A “U-shaped" Curve: Appreciating How Primary Care Residency Intention Relates to the Cost of Board Preparation and Examination
Bibliographic record
Abstract
INTRODUCTION: The shortage of primary care physicians in the United States has warranted an investigation into how medical education debt and other factors influence medical students' interests in primary care (PC) residencies. However, sparse research has studied how the cost of board preparation and examination relates to career choice. The objective of this study was to determine if there is an association between the cost of preparing and sitting for board examinations and the intention to enter a PC residency for osteopathic medical students. METHODS: We postulated that students who incurred higher financial costs from preparing and sitting for board examinations would be more likely to be interested in non-primary care (NPC) residencies. Using a non-experimental survey design, this study asked respondents to evaluate the following: "I plan to enter a Primary Care Residency (Family Medicine OR General Internal Medicine OR Pediatrics)" using a Likert scale. Respondents were also asked to select which board examination(s) and pertinent resource(s) they had purchased. Total costs were calculated per student. RESULTS: A total of 25,852 osteopathic medical students received the survey, of which 1,280 students responded to and completed it, yielding a 4.95% response rate. The distribution of respondents' intentions to pursue a primary care residency and costs spent yielded a "U" shaped curve. Respondents who Strongly Agreed and Strongly Disagreed to the statement "I plan to enter a Primary Care Residency" spent $5,744 and $5,070 on board-preparation and examination, respectively. No statistically significant differences were found between the cost of preparing and sitting for board examinations and the intention to enter primary care residencies when individuals were grouped by year in school and gender. CONCLUSIONS: Because competitive NPC specialties have relatively higher salaries, we suspected that students who intended to pursue these specialties would have had higher financial costs from board examination and preparation compared to students who intended to pursue PC residencies such as family medicine. Our findings further illustrate these specific educational costs do not correlate with students' stated intentions to enter primary care residencies. As efforts continue to determine a solution for the primary care physician shortage, it becomes clearer that the focus must also encompass non-financial influences that shape career choice.
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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 | 0.024 | 0.145 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".