The association between long-distance migration and PTSD prevalence in Syrian refugees

Predicting Mental Health Care Enrollment and Treatment Uptake among Newly Arrived Refugees in U.S. Resettlement Programs

This article examines variables that predict mental health care enrollment and engagement among refugees. The authors explore a mental health care model designed to identify mental health needs early among refugee arrivals that may interfere with adjustment and overall health outcomes using data from a Midwest refugee resettlement program. Using ecological models of mental distress and theories on help-seeking behaviors, the authors used logistic and count regressions to predict enrollment in mental health care services and utilization rates. Gender, nationality, and presenting problems were significant predictors of enrollment and length of engagement in services. The findings provide guidance to practitioners and resettlement agencies on refugee mental health and opportunities to increasing access and engagement in mental health care.

Prevalence and risk factors associated with mental disorders among migrants in the MENA region: A systematic review and meta-analysis

BACKGROUND

The MENA region has experienced extraordinary events in recent years, resulting in an influx of refugees and displaced people who are vulnerable to mental disorders. Several previous studies have examined their prevalence, but none have focused on this region. This systematic review provided an estimate of the prevalence of mental illness and associated risk factors in the MENA region, and overcame the methodological limitations of individual studies.

METHODS

Thorough searches of the relevant databases were carried out to locate relevant published articles. Furthermore, cross-sectional studies were conducted to assess mental disorders in refugees, asylum seekers, migrants, or internally displaced people residing in the MENA region. Only studies meeting the aforementioned criteria were considered. For this purpose, RStudio software version 2023.12.0 + 369 with netmeta package was used for measurement and data analysis. JBI used to assess study quality.

RESULTS

The results, including 32 cross-sectional studies with a total of 21659 participants were obtained and discussed. The overall prevalence was 42% (95% CI; 30%, 54%) for depression, 43% (95% CI; 31%, 57%) for anxiety, 22% (95% CI; 11%, 39%) for stress, and 45% (95% CI; 36%, 53%) for PTSD. As a result, it was noted that being female was associated with depression, and being female and unemployed was associated with PTSD, however being married was protective against this later.

CONCLUSION

Compared to the rest of the globe, MENA has a greater rate of mental illness among refugees. Nevertheless, much effort should be devoted on listing causes associated, as well as their management and prevention.

Association of pre-migration socioeconomic status and post-migration mental health in Syrian refugees in Lebanon: a descriptive sex-stratified cross-sectional analysis

BACKGROUND

Refugee populations present with high levels of psychological distress, which may vary among sociodemographic characteristics. Understanding the distribution across these characteristics is crucial to subsequently provide more tailored support to the most affected according to their specific healthcare needs. This study therefore seeks to investigate the association between pre-migration socioeconomic status (SES) and post-migration mental health separately for male and female Syrian refugees in Lebanon.

METHODS

In a cross-sectional study, a cluster randomized sample of 599 refugees from Syria were recruited between 2016 and 2019 within 12 months after they fled to Lebanon. Logistic regression was used to determine the association between self-reported pre-migration SES and levels of anxiety and depressive symptoms assessed on the Hopkins Symptoms Checklist-25 (HSCL-25) scale, both for the entire sample and stratified by sex. To assess the informative value of self-reported SES, its correlation with education variables was tested. All analyses were conducted in R version 4.3.

RESULTS

Using complete cases, 457 participants (322 female, 135 male) were included in the analyses. Females showed on average more symptoms of anxiety (Median: 2.5) and depression (Median: 2.4) than males (Median: 2.10 and 2.07, respectively). Below average SES was associated with significantly higher odds for mental illness compared to average SES (anxiety: OR 4.28, 95% CI [2.16, 9.49]; depression: OR 1.85, 95% CI [1.06, 3.36]). For anxiety, differences between SES strata were larger for males than females. The self-reported SES measure showed only a weak positive correlation with education.

CONCLUSIONS

This study adds additional descriptive data highlighting mental health differences in Syrian refugees in Lebanon, whereby below average SES is associated with worse mental health outcomes compared to average SES. These findings demand further research into the underlying mechanisms. Improving our understanding of the observed differences will provide valuable insights that can contribute to the future development of targeted measures.

Anxiety and mood disorders in forcibly displaced people across the world

PURPOSE OF REVIEW

Displaced persons around the world have intensified in the previous decade and are predicted to rise further with greater global instability. The mental health issues involved with fleeing one's home, and attempting to make a new life in a host country need to be understood and addressed.

RECENT FINDINGS

Prevalence of anxiety and mood disorders, including posttraumatic stress disorder appear to be higher for displaced peoples than for the population in the host country. This is consistent across different methods. Traumatic life events in the country of origin as well as during flight contribute to symptom severity. Factors in the host country increasing severity including isolation, discrimination, low social support. There are successfully implemented intercultural interventions at the individual level of the practitioner, as well as at the institutional level.

SUMMARY

There are many possibilities for successful interventions in displaced people, realizing this at a scale appropriate to the size of the problem remains a challenge.

Ventral tegmental area dopaminergic action in music therapy for post-traumatic stress disorder: A literature review

Post-traumatic stress disorder (PTSD) is a debilitating sequela of extraordinary traumatic sufferings that threaten personal health and dramatically attenuate the patient's quality of life. Accumulating lines of evidence suggest that functional disorders in the ventral tegmental area (VTA) dopaminergic system contribute substantially to PTSD symptomatology. Notably, music therapy has been shown to greatly ameliorate PTSD symptoms. In this literature review, we focused on whether music improved PTSD symptoms, based on VTA dopaminergic action, including the effects of music on dopamine (DA)-related gene expression, the promotion of DA release and metabolism, and the activation of VTA functional activities. In addition, the strengths and limitations of the studies concerning the results of music therapy on PTSD are discussed. Collectively, music therapy is an effective approach for PTSD intervention, in which the VTA dopaminergic system may hold an important position.

Considerations for Using Multiple Imputation in Propensity Score-Weighted Analysis - A Tutorial with Applied Example

Purpose

Propensity score-weighting for confounder control and multiple imputation to counter missing data are both widely used methods in epidemiological research. Combination of the two is not trivial and requires a number of decisions to produce valid inference. In this tutorial, we outline the assumptions underlying each of the methods, present our considerations in combining the two, discuss the methodological and practical implications of our choices and briefly point to alternatives. Throughout we apply the theory to a research project about post-traumatic stress disorder in Syrian refugees.

Patients and Methods

We detail how we used logistic regression-based propensity scores to produce "standardized mortality ratio"-weights and Substantive Model Compatible-Full Conditional Specification for multiple imputation of missing data to get the estimate of association. Finally, a percentile confidence interval was produced by bootstrapping.

Results

A simple propensity score model with weight truncation at 1st and 99th percentile obtained acceptable balance on all covariates and was chosen as our model. Due to computational issues in the multiple imputation, two levels of one of the substantive model covariates and two levels of one of the auxiliary covariates were collapsed. This slightly modified propensity score model was the substantive model in the SMC-FCS multiple imputation, and regression models were set up for all partially observed covariates. We set the number of imputations to 10 and number of iterations to 40. We produced 999 bootstrap estimates to compute the 95-percentile confidence interval.

Conclusion

Combining propensity score-weighting and multiple imputation is not a trivial task. We present considerations necessary to do so, realizing it is demanding in terms of both workload and computational time; however, we do not consider the former a drawback: it makes some of the underlying assumptions explicit and the latter may be a nuisance that will diminish with faster computers and better implementations.