Integrating Bright Futures Into Medical Education and Training
Bibliographic record
Abstract
<P>During the last few decades, pediatric healthcare professionals have faced increased demands to address the increasingly complex behavioral, social, and health conditions experienced by today’s children and families. At a time when it is most critical for the workforce to comprise an adept, multi-skilled cadre of professionals, the <cite>Bright Futures Guidelines for Health Supervision of Infants, Children, and Adolescents</cite>, third edition, provides guidelines for pediatric clinicians to fulfill necessary competencies and supplement their clinical skills with developmental and behavioral knowledge to treat the whole child.</P><H4>ABOUT THE AUTHORS</H4><P>Rebecca A. Stoltz, MPH, resides in Brookline, MA; Kara Connors, MPH, is with Bridgeway Health Associates, Concord, MA; Justine Blum is a junior at Dartmouth College, Hanover, NH, and a research assistant at Children’s Hospital at Dartmouth, Lebanon, NH;. Henry H. Bernstein, DO, is Chief, General Academic Pediatrics, Children’s Hospital at Dartmouth, and Dartmouth Medical School, Lebanon, NH.</P><P>Address correspondence to Henry H. Bernstein, DO, Chief, General Academic Pediatrics, Children’s Hospital at Dartmouth, One Medical Center Drive, Lebanon, NH 03756.</P><P>Ms. Stoltz and Ms. Connors have disclosed no relevant financial relationships. Dr. Bernstein has disclosed the following relevant financial relationships: Health Resources and Services Administration (HRSA) and Maternal Child Health Bureau (MCHB): Research Grant Support; and Springer Publisher: Book writing contract.</P><H4>EDUCATIONAL OBJECTIVES</H4><OL><LI>Describe the changes necessary in medical education to assure the healthcare provider is able to deliver culturally competent, comprehensive health maintenance to today’s children.</LI><LI>Discuss continuous professional development in light of increasingly available individualized education programs.</LI><LI>Review the content of select educational programs available to the practicing healthcare provider.</LI></OL>
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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 | 0.001 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".