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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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Maida CA, Marcus M, Xiong D, Ortega-Verdugo P, Agredano E, Huang Y, Zhou L, Lee SY, Shen J, Hays RD, Crall JJ, Liu H. Investigating Perceptions of Teachers and School Nurses on Child and Adolescent Oral Health in Los Angeles County. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19084722. [PMID: 35457591 PMCID: PMC9032022 DOI: 10.3390/ijerph19084722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/05/2022] [Accepted: 04/12/2022] [Indexed: 02/05/2023]
Abstract
This study reports the results of focus groups with school nurses and teachers from elementary, middle, and high schools to explore their perceptions of child and adolescent oral health. Participants included 14 school nurses and 15 teachers (83% female; 31% Hispanic; 21% White; 21% Asian; 14% African American; and 13% Others). Respondents were recruited from Los Angeles County schools and scheduled by school level for six one-hour focus groups using Zoom. Audio recordings were transcribed, reviewed, and saved with anonymization of speaker identities. NVivo software (QSR International, Melbourne, Australia) was used to facilitate content analysis and identify key themes. The nurses’ rate of “Oral Health Education” comments statistically exceeded that of teachers, while teachers had higher rates for “Parental Involvement” and “Mutual Perception” comments. “Need for Care” was perceived to be more prevalent in immigrants to the United States based on student behaviors and complaints. “Access to Care” was seen as primarily the nurses’ responsibilities. Strong relationships between community clinics and schools were viewed by some as integral to students achieving good oral health. The results suggest dimensions and questions important to item development for oral health surveys of children and parents to address screening, management, program assessment, and policy planning.
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Affiliation(s)
- Carl A. Maida
- Division of Oral and Systemic Health Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (C.A.M.); (M.M.); (D.X.); (E.A.); (Y.H.); (L.Z.); (J.S.); (J.J.C.)
| | - Marvin Marcus
- Division of Oral and Systemic Health Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (C.A.M.); (M.M.); (D.X.); (E.A.); (Y.H.); (L.Z.); (J.S.); (J.J.C.)
| | - Di Xiong
- Division of Oral and Systemic Health Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (C.A.M.); (M.M.); (D.X.); (E.A.); (Y.H.); (L.Z.); (J.S.); (J.J.C.)
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Paula Ortega-Verdugo
- Division of Preventative and Restorative Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (P.O.-V.); (S.Y.L.)
| | - Elizabeth Agredano
- Division of Oral and Systemic Health Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (C.A.M.); (M.M.); (D.X.); (E.A.); (Y.H.); (L.Z.); (J.S.); (J.J.C.)
| | - Yilan Huang
- Division of Oral and Systemic Health Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (C.A.M.); (M.M.); (D.X.); (E.A.); (Y.H.); (L.Z.); (J.S.); (J.J.C.)
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Linyu Zhou
- Division of Oral and Systemic Health Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (C.A.M.); (M.M.); (D.X.); (E.A.); (Y.H.); (L.Z.); (J.S.); (J.J.C.)
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Steve Y. Lee
- Division of Preventative and Restorative Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (P.O.-V.); (S.Y.L.)
| | - Jie Shen
- Division of Oral and Systemic Health Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (C.A.M.); (M.M.); (D.X.); (E.A.); (Y.H.); (L.Z.); (J.S.); (J.J.C.)
| | - Ron D. Hays
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA;
- Department of Health Policy and Management, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, USA
- RAND Corporation, Santa Monica, CA 90407, USA
| | - James J. Crall
- Division of Oral and Systemic Health Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (C.A.M.); (M.M.); (D.X.); (E.A.); (Y.H.); (L.Z.); (J.S.); (J.J.C.)
| | - Honghu Liu
- Division of Oral and Systemic Health Sciences, School of Dentistry, University of California Los Angeles, Los Angeles, CA 90095, USA; (C.A.M.); (M.M.); (D.X.); (E.A.); (Y.H.); (L.Z.); (J.S.); (J.J.C.)
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, USA
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA;
- Correspondence:
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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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Marcus M, Xiong D, Wang Y, Maida CA, Hays RD, Coulter ID, Spolsky VW, Lee SY, Shen J, Crall JJ, Liu H. Development of toolkits for detecting dental caries and caries experience among children using self-report and parent report. Community Dent Oral Epidemiol 2019; 47:520-527. [PMID: 31576591 DOI: 10.1111/cdoe.12494] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Revised: 07/31/2019] [Accepted: 08/08/2019] [Indexed: 12/11/2022]
Abstract
OBJECTIVES To develop child- and parent-reported toolkits for active caries and caries experience in children and adolescents, ages 8-17. METHODS A sample of 398 child/parent dyads recruited from 12 dental practices in Los Angeles County completed a computer-assisted survey that assessed oral health perceptions. In addition, children received a dental examination that identified the presence or absence of active caries and caries experience. A Multiple Adaptive Regression Splines model was used to identify a subset of survey items associated with active caries and caries experience. The splines and coefficients were refined by generalized cross-validation. Sensitivity and specificity for both dependent variables were evaluated. RESULTS Eleven child self-reported items were identified that had sensitivity of 0.82 and specificity of 0.45 relative to active caries. Twelve parent-reported items had a sensitivity of 0.86 and specificity of 0.50. Seven child self-reported items had a sensitivity of 0.86 and specificity of 0.34, and 11 parent-reported items had a sensitivity of 0.86 and specificity of 0.47 for caries experience. CONCLUSIONS The survey items identified here are useful in distinguishing children with and without active caries and with and without caries experience. This research presents a path towards using children's and their parents' reports about oral health to screen for clinically determined caries and caries exposure. The items identified in this study can be useful when clinical information is unavailable.
