When physicians forego the doctor–patient relationship, should they elect to self-prescribe or curbside? An empirical and ethical analysis
Bibliographic record
Abstract
BACKGROUND: The American Medical Association, the British Medical Association and the Canadian Medical Association have guidelines that specifically discourage physicians from self-prescribing or prescribing to family members, but only the BMA addresses informal prescription requests between colleagues. OBJECTIVE: To examine the practices of paediatric providers regarding self-prescribing, curbsiding colleagues, and prescribing and refusing to prescribe to friends and family. METHODS: 1086 paediatricians listed from the American Academy of Paediatrics 2007 web-based directory were surveyed. RESULTS: 44% (430/982) of eligible survey respondents returned usable surveys. Almost half (198/407) of respondents had prescribed for themselves. An equal number (198/411) had informally requested a prescription from a colleague. Three-quarters (325/429) stated they had been asked to prescribe a prescription drug for a first-degree or second-degree relative, and 51% (186/363) had been asked by their spouse. Eighty-six per cent (343/397) stated that they had refused to write a prescription on at least one occasion for a friend or family member. The following reasons "strongly influenced" their decision to refuse a prescription request: (1) outside of provider's expertise (88%); (2) patient's need for his or her own physician (70%); (3) not medically indicated (69%); (4) need for a physical examination (65%). CONCLUSION: These data confirm that most physicians have engaged in self-prescribing or curbside requests for prescriptions. It can be argued that curbsiding is more morally problematic than self-prescribing because it implicates a third party, and should be discouraged regardless of whether the requester is a colleague, family member or friend.
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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 | 0.220 | 0.467 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".