Psychometric evaluation of Dental Caries Utility Index (DCUI): An oral health specific Preference-Based Quality-of-Life Measure for Economic Evaluations

Psychometric evaluation of Dental Caries Utility Index (DCUI): An oral health specific Preference-Based Quality-of-Life Measure for Economic Evaluations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Psychometric evaluation of Dental Caries Utility Index (DCUI): An oral health specific Preference-Based Quality-of-Life Measure for Economic Evaluations Ruvini M. Hettiarachchi, Gouree S. Francis, Mochamad Iqbal Nurmansyah, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9399529/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose The availability of valid and reliable condition-specific preference-based quality-of-life measure (PBM) facilitates their use in economic evaluations with more sensitive and condition-relevant utility estimates. The Dental Caries Utility Index (DCUI) is a new oral health-specific PBM designed for economic evaluations of adolescent (12–17 years) oral health interventions. This study aimed to validate the DCUI by assessing its psychometric properties. Methods A validation study was conducted among adolescents attending Metro South oral health clinics, Queensland, Australia. Participants completed an online survey including sociodemographic data, two oral health–specific measures (DCUI and the Child Perceptions Questionnaire (CPQ11-14)), one generic PBM (EuroQoL-5D-Youth (EQ-5D-Y-5L)), and two global oral health questions. Dental caries data (Decayed, Missing and Filled Teeth) from treatment records were linked to survey responses. Psychometric evaluation focused on construct validity, responsiveness, and reliability. Results A total of 183 adolescents participated (mean age 14.31; (SD) 1.52 years; 54.6% female). Mean utility scores for the study sample were 0.931 (DCUI), 0.957 (EQ-5D-Y-5L), and 8.09 (CPQ11-14). DCUI scores showed a moderate negative correlation with CPQ11-14 (–0.464, p < 0.001) and a weak positive correlation with EQ-5D-Y-5L (0.302, p < 0.001). The DCUI demonstrated a moderate effect size in discriminating between caries-free (DMFT = 0) and caries affected (DMFT = 1–5) groups, outperforming other instruments. It also effectively discriminated participants across perceived oral health status. Conclusion The DCUI showed stronger associations with oral health specific constructs, greater discriminative validity compared to both generic and specific measures, and moderate reliability, supporting its suitability for adolescents’ oral health economic evaluations. Dental Caries Utility Index dental caries children adolescents psychometric Preference-based quality-of-life measures Figures Figure 1 Figure 2 Introduction Despite numerous preventive interventions, dental caries among children remains to be a significant global public health concern. The Global burden of disease study reported that untreated dental caries in permanent teeth is the most prevalent oral disease among children worldwide, with an incidence of 32,100 (24,500 − 41,000) and prevalence of 20,600 (14,500 − 27,700) cases per 100,000 population among those aged 5–19 years [ 1 , 2 ]. Among adolescents aged 15–19 years, females and males show similar incidence rates of caries in permanent teeth, having 46,126 (36,363–56,627) and 46,311 (36,297–56,805) cases per 100,000 population, respectively. The most recent Australian national data reported by the Australian Institute of Health and Welfare (AIHW) revealed that 42% of children had caries in their primary teeth and 24% in their permanent teeth [ 3 ]. The report also highlights that the prevalence of caries in permanent teeth increased to 38% among children aged 12–14 years. Moreover, Indigenous children were disproportionately affected, with 36.0% experiencing tooth decay, compared to non-Indigenous children (22.7%). Dental caries is a chronic and progressive disease that can cause a range of symptoms, including sensitive teeth, pain, difficulty in chewing, sleep disturbance and have negative impact on quality of life. If disease progresses, the management of dental caries becomes increasingly resource-intensive and costly. Interventions for caries prevention is the key to reduce this burden. However, strong evidence is required to prioritize allocation of limited health resources for dental caries prevention and to identify the most cost-effective interventions. Economic evaluations provide an important framework to prioritize health interventions in resource-scarce settings by providing evidence on health interventions that deliver the best value for money [ 4 ]. Preference-based quality-of-life measures (PBMs) are used to calculate quality-adjusted life years (QALYs) used for economic evaluations by combining both the length and quality of life. Using PBMs, each health state a person experiences is assigned a utility value based on their health-related quality of life (HRQoL) [ 4 ]. The time spent in each health state is then multiplied by its corresponding utility value, adjusting survival for the quality of health during that period. These adjusted values are summed across all time periods to estimate total quality-adjusted-life-years (QALYs), representing the equivalent years of perfect health gained [ 4 ]. Of note, most of the oral health quality of life (QoL) instruments are non-PBM, hence cannot be used in economic evaluations [ 5 ]. Therefore, previous studies have used generic PBM or mapping functions to calculate utility values in oral health economic evaluations. Disease-specific PBMs are tailored to capture the unique symptoms, impacts, and QoL changes relevant to that disease. This specificity makes them more sensitive and responsive to treatment effects, enabling more precise measurement of patient benefit [ 6 ]. In contrast, generic PBMs, while being useful for comparing across conditions, may overlook important disease-related nuances, leading to less accurate assessments in clinical trials or economic evaluations focused on a single condition [ 6 ]. Therefore, disease-specific PBMs provide deeper insights into patient experiences and more valid data for decision-making in targeted interventions. The use of oral health specific PBMs in economic evaluations is a growing field cross linking oral health research and economic evaluations. Accurate assessment of child oral health is important for guiding economic evaluations and informing healthcare decision-making [ 7 ]. The availability of valid and reliable oral health–specific PBMs facilitates their use in economic evaluations of oral health interventions, which can ultimately support more effective and efficient planning of oral health care services. The Dental Caries Utility Index (DCUI) is a new oral health-specific PBM for adolescents and the first PBM in Australia developed for the children aged 12–17 years [ 7 ]. It was created through qualitative interviews, expert consensus, and valuation studies to define key dimensions of caries-related quality of life and derive utility weights through discrete choice experiments (DCE) for use in economic evaluations of dental interventions [ 8 ]. It includes five dimensions; pain/discomfort, difficulty eating or drinking, worry, ability to join in activities, and appearance. There are only two other validated oral health paediatric PBMs; the Early Childhood Oral Health Impact Scale-4D (ECOHIS-4D) [ 9 ], and the Caries Impacts and Experiences Questionnaire for Children (CARIESQC-U) [ 10 ]. The ECOHIS-4D, developed through factor analysis and Rasch modelling, demonstrates strong face, content, and construct validity, effectively discriminates between levels of caries experience, and outperforms generic PBMs in capturing oral health impacts [ 9 ]. On the other hand, the CARIES-QC-U, developed through qualitative interviews, Rasch analysis, and think-aloud testing with children, demonstrates strong face and content validity, builds on the psychometrically robust CARIES-QC, and shows solid conceptual grounding with sensitivity to caries-specific impacts [ 10 , 11 ]. However, these tools are targeted for children of less than 7 years [ 9 ] of age and with a wider age group (5–16 years) [ 10 ] respectively. Hence, there remains a gap due to the lack of a validated oral health–specific PBM for adolescents which can be used for economic evaluations [ 12 ]. Prior to large scale application, the psychometric properties (validity and reliability) of an instrument must be established. Validity refers to what extent an instrument measures what it is supposed to measure [ 13 ] whereas reliability determines that a measurement yields reproducible and consistent results [ 14 ]. Validity of an instrument can be evaluated through several dimensions, including face, content, construct and criterion validity. During the development of DCUI, face and content validity were confirmed through qualitative interviews with adolescents, the target population, and expert opinion from clinical and dental public health specialists [ 7 ]. However, despite the availability of two validated paediatric oral health–specific PBMs, there remains a critical gap, a lack of a validated oral health–specific PBM designed for adolescents. Addressing this gap, the present study aimed to examine the construct and criterion validity of the DCUI among adolescents aged 12–17 years attending Metro South oral health clinics, Queensland, ensuring its suitability for use in economic evaluations of dental caries interventions. Methods A descriptive cross-sectional study was conducted among children 12–17 years of age, attending 17 dental clinics in Metro South Hospital and Health Service (MSHHS) area, Queensland, Australia. A convenient sampling method was adopted to recruit participants. Potential participants attending the dental clinics were invited to participate by a trained research assistant who explained about the study and directed them to the online survey with a survey link along with the information pack. Participants who preferred paper format were given the opportunity to complete the paper-based survey. Only participants proficient in English were included, as the survey was administered in English. Each participant was given a unique identification number, which served as their identifier on all data collection forms and was used to link their clinic records. The survey was administered through the Qualtrics platform and commenced with basic sociodemographic questions, including age, sex, and the postcode of the participant’s usual residence. Then the participants were asked to complete two oral health specific QoL instruments; the DCUI and the 8-item short form Child perception questionnaire (CPQ 11−14 ), and the generic QoL instrument EuroQoL-5D-Youth (EQ-5D-Y-5L) [ 15 , 16 ]. The participants’ dental caries status and treatment data were retrieved from the clinical records. DCUI The DCUI health state classification system consists of five domains and one item in each domain: Pain or discomfort, Difficulty in eating food or drinking, Worried, Ability to participate in activities and Appearance. Each item has four response levels [ 8 ]. An Australian-specific utility algorithm for the DCUI is also available to facilitate calculation of utility values corresponding to each health state in DCUI [ 17 ]. 