A systematic review and meta-analysis of pediatric integrated primary care for the prevention and treatment of physical and behavioral health conditions
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effects of behavioral health interventions delivered within pediatric integrated primary care models on clinical outcomes. METHODS: We searched Medline, EMBASE, CENTRAL, PsycINFO, and SCOPUS for studies published from January 1, 1998, to September 20, 2023. We included studies that evaluated onsite behavioral health integration in pediatric primary care using a comparator condition (usual, enhanced usual care, or waitlist). Outcome data on symptom change, impairment/quality of life, health indicator, and behavior change were extracted using Covidence software. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline was followed Risk of bias analysis was conducted using the Cochrane Risk of Bias tool. We used multilevel meta-analysis to synthesize multiple outcomes nested within studies. Open Science Foundation pre-registration: #10.17605/OSF.IO/WV7XP. RESULTS: In total, 33 papers representing 27 studies involving 6,879 children and caregivers were included. Twenty-four studies were randomized controlled trials and three were quasi-experimental designs. Seventeen papers reported on treatment trials and 16 reported on prevention trials. We found a small overall effect size (SMD = 0.19, 95% confidence interval [0.11, 0.27]) supporting the superiority of integrated primary care to usual or enhanced usual care. Moderator analyses suggested similar effectiveness between co-located and integrated models and no statistically significant differences were found between treatment and prevention trials. CONCLUSIONS: Results suggest that integrated primary care is superior to usual and enhanced usual care at improving behavior, quality of life, and symptoms. Integrated primary care research needs improved standards for reporting to promote better synthesis and understanding of the literature.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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".