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Record W4415414434 · doi:10.14740/ijcp1017

Determinants of Oral Health-Related Quality of Life in Children With Neurological Disorders: An Interdisciplinary Study

2025· article· en· W4415414434 on OpenAlexvenueno aff
Giovani Ceron Hartmann, Claudia Hartmann, Gil Guilherme Gasparello, Mohamad Jamal Bark, Sérgio Aparecido Ignácio, Jacqueline de Almeida Antunes Rozyscki, Matheus Melo Pithon, Robert Willer Farinazzo Vitral, Orlando Motohiro Tanaka

Bibliographic record

VenueInternational Journal of Clinical Pediatrics · 2025
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsCerebral palsyQuality of life (healthcare)Autism spectrum disorderSocioeconomic statusIntervention (counseling)Oral healthPublic healthActivities of daily living

Abstract

fetched live from OpenAlex

Background: Oral health-related quality of life (OHRQoL) is often compromised in children with neurological disorders, yet limited evidence exists on the contributing clinical and socioeconomic factors. Methods: A cross-sectional study was conducted among 132 children aged 6 - 14 years attending public neurology clinics. Parents or caregivers completed the validated Parental-Caregiver Perceptions Questionnaire (P-CPQ) and provided sociodemographic and health-related data. Results: Most respondents were mothers (76.5%). High rates of bullying (78.6%) and dental caries (71%) were reported. Common diagnoses included epilepsy (49.2%), autism spectrum disorder (ASD) (30.3%), and attention deficit hyperactivity disorder (ADHD) (26.5%). Poor OHRQoL was significantly associated with caregiver type (P = 0.046), low family income (P = 0.014), and living with relatives (P = 0.008). Functional limitations were the strongest OHRQoL domain (r = 0.780; P < 0.001). Children with cerebral palsy and oppositional defiant disorder (ODD) exhibited the worst OHRQoL (P = 0.008). Although only 6.8% used orthodontic appliances, their presence negatively impacted OHRQoL. Conclusions: Pediatric patients from lower-income families or non-parental households are at increased risk for impaired OHRQoL, especially those with cerebral palsy or ODD. Functional limitations, bullying, and untreated dental caries are key targets for clinical intervention in this vulnerable population.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.074
GPT teacher head0.476
Teacher spread0.402 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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