8-item short form Child perception questionnaire (CPQ 11−14 ) 8-item short form CPQ 11−14 is a non-PBM, widely used as an oral health related QoL measure to evaluate oral health related QoL among children. It has been developed from CPQ 11−14 37 item version to reduce the participants burden and shown to have excellent validity and reliability [ 15 ]. The questionnaire consisted of 8 items; Pain in teeth, lips, mouth or jaws, Food caught in or between your teeth, Difficult to bite or chew firm food, Taken longer than others to eat a meal, Been upset, Felt irritable or frustrated, Missed school because of pain, appointment or surgery, and Not wanted to talk to other children across four domains (Oral Symptoms, Functional Limitations, Emotional well-being and Social well-being) [ 18 ]. The questionnaire asks participants to report the frequency of each item over the past three months, using a five-point scale: ‘Never’ = 0, ‘Once or twice’ = 1, ‘Sometimes’ = 2, ‘Often’ = 3, and ‘Very often’ = 4. The total score ranges from 0 to 32, with higher scores indicating a lower oral health–related quality of life [ 18 ]. EuroQoL-5D-Youth-5L (EQ-5D-Y-5L) The EQ-5D-Y-5L is a generic self-report PMB designed for children aged 8–15 years [ 19 ]. It consists of two components: the EQ-5D-Y-5L descriptive system and the EQ visual analogue scale (VAS) [ 20 ]. The descriptive system includes five dimensions (mobility (walking about); looking after myself, doing usual activities, having pain or discomfort and feeling worried, sad or unhappy) each with five levels of severity. These dimensions mirror those of the adult EQ-5D-5L but are expressed in child-friendly language. In addition to these instruments, the participants were asked two global questions to rate the child's oral health: ‘How would you consider the condition of your teeth and mouth today’ and ‘How much do your teeth or mouth bother you in your everyday life?’. Responses were recorded on a five-point scale: for oral health, from ‘Excellent’ = 0 to ‘Poor’ = 4; and for oral well-being, from ‘Not at all’ = 0 to ‘Very much’ = 4. Once the survey was completed, the participants clinic records were linked using the unique identification number. The main clinical data obtained was the decayed, missing and filling tooth (DMFT) score at the index visit which was considered as the survey completion date. Ethics approval was obtained from the Children's Health Queensland, human research ethics review committee (Ethics no HREC/2024/QCHQ/110333). The COSMIN reporting guidelines for studies on measurement properties of patient reported outcome measures (PROMs) [ 21 ] has been used as a guide to report the study findings (Supplementary Table 1). Statistical analysis A minimum of 200 sample size was recommended in studies assessing psychometric properties of PROMs [ 22 ]. Therefore, it was targeted to include 200–250 study participants. Incomplete surveys with missing data were excluded from the main data analysis during the data cleaning. Data was analysed using STATA Statistical Software: Release 19 [ 23 ]. Baseline characteristics were summarised using descriptive statistics including range, mean and standard deviation (or median and inter-quartile range for non-normally distributed data). The DCUI utility values were derived based on DCUI Australian utility value set [ 8 ]. There is no EQ-5D-Y-5L value set available for Australia or any other country [ 24 ]. In such circumstances, literature suggested to use respective adult value set (I.e., Australian EQ-5D-5L) [ 25 ] or respective 3L value set (i.e., Australian EQ-5D-Y-3L) [ 26 ] to derive the utility values [ 27 ]. Therefore, we used Australian adult value set (i.e., EQ-5D-5L) to derive EQ-5D-Y-5L utility values. The high DMFT scores indicate higher clinical severity, and the participants were categorised into three clinical severity groups based on the DMFT index. The cut-off values for the clinical severity groups were determined using the Significant Caries Index (SCI), which represents the mean DMFT score of the one-third of the population with the highest caries experience [ 28 ]. The validity and reliability of the instruments were assessed based on the DCUI, EQ-5D-Y-5L and CPQ 11−14 scores. Construct validity Construct validity was assessed in terms of convergent and discriminant validity. Convergent validity refers to the correlation with similar constructs whereas the discriminant validity refers to the lack of correlation with unrelated constructs [ 29 ]. The convergent and discriminant validity of the three instruments was assessed using Spearman’s correlation and a correlation coefficient of ≥ 0.50 considered as strong correlation whereas 0.30–0.49 and < 0.30 considered as moderate and weak correlations respectively. Further, a valid instrument should be able to discriminate between groups with differing clinical severity as well as between known groups that differ in quality of life. Hence, discriminant known group validity of the instruments was assessed based on the DMFT severity group, perceived oral health status, perceived overall wellbeing and clinical group (based on reason to attend) using Kruskal-Walli’s test and effect size. The effect size determines the discriminatory ability of the instruments and calculated by dividing the mean utility difference (or score difference) of two adjacent severity groups by the standard deviation of the milder severity group. To interpret the results, the effect sizes were categorized into three groups (≤ 0.2small, 0.2–0.5 medium and ≥ 0.8 large) and higher effect size indicating better discriminating ability of the instrument [ 30 ]. Responsiveness Responsiveness, an ability to detect meaningful change over time, is an important indicator of psychometric properties of PROMs. Ceiling and floor effects are considered indirect measures of responsiveness. The ceiling effect of the three instruments was assessed by the percentage of children reporting ‘no problem’ in each dimension. The floor effect was evaluated by the percentage of children reporting the ‘worst’ across all dimensions. High percentages for these two measures indicate that the instrument may be unable to detect improvements or deteriorations in quality of life. As a general guideline, a cutoff of 15% is typically used [ 10 ]. Reliability Statistics Cronbach’s alpha was computed to assess the internal consistency of the three instruments, with α ≥ 0.70 considered indicative of acceptable internal consistency [ 13 ]. Results Of the 239 responses received, 56 were excluded due to incomplete or missing data and duplicate entries leaving 183 participants for analysis. The respondents had a mean age of 14.31 years, with a slightly higher proportion of females than males (54.6% vs. 45.4%). The majority of the sample (63.38%) attend dental clinic for check-up and cleaning. The mean DCUI and EQ-5D-Y-5L utility scores and CPQ 11−14 score were 0.931, 0.957 and 8.09 respectively (Table 1 ). The distribution of DCUI and EQ-5D-Y-5L utility scores were left skewed and CPQ 11−14 score was right skewed, indicating that most participants reported higher quality of life (Fig. 1 ). Based on the DMFT data of the study sample, the SCI was calculated as DMFT = 5, therefore, the study participants were grouped into three clinical severity categories (DMFT = 0, DMFT = 1–5 and DMFT = > 5). Table 1 Socio demographic characteristics of the participants by mean DCUI utility values, EQ-5D-Y-5L utility values and CPQ 11-14 scores Variable Participants DCUI EQ-5D-Y-5L CPQ 11−14 (n) (%) Mean health state value (SD) Mean health state value (SD) Mean score (SD) Full sample 183 100 0.931 (0.11) 0.957 (0.07) 8.09 (5.2) Gender Female 100 54.64 0.923 (0.01) 0.944 (0.01) 8.83 (0.5) Male 83 45.36 0.941 (0.01) 0.972 (0.01) 7.02 (0.5) p value p = 0.71 p = 0.03 p = 0.06 Age (years) Age mean (SD) 14.31 (1.52) N/A N/A N/A Age category 12–14 years 95 51.91 0.925 (0.012) 0.957 (0.008) 7.76 (0.531) 15–17 years 88 48.09 0.938 (0.010) 0.959 (0.007) 8.44 (0.559) p value p = 0.81 p = 0.67 p = 0.28 (CPQ 11−14 , Child perception questionnaire 11–14; DCUI, Dental Caries Utility Index; EQ-5D-Y-5L, EuroQoL-5D-Youth-5L questionnaire; N/A, not applicable; SD, Standard deviation) Construct validity There was a statistically significant moderate negative correlation between DCUI and CPQ 11−14 score (–0.4642, p = 0.000), whereas a weak correlation (0.3017, p = 0.000) was observed between DCUI and EQ-5D-5L-Y utility scores (Supplementary Table 2 and Fig. 2 ). Correlation between each item in the three instruments were provided in Supplementary Table 3. Table 2 presents the comparison of DCUI and EQ-5D-Y-5L utility values and CPQ 11−14 score across DMFT categories, perceived oral health status, perceived impact on wellbeing and reason for visit. The results indicate that mean utility values and scores varied non-significantly across the DMFT categories. Only the DCUI scores showed a significant difference across categories of perceived oral health status, with individuals reporting better oral health demonstrating higher DCUI utility values. This indicates that the DCUI was able to discriminate between participants based on their perceived oral health. However, the mean scores of all three instruments differed significantly across categories of perceived impact on quality of life (p < 0.001) and reason for dental visit. Table 2 Discrimination across DMFT group, perceived oral health status, perceived impact on QoL and reason to visit Variable Participants DCUI utility value EQ-5D-Y-5L utility value CPQ 11−14 score Mean (SD) Mean (SD) Mean (SD) DMFT Group DMFT = 0 73 0.959 (0.060) 0.965 (0.059) 7.42 (5.278) DMFT = 1–5 92 0.913 (0.014) 0.951 (0.080) 8.66 (5.310) DMFT > 5 18 0.910 (0.091) 0.961 (0.090) 7.83 (4.204) p value p = 0.09 p = 0.34 p = 0.28 Perceived oral health status Excellent 13 0.974 (0.050) 0.985 (.024) 6.61 (4.112) Very good 61 0.946 (0.097) 0.967 (.060) 6.93 (4.871) Good 76 0.928 (0.097) 0.962 (.065) 8.74 (5.068) Fair 29 0.909 (0.146) 0.920 (.113) 9.27 (6.369) Poor 5 0.781 (0.243) 0.930 (.091) 9.50 (4.359) p Value p = 0.02 p = 0.07 p = 0.14 Perceived impact on QoL Not at all 65 0.978 (0.042) 0.979 (0.056) 5.34 (3.645) A little 77 0.924 (0.110) 0.956 (0.063) 8.75 (4.472) Some 26 0.900 (0.099) 0.939 (0.094) 10.65 (6.196) A lot 11 0.818 (0.222) 0.887 (0.125) 12.18 (7.222) Very much 4 0.833 (0.210) 0.957 (0.066) 12.00 (6.879) p value p = 0.00 p = 0.00 p = 0.00 Reason to visit Check-up or cleaning 116 0.948 (0.090) 0.970 (0.059) 6.655 (4.587) Orthodontic 42 0.916 (0.135) 0.948 (0.082) 10.880 (5.540) Other reasons 3 0.898 (0.050) 0.930 (0.037) 10.333 (3.055) Caries/filling group 22 0.872 (0.145) 0.916 (0.108) 10.000 (5.246) p value p = 0.00 p = 0.01 p = 0.00 *Higher CPQ 11−14 scores denote lower quality of life. (CPQ 11−14 , Child perception questionnaire 11–14; DCUI, Dental Caries Utility Index; DMFT, Decayed, Missing and