PeerJ · 2024 · 13 citations · 36 references
DentistryOral Health SciencesHealth AssessmentOral EpidemiologyOral HealthHealth-related Quality Of LifeHealth-related Quality Of Life MeasurementOral Health IndicatorsOral Health Outcomes ResearchQuality Of LifeQuality Of Life AssessmentCross-sectional Correlation StudyCross-sectional EpidemiologyFunctional Oral Health StatusOral Health Impact ProfileOral Health Status EvaluationOral Health-related Functional LimitationPearson Correlation Coefficient
Background: The relationship between oral and overall health is of interest to health care professionals and patients alike. This study investigated the correlation between oral health-related quality of life (OHRQoL) and health-related quality of life (HRQoL) in a general adult population. Methods: This cross-sectional study used a convenience sample of adult participants (N = 607) attending the 2022 Minnesota County and State fairs in USA, the 5-item Oral Health Impact Profile (OHIP-5) assessed OHRQoL, and the 10-item PROMIS v.1.2 Global Health Instrument assessed HRQoL. Spearman and Pearson correlations were used to summarize the bivariable relationship between OHRQoL and HRQoL (both physical and mental health dimensions). A structural equation model determined OHRQoL-HRQoL correlations (r). Correlations' magnitude was interpreted according to Cohen's guidelines (r = 0.10, 0.30, and 0.50 to demarcate "small," "medium," and "large" effects, respectively). Results: OHRQoL and HRQoL correlated with r = 0.52 (95% confidence interval, CI: [0.50-0.55]), indicating that the two constructs shared 27% of their information. According to Cohen, this was a "large" effect. OHRQoL, and the physical and mental HRQoL dimensions correlated with r = 0.55 (95% CI: [0.50-0.59]) and r = 0.43 (95% CI: [0.40-0.46]), respectively, indicating a "large" and a "medium" effect. OHRQoL and HRQoL were substantially correlated in an adult population. Conclusion: Using OHIP-5 to assess their dental patients' oral health impact allows dental professionals to gain insights into patients' overall health-related wellbeing.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Paul A. Harris, Robert Taylor, Robert J. Thielke et al. · Journal of Biomedical Informatics · 2008 · 51.7K citations · Full text
Jacob Cohen · Psychological Bulletin · 1992 · 42.2K citations