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Affiliation(s)
- Marvin Marcus
- Division of Public Health and Community Dentistry, School of Dentistry, University of California Los Angeles, Los Angeles, California
| | - Di Xiong
- Division of Public Health and Community Dentistry, School of Dentistry, University of California Los Angeles, Los Angeles, California.,Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California
| | - Yan Wang
- Division of Public Health and Community Dentistry, School of Dentistry, University of California Los Angeles, Los Angeles, California.,Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California
| | - Carl A Maida
- Division of Public Health and Community Dentistry, School of Dentistry, University of California Los Angeles, Los Angeles, California.,Division of Oral Biology and Medicine, School of Dentistry, University of California Los Angeles, Los Angeles, California
| | - Ron D Hays
- Division of General Internal Medicine and Health Services Research, Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Health Policy and Management, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California.,RAND Corporation, Santa Monica, California
| | - Ian D Coulter
- Division of Public Health and Community Dentistry, School of Dentistry, University of California Los Angeles, Los Angeles, California.,RAND Corporation, Santa Monica, California
| | - Vladimir W Spolsky
- Division of Public Health and Community Dentistry, School of Dentistry, University of California Los Angeles, Los Angeles, California
| | - Steve Y Lee
- Section of Restorative Dentistry, School of Dentistry, University of California Los Angeles, Los Angeles, California
| | - Jie Shen
- Division of Public Health and Community Dentistry, School of Dentistry, University of California Los Angeles, Los Angeles, California
| | - James J Crall
- Division of Public Health and Community Dentistry, School of Dentistry, University of California Los Angeles, Los Angeles, California
| | - Honghu Liu
- Division of Public Health and Community Dentistry, School of Dentistry, University of California Los Angeles, Los Angeles, California.,Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California.,Division of General Internal Medicine and Health Services Research, Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
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Wang Y, Hays R, Marcus M, Maida C, Shen J, Xiong D, Lee S, Spolsky V, Coulter I, Crall J, Liu H. Development of a parents' short form survey of their children's oral health. Int J Paediatr Dent 2019; 29:332-344. [PMID: 30481390 PMCID: PMC8191488 DOI: 10.1111/ipd.12453] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Revised: 08/10/2018] [Accepted: 11/19/2018] [Indexed: 11/28/2022]
Abstract
BACKGROUND Parents play an important role in their children's oral health behaviors, provide oral health access, initiate prevention, and coping strategies for health care. AIM This paper develops a short form (SF) to assist parents to evaluate their children's oral health status using Patient-Reported Outcome Measurement Information System (PROMIS) framework that conceptualized health as physical, mental, and social components. DESIGN Surveys of parents were conducted at dental clinics in Los Angeles County, together with an on-site clinical examination by dentists to determine clinical outcomes, Children's Oral Health Status Index (COHSI), and referral recommendations (RRs). Graded response models in item response theory were used to create the SF. A toolkit including SF, demographic information, and algorithms was developed to predict the COHSI and RRs. RESULTS The final SF questionnaire consists of eight items. The square root mean squared error for the prediction of COHSI is 7.6. The sensitivity and specificity of using SF to predict immediate treatment needs (binary RRs) are 85% and 31%. CONCLUSIONS The parent SF is an additional component of the oral health evaluation toolkit that can be used for oral health screening, surveillance program, policy planning, and research of school-aged children and adolescents from guardian perspectives.
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Affiliation(s)
- Yan Wang
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California
| | - Ron Hays
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Marvin Marcus
- Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, Los Angeles, California
| | - Carl Maida
- Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, Los Angeles, California
| | - Jie Shen
- Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, Los Angeles, California
| | - Di Xiong
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California
| | - Steve Lee
- Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, Los Angeles, California
| | - Vladimir Spolsky
- Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, Los Angeles, California
| | - Ian Coulter
- Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, Los Angeles, California
| | - James Crall
- Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, Los Angeles, California
| | - Honghu Liu
- Public Health & Community Dentistry, School of Dentistry, University of California, Los Angeles, Los Angeles, California
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