Does it work in the real world? The effectiveness of treatments for psychological problems in children and adolescents.
Bibliographic record
Abstract
Despite the availability of hundreds of treatment studies in the scientific literature, we know little about whether these treatments work in regular practice. We present an updated review of treatment effectiveness studies for psychological problems in children and adolescents. A literature search yielded 20 recent articles describing effectiveness studies for the treatment of anxiety disorders, depression, and disruptive behavior problems. We compared data from these effectiveness studies with two benchmarks reported in meta-analyses of efficacy trials: the numbers of clients who completed services and the improvements found in those who completed services. All studies of the treatment of internalizing disorders reported completion rates above 80%; the majority of parenting interventions for the treatment of disruptive behavior problems reported that more than 75% of parents who began services completed them. The improvement rates reported in effectiveness studies for internalizing problems were comparable to the benchmarks reported in efficacy studies. There was greater variability in the treatment of disruptive behavior problems, with several studies outperforming the benchmark, and a smaller number yielding poorer results. Practitioners should be encouraged to see promising results that suggest evidence-based treatments for child and adolescent disorders can be effective when used in typical clinical settings.
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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 | 0.035 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".