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.

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.