Antidepressant Medications in Children and Adolescents
Bibliographic record
Abstract
Therapeutics Letter 52 reviews the use of antidepressant medications in children and adolescents. Conclusions: the prescription of an antidepressant to a child or adolescent is like an open trial with up to 80% of patients expected to improve. When improvement occurs, it is most likely due to a placebo group response, which includes spontaneous remission, response to supportive care, and other components. Because of the unfavorable harm to benefit balance for antidepressants in this age group, first-line therapy is multiple supportive interventions: sleep hygiene, exercise, regular dietary patterns, consistent parenting, and practical problem-solving regarding schooling and life stressors. For those who do not respond, individual or group cognitive behavioral therapy or interpersonal psychotherapy should be arranged, if possible. Medications are reserved for add-on therapy when the first two approaches are not working. When an antidepressant is prescribed, the patient must be monitored for signs of deterioration: behavioral and psychiatric changes, including increases in suicidal thinking, as emphasized by the new Health Canada labeling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".