Introduction

In Ethiopia, a country characterized by prolonged conflict, political instability, and natural disasters, internally displaced persons (IDPs) are particularly vulnerable to the effects of trauma1. The displacement caused by violence, ethnic tensions, and environmental factors has led to a significant increase in the number of individuals experiencing PTSD among these populations. Internally displaced people often face a unique set of challenges that exacerbate their mental health issues. The loss of homes, disruption of social networks, and exposure to ongoing violence and uncertainty contribute to heightened levels of stress and anxiety. Additionally, the lack of access to mental health services and support systems further complicates their ability to cope with trauma2. As a result, many IDPs in Ethiopia experience debilitating symptoms of PTSD, including flashbacks, severe anxiety, and emotional numbness, which hinder their ability to rebuild their lives and reintegrate into society3. People might experience a wide range of horrific occurrences during the conflict, which can have an emotional impact4. Furthermore, war and armed conflicts are linked to poverty, unemployment, communal violence, unstable living conditions, and changes in social dynamics5. Any traumatic event experienced during combat increases the risk of mental health issues such as post-traumatic stress disorder (PTSD), anxiety, and depression, as well as worsening life outcomes6. Mental illness, and particularly PTSD, is recognized as a major public health concern of a conflict-affected population7. PTSD in a post-war scenario is strongly linked to a lower quality of life, even after the conclusion of physical conflicts8. The symptoms of PTSD include difficulty sleeping, feelings of detachment or numbness, recurring and memories of the event(s), and they may also be easily frightened9. When PTSD is severe, it can seriously affect a person’s capacity to carry out daily activities and interact with others10.

According to previous studies, PTSD is most frequently connected with respondents’ age, sex, and social capital11. In particular, females and people with low socioeconomic status are more likely to develop PTSD12. A family history of mental illness, a personal history of mental illness, education level, being unemployed after the event, persistent physical problems, and damage to property, such as a house, are all risk factors for PTSD13. Pre-existing factors such as substance addiction history, and post-trauma elements such as lack of food or water, injury, and loss of a family member/friend have all been identified as contributing to the development of PTSD14. Substance abuse, anxiety and mood disorders, impulsive or risky behavior, and self-harm are examples of co-occurring problems15. PTSD is also associated with considerable medical comorbidities, including chronic pain and inflammation, cardiometabolic disorders, and a heightened risk of dementia16. PTSD is a significant contributor to the global disease burden, affecting the world’s population26. A study conducted in Uganda during a time of active conflict revealed that the prevalence of PTSD in the general population ranged from 18 to 54%17,18. According to a study conducted on Israelis who were exposed to terrorism when they were 18 years and older, the average prevalence of PTSD was 9.4% for men and 16.2% for women19. Moreover, numerous studies have revealed that PTSD and major depression affect established refugees at rates of 10–40% and 5–15%, respectively20. Furthermore, the mean PTSD prevalence rate was found to be 30.6% after a meta-analysis of 145 studies involving 64,332 refugees and other people affected by conflict worldwide21.

Understanding the prevalence and impact of PTSD among internally displaced persons in Ethiopia is crucial for developing effective interventions and support mechanisms22. Therefore, the primary objective of this study was to determine the prevalence and risk factors for PTSD among internally displaced individuals in the Gura Ferda district of southwest Ethiopia. By addressing these issues, we can contribute to the broader efforts to promote mental health and well-being among vulnerable populations in Ethiopia23.

Materials and methods

Give an account of the materials and methods that will be used to determine the frequency and risk factors of probable PTSD among displaced people in Southwest Ethiopia. The research will be conducted using a cross-sectional design, with data collected through validated evaluation tools and structured interviews. We hope to learn more about the causes of the mental health problems experienced by this at-risk group by examining the data. By analyzing the data, we can learn more about the mental toll that displacement takes and devise more effective ways to help those affected. Our research has the potential to inform regional mental health service policy and funding decisions.

Study design and setting

From January 1st to February 1, 2022, a community-based cross-sectional study was conducted among Internally Displaced People in Gura Ferda District, Bench Sheko zone of Southwest Ethiopia. Gura Ferda has witnessed a series of conflicts that are rooted primarily in ethnic tensions, exacerbated by political instability and competition for resources24. These conflicts have resulted in violent clashes between different ethnic groups, leading to widespread fear and insecurity. Data were collected from semi-structured interviews administered to residents selected through a simple random sample procedure25. The duration of displacement for many individuals in Gura Ferda has been prolonged, with some families living in temporary shelters or makeshift camps for months or even years26. The uncertainty surrounding their return to their original homes, coupled with ongoing violence and instability, contributes to heightened levels of stress and anxiety among IDPs.

