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Le Luyer M, Boll ME, Lemmers SAM, Stoll SJ, Hoffnagle AG, Smith ADAC, Dunn EC. How well do parents identify their child's baby teeth? Engagement and accuracy of parent-reported information on a tooth checklist survey. Community Dent Oral Epidemiol 2024. [PMID: 38680025 DOI: 10.1111/cdoe.12971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 04/05/2024] [Accepted: 04/18/2024] [Indexed: 05/01/2024]
Abstract
OBJECTIVES Naturally exfoliated primary teeth are being increasingly collected in child development studies. Most of these odontological collections and tooth biobanks use parent-reported information from questionnaires or tooth checklists to collect data on offspring teeth. To the best of the authors' knowledge, no studies have assessed parental engagement in tooth checklists, nor parental accuracy in identifying their child's baby tooth. This study aimed to evaluate these dimensions by analysing data from the about this tooth checklist returned with donated primary teeth in a natural experimental study called STRONG (the Stories Teeth Record of Newborn Growth). METHODS Parental self-reported information were analysed on checklists returned with 825 primary teeth belonging to 199 children. The percentage of blank answers was calculated for each question. The accuracy of parents-reported tooth identification was evaluated by comparing parental ratings to researchers' ratings. Reliability of researchers' tooth identification was first evaluated by calculating intra-observer and inter-observer agreements, as well as Cohen's Kappa values. The percentage of accuracy of parents' tooth identification (relative to researcher's) was then calculated, and logistic regressions were used to evaluate if time elapsed between when exfoliation occurred and the checklist was completed associated with parental accuracy in tooth identification. RESULTS Parents returned 98.4% of the checklists and completed 74.9% to 97.7% of the questions. Excellent reliability was demonstrated for researchers' intra- and inter-rater tooth identification (agreement percentages >90%; Cohen's Kappa values >.83). Moderate accuracy of parents-reported tooth identifications was found, with parents correctly identifying 49.5% of the donated tooth. Better parental accuracies were highlighted for partial identifications (87.1% of correct jaw, 75.6% of correct tooth type, and 65.8% of correct lateralization). Logistic regressions showed the odds of correct parental identifications decreased on average by 1.8% every 30 days of distance between tooth exfoliation and checklist completion. CONCLUSIONS While parental engagement is high, parents-reported tooth identifications have moderate accuracy, which decreases over time. High accuracy is however found for partial identifications. Parent-reported information on the accompanying questionnaire of naturally exfoliated primary teeth collection or tooth biobanks, even when filled in a long time after exfoliation took place, should be encouraged. However, expert identifications of teeth should remain best practice.
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Affiliation(s)
- Mona Le Luyer
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| | - Molly E Boll
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Simone A M Lemmers
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| | - Samantha J Stoll
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Alison G Hoffnagle
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Andrew D A C Smith
- Mathematics and Statistics Research Group, University of the West of England, Bristol, UK
| | - Erin C Dunn
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
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Xiong D, Marcus M, Maida CA, Lyu Y, Hays RD, Wang Y, Shen J, Spolsky VW, Lee SY, Crall JJ, Liu H. Development of short forms for screening children's dental caries and urgent treatment needs using item response theory and machine learning methods. PLoS One 2024; 19:e0299947. [PMID: 38517846 PMCID: PMC10959356 DOI: 10.1371/journal.pone.0299947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 02/20/2024] [Indexed: 03/24/2024] Open
Abstract
OBJECTIVES Surveys can assist in screening oral diseases in populations to enhance the early detection of disease and intervention strategies for children in need. This paper aims to develop short forms of child-report and proxy-report survey screening instruments for active dental caries and urgent treatment needs in school-age children. METHODS This cross-sectional study recruited 497 distinct dyads of children aged 8-17 and their parents between 2015 to 2019 from 14 dental clinics and private practices in Los Angeles County. We evaluated responses to 88 child-reported and 64 proxy-reported oral health questions to select and calibrate short forms using Item Response Theory. Seven classical Machine Learning algorithms were employed to predict children's active caries and urgent treatment needs using the short forms together with family demographic variables. The candidate algorithms include CatBoost, Logistic Regression, K-Nearest Neighbors (KNN), Naïve Bayes, Neural Network, Random Forest, and Support Vector Machine. Predictive performance was assessed using repeated 5-fold nested cross-validations. RESULTS We developed and calibrated four ten-item short forms. Naïve Bayes outperformed other algorithms with the highest median of cross-validated area under the ROC curve. The means of best testing sensitivities and specificities using both child-reported and proxy-reported responses were 0.84 and 0.30 for active caries, and 0.81 and 0.31 for urgent treatment needs respectively. Models incorporating both response types showed a slightly higher predictive accuracy than those relying on either child-reported or proxy-reported responses. CONCLUSIONS The combination of Item Response Theory and Machine Learning algorithms yielded potentially useful screening instruments for both active caries and urgent treatment needs of children. The survey screening approach is relatively cost-effective and convenient when dealing with oral health assessment in large populations. Future studies are needed to further leverage the customize and refine the instruments based on the estimated item characteristics for specific subgroups of the populations to enhance predictive accuracy.
