This study used a set of data, collected first-hand with the specific objective of the work itself, such as the different measurements (linear and angular), tracing time, Liker scale questions that measure perception of the new software, recommendations, usability and preferences. The X-rays were provided by the dental clinic of the UAQ, where the bio-ethics committee reviewed and approved the procedure, protocol to be followed and informed consent. There was no interaction with the patient at any time and only the data was provided; with ID, instead of name. The data set included the lateral x-ray of the skull, sociodemographic data of the patient such as: age, gender, socioeconomic level, municipality of origin and schooling, this with the aim of obtaining the best case-control, for the users of the software, they were informed consent was given and participation was completely voluntary, there were no vulnerable people in the contest and there were no gender conflicts.
Analysis by Björk-Jarabak
Björk's analysis was modified and adapted by Jarabak; a notable aspect of this analysis is the use of the Na-S-Ar-Go-Me polygon, to evaluate the anterior and posterior facial height relationships, as well as to predict the direction of facial growth [18, 19], For our work, points, planes and angles that are related to the facial biotype determination method will be analyzed (Fig. 1).
The points of reference are defined as follows:
Nasion (Na): Point located at the anterior limit of the frontonasal suture.
Turkish saddle (S): Geometric center of the Turkish saddle.
Articular (Ar): located on the posterior border of the neck of the condyle, where it intersects the inferior border of the spheno occipital massif.
Gonial (Go): intersection of the tangent to the posterior border of the ramus and the tangent to the inferior border of the mandibular body.
Menton (Me): lowest point of the mandibular symphysis.
Once these points have been identified, the following planes are drawn:
S-Na: Anterior cranial base.
S-Ar: Posterior cranial base.
Ar-Go: Branch height.
Go-Me: Length of the mandibular body.
From these planes, the following angles are formed :
Figure 1: Shows the Jarabak polygon, as well as the points and measurements obtained in the tracing.
Figure 1 shows exactly the points, planes and angles (linear and angular measurements) to trace, to determine whether the measurements are within the standard measurement interval; if the measurements are outside the standard range, the patient is considered to have a DMFA. Manual tracing, which has long been the gold standard per excellence, consists of reproducing Jarabak’s polygon on a translucid tracing paper, which can show the points on the lateral skull radiograph.
A first version of the application was prototyped in GeoGebra, and a comparative study between a digital and a manual cephalometry was carried out with 2 digital radiographs. The test application used the method obtained in the analysis of requirements, namely, Jarabak’s method, with the objective of demonstrating that the design and use of the application is as practical as the manual tracing and does not require a steep learning curve for potential users. This test was carried out with a random sample of students from the 10th Semester of the Bachelor of Dentistry at UAQ from January to June 2019, from the subject of Orthodontics; with the approval and full support of the professor. In this pilot test, the students were first reminded of the method, and then they performed the manual tracing of 2 radiographs and then the same radiographs were traced in the sample application. One survey was conducted per session. It is worth mentioning that both the pilot test and the intervention had informed consent of this study. The data and statistical tests were processed with Stata 10.0 and R software.
Determination of a statistical sample
The inclusion and exclusion criteria were verified (It is worth mentioning that for this work there was no contact of the patients, nor samples of tissues, blood or any other):
Digital lateral cephalic radiographs of male and female patients belonging to “Dr. Benjamín Moreno Pérez” hospital, taken in the years 2017, 2018 and 2019.
X-rays that meet the ideal imaging requirements such as: adequate definition of the structures, sharpness, contrast and resolution.
X-rays where all the anatomical structures necessary to perform the cephalometric analysis are observed, for example: chin.
Digital lateral radiographs not from the “Dr. Benjamín Moreno Pérez” hospital.
X-rays that do not meet imaging requirements
X-rays that cut out anatomical structures
Patients with deforming syndromes that compromise the analysis of the structures.
Subsequently, a 20:1 random sampling was applied to obtain a random sample of lateral skull radiographs of patients from the dental clinic in the years 2017, 2018 and 2019.
Description of the sociodemographic characteristics of the patients
In order to find the best control of each case, we described the characteristics of the individuals; a statistical analysis of frequencies of the sociodemographic and health data of the study population was carried out (age, gender, height, socioeconomic level, weight, etc), In order to reduce the effect of possible confounding variables (such as age, which is biologically the confounder par excellence, since it would not be possible to compare the dentition of an older people with that of an adolescent); and that the effect is pure from the intervention. A descriptive analysis of the data was carried out, using measures of central tendency and dispersion. The most suitable patients (case-control) were matched according to the sociodemographic characteristics obtained.
