Exploring the Connection Between Domestic Violence and Masticatory Outcomes in the Pediatric Population: A Systematic Review
Bibliographic record
Abstract
The potential interplay between domestic violence and masticatory outcomes in children and adolescents has garnered increasing attention. Understanding the association between domestic abuse and specific oral health parameters, such as biting habits, temporomandibular disorders (TMDs), and bruxism, holds implications for holistic healthcare interventions. This systematic review aims to synthesize the available evidence to elucidate the potential relationships between domestic abuse and targeted oral health outcomes in the pediatric population. A comprehensive search strategy was conducted across eight databases, namely, PubMed, Embase, Scopus, PsycINFO, Web of Science, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Cochrane Library, and Google Scholar. Boolean operators and Medical Subject Headings (MeSH) keywords were strategically employed to optimize search precision. Clinical studies investigating the relationships between domestic abuse and TMDs, or bruxism, in children and adolescents were included. Two reviewers extracted the data independently. The methodological quality and risk of bias of the selected studies were critically appraised using the Newcastle-Ottawa scale. The systematic search identified three papers investigating the associations between domestic abuse and the targeted oral health parameters. Children in the age group of 6-19 years were assessed. The synthesized evidence revealed a consistent association between domestic abuse and masticatory outcomes. Individuals subjected to domestic abuse exhibited a greater percentage of masticatory anomalies. The methodological assessment of the included studies showed good quality. This systematic review provides a notable synthesis of evidence regarding the associations between domestic abuse and masticatory outcomes in children and adolescents. The complex nature of these relationships necessitates further research to unravel the underlying mechanisms and establish causality. The insights from this review highlight the significance of integrating abuse assessment within oral health evaluations and underscore the need for interdisciplinary collaborations to address the potential impact of abusive experiences on the oral health and well-being of the pediatric population.
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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 | 0.009 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".