Inclusion and exclusion criteria

  • Inclusion criteria: All internally displaced persons (IDPs) aged 18 years or older, residing in the district during the study period, and willing to provide informed consent were eligible to participate.

  • Exclusion criteria: Individuals who were unable to communicate due to severe illness or cognitive impairment, as well as those who were younger than 18 years, were excluded from participation in the study.

Sampling procedure

The sample size was determined via a single-population proportion formula and a simple random sampling technique. The study’s sample size was 424, which was calculated by assuming a 50% prevalence of PTSD among residents in a single population for an unknown prevalence, with a margin of error of 5% and a nonresponse rate of 10%. We first identified the target population from which the sample would be drawn. This included all eligible participants within the defined study area who met our inclusion criteria. We employed a three-digit table of random numbers to ensure a systematic selection of participants. First, we compiled a list of all eligible participants, each of whom was assigned a unique identifier. We then used the random number table, starting from a randomly selected point, to sequentially choose three-digit numbers corresponding to the identifiers on our list27. This process continued until we reached our desired sample size, ensuring an unbiased selection.

Study variables

  • Study variable (outcome): PTSD symptoms are classified as present or absent based on a PCL-C score of 50 or higher. Higher scores indicate a greater severity of symptoms, which can significantly impact daily functioning and overall quality of life. Early intervention and appropriate treatment are crucial for those affected to manage their symptoms effectively. This threshold is commonly used to identify individuals who may be experiencing significant distress related to trauma. Understanding the prevalence of these symptoms can help inform treatment strategies and support for those affected. Additionally, it can guide healthcare providers in tailoring interventions to address specific needs, ultimately improving the overall quality of care for individuals coping with trauma-related challenges. By monitoring these symptoms, practitioners can better assess the effectiveness of therapeutic approaches over time.

  • Explanatory variables: The explanatory variables in this study encompass several key categories. The demographic variables include sex, age, marital status, education, and occupation. The clinical variables focus on the participants’ mental health history, specifically family history of mental illness and any previous mental health conditions. Additionally, the study examines substance use, which includes the consumption of alcohol, cigarettes, and khat. Finally, the war-related variables address the impact of conflict on individuals. This includes experiences such as property destruction, lack of food and water, physical abuse, injury, and illness without access to medical care.

Data collection tools and measurements

The data were collected via semi-structured interviews with the interviewers. Two BSc nurses obtained it regularly under the supervision of a psychiatry professional. The survey design was translated from English to the local language and back to English to maintain uniformity. Data collectors were trained to conduct participant interviews, clarify unclear questions, and describe the study’s objectives. Data on the prevalence of posttraumatic stress disorder were collected through interviews with the standard PTSD Checklist-Civilian Version (PCL-C) questionnaire. It is a general civilian version, and questions pertain to a stressful experience in the past. The respondents rated each item from 1 (“not at all”) to 5 (“extremely”) to indicate the degree to which they had been bothered by that particular symptom over the past month. Thus, the total possible scores range from 17 to 85. A total score of 50 or more is considered the cutoff point for a probable PTSD diagnosis. Two studies of both Vietnamese and Persian Gulf theatre veterans showed that the PCL was both valid and reliable. We also checked internal consistency and reliability in this study, and thus, Cronbach’s alpha was 0.812.

Statistical data analysis

We performed all the statistical analyses with SPSS version 25 (IBM). To highlight the descriptive results, we used frequency distributions and percentages. We used the chi-square test of associations to test the associations between response and explanatory variables. To identify predictors associated with PTSD symptoms among internally displaced people in the Gura Ferda district, Southwest Ethiopia, we used a logistic regression model. Multivariable logistic regressions were conducted by taking all significant covariates in the univariable analysis at a significance level of 25%. The Hosmer and Lemeshow test was performed to assess the model’s goodness of fit.

