Psychosocial Intervention Outcomes for Children with Congenital and Neonatal Conditions: Systematic Review
Bibliographic record
Abstract
There has been a historic lack of psychosocially geared treatment studies for congenital and neonatal conditions that impact brain development, despite well-established knowledge that these conditions impact cognitive development, quality of life (QoL), mental health, and academic success. OBJECTIVE: The aim of the present study was to systematically investigate the research literature focusing on the effects of interventions in psychosocially geared programs for children with neonatal brain injury on school and psychological outcomes. METHODS: Psychosocially geared programs broadly refer to interventions to improve parenting and school functioning, or child behavior, as well as other interventions that have a psychological component but may be more physically oriented, such as goal-directed physiotherapy. A comprehensive search of PubMed, Medline, PsychINFO, and Embase was completed between June and July 2020. The methodological quality of included articles was assessed using the Cochrane Risk of Bias Tool for Randomized Trials (RoB-2). RESULTS AND CONCLUSION: Twenty studies met the inclusion criteria and demonstrated adequate risk of bias (i.e., low risk of bias or some concerns). The studies included family (n = 2), parenting (n = 7), and child (n = 10) interventions. There is some evidence supporting the effectiveness of psychosocial interventions for children with neonatal brain injury and their families on academic outcomes, behavior, and QoL, indicated by positive intervention effects in 65% (n = 13) of studies.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".