Sociodemographic Characteristics and Mental and Physical Health Diagnoses of Yazidi Refugees Who Survived the Daesh Genocide and Resettled in Canada
Bibliographic record
Abstract
Importance: The health status of Yazidi refugees, a group of ethnoreligious minority individuals from northern Iraq who resettled in Canada between 2017 and 2018 after experiencing genocide, displacement, and enslavement by the Islamic State (Daesh), is unknown but important to guide health care and future resettlement planning for Yazidi refugees and other genocide victims. In addition, resettled Yazidi refugees requested documentation of the health impacts of the Daesh genocide. Objective: To characterize sociodemographic characteristics, mental and physical health conditions, and family separations among Yazidi refugees who resettled in Canada. Design, Setting, and Participants: This retrospective clinician- and community-engaged cross-sectional study included 242 Yazidi refugees seen at a Canadian refugee clinic between February 24, 2017, and August 24, 2018. Sociodemographic and clinical diagnoses were extracted through review of electronic medical records. Two reviewers independently categorized patients' diagnoses by International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes and ICD-10-CM chapter groups. Diagnosis frequencies were calculated and stratified by age group and sex. Five expert refugee clinicians used a modified Delphi approach to identify diagnoses likely to be associated with Daesh exposure, then corroborated these findings with Yazidi leader coinvestigators. A total of 12 patients without identified diagnoses during the study period were excluded from the analysis of health conditions. Data were analyzed from September 1, 2019, to November 30, 2022. Main Outcomes and Measures: Sociodemographic characteristics; exposure to Daesh captivity, torture, or violence (hereinafter, Daesh exposure); mental and physical health diagnoses; and family separations. Results: Among 242 Yazidi refugees, the median (IQR) age was 19.5 (10.0-30.0) years, and 141 (58.3%) were female. A total of 124 refugees (51.2%) had direct Daesh exposure, and 60 of 63 families (95.2%) experienced family separations after resettlement. Among 230 refugees included in the health conditions analysis, the most common clinical diagnoses were abdominal and pelvic pain (47 patients [20.4%]), iron deficiency (43 patients [18.7%]), anemia (36 patients [15.7%]), and posttraumatic stress disorder (33 patients [14.3%]). Frequently identified ICD-10-CM chapters were symptoms and signs (113 patients [49.1%]), nutritional diseases (86 patients [37.4%]), mental and behavioral disorders (77 patients [33.5%]), and infectious and parasitic diseases (72 patients [31.3%]). Clinicians identified mental health conditions (74 patients [32.2%]), suspected somatoform disorders (111 patients [48.3%]), and sexual and physical violence (26 patients [11.3%]) as likely to be associated with Daesh exposure. Conclusions and Relevance: In this cross-sectional study, Yazidi refugees who resettled in Canada after surviving the Daesh genocide experienced substantial trauma, complex mental and physical health conditions, and nearly universal family separations. These findings highlight the need for comprehensive health care, community engagement, and family reunification and may inform care for other refugees and genocide victims.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".