Bibliographic record
Abstract
Background/rationale: Physicians and medical students are at risk for some serious mental health issues by the very attributes that make us good at what we do.There is a tendency in many physicians towards a strong preference to be independent, to not be seen as weak, to be respected by peers, to fit with the general medical culture of service and selflessness, and to make work the major aspect of their lives.We also tend, as a profession, to select for personality type (Myers).Some common characteristics of those entering medicine are perfectionism, organizational capacity, placing high demands on self, obsessiveness and compulsiveness (not necessarily OCD), and intolerance of feeling helpless (Myers).Despite medical learners being apt to care for their health very well in terms of managing diet and exercise even with very busy schedules, there is a high rate of depression, anxiety, and related mental health issues including substance misuse/abuse (Myers).We (physicians and medical learners) use many defense mechanisms (Myers) and learn them early as part of the cultural immersion in the discipline.These are not always positively adaptive.Stressors, coupled with these characteristics, often put severe strains on relationships outside medicine including families/partners.In medical school, this may be a particular challenge.Although partners recognize that the terms of medical school are temporary, there is still the need to go where the program sends the student.Partners can't always go to the same place -they may have careers of their own, lack child care, supports, or even the basic amenities of adequate family housing or ability to maintain a main home base for the family.Some programs require extended rotations in different areas, some of which have their own related challenges.The literature regarding medical practice in rural areas suggests barriers to care specific to these areas that include (but are certainly not limited to) lack of relationship opportunities, work hours, isolation in practice or personal life, access, confidentiality, and cultural safety.There are several risk factors that apply to medical learners of all levels.Among them are number of hours worked, sleep deprivation, imbalance between work and personal life, lack of control of duties and hours, decreased social networking, lack of convenient access to care, not wanting to appear 'weak' to preceptors, feeling isolated and 'uncared for,' and concerns regarding confidentiality, mandatory reporting, and lack of knowledge of available resources (Myers).Learners also sometimes feel as though the administration/medical school staff doesn't care about them, and leave them to deal with stressors on their
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".