Medical Students’ Views on Psychiatry in Germany and Italy: Survey
Bibliographic record
Abstract
Objectives: In 2019, the Insititue for Health Metrics and Evaluation reported that 16% of life lost were attributed to mental health. As a result, global shortage of psychiatrists is a pressing issue due to the increasing burden of mental illness. In 2016, a mere 5% of US medical students chose psychiatry as a career, a trend mirrored in Germany and Italy. As the medical students of 2016 have graduated or transitioned into residency in 2023, their attitudes towards psychiatry could have contributed to today’s shortage of psychiatrists. The global mental health burden has only been exacerbated by the COVID-19 pandemic. This study explores the attitudes of German and Italian medical students towards psychiatry, their career aspirations, and the influence of factors such as personal experience and education on their interest in the field. Methods: A cross-sectional survey was conducted among 799 medical students in two European countries in 2016. Participants answered questions about their attitudes towards psychiatry, their psychiatric education, and personal experiences. Inferential analyses were performed using chi-square tests and a significance level of 0.05. Results: The number of years in medical school, personal experiences, and perceived quality of education significantly affected specialty choice and ranking of psychiatry compared to other specialties. Internships, psychiatric placements, and views on psychiatric instructors also played a significant role in choosing psychiatry as a career. Conclusions: Assessing medical students’ attitudes towards psychiatry and the factors that influence their career choices, such as psychiatric education and personal experiences, can inform changes to attract students to the field. Addressing the worldwide shortage of psychiatrists is crucial to reduce the burden of mental health and substance use disorders.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".