Negative Symptom Interventions in Youth at Risk of Psychosis: A Systematic Review and Network Meta-analysis
Bibliographic record
Abstract
Objective: Youth at clinical high risk (CHR) for psychosis often demonstrate significant negative symptoms, which have been reported to be predictive of conversion to psychosis and a reduced quality of life but treatment options for negative symptoms remain inadequate. Therefore, we conducted a systematic review and network meta-analysis of all intervention studies examining negative symptom outcomes in youth at CHR for psychosis. Method: The authors searched PsycINFO, Medline, Embase, CINAHL, and EBM from inception to December 2016. Studies were selected if they included any intervention that reported follow-up negative symptoms in youth at CHR for psychosis. Treatment comparisons were evaluated using both pairwise and network meta-analyses. Due to the differences in negative symptom scales the effect sizes were reported as the standardized mean difference (SMD). Results: Of 3027 citations, 32 studies met our inclusion criteria, including a total of 2463 CHR participants. The null hypothesis was not rejected for any of the 11 treatments. N-methyl-D-aspartate-receptor (NMDAR) modulators trended toward a significant reduction in negative symptoms compared to placebo (SMD = -0.54; 95% CI = -1.09 to 0.02; I2 = 0%, P = .06). In respective order of descending effectiveness as per the treatment hierarchy, NMDAR modulators were more effective than family therapy, need-based interventions, risperidone, amisulpride, cognitive behavioral therapy, omega-3, olanzapine, supportive therapy, and integrated psychological interventions. Conclusions: Efficacy and effectiveness were not confirmed for any negative symptom treatment. Many studies had small samples and the majority were not designed to target negative symptoms.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".