Pediatric Prescribing Practices and the FDA Black-box Warning on Antidepressants
Bibliographic record
Abstract
BACKGROUND: Since the FDA Black box warning in 2004, there has been a 58% drop in antidepressant use among children and adolescents with depression. Paralleling this decrease is an associated increase in completed suicides in youth. To date, no study has examined, on a clinician level, the changes in practice that have occurred subsequent to the FDA warning. OBJECTIVE: To examine changes in pediatrician clinical practice resulting from the FDA warning on antidepressants. METHODS: Subjects were recruited through a national program sponsored by the Canadian Pediatric Society that regularly surveys practicing pediatricians. The mail survey inquired about knowledge of the Black-box warning, whether their practice changed and reasons for changes in prescribing practices with antidepressants after the warning. We surveyed a total of 2395 pediatricians in Canada. RESULTS: Of the 1748 eligible pediatricians, 670 (38%) responded.Seventy-two percent (n = 484) of respondents were aware of the FDA warning. Of the 484 respondents who were aware of the warning, 80% (n = 386) changed their prescribing practices including 32% (n = 154) who followed their patients more closely. Seven percent (n = 35) stopped treatment with SSRIs in at least one patient. Physicians who had observed worsening depression/suicidality were more likely to discontinue treatment with SSRI's compared to those who had not observed these side effects previously (25% versus 6%, p < 0.001). CONCLUSION: This is the first national study to examine individual pediatrician practice changes in antidepressant use subsequent to the FDA warning. Further research is needed to better understand the reasons for these changes to aid in the development of strategies that could help clinicians to optimally integrate these warnings into clinical practice.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".