Trauma and Demographics in Asylum Outcomes: Insights from a Decade of Forensic Evaluations at a Student-Run Clinic

Sophia Xu BA, Alan Chen BA, Ted Shi BS, Prantik Saha MD, Michael Devlin MD, on behalf of Columbia Human Rights Initiative Asylum Clinic

What is Asylum?

• The US is the world's leading recipient of new individual applications for asylum, with 3.4 million total open cases as of July 2025.
• Under US law, asylum is a protection granted to foreign nationals who meet the international law definition of a “refugee”.
• Must undergo a lengthy screening process to prove that they are facing a “well-founded fear of persecution” on account of their race, religion, nationality, political group, or membership in a social group.

FMEs are “an absolutely necessary piece”* for Asylum Seekers

• Asylum seekers face significant challenges in substantiating their claims of trauma and persecution.
• A forensic medical evaluation (FME) documents facts relevant to an applicant’s history of torture, ill-treatment, or persecution.
• Inclusion of FMEs significantly improves asylum case outcomes by substantiating applicant testimonies and clarifying the medical and psychological consequences of persecution.
• PHR study: 89% of cases with a FME resulted in a grant of asylum, compared to the national average of 37.5% (Lustig et al. 2008).

*Quote from (Scruggs et al. 2016)

CHRIA provides pro bono access to FMEs

• In 1989, Physicians for Human Rights (PHR) launched an Asylum Network to connect lawyers and asylum seekers with medical professionals to conduct FMEs,
• CHRIA was founded in 2010 to expand access to FMEs. We are a member of PHR’s Asylum Network and receive cases through PHR as well as Columbia Law’s Immigrants’ Rights Clinic and various private law offices.

Which demographic factors and traumatic experiences predict asylum approval at a student run clinic?

Data

• 256 completed cases from 2014-2024 were included from a single student-run clinic.
• 63 (24.5%) were granted asylum as of January 2025.
• Cases that remain unapproved consisted of 6 “denied” (2.3%), 14 “dismissed” (5.5%), and 173 still awaiting due process (67.6%).
• 8 demographic factors and 12 traumatic experiences binarized
• Demographic: adult age, has children, has family in the US, has a job, use of interpreter, LGBTQ affiliation, married, female gender
• Trauma: detained, domestic violence, ethnic violence, gang violence, genital mutilation, kiddnapped, police violence, political violence, psychiatric diagnosis, sexual violence, torture, trafficking

Adult age, having family in the US, and use of an interpreter were the most common demographic factors.

Psychiatric diagnosis, domestic violence, and sexual violence were the most common trauma factors.

3 Trauma Experiences: Ethnic Violence, Being Kidnapped, and Presence of a Psychiatric Diagnosis Significantly Predict Asylum Approval

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No Demographic Factors Reached Significance, but Having Children Neared Significance.

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Conclusions

• Trauma-related factors, such as kidnapping, ethnic violence, and psychiatric diagnoses, significantly predict asylum success.

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• Although demographics like income, age, and gender showed limited predictive value, they may reflect systemic barriers faced by asylum seekers.
• Addressing these issues is essential for fostering a more equitable asylum process.

Limitations

• Data storage practices were inconsistent over time, and data cleaning is ongoing
• Analysis reflects currently available data; findings are preliminary
• Many pending and unknown outcomes
• Some could have been granted asylum
• Only include known outcomes: granted (1), denied (0), dismissal (0), administrative action (0)
• Gender binarization non-inclusive and arbitrary
• Cisgender man (1) vs all other genders (0)
• Expand and specify psychiatric and medical diagnoses
• PTSD, depression, anxiety, others
• Include physical symptoms: scars, burns, lacerations, gait abnormalities, others

Future Directions

• In the process of publishing our full findings using updated guidelines (only analyzing known outcomes, non-arbitrary binarizations, inclusion of physical symptoms and expansion of psychiatric diagnoses)
• First such data from a student run asylum clinic
• Compare with PHR data (Atkinson et al. 2021)
• Analyze trends across time
• Effect of policy changes, different government administrations, Covid-19
• Will continue to update data as case outcomes become known

Thanks!