Filled Teeth; EQ-5D-Y-5L, EuroQoL-5D-Youth-5L questionnaire; QoL, Quality of Life; SD, Standard deviation) Table 3 demonstrates the discrimination by effect size (ES) by the three instruments DCUI, EQ-5D-Y-5L and CPQ 11−14 across the DMFT category, perceived oral health status, perceived impact on quality of life and reason for visit groups. DCUI demonstrated a greater ability to distinguish between participants with DMFT = 0 and DMFT = 1–5, as well as between those reporting fair and poor perceived oral health, showing medium to large effect sizes compared to EQ-5D-Y-5L and CPQ11-14. Table 3 Discrimination by effect size (ES) by the three instruments DCUI, EQ-5D-Y-5L and CPQ 11-14 across the DMFT category, perceived oral health group, perceived overall wellbeing groups and reason to visit Variable DCUI EQ-5D-Y-5L CPQ 11−14 * n Median Mean (SD) Effect size Median Mean (SD) Effect Size Median Mean (SD) Effect Size DMFT Group DMFT = 0 73 1.00 0.96 (0.06) 1.00 0.96 (0.06) 7.0 7.42 (5.29) DMFT = 1–5 92 0.98 0.91 (0.01) 0.76 0.97 0.95 (0.08) 0.24 8.0 8.66 (5.31) 0.23 DMFT > 5 18 0.95 0.91 (0.09) 0.02 1.00 0.96 (0.09) 0.13 8.5 7.83 (4.20) 0.15 Perceived oral health status Excellent 13 1.00 0.97 (0.05) 1.00 0.98 (0.02) 6.0 6.61 (4.11) Very good 61 1.00 0.94 (0.10) 0.56 1.00 0.97 (0.06) 0.74 6.0 6.93 (4.87) 0.08 Good 76 0.98 0.93 (0.10) 0.19 1.00 0.96 (0.06) 0.08 8.0 8.74 (5.07) 0.37 Fair 29 0.96 0.91 (0.15) 0.19 0.97 0.92 (0.11) 0.64 9.0 9.27 (6.37) 0.11 Poor 5 0.88 0.78 (0.24) 0.87 0.96 0.93 (0.09) 0.09 10.5 9.50 (4.36) 0.04 Perceived impact on QoL Not at all 65 1.00 0.98 (0.04) 1.00 0.98 (0.06) 4.0 5.34 (3.64) A little 77 0.98 0.92 (0.11) 1.28 0.97 0.96 (0.06) 0.42 8.0 8.75 (4.47) 0.94 Some 26 0.91 0.90 (0.10) 0.22 0.97 0.94 (0.09) 0.27 10.0 10.65 (6.20) 0.42 A lot 11 0.92 0.82 (0.22) 0.82 0.96 0.89 (0.12) 0.56 15.0 12.18 (7.22) 0.25 Very much 4 0.90 0.83 (0.21) 0.07 0.98 0.96 (0.07) 0.56 9.5 12.00 (6.88) 0.02 Reason to visit Check-up/ cleaning 116 1.00 0.95 (0.09) 1.00 0.97 (0.06) 6.0 6.65 (4.59) Orthodontic 42 0.98 0.92 (0.14) 0.35 0.98 0.95 (0.08) 0.38 11.0 10.88 (5.54) 0.92 Other reasons 3 0.88 0.90 (0.05) 0.14 0.93 0.93 (0.04) 0.21 11.0 10.33 (3.05) 0.10 Caries/ filling 22 0.90 0.87 (0.14) 0.50 0.96 0.92 (0.11) 0.40 10.0 10.00 (5.25) 0.11 *Higher CPQ 11−14 scores denote lower quality of life. (CPQ 11−14 , Child perception questionnaire 11–14; DCUI, Dental Caries Utility Index; DMFT, Decayed, Missing and Filled Teeth; EQ-5D-Y-5L, EuroQoL-5D-Youth-5L questionnaire; SD, Standard Deviation) Responsiveness Table 4 showed descriptive statistics for the three instruments. DCUI and EQ-5D-Y-5L reported higher ceiling effect than the cutoff value of 15%. Table 4 Descriptive statistics for the DCUI utility values, EQ-5D-Y-5L utility values and CPQ 11−14 scores Instrument Range of possible values Mean (SD) Range of scores in the sample % with worst QoL score % with best QoL score DCUI (0–1) 0.931 (0.111) (0.379–1.000) 0% 46.99% EQ-5D-Y-5L (0–1) 0.957 (0.073) (0.625–1.000) 0% 53.55% CPQ 11−14 (0–32) 8.087 (5.208) (0.000–25.00) 0%* 1.64%* *Higher CPQ11-14 scores denote lower quality of life. ((CPQ 11−14 , Child perception questionnaire 11–14; DCUI, Dental Caries Utility Index; EQ-5D-Y-5L, EuroQoL-5D-Youth-5L questionnaire; QoL, Quality of Life; SD, Standard Deviation) Reliability Statistics DCUI and EQ-5D-Y-5L showed Cronbach’s alpha values 0.622 and 0.618, respectively indicating moderate internal consistency, while CPQ 11−14 reported higher reliability with a Cronbach’s alpha of 0.771. Discussion The use of oral health–specific PBMs in economic evaluations of oral health interventions is gaining attention among researchers, with limited evidence currently available regarding their psychometric properties. Evaluating these properties is crucial to determine whether an instrument accurately measures the construct it is intended to assess. Establishing such evidence within a clinical sample is particularly valuable, as it supports the instrument’s future application. This study aimed to evaluate the psychometric properties of a newly developed adolescent oral health–specific PBM, the DCUI. Findings indicated that the DCUI demonstrated stronger correlations with similar constructs (CPQ 11−14 ), superior discriminative ability across perceived oral health status and DMFT groups compared with EQ-5D-Y-5L and CPQ 11−14 , moderate reliability and limited responsiveness. These findings hold significant implications for the conduct of economic evaluations in oral health. Generic PBMs, such as the EQ-5D-Y-5L, have comparatively limited ability to capture the full spectrum of oral health–related impacts, particularly among adolescent populations. The demonstrated validity, discriminative capacity, and moderate internal consistency of the DCUI indicate that it is a psychometrically robust instrument capable of more accurately reflecting variations in oral health related quality of life. This enhanced sensitivity supports the derivation of more precise utility values and, consequently, more accurate estimations of quality-adjusted life years (QALYs) in cost-utility analyses. Establishing the psychometric soundness of the DCUI, therefore strengthens its potential for future use in oral health economic evaluations and contributes to the advancement of disease-specific outcome measures for informing evidence-based policy and resource allocation decisions. The correlation of DCUI with both CPQ 11−14 and EQ-5D-Y-5L were statistically significant; however, the correlation with EQ-5D-Y-5L was weak and notably lower than that observed with CPQ 11−14 . These correlation patterns provide important evidence for the construct validity of the DCUI, like being more sensitive to oral health–related quality of life and capturing constructs that are distinct from general health measures. This specificity is particularly valuable in the context of economic evaluations, as generic PBMs may underestimate the impact of oral conditions due to limited sensitivity to oral health domains.[ 27 ] Similarly previous studies also reported that the ECOHIS-4D, an oral health specific PBM targeted for younger children was weakly correlated with commonly used paediatric generic PBM; EQ-5D-Y-3L[ 27 ] and child health utility index (CHU-9D).[ 29 ] Furthermore, the DCUI was able to demonstrate moderate effect size between DMFT = 0 and DMFT = 1–5 groups whereas the other two instruments showed only small effect size between DMFT groups indicating that DCUI is better at discriminating between DMFT groups. This was in line with the previous studies that have shown that the condition specific measures are more sensitive to changes in disease severity groups. The DCUI was specifically developed for dental caries as a condition specific measure, hence it has an ability to discriminate among DMFT groups. Even though CPQ 11−14 is an oral health specific measure, it does not specifically focus on dental caries, therefore, shows less discrimination ability. This study had limitations. The sample was drawn from a single health area in Australia, which may limit the generalizability of the findings to broader adolescent populations. The cross-sectional design precluded assessment of test–retest reliability and responsiveness, which are important for evaluating the instrument’s sensitivity to changes over time. Furthermore, the reliance on self-reported measures may have introduced recall or social desirability bias, potentially affecting the observed correlations and discriminative ability. Future studies employing larger, more diverse samples and longitudinal designs are warranted to further validate the DCUI and confirm its utility in clinical and economic evaluations. Conclusion In conclusion, this study provides evidence supporting the psychometric validity of the DCUI as an adolescent oral health–specific preference-based measure. The DCUI demonstrated moderate correlations with an established oral health–specific instrument (CPQ11-14), superior discrimination across perceived oral health and DMFT groups compared with the generic measure EQ-5D-Y-5L, and moderate reliability. These findings suggest that the DCUI is a promising tool for capturing oral health–related quality of life in adolescents and has potential for use in economic evaluations of oral health interventions. Further research in larger, more diverse populations and longitudinal studies is warranted to confirm its reliability, responsiveness, and broader applicability. Implications The psychometric validation of the DCUI demonstrated that DCUI captures adolescent oral health impacts more sensitively than generic quality-of-life instruments. Therefore, establishing the psychometric properties of the DCUI strengthens its potential for future use in oral health economic evaluations and contributes to the advancement of disease-specific outcome measures for informing evidence-based policy and resource allocation decisions. Declarations Acknowledgments The authors thank all participating adolescents and their parents or guardians for their time and contribution. We would like to acknowledge Dr Sumit Sachdeva, Director, Metro South Oral Health services for his kind support throughout the research project. We also acknowledge the administrative staff and clinical teams at the Metro South Oral Health dental clinics and Mrs Nadine Turco for their assistance with data collection. Declaration of conflicting interests The authors have no relevant financial or non-financial interests to disclose. Funding statement Financial support for this study was provided by the 2024 BEL Connect Grants Scheme, The University of Queensland (Grant number BEL240023). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. Author Contributions All authors certify that they meet the ICMJE criteria for authorship. Ruvini Hettiarachchi and Haitham Tuffaha conceived and designed the study. Material preparation, data collection and analysis were performed by Ruvini Hettiarachchi and Mochamad Iqbal Nurmansyah. Ruvini Hettiarachchi, Sanketha Francis and Mochamad Iqbal Nurmansyah drafted the first and subsequent versions of the manuscript. Anura Ariyawardana, Leah Hobbs, Loc Do and Haitham Tuffaha provided critical intellectual input and revised the manuscript. All authors read and approved the final manuscript. Ethical Considerations This study was performed in line with the principles of the Declaration of Helsinki. Ethics approval was obtained from the Children’s Health Queensland Human Research Ethics Committee (HREC/2024/QCHQ/110333). Consent to Participate Written informed consent was obtained from the parents of the participants prior to the data collection. Consent for publication Not applicable. Data availability The datasets generated and/or analysed during the current study are not publicly available due to ethical and privacy restrictions but are available from the corresponding author on reasonable request. JEL classification code I19 References Trends in the: global, regional, and national burden of oral conditions from 1990 to 2021: a systematic analysis for the Global Burden of Disease Study 2021 (2025). 