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Affiliation(s)
- Di Xiong
- Section of Public and Population Health, Division of Oral and Systemic Health Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, California, United States of America
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Marvin Marcus
- Section of Public and Population Health, Division of Oral and Systemic Health Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Carl A. Maida
- Section of Public and Population Health, Division of Oral and Systemic Health Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Yuetong Lyu
- Section of Public and Population Health, Division of Oral and Systemic Health Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, California, United States of America
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Ron D. Hays
- Division of General Internal Medicine and Health Services Research, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
- Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, United States of America
- RAND Corporation, Santa Monica, California, United States of America
| | - Yan Wang
- Section of Public and Population Health, Division of Oral and Systemic Health Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Jie Shen
- Section of Public and Population Health, Division of Oral and Systemic Health Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Vladimir W. Spolsky
- Section of Public and Population Health, Division of Oral and Systemic Health Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Steve Y. Lee
- Sectopm of Interdisciplinary Dentistry, Division of Diagnostic and Surgical Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, California, United States of America
| | - James J. Crall
- Section of Public and Population Health, Division of Oral and Systemic Health Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Honghu Liu
- Section of Public and Population Health, Division of Oral and Systemic Health Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, California, United States of America
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, United States of America
- Division of General Internal Medicine and Health Services Research, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
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Ramos-Gomez F, Marcus M, Maida CA, Wang Y, Kinsler JJ, Xiong D, Lee SY, Hays RD, Shen J, Crall JJ, Liu H. Using a Machine Learning Algorithm to Predict the Likelihood of Presence of Dental Caries among Children Aged 2 to 7. Dent J (Basel) 2021; 9:141. [PMID: 34940038 PMCID: PMC8700143 DOI: 10.3390/dj9120141] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 11/17/2021] [Accepted: 11/21/2021] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Dental caries is the most common chronic childhood infectious disease and is a serious public health problem affecting both developing and industrialized countries, yet it is preventable in most cases. This study evaluated the potential of screening for dental caries among children using a machine learning algorithm applied to parent perceptions of their child's oral health assessed by survey. METHODS The sample consisted of 182 parents/caregivers and their children 2-7 years of age living in Los Angeles County. Random forest (a machine learning algorithm) was used to identify survey items that were predictors of active caries and caries experience. We applied a three-fold cross-validation method. A threshold was determined by maximizing the sum of sensitivity and specificity conditional on the sensitivity of at least 70%. The importance of survey items to classifying active caries and caries experience was measured using mean decreased Gini (MDG) and mean decreased accuracy (MDA) coefficients. RESULTS Survey items that were strong predictors of active caries included parent's age (MDG = 0.84; MDA = 1.97), unmet needs (MDG = 0.71; MDA = 2.06) and the child being African American (MDG = 0.38; MDA = 1.92). Survey items that were strong predictors of caries experience included parent's age (MDG = 2.97; MDA = 4.74), child had an oral health problem in the past 12 months (MDG = 2.20; MDA = 4.04) and child had a tooth that hurt (MDG = 1.65; MDA = 3.84). CONCLUSION Our findings demonstrate the potential of screening for active caries and caries experience among children using surveys answered by their parents.
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Affiliation(s)
- Francisco Ramos-Gomez
- Section of Pediatric Dentistry, Division of Growth & Development, School of Dentistry, University of California, Los Angeles, CA 90095, USA;
| | - Marvin Marcus
- Division of Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, CA 90095, USA; (M.M.); (C.A.M.); (D.X.); (J.S.); (J.J.C.); (H.L.)
| | - Carl A. Maida
- Division of Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, CA 90095, USA; (M.M.); (C.A.M.); (D.X.); (J.S.); (J.J.C.); (H.L.)
