Long-term use of antidepressants, mood stabilizers, and antipsychotics in pediatric patients with a focus on appropriate deprescribing
Bibliographic record
Abstract
It is estimated that 8% to 12% of youth are prescribed psychotropic medications. Those in foster care, juvenile justice systems, residential treatment facilities, and with developmental or intellectual disabilities are more likely to be prescribed high-risk regimens. The use of psychotropic medications in this age group is often off-label and can be associated with significant risk, warranting critical evaluation of their role. Landmark trials, pediatric-specific guidelines, and state-driven initiatives play critical roles in supporting evidence-based use of psychotropic medications in children. Overall, there is a lack of literature describing the long-term use of psychotropic medications in youth-particularly with regard to neurobiological, physical, and social changes that occur throughout development. Deprescribing is an important practice in child and adolescent psychiatry, given concerns for over-prescribing, inappropriate polytherapy, and the importance of reevaluating the role of psychotropic medications as children develop.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".