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Oral Epidemiol. 50 (3), 191–198 (2022) Rogers, H.J., Gilchrist, F., Marshman, Z., Rodd, H.D., Rowen, D.: Selection and validation of a classification system for a child-centred preference-based measure of oral health-related quality of life specific to dental caries. J. Patient-Reported Outcomes. 4 (1), 105 (2020). 10.1186/s41687-020-00268-9 Rogers, H.J., Sagabiel, J., Marshman, Z., Rodd, H.D., Rowen, D.: Adolescent valuation of CARIES-QC-U: a child-centred preference-based measure of dental caries. Health Qual. Life Outcomes. 20 (1), 18 (2022). 10.1186/s12955-022-01918-w Kularatna, S., Amilani, U., Senanayake, S., Tonmukayakul, U., Jamieson, L., Arrow, P.: Developing an early childhood oral health impact–specific health-state classification system for a new preference-based instrument, the ECOHIS-4D. Commun. Dent. Oral Epidemiol. 50 (3), 191–198 (2022). https://doi.org/10.1111/cdoe.12650 Bahrampour, M., Downes, M., Scuffham Pa, Byrnes, J.: Comparing multi-attribute utility instruments: CP-6D, a Cerebral palsy specific instrument, vs AQoL-4D. Expert Rev. PharmacoEcon. Outcomes Res. 22 (2), 217–224 (2022). 10.1080/14737167.2021.1909477 Anthoine, E., Moret, L., Regnault, A., Sébille, V., Hardouin, J.B.: Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures. Health Qual. Life Outcomes. 12 , 176 (2014). 10.1186/s12955-014-0176-2 Jokovic, A., Locker, D., Guyatt, G.: Short forms of the Child Perceptions Questionnaire for 11–14-year-old children (CPQ11–14): Development and initial evaluation. Health Qual. Life Outcomes. 4 (1), 4 (2006). 10.1186/1477-7525-4-4 EuroQol Research Foundation: EQ-5D-Y User Guide How to apply, score, and present results from the EQ-5D-Y (2021) Hettiarachchi, R.M., Kularatna, S., Byrnes, J., Mulhern, B., Chen, G., Scuffham, P.A.: Valuing the Dental Caries Utility Index in Australia. Med. Decis. Mak. 43 (7–8), 901–913 (2023). 10.1177/0272989x231197149 Ju, X., Ribeiro Santiago, P.H., Do, L., Jamieson, L.: Validation of a 4-item child perception questionnaire in Australian children. PLOS ONE. 15 (9), e0239449 (2020). 10.1371/journal.pone.0239449 Kreimeier, S., Åström, M., Burström, K., Egmar, A.C., Gusi, N., Herdman, M., Kind, P., Perez-Sousa, M.A., Greiner, W.: EQ-5D-Y-5L: developing a revised EQ-5D-Y with increased response categories. Qual. Life Res. 28 (7), 1951–1961 (2019). 10.1007/s11136-019-02115-x EuroQol Research Foundation: EQ-5D-Y-5L. EOROQOL Research foundation. (2025). https://euroqol.org/information-and-support/euroqol-instruments/eq-5d-y-5l/#148c2053-b414-4ac5-94b3-dbe00e81bd35-link Gagnier, J.J., de Arruda, G.T., Terwee, C.B., Mokkink, L.B., Elsman, E.B.M., Firth, A.D., Mehdipour, A., Coon, C.D., Bjorner, J.B., Peipert, J.D., Haywood, K.L., Calvert, M.J., Offringa, M., Avila, M.A., Aiyegbusi, O.L., Reeve, B.B., Ruseckaite, R., Apfelbacher, C., Sawatzky, R., Beaton, D., Ahmed, S., Consensus: COSMIN reporting guideline for studies on measurement properties of patient–reported outcome measures: version 2.0. Qual. Life Res. 34 (7), 1901–1911 (2025). 10.1007/s11136-025-03950-x Frost, M.H., Reeve, B.B., Liepa, A.M., Stauffer, J.W., Hays, R.D.: What Is Sufficient Evidence for the Reliability and Validity of Patient-Reported Outcome Measures? Value Health. 10 , S94–S105 (2007). https://doi.org/10.1111/j.1524-4733.2007.00272.x StataCorp: Stata Statistical Software: Release 19. StataCorp LLC, College Station, TX (2025) EuroQol Group EQ-5D-Y-5L: (2025). https://euroqol.org/information-and-support/euroqol-instruments/eq-5d-y-5l/ . Accessed September 24 Norman, R., Mulhern, B., Lancsar, E., Lorgelly, P., Ratcliffe, J., Street, D., Viney, R.: The Use of a Discrete Choice Experiment Including Both Duration and Dead for the Development of an EQ-5D-5L Value Set for Australia. PharmacoEconomics. 41 (4), 427–438 (2023). 10.1007/s40273-023-01243-0 Pan, T., Roudijk, B., Devlin, N., Mulhern, B., Norman, R.: An Australian Value Set for the EQ-5D-Y-3L. Health Qual. Life Outcomes. 23 (1), 72 (2025). 10.1186/s12955-025-02402-x Amarasinghe, G.S., Kularatna, S., Weerasuriya, S.R., Arrow, P., Jamieson, L., Tonmukayakul, U., Senanayake, S.: Comparison of the early childhood oral health impact scale (ECOHIS-4D) and EuroQol-5D-Y for measuring oral health-related quality of life utility in children. Qual. Life Res. 34 (2), 385–393 (2025). 10.1007/s11136-024-03816-8 Bratthall, D.: Introducing the Significant Caries Index together with a proposal for a new global oral health goal for 12-year-olds. Int. Dent. J. 50 (6), 378–384 (2000). https://doi.org/10.1111/j.1875-595X.2000.tb00572.x Weerasuriya, S.R., Hettiarachchi, R.M., Kularatna, S., Rohde, A., Arrow, P., Jamieson, L., Tonmukayakul, U., Senanayake, S.: Comparison of the Early Childhood Oral Health Impact Scale (ECOHIS-4D) and Child Health Utility Index (CHU-9D) in children with oral diseases. Commun. Dent. Oral Epidemiol. 52 (2), 224–231 (2024). https://doi.org/10.1111/cdoe.12917 Serdar, C.C., Cihan, M., Yucel, D., Serdar, M.A.: Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies. Biochem. Med. (Zagreb). 31 (1), 010502 (2021). 10.11613/BM.2021.010502 Additional Declarations No competing interests reported. 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The Global burden of disease study reported that untreated dental caries in permanent teeth is the most prevalent oral disease among children worldwide, with an incidence of 32,100 (24,500\u0026thinsp;\u0026minus;\u0026thinsp;41,000) and prevalence of 20,600 (14,500\u0026thinsp;\u0026minus;\u0026thinsp;27,700) cases per 100,000 population among those aged 5\u0026ndash;19 years [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Among adolescents aged 15\u0026ndash;19 years, females and males show similar incidence rates of caries in permanent teeth, having 46,126 (36,363\u0026ndash;56,627) and 46,311 (36,297\u0026ndash;56,805) cases per 100,000 population, respectively. The most recent Australian national data reported by the Australian Institute of Health and Welfare (AIHW) revealed that 42% of children had caries in their primary teeth and 24% in their permanent teeth [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The report also highlights that the prevalence of caries in permanent teeth increased to 38% among children aged 12\u0026ndash;14 years. Moreover, Indigenous children were disproportionately affected, with 36.0% experiencing tooth decay, compared to non-Indigenous children (22.7%).\u003c/p\u003e \u003cp\u003eDental caries is a chronic and progressive disease that can cause a range of symptoms, including sensitive teeth, pain, difficulty in chewing, sleep disturbance and have negative impact on quality of life. If disease progresses, the management of dental caries becomes increasingly resource-intensive and costly. Interventions for caries prevention is the key to reduce this burden. However, strong evidence is required to prioritize allocation of limited health resources for dental caries prevention and to identify the most cost-effective interventions.\u003c/p\u003e \u003cp\u003eEconomic evaluations provide an important framework to prioritize health interventions in resource-scarce settings by providing evidence on health interventions that deliver the best value for money [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Preference-based quality-of-life measures (PBMs) are used to calculate quality-adjusted life years (QALYs) used for economic evaluations by combining both the length and quality of life. Using PBMs, each health state a person experiences is assigned a utility value based on their health-related quality of life (HRQoL) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The time spent in each health state is then multiplied by its corresponding utility value, adjusting survival for the quality of health during that period. These adjusted values are summed across all time periods to estimate total quality-adjusted-life-years (QALYs), representing the equivalent years of perfect health gained [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Of note, most of the oral health quality of life (QoL) instruments are non-PBM, hence cannot be used in economic evaluations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, previous studies have used generic PBM or mapping functions to calculate utility values in oral health economic evaluations. Disease-specific PBMs are tailored to capture the unique symptoms, impacts, and QoL changes relevant to that disease. This specificity makes them more sensitive and responsive to treatment effects, enabling more precise measurement of patient benefit [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In contrast, generic PBMs, while being useful for comparing across conditions, may overlook important disease-related nuances, leading to less accurate assessments in clinical trials or economic evaluations focused on a single condition [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, disease-specific PBMs provide deeper insights into patient experiences and more valid data for decision-making in targeted interventions.\u003c/p\u003e \u003cp\u003eThe use of oral health specific PBMs in economic evaluations is a growing field cross linking oral health research and economic evaluations. Accurate assessment of child oral health is important for guiding economic evaluations and informing healthcare decision-making [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The availability of valid and reliable oral health\u0026ndash;specific PBMs facilitates their use in economic evaluations of oral health interventions, which can ultimately support more effective and efficient planning of oral health care services. The Dental Caries Utility Index (DCUI) is a new oral health-specific PBM for adolescents and the first PBM in Australia developed for the children aged 12\u0026ndash;17 years [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. It was created through qualitative interviews, expert consensus, and valuation studies to define key dimensions of caries-related quality of life and derive utility weights through discrete choice experiments (DCE) for use in economic evaluations of dental interventions [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. It includes five dimensions; pain/discomfort, difficulty eating or drinking, worry, ability to join in activities, and appearance. There are only two other validated oral health paediatric PBMs; the Early Childhood Oral Health Impact Scale-4D (ECOHIS-4D) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and the Caries Impacts and Experiences Questionnaire for Children (CARIESQC-U) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The ECOHIS-4D, developed through factor analysis and Rasch modelling, demonstrates strong face, content, and construct validity, effectively discriminates between levels of caries experience, and outperforms generic PBMs in capturing oral health impacts [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. On the other hand, the CARIES-QC-U, developed through qualitative interviews, Rasch analysis, and think-aloud testing with children, demonstrates