- Division of Oral Biology and Medicine, School of Dentistry, University of California, Los Angeles, CA 90095, USA
| | - Yan Wang
- Division of Infectious Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA;
| | - Janni J. Kinsler
- Section of Pediatric Dentistry, Division of Growth & Development, School of Dentistry, University of California, Los Angeles, CA 90095, USA;
| | - Di Xiong
- Division of Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, CA 90095, USA; (M.M.); (C.A.M.); (D.X.); (J.S.); (J.J.C.); (H.L.)
- Department of Biostatistics, School of Public Health, University of California, Los Angeles, CA 90095, USA
| | - Steve Y. Lee
- Division of Constitutive and Regenerative Sciences, School of Dentistry, University of California, Los Angeles, CA 90095, USA;
| | - Ron D. Hays
- Department of Health Policy and Management, School of Public Health, University of California, Los Angeles, CA 90095, USA;
- Division of General Internal Medicine and Health Services Research, Department of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Jie Shen
- Division of Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, CA 90095, USA; (M.M.); (C.A.M.); (D.X.); (J.S.); (J.J.C.); (H.L.)
| | - James J. Crall
- Division of Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, CA 90095, USA; (M.M.); (C.A.M.); (D.X.); (J.S.); (J.J.C.); (H.L.)
| | - Honghu Liu
- Division of Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, CA 90095, USA; (M.M.); (C.A.M.); (D.X.); (J.S.); (J.J.C.); (H.L.)
- Division of Oral Biology and Medicine, School of Dentistry, University of California, Los Angeles, CA 90095, USA
- Division of General Internal Medicine and Health Services Research, Department of Medicine, University of California, Los Angeles, CA 90095, USA
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Costa FDS, Costa CDS, Chisini LA, Wendt A, Santos IDSD, Matijasevich A, Correa MB, Demarco FF. Socio-economic inequalities in dental pain in children: A birth cohort study. Community Dent Oral Epidemiol 2021; 50:360-366. [PMID: 34137065 DOI: 10.1111/cdoe.12660] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Revised: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 11/29/2022]
Abstract
OBJECTIVE To describe socio-economic inequalities in dental pain and dental caries in 5 and 12-year-old children enrolled in a birth cohort. METHODS This prospective study was carried out with children enrolled in a birth cohort in Pelotas, Brazil. The main outcome was history of dental pain in the last six months, collected at 5 and 12 years of age. Dental caries was evaluated as a secondary outcome. Inequalities dimensions were investigated using maternal education and family income. The inequalities indicators used were the slope index of inequality (SII) and the concentration index (CIX). RESULTS Some 1,114 and 990 children were included in the analyses at the 5- and 12-year follow-ups, respectively. The prevalence of dental pain was 16.5% (95% CI 14.4-18.8) at 5 years and 31.6% (95% CI 28.7-34.6) at 12 years. Regarding SII, the difference in the prevalence of dental pain was 14 and 11 percentage points at 5 and 12 years, respectively, when comparing the less to the more maternal schooled strata. Relative inequalities (CIX) were found for dental pain only at age 12, considering family income (-5.8 CI95% -11.0; -0.6). Absolute socio-economic inequalities were also observed for dental caries in both ages. CONCLUSION Dental pain in the last six months and dental caries was unequally distributed. Economically disadvantaged groups had the highest prevalence of dental pain and dental caries in both dentitions. Actions to tackle socio-economic inequalities must be designed throughout life.
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Affiliation(s)
| | | | - Luiz Alexandre Chisini
- Center of Biological Sciences and Health, Taquari Valley University, Lajeado, RS, Brazil
| | - Andrea Wendt
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Iná da Silva Dos Santos
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil.,Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, RS, Brazil
| | - Alicia Matijasevich
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil.,Department of Preventive Medicine, Faculty of Medicine FMUSP, University of São Paulo, São Paulo, SP, Brazil
| | - Marcos Britto Correa
- Postgraduate Program in Dentistry, Federal University of Pelotas, Pelotas, RS, Brazil
| | - Flávio Fernando Demarco
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil.,Postgraduate Program in Dentistry, Federal University of Pelotas, Pelotas, RS, Brazil
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