Individual-based prediction of the size of the supporting zones in the permanent dentition. A comparison of the Moyers method with a unitary prediction value

Preferences and Satisfaction Toward an Orthodontic Clinical App

OBJECTIVES

 To promote the development of professional orthodontic apps and to grow app engagement, many contributing factors should first be scrutinized. The main purpose of this research was to assess whether gap analysis facilitates strategic app design.

MATERIALS AND METHODS

 Gap analysis was first conducted to reveal users' preferences. Then, the OrthoAnalysis app was developed on an Android operating system using Java programming language. Finally, a self-administered survey was issued to 128 orthodontic specialists to assess their satisfaction toward usage of the app.

STATISTICAL ANALYSIS

 The content validity of the questionnaire was ascertained using an index of Item-Objective Congruence of more than 0.5. The reliability of the questionnaire was also analyzed with Cronbach's Alpha reliability coefficient (ɑ = 0.87).

RESULTS

 Besides the most important factor, "content," many issues were listed, and all were required to engage users. A strong and engaging app should show accurate, trustworthy, and practical clinical analysis that operates smoothly and fast with ease, along with a user-friendly, appealing, and trustworthy interface. In short, because of the preliminary gap analysis that was done to evaluate the potential app engagement power prior to app design, the result of the satisfaction assessment showed that nine traits including overall satisfaction were of high levels.

CONCLUSIONS

 Orthodontic specialists' preferences were assessed using gap analysis and an orthodontic app was designed and appraised. This article presents the orthodontic specialists' preferences and summarizes the process of achieving app satisfaction. Therefore, to create a clinical app with strong engagement power, a strategic initial plan using gap analysis can be recommended.

Agreement of the Newly Developed Moyers' Equations and Moyers' Tables

OBJECTIVE

 This study aimed to develop the Moyers' prediction equation to be used with tooth widths predicting app on smartphone.

MATERIALS AND METHODS

 Four equations were developed separately for sex and dental arches. Internal validation with Moyers' table was finished. External validation on 37 subjects with agreement test of both Moyers' prediction equations and Moyers' prediction tables was performed.

STATISTICAL ANALYSIS

 A general linear model procedure was used to create four prediction equations. Internal validation was evaluated using the coefficient of determination. External validation was performed using Bland and Altman (BA) test.

RESULTS

 Four equations were developed for OrthoAnalysis app on smartphone. The overall coefficient of determination of all equations and prediction table was 0.998 (p < 0.05) indicating good agreement of the two methods. The agreement test on the 37 subjects was that the BA test revealed the BA limits of agreement between the residuals of two predictions was -0.001 mm and ranged from -0.143 to 0.140 mm with almost all plots lying inside this difference interval.

CONCLUSIONS

 In summary, four novel estimation equations were developed and showed very low difference to the well accepted original Moyers' prediction tables. Therefore, the equations used in the orthodontic app for predicting unerupted tooth width were verified and valid for clinical use.

Effect of intermaxillary tooth-size discrepancy on accuracy of prediction equations for mixed dentition space analysis

AIM

Correlation-statistical methods are widely used for prediction of size of unerupted permanent canines and premolars in mixed dentition space analysis. The present study was planned to evaluate the effect of selecting dental study casts with no intermaxillary tooth-size discrepancy on the accuracy of predicting mesiodistal widths (MDWS) of permanent canines and premolars.

STUDY DESIGN

Bolton ratios were calculated for all the screened study dental casts fulfilling the inclusion criteria. Subjects were divided into two groups. Group A: all subjects with no intermaxillary tooth-size discrepancy within ±2 SD (Standard deviation) of the mean values. Group B: increased percentage of subjects with intermaxillary tooth-size discrepancy beyond ±2 SD (Standard deviation) of the mean values.

STATISTICS

Linear regression equations were established for both maxilla and mandible in both the groups, with different tooth combinations as independent variables. Validation of best possible regression equations was done on an independent set of 40 subjects. The actual and predicted values of MDWS of permanent canines and premolars were compared by paired samples t test in both groups, for both arches.