strong face and content validity, builds on the psychometrically robust CARIES-QC, and shows solid conceptual grounding with sensitivity to caries-specific impacts [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, these tools are targeted for children of less than 7 years [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] of age and with a wider age group (5\u0026ndash;16 years) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] respectively. Hence, there remains a gap due to the lack of a validated oral health\u0026ndash;specific PBM for adolescents which can be used for economic evaluations [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrior to large scale application, the psychometric properties (validity and reliability) of an instrument must be established. Validity refers to what extent an instrument measures what it is supposed to measure [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] whereas reliability determines that a measurement yields reproducible and consistent results [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Validity of an instrument can be evaluated through several dimensions, including face, content, construct and criterion validity. During the development of DCUI, face and content validity were confirmed through qualitative interviews with adolescents, the target population, and expert opinion from clinical and dental public health specialists [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, despite the availability of two validated paediatric oral health\u0026ndash;specific PBMs, there remains a critical gap, a lack of a validated oral health\u0026ndash;specific PBM designed for adolescents. Addressing this gap, the present study aimed to examine the construct and criterion validity of the DCUI among adolescents aged 12\u0026ndash;17 years attending Metro South oral health clinics, Queensland, ensuring its suitability for use in economic evaluations of dental caries interventions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA descriptive cross-sectional study was conducted among children 12\u0026ndash;17 years of age, attending 17 dental clinics in Metro South Hospital and Health Service (MSHHS) area, Queensland, Australia. A convenient sampling method was adopted to recruit participants. Potential participants attending the dental clinics were invited to participate by a trained research assistant who explained about the study and directed them to the online survey with a survey link along with the information pack. Participants who preferred paper format were given the opportunity to complete the paper-based survey. Only participants proficient in English were included, as the survey was administered in English. Each participant was given a unique identification number, which served as their identifier on all data collection forms and was used to link their clinic records. The survey was administered through the Qualtrics platform and commenced with basic sociodemographic questions, including age, sex, and the postcode of the participant\u0026rsquo;s usual residence. Then the participants were asked to complete two oral health specific QoL instruments; the DCUI and the 8-item short form Child perception questionnaire (CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e), and the generic QoL instrument EuroQoL-5D-Youth (EQ-5D-Y-5L) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The participants\u0026rsquo; dental caries status and treatment data were retrieved from the clinical records.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDCUI\u003c/h2\u003e \u003cp\u003eThe DCUI health state classification system consists of five domains and one item in each domain: Pain or discomfort, Difficulty in eating food or drinking, Worried, Ability to participate in activities and Appearance. Each item has four response levels [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. An Australian-specific utility algorithm for the DCUI is also available to facilitate calculation of utility values corresponding to each health state in DCUI [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003e8-item short form Child perception questionnaire (CPQ\u003c/b\u003e \u003csub\u003e \u003cb\u003e11\u0026minus;14\u003c/b\u003e \u003c/sub\u003e \u003cb\u003e)\u003c/b\u003e \u003c/p\u003e \u003cp\u003e8-item short form CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e is a non-PBM, widely used as an oral health related QoL measure to evaluate oral health related QoL among children. It has been developed from CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e 37 item version to reduce the participants burden and shown to have excellent validity and reliability [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The questionnaire consisted of 8 items; Pain in teeth, lips, mouth or jaws, Food caught in or between your teeth, Difficult to bite or chew firm food, Taken longer than others to eat a meal, Been upset, Felt irritable or frustrated, Missed school because of pain, appointment or surgery, and Not wanted to talk to other children across four domains (Oral Symptoms, Functional Limitations, Emotional well-being and Social well-being) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The questionnaire asks participants to report the frequency of each item over the past three months, using a five-point scale: \u0026lsquo;Never\u0026rsquo; = 0, \u0026lsquo;Once or twice\u0026rsquo; = 1, \u0026lsquo;Sometimes\u0026rsquo; = 2, \u0026lsquo;Often\u0026rsquo; = 3, and \u0026lsquo;Very often\u0026rsquo; = 4. The total score ranges from 0 to 32, with higher scores indicating a lower oral health\u0026ndash;related quality of life [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEuroQoL-5D-Youth-5L (EQ-5D-Y-5L)\u003c/h3\u003e\n\u003cp\u003eThe EQ-5D-Y-5L is a generic self-report PMB designed for children aged 8\u0026ndash;15 years [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. It consists of two components: the EQ-5D-Y-5L descriptive system and the EQ visual analogue scale (VAS) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The descriptive system includes five dimensions (mobility (walking about); looking after myself, doing usual activities, having pain or discomfort and feeling worried, sad or unhappy) each with five levels of severity. These dimensions mirror those of the adult EQ-5D-5L but are expressed in child-friendly language.\u003c/p\u003e \u003cp\u003e In addition to these instruments, the participants were asked two global questions to rate the child's oral health: \u0026lsquo;How would you consider the condition of your teeth and mouth today\u0026rsquo; and \u0026lsquo;How much do your teeth or mouth bother you in your everyday life?\u0026rsquo;. Responses were recorded on a five-point scale: for oral health, from \u0026lsquo;Excellent\u0026rsquo; = 0 to \u0026lsquo;Poor\u0026rsquo; = 4; and for oral well-being, from \u0026lsquo;Not at all\u0026rsquo; = 0 to \u0026lsquo;Very much\u0026rsquo; = 4. Once the survey was completed, the participants clinic records were linked using the unique identification number. The main clinical data obtained was the decayed, missing and filling tooth (DMFT) score at the index visit which was considered as the survey completion date. Ethics approval was obtained from the Children's Health Queensland, human research ethics review committee (Ethics no HREC/2024/QCHQ/110333). The COSMIN reporting guidelines for studies on measurement properties of patient reported outcome measures (PROMs) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] has been used as a guide to report the study findings (Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eA minimum of 200 sample size was recommended in studies assessing psychometric properties of PROMs [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Therefore, it was targeted to include 200\u0026ndash;250 study participants. Incomplete surveys with missing data were excluded from the main data analysis during the data cleaning. Data was analysed using STATA Statistical Software: Release 19 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Baseline characteristics were summarised using descriptive statistics including range, mean and standard deviation (or median and inter-quartile range for non-normally distributed data). The DCUI utility values were derived based on DCUI Australian utility value set [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. There is no EQ-5D-Y-5L value set available for Australia or any other country [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In such circumstances, literature suggested to use respective adult value set (I.e., Australian EQ-5D-5L) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] or respective 3L value set (i.e., Australian EQ-5D-Y-3L) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] to derive the utility values [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Therefore, we used Australian adult value set (i.e., EQ-5D-5L) to derive EQ-5D-Y-5L utility values.\u003c/p\u003e \u003cp\u003eThe high DMFT scores indicate higher clinical severity, and the participants were categorised into three clinical severity groups based on the DMFT index. The cut-off values for the clinical severity groups were determined using the Significant Caries Index (SCI), which represents the mean DMFT score of the one-third of the population with the highest caries experience [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The validity and reliability of the instruments were assessed based on the DCUI, EQ-5D-Y-5L and CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e scores.