Culturally Adapting a Digital Intervention to Reduce Suicidal Ideation for Syrian Asylum Seekers and Refugees in the United Kingdom: Protocol for a Qualitative Study
Bibliographic record
Abstract
BACKGROUND: The conflict in Syria has produced the largest forced displacement crisis since the Second World War. As a result, Syrians have experienced various stressors across the migratory process, putting them at an increased risk of developing mental health issues, including, crucially, suicidal ideation (SI). Despite their high rates of SI across Europe, there remain various barriers to accessing treatment. One way to increase access is the use of culturally adapted digital interventions, which have already shown potential for other minority populations. To culturally adapt the intervention, further research is needed to better understand Syrian asylum seekers' and refugees' cultural conceptualizations, coping strategies, and help-seeking behavior for SI. To do so, this study will use a unique cultural adaptation framework to intervene at points of lived experience with the migratory process where Syrian culture and signs of psychopathology converge. Likewise, co-design events will be used to adapt points of experience with the intervention where Syrian culture and the intervention conflict. As the first cultural adaption of a digital SI intervention for Syrian asylum seekers and refugees, this study will hopefully encourage further development of culturally sensitive interventions for the largest refugee population in the United Kingdom and the world. OBJECTIVE: The objective of the study is to increase access to mental health treatment for Syrian asylum seekers and refugees in the United Kingdom by culturally adapting a digital intervention to reduce SI. METHODS: The study will use experience-based co-design, an action research method, to culturally adapt a digital intervention to reduce SI for Syrian asylum seekers and refugees in the United Kingdom. This will involve conducting 20-30 interviews to understand their lived experiences with the migratory process, cultural conceptualizations of mental health and SI, coping strategies, mental health help-seeking behavior, and perceptions of digital mental health interventions. In addition, 3 co-design events with 6 participants in each will be held to collaboratively adapt the intervention. Touchpoints and themes extracted from each phase will be prioritized by a community panel before adapting the intervention. RESULTS: The study began in November 2022 and will continue until the last co-design event in August 2023. The results of the study will then be published by December 2023. CONCLUSIONS: Access to treatment for some of the most severe mental health issues is still limited for Syrian asylum seekers and refugees in the United Kingdom. Cultural adaptations of digital interventions developed for general populations have the potential to increase access to treatment for this population. Specifically, adapting the intervention for Syrian asylum seekers' and refugees' experiences with SI in relation to their lived experience with the migratory process may enable greater recruitment and adherence for users of various cultural and ethnic subgroups and levels of SI. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47627.
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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 | 0.038 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.035 | 0.005 |
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".