An application is designed, programmed in Java or Android API; improving the orientation to the user and the application in general, based on the results obtained from the pilot test and thinking about portability to Android.
An application for Android was designed (UCef), this allows the portability of the application to any mobile device such as tablet or cell phone; This application was made with the points required in the pilot test, focused on digital cephalometry to provide an easy-to-use tool that allows locating key points of an X-ray and obtaining a report with the necessary measures to make decisions. related to orthodontics.
The objective was to reduce time and costs in carrying out calculations that can be automated with the use of this application, as well as to facilitate the exchange of the results obtained by different electronic means.
The development was carried out in Java language using Android API Version 28, focused on Android 9.0 (Android Pie) but having Android 5.0 (Android Lollipop) support. The application uses only the client's platform; that is, it does not save or send anything to any server. All data is stored locally.
Applying the same inclusion and exclusion criteria that were applied in the pilot test, only now 5:1 simple random sampling; subsequently, the detection of points and the required measurements were executed, see tables in section 5.2.2: Required parametric measurements. 3 types of users participated:
• Case: Students of 9th and 10th semester of Dentistry.
• Control 1: students of lower semesters of the degree in dentistry.
• Control 2 (experts): specialty or master's degree students in orthodontics or graduates.
First, the cephalometric tracings were made manually with the support of the title teacher, and then the angles and measurements; then you did the same procedure with UCeph. Materials needed for the tracing manual: The instruments needed for the cephalometric study with manual tracing are:
• Lateral skull x-ray: life-size printed (91%)
• Scribing instruments: pencil and eraser, fine-tipped markers.
• Polyester film, acetate sheet or vegetable paper with good transparency.
• System that allows to fix radiography and radiography: Adhesive tape
Materials needed for in-app tracking:
• Schools that wish to participate in the project, with an orthodontist who supports us.
• Computer center, personal computers, Tablet or cell phone for each of the users.
• UCEF application, installed on each computer.
• Radiography: Digital in jpeg format, 100% resolution.
An analysis of the legal framework corresponding to the project, value assessed by end users, as well as an analysis of comparable software in the market is carried out. To carry out our financial viability analysis, we opted for a hybrid model based on discounted cash flows (Net Present Value) and Real Option Valuation, although the discounted cash flow model has become a classic of financial analysis, the effectiveness has been proven, part of it lies in the need for historical information and little volatility. It seeks to obtain the value that does not consider a conservative estimate of cash flows, while protecting itself from the risks of assuming high uncertainty projects, On the other hand, the real options model is avoided because, unlike the well-defined financial options, the former are difficult to estimate due to their multifactorial nature and the fact that they typically ignore the initial investments made to the project (which is later solved by establishing an abandonment value), in addition to focusing on the risks associated with returns, but not those associated with costs. But if an approximate value will be sought by comparable in the market.
The main point is that it seeks to obtain the value that is not taken into account in a conservative estimate of cash flows, while still protecting against the risks of taking on projects with high uncertainty. Additionally, the Black-Scholes-Merton Model and 0Montecarlo simulation model were made with 1000 interactions.
For the analysis of comparable, we must mention that, for cephalometric tracing, the gold standard is manual tracing, but there is a considerable number of authors who have compared software, as shown in Table 3, which shows the most recent works. The vast majority of which point to the use of Software as the best tracing method, which apart from benefits such as ICT, gives additional advantages. One of the main methods of valuing goods, including intangibles as is the case, is by comparable, an investigation of the software that exists in the market is done, and a value is obtained based on their cost. There are different cephalometric software on the market, used in different countries, especially with advanced levels in ICT and advanced economies; although there is already one in Mexico, in the following table we will show the characteristics of the most used, as shown in Table 4. As shown in table 5, the first value could be obtained from the pilot test, which is for savings at the Autonomous University of Querétaro in a school semester; where we show that on average 13 students enter the specialty of dentistry, requiring 10 patients, who need four x-rays during their treatment, four generations at the same time.
So far, this model does not take into account the fact that the abandonment value of a project, that is, in the event of giving up or failing, there is a certain value that can be recovered. The following formula remains at the end .
PTV = NAV + VOA + VAB
VTP = Total Project Value.
NPV = Net Present Value.
VOA = Adjusted Option Value.
VAB = Abandonment value.