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eConstruct validity\u003c/h3\u003e\n\u003cp\u003eConstruct validity was assessed in terms of convergent and discriminant validity. Convergent validity refers to the correlation with similar constructs whereas the discriminant validity refers to the lack of correlation with unrelated constructs [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The convergent and discriminant validity of the three instruments was assessed using Spearman\u0026rsquo;s correlation and a correlation coefficient of \u0026ge;\u0026thinsp;0.50 considered as strong correlation whereas 0.30\u0026ndash;0.49 and \u0026lt;\u0026thinsp;0.30 considered as moderate and weak correlations respectively. Further, a valid instrument should be able to discriminate between groups with differing clinical severity as well as between known groups that differ in quality of life. Hence, discriminant known group validity of the instruments was assessed based on the DMFT severity group, perceived oral health status, perceived overall wellbeing and clinical group (based on reason to attend) using Kruskal-Walli\u0026rsquo;s test and effect size. The effect size determines the discriminatory ability of the instruments and calculated by dividing the mean utility difference (or score difference) of two adjacent severity groups by the standard deviation of the milder severity group. To interpret the results, the effect sizes were categorized into three groups (\u0026le;\u0026thinsp;0.2small, 0.2\u0026ndash;0.5 medium and \u0026ge;\u0026thinsp;0.8 large) and higher effect size indicating better discriminating ability of the instrument [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eResponsiveness\u003c/h3\u003e\n\u003cp\u003eResponsiveness, an ability to detect meaningful change over time, is an important indicator of psychometric properties of PROMs. Ceiling and floor effects are considered indirect measures of responsiveness. The ceiling effect of the three instruments was assessed by the percentage of children reporting \u0026lsquo;no problem\u0026rsquo; in each dimension. The floor effect was evaluated by the percentage of children reporting the \u0026lsquo;worst\u0026rsquo; across all dimensions. High percentages for these two measures indicate that the instrument may be unable to detect improvements or deteriorations in quality of life. As a general guideline, a cutoff of 15% is typically used [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eReliability Statistics\u003c/h2\u003e \u003cp\u003eCronbach\u0026rsquo;s alpha was computed to assess the internal consistency of the three instruments, with α\u0026thinsp;\u0026ge;\u0026thinsp;0.70 considered indicative of acceptable internal consistency [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 239 responses received, 56 were excluded due to incomplete or missing data and duplicate entries leaving 183 participants for analysis. The respondents had a mean age of 14.31 years, with a slightly higher proportion of females than males (54.6% vs. 45.4%). The majority of the sample (63.38%) attend dental clinic for check-up and cleaning. The mean DCUI and EQ-5D-Y-5L utility scores and CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e score were 0.931, 0.957 and 8.09 respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The distribution of DCUI and EQ-5D-Y-5L utility scores were left skewed and CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e score was right skewed, indicating that most participants reported higher quality of life (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Based on the DMFT data of the study sample, the SCI was calculated as DMFT\u0026thinsp;=\u0026thinsp;5, therefore, the study participants were grouped into three clinical severity categories (DMFT\u0026thinsp;=\u0026thinsp;0, DMFT\u0026thinsp;=\u0026thinsp;1\u0026ndash;5 and DMFT\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;5).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio demographic characteristics of the participants by mean DCUI utility values, EQ-5D-Y-5L utility values and CPQ\u003csub\u003e11-14\u003c/sub\u003e scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eParticipants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDCUI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEQ-5D-Y-5L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean health state value (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean health state value (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean score\u003c/p\u003e \u003cp\u003e(SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFull sample\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.931 (0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.957 (0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.09 (5.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.923 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.944 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.83 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.941 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.972 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.02 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026nbsp;(years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14.31 (1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u0026ndash;14 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.925 (0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.957 (0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.76 (0.531)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;17 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.938 (0.010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.959 (0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.44 (0.559)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003e(CPQ\u003c/em\u003e\u003csub\u003e\u003cem\u003e11\u0026minus;14\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eChild perception questionnaire 11\u0026ndash;14; DCUI, Dental Caries Utility Index; EQ-5D-Y-5L, EuroQoL-5D-Youth-5L questionnaire; N/A, not applicable; SD, Standard deviation)\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eConstruct validity\u003c/h3\u003e\n\u003cp\u003eThere was a statistically significant moderate negative correlation between DCUI and CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e score (\u0026ndash;0.4642, p\u0026thinsp;=\u0026thinsp;0.000), whereas a weak correlation (0.3017, p\u0026thinsp;=\u0026thinsp;0.000) was observed between DCUI and EQ-5D-5L-Y utility scores (Supplementary Table\u0026nbsp;2 and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Correlation between each item in the three instruments were provided in Supplementary Table\u0026nbsp;3.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the comparison of DCUI and EQ-5D-Y-5L utility values and CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e score across DMFT categories, perceived oral health status, perceived impact on wellbeing and reason for visit. The results indicate that mean utility values and scores varied non-significantly across the DMFT categories. Only the DCUI scores showed a significant difference across categories of perceived oral health status, with individuals reporting better oral health demonstrating higher DCUI utility values. This indicates that the DCUI was able to discriminate between participants based on their perceived oral health. However, the mean scores of all three instruments differed significantly across categories of perceived impact on quality of life (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and reason for dental visit.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiscrimination across DMFT group, perceived oral health status, perceived impact on QoL and reason to visit\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDCUI utility value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEQ-5D-Y-5L utility value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMFT Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMFT\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.959 (0.060)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.965 (0.059)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.42 (5.278)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMFT\u0026thinsp;=\u0026thinsp;1\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.913 (0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.951 (0.080)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.66 (5.310)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMFT\u0026thinsp;\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.910 (0.091)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.961 (0.090)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.83 (4.204)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerceived oral health status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcellent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.974 (0.050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.985 (.024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.61 (4.112)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.946 (0.097)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.967 (.060)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.93 (4.871)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.928 (0.097)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.962 (.065)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.74 (5.068)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.909 (0.146)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.920 (.113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.27 (6.369)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.781 (0.243)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.930 (.091)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.50 (4.359)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerceived impact on QoL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.978 (0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.979 (0.056)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.34 (3.645)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA little\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.924 (0.110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.956 (0.063)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.75 (4.472)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.900 (0.099)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.939 (0.094)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.65 (6.196)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA lot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.818 (0.222)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.887 (0.125)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.18 (7.222)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery much\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.833 (0.210)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.957 (0.066)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.00 (6.879)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReason to visit\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCheck-up or cleaning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.948 (0.090)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.970 (0.059)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.655 (4.587)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthodontic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.916 (0.135)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.948 (0.082)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.880 (5.540)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther reasons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.898 (0.050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.930 (0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.333 (3.055)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaries/filling group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.872 (0.145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.916 (0.108)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.000 (5.246)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003e*Higher CPQ\u003c/em\u003e\u003csub\u003e\u003cem\u003e11\u0026minus;14\u003c/em\u003e\u003c/sub\u003e \u003cem\u003escores denote lower quality of life.