Chronic Care Education in Medical School
Bibliographic record
Abstract
The healthcare system is faced with a rapidly increasing number of individuals with chronic conditions and disabilities. The need for a chronic care model of health care with interdisciplinary treatment involving the patient and family with a focus on functional health is recognized but not fully established in the medical community. The education of medical students in a chronic care model is essential so that physicians in all specialties may provide effective and efficient care to their patients. Physiatrists and physicians trained in the specialty of Physical Medicine and Rehabilitation are uniquely situated to be leaders in the education of medical students in the appropriate care for individuals with chronic conditions and disabilities. Academic physiatrists must be involved in the education of medical students. This involvement will result in a higher level of patient care for all patients with chronic conditions and disabilities. In 2007, the Association of Academic Physiatrists formed a task force to evaluate educational models and make recommendations regarding the education of medical students in the management of individuals with chronic conditions and disabilities. The task force also evaluated opportunities for physiatrists to participate in the education of medical students. This article summarizes the work of the task force.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.002 |
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".