The Effectiveness of Selective Serotonin Reuptake Inhibitors for Treatment of Obsessive-Compulsive Disorder in Adolescents and Children: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Obsessive-compulsive disorder (OCD) is a common behavioral disorder among adolescents and children. The selective serotonin reuptake inhibitors (SSRI) are the first pharmacological choice for this condition due to mild adverse effect profile. Objective: This systematic review was performed to evaluate the efficacy of SSRI for OCD in adolescents and children. Methods: Search terms were entered into PubMed, PsycINFO, Scopus, CINAHL and Google Scholar. The included studies were randomized, placebo-controlled trials of SSRIs conducted in populations of children and adolescents younger than 18 years. Change from baseline CY-BOCS, end-treatment CY-BOCS with respective SD and response and remission rates were collected for continuous and dichotomous outcome assessment, respectively. Cochrane Rev Man software was used for meta-analyses, providing Forest plots where applicable. Results: SSRIs were superior to placebo with a small effect size. There was no additional benefit of combination treatment over CBT alone, but CBT added substantial benefit to SSRI monotherapy. Fluoxetine and Sertraline appear to be superior to Fluvoxamine. Conclusion: The results of current systematic review and meta-analysis support the existing NICE guidelines for choosing CBT as the first line of treatment and substituting it with SSRI depending on patient preference. Adding CBT to current SSRI treatment is effective for non-responders and partial responders but adding SSRI to ongoing CBT does not prove beneficial. The SSRIs have different effectiveness and their relative efficacy remains to be investigated.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".