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Record W4324129214 · doi:10.1111/jphd.12564

The association between adverse childhood experiences and oral health: A systematic review

2023· review· en· W4324129214 on OpenAlexaboutno aff
Lina Bahanan, Solafa Ayoub

Bibliographic record

VenueJournal of Public Health Dentistry · 2023
Typereview
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCINAHLMEDLINEOral healthCochrane LibraryCross-sectional studyFamily medicineMeta-analysisEnvironmental healthGerontologyPsychological interventionPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: It is well established that adverse childhood experiences (ACEs) negatively affect health and are associated with health-risk behaviors. This study aimed to provide a systematic review of the studies that examine the relationship between ACE exposure and oral health among adults aged 18 years and older. METHODS: The following electronic databases were searched in January 2022: MEDLINE, Cochrane, Web of Science, CINAHL via EBSCOhost, ProQuest, ScienceDirect, and Google Scholar. Data were extracted independently by two reviewers. The quality of the studies was assessed using the Newcastle-Ottawa Scale. RESULTS: Among the 292 articles identified, four met the eligibility criteria. All included studies were cross-sectional and of satisfactory quality. The dental outcomes included: last dental visit, last dental cleaning, number of filled teeth, number of extracted teeth, and number of remaining teeth. The studies showed that exposure to ACE was negatively associated with oral health. The relationship between ACE score and oral health outcome measures was found to be directly proportional. CONCLUSION: There is an association between ACE and poor oral health. Moreover, the association was proven to have a dose-response relationship. Given that the studies in the literature were cross-sectional, causality cannot be determined with certainty, therefore interpretation of the results should be cautious. Longitudinal follow-up studies are needed to understand how ACEs contribute to oral diseases later in life.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.571
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.189
GPT teacher head0.462
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations25
Published2023
Admission routes1
Has abstractyes

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