Results

Among the 424 study participants, 217 (51.2%) exhibited PTSD symptoms, while 207 (48.8%) did not. This significant prevalence of PTSD indicates that there is an urgent need for targeted mental health interventions and support for those affected. Understanding the factors contributing to these symptoms could further inform prevention and treatment strategies. Identifying these factors may involve examining personal histories, environmental stressors, and coping mechanisms. By addressing these elements, researchers and clinicians can develop more effective programs to assist individuals in managing their mental health.

Demographic characteristics of the participants

Among the 424 participants in this study, 237 (55.9%) were male, and 109 (46.0%) developed PTSD symptoms. More than half of the respondents, 213 (50.2%), were aged 31–45 years, of whom 109 (51.2%) experienced PTSD symptoms. More than half of the respondents (264, 62.3%) were married, and the majority (234, 55.3%) were farmers (Table 1).

Table 1 Demographic characteristics of the study participants.
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Substance use, clinical, and war-related events of the respondents

In terms of substance usage, 118(27.8%), 111(26.2%), and 115(27.1%) respondents were alcohol users, smokers, and Khat chewers, respectively, with 80(67.8%), 75(67.6%), and 102(88.7%) experiencing PTSD symptoms. In terms of war-related occurrences, 158 (37.3%), 129 (30.4%), and 116 (27.3%) of the respondents reported damage to personal property, physical abuse, and lower to more significant injury, respectively. According to our data, 37.3% of the respondents had insufficient food or drink, and 42.2% were ill without medical attention. With respect to clinical characteristics of the respondents, 45(10.6%) had a family history of mental illness, and 29(6.8%) had a history of mental illness (Table 2).

Table 2 Substance use, clinical, and war-related events of the respondents.
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Univariable analysis

Covariates with a p-value of less than 25% were evaluated for multivariable analysis via univariate analysis. The univariate analysis indicated that the covariates sex, family history of mental illness, previous history of mental illness, destruction of personal property, lack of food or water, physical abuse, being ill without medical care, alcohol consumption habit, chewing Khat, and smoking habit were significantly associated with PTSD symptoms. However, age, marital status, occupation, and education level were insignificant at the 25% level. Based on these findings, excluding these non-significant covariates and conducting the multivariable analysis using only the significant variables would be appropriate. Consequently, the effects of these critical factors should be more effectively elucidated via multivariable analysis.

Multivariable analysis

In a multivariable binary logistic regression, sex, family history of mental illness, previous history of mental illness, destruction of personal property, lack of food and water, physical abuse, disease without medical care, alcohol consumption, and Khat chewing were statistically significant at the 5% level (Table 2). Compared with males, females were 1.887 (95% CI: 1.127–3.160) times more likely to experience PTSD. Compared with non-consumers of alcohol, those who consumed alcohol demonstrated a 1.872 [95% CI: 1.034–3.390] greater risk of developing PTSD. Individuals who chewed Khat were 2.459 (95% CI: 1.046–5.781) times more likely than their non-chewing counterparts to exhibit PTSD symptoms (Table 3).

Table 3 Multivariable binary logistic regression results for PTSD among internally displaced people in the Gura Ferda district, Southwest Ethiopia.
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Residents with a family history of mental illness presented a 10.668 [95% CI: 4.361–38.026] higher risk of developing PTSD symptoms compared to those without such a history. Moreover, individuals with a personal history of mental illness demonstrated a 2.559 [95% CI: 1.346–4.869] higher prevalence of PTSD than those without such a history. These findings indicate that the destruction of personal property is associated with PTSD symptoms. Individuals who experienced the destruction of their belongings were 2.242 [95% CI: 1.237–4.059] times more likely to exhibit PTSD symptoms than those who did not. Subjects who lacked necessities, such as food and water, were 2.017 (95% CI: 1.102–3.686) times more likely to manifest PTSD symptoms than those who did not experience such deprivation. Those who experienced illness without access to medical care had a 2.132 [95% CI: 1.236–3.676] greater likelihood of developing PTSD than their counterparts. Additionally, the risk of developing PTSD symptoms was 2.058 [95% CI: 1.102–3.847] times higher among individuals who sustained injuries than among those who did not.

Model adequacy checking

The Hosmer-Lemeshow test statistic is insignificant (p-value = 0.432), suggesting that the model matched the data well. Furthermore, Nagelkerke’s R-squared equals 0.526, demonstrating that the model’s existing explanatory variables explained 52.6% of the variation across response variables (Table 2). These results indicate a strong model fit, providing confidence in the predictive capabilities of the chosen variables. Further analysis could explore additional predictors or interactions to enhance the model’s explanatory power even more. This could lead to a more nuanced appraisal of the factors influencing the response variables. Additionally, validating the model with a different dataset may further confirm its robustness and applicability in various contexts.

