Forcibly displaced persons and mental health: A survey of the experiences of Europe-wide psychiatry trainees during their training
Bibliographic record
Abstract
Many European countries have seen increasing refugee populations and asylum applications over the past decade. Forcibly displaced persons (FDPs) are known to be at higher risk of developing mental disorders and are in need of specific care. Thus, specific training for mental health professionals is recommended by international health organizations. The aim of this exploratory study was to assess the experience of clinical work with FDPs among psychiatric trainees in Europe and Central Asia as well as their interest and specific training received on this topic. An online questionnaire was designed by the Psychiatry Across Borders working group of the European Federation of Psychiatric Trainees (EFPT) and was distributed via email through local networks among European trainees from 47 countries between March 2017 and April 2019. Answers of 342 psychiatric trainees from 15 countries were included in the survey analysis. A majority of trainees (71%) had had contact with FDPs in the last year of their clinical work. Although three-quarters expressed a strong interest in the mental health of FDPs, only 35% felt confident in assessing and treating them. Specific training was provided to 25% of trainees; of this subset, only a quarter felt this training prepared them adequately. Skills training on transcultural competencies, post-traumatic stress disorder, and trauma management was regarded as essential to caring for refugees with confidence. Although psychiatric trainees are motivated to improve their skills in treating FDPs, a lack of adequate specific training has been identified. The development of practical skills training is essential. International online training courses could help meet this pressing need.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".