Association of cesarean section delivery with childhood behavior: a systematic review protocol
Bibliographic record
Abstract
OBJECTIVE: This review will evaluate the association between cesarean section delivery and child behavior problems. INTRODUCTION: Cesarean section (C-section) deliveries account for over 30% of deliveries in Canada and 21% of all births globally. Mode of delivery via C-section has been associated with altered maternal mental health in the postpartum period, and postpartum depression is linked to an increased risk of internalizing and externalizing behaviors in children. Given the high rates of C-section deliveries worldwide, it is important to determine how mode of delivery impacts child behavior. INCLUSION CRITERIA: The review will examine child behavior outcomes among preschool and school-aged children as determined by medical diagnosis or a standardized assessment tool. Multiple gestation pregnancies and pre-term delivery will be excluded. METHODS: A search will be conducted using APA PsycINFO (Ovid), MEDLINE (Ovid), Embase (Ovid), CINAHL (EBSCOhost), and Scopus. This review will evaluate peer-reviewed primary observational research studies specifically looking at examining C-section delivery. Two reviewers will independently screen titles, abstracts, and full-text studies to determine alignment with the inclusion and exclusion criteria. Data will be recorded using the standardized JBI data extraction tool and be presented using figures, tables, and a summary. Where feasible, we will conduct a meta-analysis and subgroup analysis of suitable populations. Critical appraisal of studies will be performed for included studies. The certainty of the evidence will be assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. REVIEW REGISTRATION: PROSPERO CRD42022371294.
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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 | 0.054 | 0.059 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.019 | 0.017 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.055 | 0.007 |
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".