Geopsychiatry and its integration into psychiatry residency curricula: A very first global survey for faculty and psychiatry residents
Bibliographic record
Abstract
Geopsychiatry, an emerging field, explores the interaction between environmental factors and mental health, addressing how sociopolitical, economic, and ecological crises impact psychological well-being. Despite its relevance, Geopsychiatry is largely absent from psychiatric training curricula globally. This study aimed to evaluate the current integration of Geopsychiatry in psychiatry residency programs worldwide, and to understand the perceptions of faculty and residents regarding its importance in clinical training. This mixed-methods cross-sectional study collected data from 401 psychiatry faculty members and residents across various regions via an online survey from May to September 2024. The survey assessed familiarity with Geopsychiatry, perceived importance of its inclusion in psychiatric education, and barriers to integration. Descriptive and inferential statistical analyses, including chi-square tests, were conducted to evaluate the associations among participant demographics, knowledge, and interest levels. The findings revealed limited knowledge of Geopsychiatry, with only 4.2 % of the participants reporting high familiarity. Nonetheless, 62.6 % viewed its inclusion in psychiatric education as “very important,” particularly those from Latin America and MENA regions. A lack of faculty expertise (48.1 %) and insufficient resources (52.9 %) were cited as significant barriers. However, participation in training activities was significantly associated with higher levels of familiarity (χ 2 = 83.063, p < 0.001), underscoring the importance of educational access. Collaborative efforts also enhanced research opportunities in Geopsychiatry (χ 2 = 59.530, p < 0.001). There is a significant gap between the perceived importance of Geopsychiatry and its formal inclusion in training programs. Expanding training opportunities, particularly through online modules and inter-institutional collaborations, may support the integration of this field into psychiatric education, addressing the growing need to prepare future psychiatrists for mental health challenges posed by environmental changes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".