A systematic review and meta-analysis of failure to take history as a barrier of reporting child abuse by dentists in private and state clinics
Bibliographic record
Abstract
BACKGROUND: Since the symptoms of child abuse and neglect often manifest in the orofacial region, the dental team has a key role in identifying children subjected to abuse. This study was aimed to explore the prevalence of failure to take history as a barrier to reporting child abuse by dentist around the world. MATERIALS AND METHODS: In this systematic review and meta-analysis, PubMed, Embase, Scopus, Google Scholar, ProQuest, Cochrane, and ISI databases were searched for the cross-sectional articles in English languages on barriers to reporting child abuse and lack of knowledge about referral procedures by dentists since 1985 using Medical Subject Headings (MeSH). The full-texts of all included articles were obtained and assessed for quality according to Newcastle-Ottawa Scale adapted for cross-sectional studies. The qualified articles were then studied thoroughly and results were extracted. Data were analyzed by Comprehensive Meta-Analysis software using meta-analysis and random effects model. Heterogeneity was determined by Q-test and I-square index. RESULTS: A total of 17 articles were included in the meta-analysis. The prevalence of lack of knowledge about referral procedures as a barrier was determined according to the meta-analysis of the number of relevant articles and was (55%, confidence interval: 0.48, 0.62). CONCLUSION: The analysis of various studies revealed lack of information about referral procedures as an important barrier to report child abuse by dentists.
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".