Can Prenatal and Postnatal Cell Phone Exposure Increase Adverse Maternal, Infant and Child Outcomes?
Bibliographic record
Abstract
Abstract Objective To determine the association between maternal mobile phone use and adverse outcomes in infants, children, and mothers. Method In March 202, we conducted a search on the MEDLINE, Embase, and Scopus databases. Data extraction and an assessment of the quality of the studies were performed by two authors. The quality of the studies was assessed using the checklist of the Newcastle-Ottawa scale. Results Studies assessing behavioral problems in infants aged 6 to 18 months reported null findings. However, an increased risk of emotional and behavioral disorders was observed in children aged between 7 and 11 years whose mothers had been exposed to cell phones. The findings regarding the association between maternal cell phone exposure and adverse outcomes in children aged 3 to 5 are controversial. A study found a significant association between the call time (p = 0.002) or the history of mobile phone use (in months) and speech disorders in the children (p = 0.003). However, another study found that maternal cell phone use during pregnancy was not significantly associated with child psychomotor and mental developments. Inconclusive results were observed about the adverse outcomes in fetuses, such as fetal growth restriction or t scores for birth weight in cell phone users as opposed to non-users. On the contrary, the children of mothers who were cell phone users had a lower risk of scoring low on motor skills. Similar results were observed regarding the adverse outcomes of cell phone use in infants, such as fetal growth restriction or low birth weight, and the risk of preeclampsia was lower among subjects with medium and high cell phone exposure, as opposed to those with low exposure. Conclusion Studies on behavioral problems have reported different postnatal results, such as null findings among infants and a positive association in children.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".