Finally, we consider that due to the nature of this analysis (financial feasibility of a software) the UCef project will be evaluated in a more realistic way with this hybrid method than using each of these separately, these values are achievable since it has a well-defined initial investment, the projected cash flows said elements will serve to build an initial valuation which will be adjusted over time according to the difference between projected and actual flows.
Determination of diagnostic agreement
In any research study, a key issue is the reliability of the measurement procedures used; "In the context of clinical studies, not even the most elegant of designs would be able to mitigate the damage caused by an unreliable measurement system"  An important source of measurement error in interobserver variability has been identified in the literature . In this sense and for this work, two different aspects enter into the study of reliability: on the one hand, the bias between observers; Said less rigorously, the tendency of one observer to consistently give higher values than another and of another, which is minimized with matching and the agreement between observers; that is, to what extent the observers coincide in their measurement and this is where we occupy the Kappa coefficient that relates the agreement exhibited by the observers, beyond chance, with the potential agreement also beyond chance. In essence, the process of constructing the index is as follows: the difference between the observed proportion of agreement and the proportion of agreement expected by chance is calculated; if it is equal to zero, then the degree of agreement that has been observed can be attributed entirely to chance; if the difference is positive, this indicates that the degree of concordance is greater than what would be expected if only chance were to operate and vice versa: if the difference were negative, then the data would be showing less concordance than expected only due to of opportunity. Kappa is the quotient between that quantity and the maximum concordance that can be expected without the intervention of chance. This index complies with the characteristics that a concordance measure should have according to Hirji and Rosove, first, when the observers are independent, it takes the value 0; second, it reaches the maximum value of 1 only if there is perfect agreement between the observers and, finally, it is never less than − 1 .
To measure the matching ratio, the kappa (κ) coefficient method is used, it corresponds to the proportion of concordance achieved over the total number of observations, having excluded concordances attributable to factor. In addition, inferential statistics for hypothesis verification: t and chi2 test. All case-control students will perform manual cephalometry, then use the app.
Analysis of the effect of the program
There are various methodological strategies that can be used to evaluate the impact of a computer program or social policy; In general, this type of evaluative study relies on a posteriori or post-hoc observational designs, commonly called observational studies . They basically consist of the use of regression models to identify the effects of an intervention after the program has been implemented . In essence, this procedure compares the results of the intervention in at least two groups of individuals: intervention versus control, with the intervention group receiving the benefits of the program, while the control group does not. All this taking into consideration a variety of characteristics or variables that have been previously measured or observed ; when working with people, for example, are the sociodemographic characteristics. Observational studies of this type may have shortcomings; the most common and unfavorable is the so-called selection bias . Selection bias arises from the fact that observational studies do not control for who has access to the program, or who receives the intervention. The result is that there may be unobservable characteristics that influence participation in the program and that are also related to the observed response to the program . The use of conventional regression analysis cannot overcome the problems of selection bias arising from unmeasured or unobservable factors, as there is no way to control for bias at the program reduction level .
Regression discontinuity design has become a widely used methodology for identifying and estimating program effects in the field of program evaluation of this type . This design may be useful if there is a 'cut-off point' in treatment assignment or treatment assignment probability. In fact, and under certain conditions of regularity, the assignment near the cut-off point behaves almost randomly . This implies that regression discontinuity models use only the information close to the cut-off point to estimate the treatment effect without having to make assumptions about the distribution of the variables of interest or about the functional form of the relationship between the event of interest and the variable that identifies the status of assignment to the program or other covariates . In slightly simpler terms, the main characteristic of the regression discontinuity design is that the assignment to the treatment is made on a value (cut-off point) of one or more variables, measured before the implementation of the program.
In the case of two groups, the application of a cut-off point implies :
That all people on one side of the cut-off point will be assigned to the control group.
That all people on the other side of the cut-off point will be assigned to the intervention group.
The need for a continuous variable, measured before the program .
Due to its results, the regression discontinuity design can share the strengths of an experimental design, although with differences . In the case of the experimental design, and due to the randomization process, it is assumed that the comparison groups are equivalent in all their characteristics, except in receiving the treatment, so that the differences found after exposure to the treatment can be attributed to the implementation of the program . The discontinuous regression design, on the other hand, does not start from this assumption, since it assumes, in the absence of a program, that the “pre-post” program relationship should be equivalent for both groups, control and treatment . From this, it is possible to affirm that the implementation of this design will allow an estimation of the average effect of the program when comparing the indicators of interest between the control group and the treatment group .
We do evaluation of the impact of the application, use of discontinuous regression and the cut-off point for the ninth semester.