Mental health services among Rohingya refugees in Bangladesh: perspectives from field service providers
Bibliographic record
Abstract
Purpose This paper aims to understand the mental health experiences and needs of Rohingya refugees in Bangladesh from the perspective of mental health-care providers and hospital administrators. Design/methodology/approach This paper conducted a mixed methods study. Clinical data about refugee mental health care of 722 adult and pediatric patients were analyzed, and four focus groups with mental health providers (n = 4), primary health-care providers (n = 5), hospital administrators (n = 4) and midwives (n = 5) were held. Findings Clinical data analysis found that patients were diagnosed and treated for a variety of mental illnesses, including depression, anxiety, psychotic and neurological disorders. Misalignment between diagnosis and psychotropic medication prescription partly exists because of the unavailability of medications. Focus group findings indicate a lack of awareness of mental health conditions, and Rohingya visit hospitals for symptomatic physical ailments. Cultural and social factors discourage people from seeking mental health care. Patients are often brought by concerned family members or community health workers. A limited number of mental health-care providers are available to diagnose and treat Rohingya refugees, and follow-up care is often lacking. Research limitations/implications First, this paper only drew data from one field hospital in the camps. Future research should sample practitioners working in other health centers across all camps for a more comprehensive look at the prevalence and variations in mental health issues and mental health services provision. Second, this paper did not interview patients for this study as the study focused on the perspectives of administrators, health-care providers and support staff. Nevertheless, the inclusion of patients would have illuminated perceptions and attitudes and the social, familial and religious dynamics toward identifying mental health problems and seeking mental health services. Therefore, future research should aim to focus on participants’ voices and experiences. Practical implications Clinics across the camps should enhance the screening of refugees for common mental disorders and encourage them to report cases within their families. Further, health-care providers and support staff should explain to refugees the importance of non-pharmacological treatment approaches and that, according to studies, their effectiveness is equal to or sometimes more effective than pharmacological treatment. Social implications To address mental health-related stigma, conducting awareness campaigns in close collaboration with local leaders is critical to improving the level of knowledge among refugees, which could improve mental health-seeking behaviors. Originality/value This paper fulfills an identified gap in the mental health experiences and needs among the Rohingya refugees. The true prevalence of the range of mental health challenges among the Rohingya population is not accurately known; however, its impact is immense. The data indicates that mental health providers in remote regions be provided with training opportunities so they can effectively treat mental health conditions. Additionally, existing underlying root causes should be addressed through inclusive awareness programs in tandem with increasing the number of mental health clinics and providers across the camps and allocating more resources to provide medications for appropriate case treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".