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003e(CPQ\u003c/em\u003e\u003csub\u003e\u003cem\u003e11\u0026minus;14\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eChild perception questionnaire 11\u0026ndash;14; DCUI, Dental Caries Utility Index; DMFT, Decayed, Missing and Filled Teeth; EQ-5D-Y-5L, EuroQoL-5D-Youth-5L questionnaire; QoL, Quality of Life; SD, Standard deviation)\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e demonstrates the discrimination by effect size (ES) by the three instruments DCUI, EQ-5D-Y-5L and CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e across the DMFT category, perceived oral health status, perceived impact on quality of life and reason for visit groups. DCUI demonstrated a greater ability to distinguish between participants with DMFT\u0026thinsp;=\u0026thinsp;0 and DMFT\u0026thinsp;=\u0026thinsp;1\u0026ndash;5, as well as between those reporting fair and poor perceived oral health, showing medium to large effect sizes compared to EQ-5D-Y-5L and CPQ11-14.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiscrimination by effect size (ES) by the three instruments DCUI, EQ-5D-Y-5L and CPQ\u003csub\u003e11-14\u003c/sub\u003e across the DMFT category, perceived oral health group, perceived overall wellbeing groups and reason to visit\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eDCUI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eEQ-5D-Y-5L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eCPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEffect size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003cp\u003eSize\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003cp\u003eSize\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMFT Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMFT\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.96 (0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.96 (0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.42 (5.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMFT\u0026thinsp;=\u0026thinsp;1\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.95 (0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.66 (5.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMFT\u0026thinsp;\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.96 (0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.83 (4.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerceived oral health status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcellent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.97 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.98 (0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.61 (4.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.94 (0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.97 (0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.93 (4.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.93 (0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.96 (0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.74 (5.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.92 (0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.27 (6.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.78 (0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.93 (0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.50 (4.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerceived impact on QoL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.98 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.98 (0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.34 (3.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA little\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.96 (0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.75 (4.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.90 (0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.94 (0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.65 (6.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA lot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.82 (0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.89 (0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12.18 (7.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery much\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.83 (0.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.96 (0.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12.00 (6.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReason to visit\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCheck-up/ cleaning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.95 (0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.97 (0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.65 (4.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthodontic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.95 (0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.88 (5.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther reasons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.90 (0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.93 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.33 (3.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaries/ filling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.87 (0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.92 (0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.00 (5.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003e*Higher CPQ\u003c/em\u003e\u003csub\u003e\u003cem\u003e11\u0026minus;14\u003c/em\u003e\u003c/sub\u003e \u003cem\u003escores denote lower quality of life.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003e(CPQ\u003c/em\u003e\u003csub\u003e\u003cem\u003e11\u0026minus;14\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eChild perception questionnaire 11\u0026ndash;14; DCUI, Dental Caries Utility Index; DMFT, Decayed, Missing and Filled Teeth; EQ-5D-Y-5L, EuroQoL-5D-Youth-5L questionnaire; SD, Standard Deviation)\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eResponsiveness\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e showed descriptive statistics for the three instruments. DCUI and EQ-5D-Y-5L reported higher ceiling effect than the cutoff value of 15%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics for the DCUI utility values, EQ-5D-Y-5L utility values and CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstrument\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange of possible values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRange of scores in the sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e% with worst QoL score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e% with best QoL score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDCUI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0\u0026ndash;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.931 (0.111)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e(0.379\u0026ndash;1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.99%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEQ-5D-Y-5L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0\u0026ndash;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.957 (0.073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e(0.625\u0026ndash;1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e53.55%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0\u0026ndash;32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.087 (5.208)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e(0.000\u0026ndash;25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.64%*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003e*Higher CPQ11-14 scores denote lower quality of life.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003e((CPQ\u003c/em\u003e\u003csub\u003e\u003cem\u003e11\u0026minus;14\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eChild perception questionnaire 11\u0026ndash;14; DCUI, Dental Caries Utility Index; EQ-5D-Y-5L, EuroQoL-5D-Youth-5L questionnaire; QoL, Quality of Life; SD, Standard Deviation)\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eReliability Statistics\u003c/h2\u003e \u003cp\u003eDCUI and EQ-5D-Y-5L showed Cronbach\u0026rsquo;s alpha values 0.622 and 0.618, respectively indicating moderate internal consistency, while CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e reported higher reliability with a Cronbach\u0026rsquo;s alpha of 0.771.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e The use of oral health\u0026ndash;specific PBMs in economic evaluations of oral health interventions is gaining attention among researchers, with limited evidence currently available regarding their psychometric properties. Evaluating these properties is crucial to determine whether an instrument accurately measures the construct it is intended to assess. Establishing such evidence within a clinical sample is particularly valuable, as it supports the instrument\u0026rsquo;s future application. This study aimed to evaluate the psychometric properties of a newly developed adolescent oral health\u0026ndash;specific PBM, the DCUI. Findings indicated that the DCUI demonstrated stronger correlations with similar constructs (CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e), superior discriminative ability across perceived oral health status and DMFT groups compared with EQ-5D-Y-5L and CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e, moderate reliability and limited responsiveness. These findings hold significant implications for the conduct of economic evaluations in oral health. Generic PBMs, such as the EQ-5D-Y-5L, have comparatively limited ability to capture the full spectrum of oral health\u0026ndash;related impacts, particularly among adolescent populations. The demonstrated validity, discriminative capacity, and moderate internal consistency of the DCUI indicate that it is a psychometrically robust instrument capable of more accurately reflecting variations in oral health related quality of life. This enhanced sensitivity supports the derivation of more precise utility values and, consequently, more accurate estimations of quality-adjusted life years (QALYs) in cost-utility analyses. Establishing the psychometric soundness of the DCUI, therefore strengthens its potential for future use in oral health economic evaluations and contributes to the advancement of disease-specific outcome measures for informing evidence-based policy and resource allocation decisions.\u003c/p\u003e \u003cp\u003eThe correlation of DCUI with both CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e and EQ-5D-Y-5L were statistically significant; however, the correlation with EQ-5D-Y-5L was weak and notably lower than that observed with CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e. These correlation patterns provide important evidence for the construct validity of the DCUI, like being more sensitive to oral health\u0026ndash;related quality of life and capturing constructs that are distinct from general health measures. This specificity is particularly valuable in the context of economic evaluations, as generic PBMs may underestimate the impact of oral conditions due to limited sensitivity to oral health domains.