Use of Electronic Communication by Physician Breastfeeding Experts for Support of the Breastfeeding Mother
Bibliographic record
Abstract
BACKGROUND: Breastfeeding initiation and duration increase because of physician encouragement. However, many physicians have not received education on breastfeeding, and some may not have a supportive attitude or commitment to breastfeeding. Patients identify dissatisfaction with their current provider as a motivating factor in seeking health information on the Internet. This survey was performed to determine how many physicians with an interest and expertise in breastfeeding are being contacted for breastfeeding information over the Internet and to examine physicians' attitudes to these requests. SUBJECTS AND METHODS: An e-mail describing the survey, inviting participation, and containing a link to the online questionnaire was posted on the Web site of the Academy of Breastfeeding Medicine and as well as on the Listserv of the American Academy of Pediatrics-Section on Breastfeeding. Information collected included physician training, successes and challenges related to providing breastfeeding medicine support by e-mail, and current level of e-mail communication with patients regarding breastfeeding issues. RESULTS: One-fourth of physicians in our survey receive e-mails with questions about breastfeeding issues from patients with whom they have no preexisting relationships. More receive e-mail from known patients. This suggests that breastfeeding mothers seek expert information on the Internet. Over half of the physicians replied to e-mails individually and without any financial reimbursement. CONCLUSIONS: Many breastfeeding mothers reach out to breastfeeding experts over the Internet. Our findings suggest that physicians who provide care to breastfeeding mothers need further education on breastfeeding to provide adequate support to their own patients.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 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".