis Ababa, capital city of Ethiopia. It is main government institutes in Jimma town; currently, it is a teaching tertiary level hospital and provides inpatient and outpatient health services for around 15 million people living in the southwest area of Ethiopia. It was established in 1988 and serving for 40-60 patients per day. Currently, the clinic has 42 beds for inpatient service.
The study design of the current study was institutional-based cross-sectional study design.
All mentally ill patients age is 18 and above were included.
Patients with an emergency mental health condition and unable to communicate were not included in the study.
All patients who were fulfilled the eligibility criteria and came for follow up during a month of data collection were included, and 300 respondents were the final sample size for this study.
After obtaining the written informed consent from each respondents , all respondents were interviewed in their order of visiting the clinic. After the interview, all patient’s card numbers were circulated to each data collector and supervisor to avoid laying-off of patients at the time data collection.
Data collection instrument
Internalized Stigma of Mental Illness (ISMI) scale: It is the 24-item Likert scale used to assess stigma. It has Social with drawl , stereotype endorsement , alienation, and discrimination experience components and categorized as low stigma if score ≤ 2.5 and high stigma if > 2.5 . Oslo’s three items social support scale used to assess social support with range [3-14], which further categorized as “poor support” 3–8, “moderate support” 9–11, and “strong support” 12 and above . The Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST-3.0) were adopted to assess the current alcohol, cigarettes, and khat and cannabis use status of the participants. The tool has developed by WHO and had Cronbach alpha ( 0.73) . Medication non-adherence – if patients who discontinued for more than a 3-month duration considered as they are non-adherent .
According DSM-IV definition of illness relapse to say a patient had a relapse history patient should have a history worsening of symptoms or more than one admission history, which was measured by reviewing the card and interviewing patients .
World Health Organization Disability Assessment Schedule 2.0, – (WHODAS V.2.0)
A 12 items structured interviewer-administered questioner was used to determine mental ill patient’s current functional disability .
Data collection procedures
Face to face interview and document review were the main method used to collect the data from each respondent. Trained bachelor of a degree in psychiatry nursing was participated in collecting the data. Each data collector was followed the principles of data quality management techniques during the whole data collection procedure.
Socio-demographic related factors:- Gender, age, marital status, educational status, place of residence, monthly income and current employment status, number of family members and current living status.
Psycho-Social Factors: – functional disability and self-stigma.
Patient clinical characteristics :- Current diagnosis and substance use, age onset of the illness, duration of illness and treatment, duration of delay of treatment, admission status, medication adherence and family history of substance use.
The coded data were submitted and analyzed using Epidata 3.1 and SPSS 22.00. This study used descriptive statistics such as texts, percentages, graphs, and tables for categorical data, and calculated mean and standard deviation for continuous variables. The main measurement analysis of the study to identify variables related to the outcome variable was pearson correlation coefficient analysis at 95%, p< 0.05.
Data quality assurance
We calculated the possible maximum sample size with census sampling. Standard and carefully designed questionnaires were used and translated to local language Affan Oromo, and Amharic by two different persons and back translate to English. We did the pretest at the shenen gibe General hospital outpatient psychiatry clinic.
Acknowledgement: Authors would like to thank all the respondents and data collectors who participated in the study and Jimma University.
Authors’ contribution: All authors contributed equally in designing the study, executing the study, collecting and analyzing the data. All authors have read and approved the final manuscript for publication.
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