Mental Health in the Middle East: Historical Perspectives, Current Challenges, and Future Implications
Bibliographic record
Abstract
Mental health practices and services in the Middle East have been profoundly shaped by the region's rich historical and cultural context, intertwined with the traditions of major monotheistic religions. This analytical literature review synthesizes existing scholarly research to examine the historical development of mental health approaches, current challenges and barriers, and potential future implications. Tracing the evolution from ancient practices to the establishment of psychiatric institutions and the integration of Western medicine, the review uncovers the impact of the Middle East's unique heritage on its mental health landscape. Current challenges include pervasive stigma, inadequate training for healthcare professionals, limited access to evidence-based interventions, and cultural barriers hindering open communication. The review explores recommendations such as implementing e-mental health interventions, developing national mental health strategies, collaborating with traditional healers, promoting public education campaigns, providing culturally responsive services and training, and garnering robust government support. By bridging knowledge gaps, challenging systemic barriers, and fostering cross-cultural collaborations, the Middle East can pave the way towards destigmatizing mental health, increasing accessibility, and embracing comprehensive, culturally sensitive support for individuals and communities.
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".