RESULTS

The accuracy of equations derived from group A was higher than those derived from group B. The difference between actual and predicted values was statistically insignificant in group A and statistically significant in group B.

CONCLUSION

The results confirm the accuracy of simple linear regression equations derived from a sample of children with no intermaxillary tooth-size discrepancy.

Prediction of the mesiodistal size of unerupted canines and premolars for a group of Romanian children: a comparative study

Objectives:

The aim of the present study was to develop an optimization method of multiple linear regression equation (MLRE), using a genetic algorithm to determine a set of coefficients that minimize the prediction error for the sum of permanent premolars and canine dimensions in a group of young people from a central area of Romania represented by a city called Sibiu.

Material and Methods:

To test the proposed method, we used a multiple linear regression equation derived from the estimation method proposed by Mojers, to which we adjusted regression coefficients using the Breeder genetic algorithm. A total of 92 children were selected with complete permanent teeth with no clinically visible dental caries, proximal restorations or orthodontic treatment. A hard dental stone was made for each of these models, which was then measured with a digital calliper. The Dahlberg analyses of variance had been performed to determine the error of method, then the Correlation t Test was applied, and finally the MLRE equations were obtained using the version 16 for Windows of the SPSS program.

Results:

The correlation coefficient of MLRE was between 51-67% and the significance level was set at α=0.05. Comparing predictions provided by the new and respectively old method, we can conclude that the Breeder genetic algorithm is capable of providing the best values for parameters of multiple linear regression equations, and thus our equations are optimized for the best performance.

Conclusion:

The prediction error rates of the optimized equations using the Breeder genetic algorithm are smaller than those provided by the multiple linear regression equations proposed in the recent study.

A comparison of methods for predicting the size of unerupted permanent canines and premolars

The aim of this study was to examine the reliability of eight methods for determining the mesio-distal crown diameters (MDD) of the permanent canines and premolars (C, P(1), and P(2)). The study models of 120 children (60 boys and 60 girls) aged from 14 to 18 years treated in orthodontic clinics were measured using Seipel's method, with callipers accurate to 0.01 mm. The correlation coefficients were determined between the MDD of C, P(1), and P(2) measured on the study models and the sums calculated using various other methods. The correlation coefficients derived by comparison with the methods of Moyers, Tanka and Johnston, Droschl et al., Legović and Hauz, and Berendonk-Nawrath showed a tendency to over-estimate the MDD of C, P(1), and P(2), while the regression methods of Gross and Hasund, Bachmann, and Tränkmann et al. under-estimated the values. Bachmann's method appeared to give the most reliable results.

Dental arch space and permanent tooth size in the mixed dentition of a skeletal sample from the 14th to the 19th centuries and 3 contemporary samples

Dental arch space and permanent tooth size in the mixed dentition were studied in 4 cohorts: (1) 48 skulls from the 14th to the 19th centuries from The Schreiner Collection in the Department of Anatomy, University of Oslo; (2) 39 boys and 34 girls of Sami origin born in the 1980s living in northern Norway; (3) 31 boys and 30 girls born in the 1960s living in southern Norway; and (4) 32 boys and 26 girls born in the 1980s living in the same part of southern Norway as the previous group. The sexes were unknown in the skeletal sample, and the groups were analyzed with the sexes pooled. The crown sizes of the permanent teeth in the mixed dentition of the Norwegian children who had lived between the 14th and the 19th centuries were smaller than those of contemporary children living in the same country. Probable reasons for this increase in tooth size include improved nutrition and reduced morbidity, because this study ruled out attrition as a major cause of the discrepancy in tooth size. The relative space (arch perimeter minus tooth size) in the group born in the 1960s deviated from that in the other 3 groups, indicating a greater degree of crowding in this group. The relative space in the skulls did not differ significantly from that in the groups born in the 1980s. This means that the improved caries situation during the last decades has changed the dental arch space in these populations. The irregularity index of the 4 mandibular permanent incisors was larger in the skulls than in the modern samples.