DOI: 10.17151/hpsal.2018.23.1.3
How to Cite
1.
Bernal Castro ML, Rincón Becerra O, Zea Forero CR, Durán Cortés LV. Method to categorize postures in the classroom using a graphic matrix. Hacia Promoc. Salud [Internet]. 2017 Dec. 28 [cited 2024 Jul. 3];23(1):26-40. Available from: https://revistasojs.ucaldas.edu.co/index.php/hacialapromociondelasalud/article/view/3614

Authors

Martha Lucía Bernal Castro
Pontificia Universidad Javeriana, Bogotá
marthabernal@javeriana.edu.co
http://orcid.org/0000-0003-0343-7577
Ovidio Rincón Becerra
Pontificia Universidad Javeriana, Bogotá
rincono@javeriana.edu.co
http://orcid.org/0000-0001-9122-535X
Christian Ricardo Zea Forero
Pontificia Universidad Javeriana, Bogotá
crzea@javeriana.edu.co
http://orcid.org/0000-0003-0987-6212
Laura Vanesa Durán Cortés
Pontificia Universidad Javeriana, Bogotá
duran.laura@javeriana.edu.co
http://orcid.org/0000-0003-2813-5022

Abstract

Objective: To present the process conducted and its application in order to identify and categorize the seated posture behavior of students in the classroom, using video capture and the development of a graphic matrix to register postures. Material and method: Students from second to eleven grade (between 7 and 16 years of age) male and female from a coeducational school in Bogotá, Colombia participated in the study. The seated postures of 20 students, distributed according to age, school grade, and school dynamics (individual / group), were recorded in ten videos. The postures observed were drawn, categorized and captured in a graphical matrix used as an instrument to identify them, and then, a database was consolidated. Results: A total of 138 posture variations were identified and classified into seven categories. The matrix was applied to compare the frequency of the postures adopted during the first and second half of the class in individual dynamics, the frequency of neck rotation between the two school dynamics, and the frequency of posture categories between class dynamics. Conclusions: The graphic matrix is a qualitative type screening tool which, with the elaboration of a database, makes it possible to calculate the frequencies of movement in the body parts (neck, extremities, and trunk) and percentages of time of permanence in the established categories or in certain posture variation, without the need for specialized equipment or software, or specialized technical staff for data collection and analysis.

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