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] Similarly previous studies also reported that the ECOHIS-4D, an oral health specific PBM targeted for younger children was weakly correlated with commonly used paediatric generic PBM; EQ-5D-Y-3L[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and child health utility index (CHU-9D).[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eFurthermore, the DCUI was able to demonstrate moderate effect size between DMFT\u0026thinsp;=\u0026thinsp;0 and DMFT\u0026thinsp;=\u0026thinsp;1\u0026ndash;5 groups whereas the other two instruments showed only small effect size between DMFT groups indicating that DCUI is better at discriminating between DMFT groups. This was in line with the previous studies that have shown that the condition specific measures are more sensitive to changes in disease severity groups. The DCUI was specifically developed for dental caries as a condition specific measure, hence it has an ability to discriminate among DMFT groups. Even though CPQ\u003csub\u003e11\u0026minus;14\u003c/sub\u003e is an oral health specific measure, it does not specifically focus on dental caries, therefore, shows less discrimination ability.\u003c/p\u003e \u003cp\u003eThis study had limitations. The sample was drawn from a single health area in Australia, which may limit the generalizability of the findings to broader adolescent populations. The cross-sectional design precluded assessment of test\u0026ndash;retest reliability and responsiveness, which are important for evaluating the instrument\u0026rsquo;s sensitivity to changes over time. Furthermore, the reliance on self-reported measures may have introduced recall or social desirability bias, potentially affecting the observed correlations and discriminative ability. Future studies employing larger, more diverse samples and longitudinal designs are warranted to further validate the DCUI and confirm its utility in clinical and economic evaluations.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study provides evidence supporting the psychometric validity of the DCUI as an adolescent oral health\u0026ndash;specific preference-based measure. The DCUI demonstrated moderate correlations with an established oral health\u0026ndash;specific instrument (CPQ11-14), superior discrimination across perceived oral health and DMFT groups compared with the generic measure EQ-5D-Y-5L, and moderate reliability. These findings suggest that the DCUI is a promising tool for capturing oral health\u0026ndash;related quality of life in adolescents and has potential for use in economic evaluations of oral health interventions. Further research in larger, more diverse populations and longitudinal studies is warranted to confirm its reliability, responsiveness, and broader applicability.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eImplications\u003c/h2\u003e \u003cp\u003eThe psychometric validation of the DCUI demonstrated that DCUI captures adolescent oral health impacts more sensitively than generic quality-of-life instruments. Therefore, establishing the psychometric properties of the DCUI strengthens its potential for future use in oral health economic evaluations and contributes to the advancement of disease-specific outcome measures for informing evidence-based policy and resource allocation decisions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all participating adolescents and their parents or guardians for their time and contribution. We would like to acknowledge Dr Sumit Sachdeva, Director, Metro South Oral Health services for his kind support throughout the research project. We also acknowledge the administrative staff and clinical teams at the Metro South Oral Health dental clinics and Mrs Nadine Turco for their assistance with data collection.\u0026nbsp;\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eDeclaration of conflicting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinancial support for this study was provided by the 2024 BEL Connect Grants Scheme, The University of Queensland (Grant number \u0026nbsp; BEL240023). The funding agreement ensured the authors\u0026rsquo; independence in designing the study, interpreting the data, writing, and publishing the report.\u0026nbsp;\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors certify that they meet the ICMJE criteria for authorship. Ruvini Hettiarachchi and Haitham Tuffaha conceived and designed the study. Material preparation, data collection and analysis were performed by Ruvini Hettiarachchi and Mochamad Iqbal Nurmansyah. Ruvini Hettiarachchi, Sanketha Francis and Mochamad Iqbal Nurmansyah drafted the first and subsequent versions of the manuscript. Anura Ariyawardana, Leah Hobbs, Loc Do and Haitham Tuffaha provided critical intellectual input and revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthical Considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Ethics approval was obtained from the Children\u0026rsquo;s Health Queensland Human Research Ethics Committee (HREC/2024/QCHQ/110333).\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from the parents of the participants prior to the data collection.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due to ethical and privacy restrictions but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eJEL classification code\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eI19\u003c/strong\u003e\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTrends in the: global, regional, and national burden of oral conditions from 1990 to 2021: a systematic analysis for the Global Burden of Disease Study 2021 (2025). 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Accessed September 24\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNorman, R., Mulhern, B., Lancsar, E., Lorgelly, P., Ratcliffe, J., Street, D., Viney, R.: The Use of a Discrete Choice Experiment Including Both Duration and Dead for the Development of an EQ-5D-5L Value Set for Australia. PharmacoEconomics. \u003cb\u003e41\u003c/b\u003e(4), 427\u0026ndash;438 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s40273-023-01243-0\u003c/span\u003e\u003cspan address=\"10.1007/s40273-023-01243-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan, T., Roudijk, B., Devlin, N., Mulhern, B., Norman, R.: An Australian Value Set for the EQ-5D-Y-3L. Health Qual. Life Outcomes. \u003cb\u003e23\u003c/b\u003e(1), 72 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12955-025-02402-x\u003c/span\u003e\u003cspan address=\"10.1186/s12955-025-02402-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmarasinghe, G.S., Kularatna, S., Weerasuriya, S.R., Arrow, P., Jamieson, L., Tonmukayakul, U., Senanayake, S.: Comparison of the early childhood oral health impact scale (ECOHIS-4D) and EuroQol-5D-Y for measuring oral health-related quality of life utility in children. Qual. Life Res. \u003cb\u003e34\u003c/b\u003e(2), 385\u0026ndash;393 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11136-024-03816-8\u003c/span\u003e\u003cspan address=\"10.1007/s11136-024-03816-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBratthall, D.: Introducing the Significant Caries Index together with a proposal for a new global oral health goal for 12-year-olds. Int. Dent. 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Oral Epidemiol. \u003cb\u003e52\u003c/b\u003e(2), 224\u0026ndash;231 (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/cdoe.12917\u003c/span\u003e\u003cspan address=\"10.1111/cdoe.12917\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSerdar, C.C., Cihan, M., Yucel, D., Serdar, M.A.: Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies. Biochem. Med. (Zagreb). \u003cb\u003e31\u003c/b\u003e(1), 010502 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.11613/BM.2021.010502\u003c/span\u003e\u003cspan address=\"10.11613/BM.2021.010502\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Dental Caries Utility Index, dental caries, children, adolescents, psychometric, Preference-based quality-of-life measures","lastPublishedDoi":"10.21203/rs.3.rs-9399529/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9399529/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003ePurpose\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe availability of valid and reliable condition-specific preference-based quality-of-life measure (PBM) facilitates their use in economic evaluations with more sensitive and condition-relevant utility estimates. The Dental Caries Utility Index (DCUI) is a new oral health-specific PBM designed for economic evaluations of adolescent (12\u0026ndash;17 years) oral health interventions. This study aimed to validate the DCUI by assessing its psychometric properties.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003e A validation study was conducted among adolescents attending Metro South oral health clinics, Queensland, Australia. Participants completed an online survey including sociodemographic data, two oral health\u0026ndash;specific measures (DCUI and the Child Perceptions Questionnaire (CPQ11-14)), one generic PBM (EuroQoL-5D-Youth (EQ-5D-Y-5L)), and two global oral health questions. Dental caries data (Decayed, Missing and Filled Teeth) from treatment records were linked to survey responses. Psychometric evaluation focused on construct validity, responsiveness, and reliability.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 183 adolescents participated (mean age 14.31; (SD) 1.52 years; 54.6% female). Mean utility scores for the study sample were 0.931 (DCUI), 0.957 (EQ-5D-Y-5L), and 8.09 (CPQ11-14). DCUI scores showed a moderate negative correlation with CPQ11-14 (\u0026ndash;0.464, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and a weak positive correlation with EQ-5D-Y-5L (0.302, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The DCUI demonstrated a moderate effect size in discriminating between caries-free (DMFT\u0026thinsp;=\u0026thinsp;0) and caries affected (DMFT\u0026thinsp;=\u0026thinsp;1\u0026ndash;5) groups, outperforming other instruments. It also effectively discriminated participants across perceived oral health status.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003e The DCUI showed stronger associations with oral health specific constructs, greater discriminative validity compared to both generic and specific measures, and moderate reliability, supporting its suitability for adolescents\u0026rsquo; oral health economic evaluations.\u003c/p\u003e","manuscriptTitle":"Psychometric evaluation of Dental Caries Utility Index (DCUI): An oral health specific Preference-Based Quality-of-Life Measure for Economic Evaluations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-28 13:06:11","doi":"10.21203/rs.3.rs-9399529/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f874ac96-a8fa-4e78-856b-d7faab99da00","owner":[],"postedDate":"April 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T13:06:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-28 13:06:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9399529","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9399529","identity":"rs-9399529","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}