Discussion

This study assessed the prevalence and factors associated with PTSD among internally displaced people in the Bench Sheko zone, Gura Ferda District, Southwest Ethiopia. In this study, the prevalence of posttraumatic respondents was 217 (51.2%). This finding is consistent with the study done in northern Uganda at (54%)28, Sri Lanka (56%)29, and Darfur (54%)30. However, this finding was higher than the study findings noted in Turkey 34.9%31, Syrian refugees in Lebanon (35.4%)32, and 34.3% among the bombing victims of Oklahoma City, USA33. This finding is higher than that of a survey conducted in the East Wollega Zone, Oromia, where 33 (17.1%) patients had PTSD34. Conversely, our finding was lower than the study done in Kenya among internally displaced people at Maai Mahiu Camps, which reported that 60% of the respondents were younger than 45 years of age35.

In addition, the destruction of personal property was significantly associated with PTSD in this study. Those who had experienced this event were 2.2 times more likely to have PTSD than those who had not. In line with this, a prior study by Madoro et al. indicated that those who had encountered this event were 1.58 times more likely to develop PTSD than those who had not17. This could be because participants believe that such types of losses will be difficult or impossible to replace, making it difficult to avoid reminders of the event, feeling self-isolation, losing hope, and being prone to stressful situations36.

In this study, lack of food or water was associated with PTSD. This is consistent with studies conducted in rural Ethiopia and Rwanda37. In their study, researchers reported that symptoms of severe posttraumatic stress disorder were associated with both food insecurity and stressful life events, both of which contribute to a stressful life38. Furthermore, Hadley et al. also discovered that food insecurity contributes to symptoms of high post-traumatic stress disorder in their study in rural Ethiopia39. In line with this, our study findings demonstrated that food and water insecurity were linked to PTSD symptoms. James et al. also reported similar findings in their investigation in northern Uganda40.

In this study, substance abuse, such as alcohol consumption and khat chewing, was associated with PTSD. This finding is consistent with a study conducted in western Ethiopia, in which participants with a history of substance use were 1.7 times more likely than non-substance users to acquire post-traumatic stress disorder41. Furthermore, this conclusion is also consistent with a study conducted in the Netherlands, which found that individuals with drug use disorder were a significant and vulnerable subgroup for developing PTSD42. This could be because when individuals do not have access to such substances, they are more likely to feel weary, lack energy, experience irritability, restlessness, and other unpleasant emotions, which may be associated with more severe PTSD symptoms.

Furthermore, PTSD was found to be substantially related to a family history of mental illness. Respondents with a family history of mental illness were 10.8 times more likely to have PTSD than those without. This outcome was similar to the findings of South Korean investigations43. According to a recent study, the odds of having PTSD were 2.8 times higher among those who had a family history of mental illness than among those who did not have such a history. The finding that PTSD is substantially related to a family history of mental illness highlights the significant role that genetic and environmental factors play in the development of psychological disorders. The inheritance of the serotonin transporter gene, as well as genes involved with the hypothalamic-pituitary-adrenal axis and psychological characteristics that predispose participants to PTSD, could be one explanation44.

This study had its limitations and strengths. This study assessed the prevalence and factors associated with posttraumatic stress disorder45 among internally displaced people in the Gura Ferda district in southwestern Ethiopia. This study has several limitations. (i) We could not prove a causal relationship in this cross-sectional study41. (ii) In addition to the variables we considered, there may be other factors associated with the prevalence46 of depressive symptoms among residents that require further study. Despite this drawback, this study is one of the few studies in developing nations to employ standardized methods and thorough analysis47 .

Conclusions

We studied the prevalence and associated factors of PTSD in a community-based cross-sectional study in post-conflict among internally displaced people in the Gura Ferda district, Southwest Ethiopia. This study confirmed that PTSD is common in the study area. Gender, a history of mental illness, alcohol use, khat chewing habits, destruction of personal property, and a lack of food or water were found to be significant predictors of PTSD. To ensure the inhabitants’ mental health, interventions based on influencing factors must be put into practice.