Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

These protocol was performing compliance with the procedural regulations of the Bioethical Committee of the university of Burgos Spain prior to their participation, both the students and their parents, in some cases, legal tutors had all provided their informed consent and I’d been fully made aware of the objectives of the study. No financial compensation was offered for their participation. The protocol analyze the use of the software for recording and interpretation of results in a scale for the measurement of functional abilities, In 30 to 60 households.

These scales analyze functional abilities, That are distributed in 11 areas. The server allows the recording interpretation of the functional development of users comparing the evolutionary development in each ability. It is measured in a lighter scale from one to five, from nothing to everything.

This tool facilitates the detection of problems in the development of functional skills guides in implementation of training programs, and in turn facilitates the monitoring of user within such programs. Before using this server the teacher therapies cannot serve different abilities in a drug context. Also, it can compare these results with parents’information, Participant recruitment.

Recruit children between zero to six years of development age with a history of special educational needs related to alteration in the area of motor development, cognitive, personal autonomy, and socialization, and with moderate to severe intellectual disabilities. A total of 11 participants, seven boys and four girls were recruited for the present study. Include children who show confirmed diagnosis of either moderate or severe intellectual disability in accordance with the diagnostic and statistical manual of mental disorders and attend a special education center for their schooling.

The diagnosis should, in each case, have been confirmed by a Pediatric Neurologist at a hospital or a Psychologist on behalf of a multidisciplinary team in accordance with DSM-5. Ideally there should be no fewer than 15 participants. Exclude children with normal development in functional areas, motor cognitive, personal autonomy, and socialization development and children with an intellectual functioning limitation.

Data collection. Collect data on the development of the children in different functional areas, food autonomy, personal care and hygiene, dressing and undressing independently, sphincter Control, functional mobility, communication and language, daily life routine, adapted behavior and attention. For the observation using the scale for the measurement of functional abilities in children between zero to six years old and conduct deo observation in a natural context.

For example, schooling settings. Record observation throughout the week in different natural environment that reflect the daily life of the students at the center. For example, while playing, et cetera.

let the teacher and the therapist who directly attend the child at the educational institution, record the observations and then put the results into the software. Experiment Procedures. Assigning a student to a teacher in the software.

This step is unusually performed by the study director, who generally as the coordinator of the program. Login the software package with a username and password and select language, either English or Spanish. Enter on the information relating to student data from the register’s help by the director of the center.

Fill in the following field for each student. Name, sir name, code, sex, date of birth, developmental age, primary diagnosis, secondary diagnosis where appropriate and observation that are relevant to mediation, data, allergies and other information or interest to the management of the center. Enter the information relating to the teacher or therapist from the records held at the center.

Assign the teachers to a group with a teacher or therapist by clicking on classroom, then go to the column Students, then choose the student to be assigned to the classroom and then click on teachers and select one Allocate each group of students and their teacher or therapist to a classroom by clicking in teachers’input dates, name, surname, identification code, mail, password, and observation. Then click accept Director can then devolve responsibility for student assessments to each teacher. The director can consult the assessments that the teacher will input into the software at any time throughout the academic year.

Use of the software by the Teacher. The teacher or therapist performing the assessment can then select an academic year, and or a term. The scale offers the possibility of selecting different functional areas for each term, Login to the software with a username and password that the director can previously assigned.

Enter the result of the assessments completed in natural environments for each participant assigned to a classroom. Choose a student in the software by clicking on his name and then start the assessment of a different functional area. Perform the comparative analysis between the development of each user and the expected development at that chronological age.

Do this by following the steps. Once the data is registered select the column evaluation by right clicking select the year, and then the trimester select the column students and select the students of the class of whom you want to make the evaluation. Then select the column areas, clicking on the area and sub area that needs to be evaluated.

Then click on the maximum tab. It gets the development of the students and the comparison in the development expected for their age Compare the different functional areas of each user from the classroom An analysis of the functional areas of each user can be performed with the software. Exporting data from the software.

Select the user data and functional areas, then export the database. Select the column Excel, then get the database, then export database in the statistics program or library of your choice. Import the data into statistical packages and libraries such as SPSS, Weaker, Python, et cetera, and perform clustering analysis.

Here, analysis with SPSS is detailed as below. Clustering or cluster analysis in an unsupervised machine learning technique N within K means it is a grouping method, which aims to partition a set of N observation into K groups in which N observation belongs to a group with a closer mean value. In this experiment K means clustering was used to check the clusters of children and their functional development measured with SFA Select the option analyze, and then classify followed by the option.

K means cluster in the statistical package. Select cross tabs under descriptive statistics, and then the following two variables. Select the descriptive statistics option and then select cross tabs, and then the Cohen Kappa coefficient option.

Use a spreadsheet to generate the spider chat and specific bar graphs for the groups of children with moderate and severe intellectual disabilities.Results. In this study, we present some example of data analysis with the observational protocol, coupled with the use of the software application. We first perform a cluster analysis in order to check whether both the diagnosis of medium and severe intellectual disabilities of the children with special educational needs corresponded to their actual development.

Using the K means method, we found two clusters of belonging to either group. Cluster one and cluster two integrated 55%and 45%of the sample respectively. A cross table was then generated to study the relationship between the belonging cluster and the variable degree of disability cluster.

It was found that all the subject grouped in cluster one belong to a group A, moderate intellectual disabilities, and cluster two included all the students belonging to a group B, severe intellectual disabilities. and there was only one with moderate intellectual disabilities. See table three, A Cohen Kappa coefficient 820, p=006 was obtained.

Progressing with this analysis of study can be performed of the capabilities of the participant in each functional group, disability moderate versus disability severe. Spider chart and specific bar graphs were used for this purpose.Conclusions. The server improves the study of Austro Vascular Disorder In natural environments, because if a law record on professing of the data or filling the tissue therapist and analyze practically in real time.

also the software facilitates the export of data from the center on classroom to file in excel a specific format, quit facilitate the insertion in a statical page Which is possible to perform other more complex analysis, such as the cluster analysis different of means with paramic or no paramic studies Analyze of the reliability of the server for that sample etc.